diff --git a/.github/actions/windows-setup-cuda/action.yml b/.github/actions/windows-setup-cuda/action.yml index 5575caeca3..6ad61582a5 100644 --- a/.github/actions/windows-setup-cuda/action.yml +++ b/.github/actions/windows-setup-cuda/action.yml @@ -65,3 +65,34 @@ runs: echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\libnvvp" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append echo "CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8 echo "CUDA_PATH_V12_4=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8 + + - name: Install Cuda Toolkit 13.1 + if: ${{ inputs.cuda_version == '13.1' }} + shell: pwsh + run: | + mkdir -p "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" + choco install unzip -y + curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_crt/windows-x86_64/cuda_crt-windows-x86_64-13.1.80-archive.zip" + curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cudart/windows-x86_64/cuda_cudart-windows-x86_64-13.1.80-archive.zip" + curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvcc/windows-x86_64/cuda_nvcc-windows-x86_64-13.1.80-archive.zip" + curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvrtc/windows-x86_64/cuda_nvrtc-windows-x86_64-13.1.80-archive.zip" + curl -O "https://developer.download.nvidia.com/compute/cuda/redist/libcublas/windows-x86_64/libcublas-windows-x86_64-13.2.0.9-archive.zip" + curl -O "https://developer.download.nvidia.com/compute/cuda/redist/libnvvm/windows-x86_64/libnvvm-windows-x86_64-13.1.80-archive.zip" + curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvtx/windows-x86_64/cuda_nvtx-windows-x86_64-13.1.68-archive.zip" + curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_profiler_api/windows-x86_64/cuda_profiler_api-windows-x86_64-13.1.80-archive.zip" + curl -O "https://developer.download.nvidia.com/compute/cuda/redist/visual_studio_integration/windows-x86_64/visual_studio_integration-windows-x86_64-13.1.68-archive.zip" + curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cccl/windows-x86_64/cuda_cccl-windows-x86_64-13.1.78-archive.zip" + unzip '*.zip' -d "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" + xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\cuda_crt-windows-x86_64-13.1.80-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y + xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\cuda_cudart-windows-x86_64-13.1.80-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y + xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\cuda_nvcc-windows-x86_64-13.1.80-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y + xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\cuda_nvrtc-windows-x86_64-13.1.80-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y + xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\libcublas-windows-x86_64-13.2.0.9-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y + xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\libnvvm-windows-x86_64-13.1.80-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y + xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\cuda_nvtx-windows-x86_64-13.1.68-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y + xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\cuda_profiler_api-windows-x86_64-13.1.80-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y + xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\visual_studio_integration-windows-x86_64-13.1.68-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y + xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\cuda_cccl-windows-x86_64-13.1.78-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y + echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append + echo "CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8 + echo "CUDA_PATH_V13_1=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8 diff --git a/.github/workflows/build-linux-cross.yml b/.github/workflows/build-linux-cross.yml index 36201281f0..c2c6ea12ae 100644 --- a/.github/workflows/build-linux-cross.yml +++ b/.github/workflows/build-linux-cross.yml @@ -291,6 +291,7 @@ jobs: -DGGML_RVV=ON \ -DGGML_RV_ZFH=ON \ -DGGML_RV_ZICBOP=ON \ + -DGGML_RV_ZIHINTPAUSE=ON \ -DRISCV64_SPACEMIT_IME_SPEC=RISCV64_SPACEMIT_IME1 \ -DCMAKE_TOOLCHAIN_FILE=${PWD}/cmake/riscv64-spacemit-linux-gnu-gcc.cmake diff --git a/.github/workflows/build-riscv-native.yml b/.github/workflows/build-riscv-native.yml deleted file mode 100644 index a3a0b0d663..0000000000 --- a/.github/workflows/build-riscv-native.yml +++ /dev/null @@ -1,120 +0,0 @@ -name: Build on RISCV Linux Machine by Cloud-V -on: - pull_request: - workflow_dispatch: - workflow_call: - -jobs: - debian-13-riscv64-native: # Bianbu 2.2 - runs-on: [self-hosted, RISCV64] - - steps: - - name: Install prerequisites - run: | - sudo apt-get update || true - sudo apt-get install -y libatomic1 - - uses: actions/checkout@v4 - - name: Setup Riscv - run: | - sudo apt-get update || true - sudo apt-get install -y --no-install-recommends \ - build-essential \ - gcc-14-riscv64-linux-gnu \ - g++-14-riscv64-linux-gnu \ - ccache \ - cmake - - - name: Setup ccache - run: | - mkdir -p $HOME/.ccache - ccache -M 5G -d $HOME/.ccache - export CCACHE_LOGFILE=/home/runneruser/ccache_debug/ccache.log - export CCACHE_DEBUGDIR="/home/runneruser/ccache_debug" - echo "$GITHUB_WORKSPACE" - echo "CCACHE_LOGFILE=$CCACHE_LOGFILE" >> $GITHUB_ENV - echo "CCACHE_DEBUGDIR=$CCACHE_DEBUGDIR" >> $GITHUB_ENV - echo "CCACHE_BASEDIR=$GITHUB_WORKSPACE" >> $GITHUB_ENV - echo "CCACHE_DIR=$HOME/.ccache" >> $GITHUB_ENV - - - name: Build - run: | - cmake -B build \ - -DLLAMA_CURL=OFF \ - -DCMAKE_BUILD_TYPE=Release \ - -DGGML_OPENMP=OFF \ - -DLLAMA_BUILD_EXAMPLES=ON \ - -DLLAMA_BUILD_TOOLS=ON \ - -DLLAMA_BUILD_TESTS=OFF \ - -DCMAKE_SYSTEM_NAME=Linux \ - -DCMAKE_SYSTEM_PROCESSOR=riscv64 \ - -DCMAKE_C_COMPILER=riscv64-linux-gnu-gcc-14 \ - -DCMAKE_CXX_COMPILER=riscv64-linux-gnu-g++-14 \ - -DCMAKE_C_COMPILER_LAUNCHER=ccache \ - -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \ - -DCMAKE_POSITION_INDEPENDENT_CODE=ON \ - -DCMAKE_FIND_ROOT_PATH=/usr/lib/riscv64-linux-gnu \ - -DCMAKE_FIND_ROOT_PATH_MODE_PROGRAM=NEVER \ - -DCMAKE_FIND_ROOT_PATH_MODE_LIBRARY=ONLY \ - -DCMAKE_FIND_ROOT_PATH_MODE_INCLUDE=BOTH - - cmake --build build --config Release -j $(nproc) - - # debian-13-riscv64-spacemit-ime-native: # Bianbu 2.2 - # runs-on: [self-hosted, RISCV64] - - # steps: - # - name: Install prerequisites - # run: | - # sudo apt-get update || true - # sudo apt-get install -y libatomic1 - # - uses: actions/checkout@v4 - # - name: Setup Riscv - # run: | - # sudo apt-get update || true - # sudo apt-get install -y --no-install-recommends \ - # build-essential \ - # gcc-14-riscv64-linux-gnu \ - # g++-14-riscv64-linux-gnu \ - # ccache \ - # cmake - # sudo apt-get upgrade binutils -y - - # - name: Setup ccache - # run: | - # mkdir -p $HOME/.ccache - # ccache -M 5G -d $HOME/.ccache - # export CCACHE_LOGFILE=/home/runneruser/ccache_debug/ccache.log - # export CCACHE_DEBUGDIR="/home/runneruser/ccache_debug" - # echo "$GITHUB_WORKSPACE" - # echo "CCACHE_LOGFILE=$CCACHE_LOGFILE" >> $GITHUB_ENV - # echo "CCACHE_DEBUGDIR=$CCACHE_DEBUGDIR" >> $GITHUB_ENV - # echo "CCACHE_BASEDIR=$GITHUB_WORKSPACE" >> $GITHUB_ENV - # echo "CCACHE_DIR=$HOME/.ccache" >> $GITHUB_ENV - - # - name: Build - # run: | - # cmake -B build \ - # -DLLAMA_CURL=OFF \ - # -DCMAKE_BUILD_TYPE=Release \ - # -DGGML_OPENMP=OFF \ - # -DLLAMA_BUILD_EXAMPLES=ON \ - # -DLLAMA_BUILD_TOOLS=ON \ - # -DLLAMA_BUILD_TESTS=OFF \ - # -DCMAKE_SYSTEM_NAME=Linux \ - # -DCMAKE_SYSTEM_PROCESSOR=riscv64 \ - # -DCMAKE_C_COMPILER=riscv64-linux-gnu-gcc-14 \ - # -DCMAKE_CXX_COMPILER=riscv64-linux-gnu-g++-14 \ - # -DCMAKE_C_COMPILER_LAUNCHER=ccache \ - # -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \ - # -DCMAKE_POSITION_INDEPENDENT_CODE=ON \ - # -DCMAKE_FIND_ROOT_PATH=/usr/lib/riscv64-linux-gnu \ - # -DCMAKE_FIND_ROOT_PATH_MODE_PROGRAM=NEVER \ - # -DCMAKE_FIND_ROOT_PATH_MODE_LIBRARY=ONLY \ - # -DCMAKE_FIND_ROOT_PATH_MODE_INCLUDE=BOTH \ - # -DGGML_RVV=ON \ - # -DGGML_RV_ZFH=ON \ - # -DGGML_RV_ZICBOP=ON \ - # -DGGML_CPU_RISCV64_SPACEMIT=ON \ - # -DRISCV64_SPACEMIT_IME_SPEC=RISCV64_SPACEMIT_IME1 - - # cmake --build build --config Release -j $(nproc) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index eee42759fc..ad205f3ec9 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -547,6 +547,46 @@ jobs: # This is using llvmpipe and runs slower than other backends ctest -L main --verbose --timeout 3600 + ubuntu-24-wasm-webgpu: + runs-on: ubuntu-24.04 + + steps: + - name: Clone + id: checkout + uses: actions/checkout@v4 + + - name: ccache + uses: ggml-org/ccache-action@v1.2.16 + with: + key: ubuntu-latest-wasm-webgpu + evict-old-files: 1d + + - name: Install Emscripten + run: | + git clone https://github.com/emscripten-core/emsdk.git + cd emsdk + ./emsdk install latest + ./emsdk activate latest + + - name: Fetch emdawnwebgpu + run: | + DAWN_TAG="v20251027.212519" + EMDAWN_PKG="emdawnwebgpu_pkg-${DAWN_TAG}.zip" + echo "Downloading ${EMDAWN_PKG}" + curl -L -o emdawn.zip \ + "https://github.com/google/dawn/releases/download/${DAWN_TAG}/${EMDAWN_PKG}" + unzip emdawn.zip + + - name: Build WASM WebGPU + run: | + source emsdk/emsdk_env.sh + emcmake cmake -B build-wasm \ + -DGGML_WEBGPU=ON \ + -DLLAMA_CURL=OFF \ + -DEMDAWNWEBGPU_DIR=emdawnwebgpu_pkg + + cmake --build build-wasm --target test-backend-ops -j $(nproc) + ubuntu-22-cmake-hip: runs-on: ubuntu-22.04 container: rocm/dev-ubuntu-22.04:6.1.2 @@ -1562,33 +1602,33 @@ jobs: run: | bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp - ggml-ci-x64-amd-vulkan: - runs-on: [self-hosted, Linux, X64, AMD] + # ggml-ci-x64-amd-vulkan: + # runs-on: [self-hosted, Linux, X64, AMD] - steps: - - name: Clone - id: checkout - uses: actions/checkout@v4 + # steps: + # - name: Clone + # id: checkout + # uses: actions/checkout@v4 - - name: Test - id: ggml-ci - run: | - vulkaninfo --summary - GG_BUILD_VULKAN=1 bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp + # - name: Test + # id: ggml-ci + # run: | + # vulkaninfo --summary + # GG_BUILD_VULKAN=1 bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp - ggml-ci-x64-amd-rocm: - runs-on: [self-hosted, Linux, X64, AMD] + # ggml-ci-x64-amd-rocm: + # runs-on: [self-hosted, Linux, X64, AMD] - steps: - - name: Clone - id: checkout - uses: actions/checkout@v4 + # steps: + # - name: Clone + # id: checkout + # uses: actions/checkout@v4 - - name: Test - id: ggml-ci - run: | - amd-smi static - GG_BUILD_ROCM=1 GG_BUILD_AMDGPU_TARGETS="gfx1101" bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp + # - name: Test + # id: ggml-ci + # run: | + # amd-smi static + # GG_BUILD_ROCM=1 GG_BUILD_AMDGPU_TARGETS="gfx1101" bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp ggml-ci-mac-metal: runs-on: [self-hosted, macOS, ARM64] @@ -1642,6 +1682,337 @@ jobs: run: | GG_BUILD_KLEIDIAI=1 GG_BUILD_EXTRA_TESTS_0=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt + ubuntu-cpu-cmake-riscv64-native: + runs-on: RISCV64 + + steps: + - name: Install dependencies + run: | + sudo apt-get update + + # Install necessary packages + sudo apt-get install -y libatomic1 libtsan2 gcc-14 g++-14 rustup cmake build-essential libssl-dev wget ccache + + # Set gcc-14 and g++-14 as the default compilers + sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-14 100 + sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-14 100 + sudo ln -sf /usr/bin/gcc-14 /usr/bin/gcc + sudo ln -sf /usr/bin/g++-14 /usr/bin/g++ + + # Install Rust stable version + rustup install stable + rustup default stable + + - name: Clone + id: checkout + uses: actions/checkout@v4 + + - name: Check environment + run: | + uname -a + gcc --version + g++ --version + ldd --version + cmake --version + rustc --version + + - name: Setup ccache + run: | + # Set unique cache directory for this job + export CCACHE_DIR="$HOME/.ccache/cpu-cmake-rv64-native" + mkdir -p "$CCACHE_DIR" + + # Configure ccache for optimal performance + ccache --set-config=max_size=5G + ccache --set-config=compression=true + ccache --set-config=compression_level=6 + ccache --set-config=cache_dir="$CCACHE_DIR" + + # Enable more aggressive caching + ccache --set-config=sloppiness=file_macro,time_macros,include_file_mtime,include_file_ctime + ccache --set-config=hash_dir=false + + # Export for subsequent steps + echo "CCACHE_DIR=$CCACHE_DIR" >> $GITHUB_ENV + echo "PATH=/usr/lib/ccache:$PATH" >> $GITHUB_ENV + + - name: Build + id: cmake_build + run: | + cmake -B build \ + -DLLAMA_CURL=OFF \ + -DLLAMA_OPENSSL=ON \ + -DCMAKE_BUILD_TYPE=Release \ + -DGGML_OPENMP=OFF \ + -DLLAMA_BUILD_EXAMPLES=ON \ + -DLLAMA_BUILD_TOOLS=ON \ + -DLLAMA_BUILD_TESTS=ON \ + -DCMAKE_C_COMPILER_LAUNCHER=ccache \ + -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \ + -DGGML_RPC=ON \ + -DCMAKE_C_COMPILER=riscv64-linux-gnu-gcc-14 \ + -DCMAKE_CXX_COMPILER=riscv64-linux-gnu-g++-14 + + cmake --build build --config Release -j $(nproc) + + - name: Test + id: cmake_test + run: | + cd build + ctest -L 'main|curl' --verbose --timeout 900 + + - name: Test llama2c conversion + id: llama2c_test + run: | + cd build + echo "Fetch tokenizer" + wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories260K/tok512.bin + echo "Fetch llama2c model" + wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories260K/stories260K.bin + ./bin/llama-convert-llama2c-to-ggml --copy-vocab-from-model ./tok512.bin --llama2c-model stories260K.bin --llama2c-output-model stories260K.gguf + ./bin/llama-cli -m stories260K.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256 + + ubuntu-cmake-sanitizer-riscv64-native: + runs-on: RISCV64 + + continue-on-error: true + + strategy: + matrix: + sanitizer: [ADDRESS, THREAD, UNDEFINED] + build_type: [Debug] + + steps: + - name: Install dependencies + run: | + sudo apt-get update + + # Install necessary packages + sudo apt-get install -y libatomic1 libtsan2 gcc-14 g++-14 rustup cmake build-essential wget ccache + + # Set gcc-14 and g++-14 as the default compilers + sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-14 100 + sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-14 100 + sudo ln -sf /usr/bin/gcc-14 /usr/bin/gcc + sudo ln -sf /usr/bin/g++-14 /usr/bin/g++ + + # Install Rust stable version + rustup install stable + rustup default stable + + - name: GCC version check + run: | + gcc --version + g++ --version + + - name: Clone + id: checkout + uses: actions/checkout@v4 + + - name: Setup ccache + run: | + # Unique cache directory per matrix combination + export CCACHE_DIR="$HOME/.ccache/sanitizer-${{ matrix.sanitizer }}-${{ matrix.build_type }}" + mkdir -p "$CCACHE_DIR" + + # Configure ccache + ccache --set-config=max_size=5G + ccache --set-config=compression=true + ccache --set-config=compression_level=6 + ccache --set-config=cache_dir="$CCACHE_DIR" + ccache --set-config=sloppiness=file_macro,time_macros,include_file_mtime,include_file_ctime + ccache --set-config=hash_dir=false + + # Export for subsequent steps + echo "CCACHE_DIR=$CCACHE_DIR" >> $GITHUB_ENV + echo "PATH=/usr/lib/ccache:$PATH" >> $GITHUB_ENV + + - name: Build + id: cmake_build + if: ${{ matrix.sanitizer != 'THREAD' }} + run: | + cmake -B build \ + -DLLAMA_CURL=OFF \ + -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \ + -DGGML_OPENMP=ON \ + -DLLAMA_BUILD_EXAMPLES=ON \ + -DLLAMA_BUILD_TOOLS=ON \ + -DLLAMA_BUILD_TESTS=OFF \ + -DCMAKE_C_COMPILER_LAUNCHER=ccache \ + -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \ + -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON \ + -DCMAKE_C_COMPILER=riscv64-linux-gnu-gcc-14 \ + -DCMAKE_CXX_COMPILER=riscv64-linux-gnu-g++-14 + + cmake --build build --config ${{ matrix.build_type }} -j $(nproc) + + - name: Build (no OpenMP) + id: cmake_build_no_openmp + if: ${{ matrix.sanitizer == 'THREAD' }} + run: | + cmake -B build \ + -DLLAMA_CURL=OFF \ + -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \ + -DGGML_OPENMP=OFF \ + -DLLAMA_BUILD_EXAMPLES=ON \ + -DLLAMA_BUILD_TOOLS=ON \ + -DLLAMA_BUILD_TESTS=OFF \ + -DCMAKE_C_COMPILER_LAUNCHER=ccache \ + -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \ + -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON \ + -DCMAKE_C_COMPILER=riscv64-linux-gnu-gcc-14 \ + -DCMAKE_CXX_COMPILER=riscv64-linux-gnu-g++-14 + + cmake --build build --config ${{ matrix.build_type }} -j $(nproc) + + - name: Test + id: cmake_test + run: | + cd build + ctest -L main --verbose --timeout 900 + + + ubuntu-llguidance-riscv64-native: + runs-on: RISCV64 + steps: + - name: Install dependencies + run: | + sudo apt-get update + + # Install necessary packages + sudo apt-get install -y libatomic1 libtsan2 gcc-14 g++-14 rustup cmake build-essential wget ccache + + # Set gcc-14 and g++-14 as the default compilers + sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-14 100 + sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-14 100 + sudo ln -sf /usr/bin/gcc-14 /usr/bin/gcc + sudo ln -sf /usr/bin/g++-14 /usr/bin/g++ + + # Install Rust stable version + rustup install stable + rustup default stable + + - name: GCC version check + run: | + gcc --version + g++ --version + + - name: Clone + id: checkout + uses: actions/checkout@v4 + + - name: Setup ccache + run: | + export CCACHE_DIR="$HOME/.ccache/llguidance-riscv64" + mkdir -p "$CCACHE_DIR" + + ccache --set-config=max_size=5G + ccache --set-config=compression=true + ccache --set-config=compression_level=6 + ccache --set-config=cache_dir="$CCACHE_DIR" + ccache --set-config=sloppiness=file_macro,time_macros,include_file_mtime,include_file_ctime + ccache --set-config=hash_dir=false + + echo "CCACHE_DIR=$CCACHE_DIR" >> $GITHUB_ENV + echo "PATH=/usr/lib/ccache:$PATH" >> $GITHUB_ENV + + - name: Build + id: cmake_build + run: | + cmake -B build \ + -DLLAMA_CURL=OFF \ + -DCMAKE_BUILD_TYPE=Release \ + -DGGML_OPENMP=OFF \ + -DLLAMA_BUILD_EXAMPLES=ON \ + -DLLAMA_BUILD_TOOLS=ON \ + -DLLAMA_BUILD_TESTS=OFF \ + -DCMAKE_C_COMPILER_LAUNCHER=ccache \ + -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \ + -DLLAMA_LLGUIDANCE=ON \ + -DCMAKE_C_COMPILER=riscv64-linux-gnu-gcc-14 \ + -DCMAKE_CXX_COMPILER=riscv64-linux-gnu-g++-14 + + cmake --build build --config Release -j $(nproc) + + - name: Test + id: cmake_test + run: | + cd build + ctest -L main --verbose --timeout 900 + + + ubuntu-cmake-rpc-riscv64-native: + runs-on: RISCV64 + + continue-on-error: true + + steps: + - name: Install dependencies + run: | + sudo apt-get update + + # Install necessary packages + sudo apt-get install -y libatomic1 libtsan2 gcc-14 g++-14 rustup cmake build-essential libssl-dev wget ccache + + # Set gcc-14 and g++-14 as the default compilers + sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-14 100 + sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-14 100 + sudo ln -sf /usr/bin/gcc-14 /usr/bin/gcc + sudo ln -sf /usr/bin/g++-14 /usr/bin/g++ + + # Install Rust stable version + rustup install stable + rustup default stable + + - name: GCC version check + run: | + gcc --version + g++ --version + + - name: Clone + id: checkout + uses: actions/checkout@v4 + + - name: Setup ccache + run: | + export CCACHE_DIR="$HOME/.ccache/rpc-riscv64" + mkdir -p "$CCACHE_DIR" + + ccache --set-config=max_size=5G + ccache --set-config=compression=true + ccache --set-config=compression_level=6 + ccache --set-config=cache_dir="$CCACHE_DIR" + ccache --set-config=sloppiness=file_macro,time_macros,include_file_mtime,include_file_ctime + ccache --set-config=hash_dir=false + + echo "CCACHE_DIR=$CCACHE_DIR" >> $GITHUB_ENV + echo "PATH=/usr/lib/ccache:$PATH" >> $GITHUB_ENV + + - name: Build + id: cmake_build + run: | + cmake -B build \ + -DLLAMA_CURL=OFF \ + -DLLAMA_OPENSSL=ON \ + -DCMAKE_BUILD_TYPE=Release \ + -DGGML_OPENMP=OFF \ + -DLLAMA_BUILD_EXAMPLES=ON \ + -DLLAMA_BUILD_TOOLS=ON \ + -DLLAMA_BUILD_TESTS=ON \ + -DCMAKE_C_COMPILER_LAUNCHER=ccache \ + -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \ + -DCMAKE_C_COMPILER=riscv64-linux-gnu-gcc-14 \ + -DCMAKE_CXX_COMPILER=riscv64-linux-gnu-g++-14 \ + -DGGML_RPC=ON + + cmake --build build --config Release -j $(nproc) + + - name: Test + id: cmake_test + run: | + cd build + ctest -L main --verbose + ggml-ci-arm64-graviton4-kleidiai: runs-on: ah-ubuntu_22_04-c8g_8x diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml index 0d5739c24b..77aec20c11 100644 --- a/.github/workflows/release.yml +++ b/.github/workflows/release.yml @@ -66,14 +66,21 @@ jobs: id: pack_artifacts run: | cp LICENSE ./build/bin/ - zip -r llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.zip ./build/bin/* + zip -y -r llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.zip ./build/bin/* + tar -czvf llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.tar.gz -s ",./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin . - - name: Upload artifacts + - name: Upload artifacts (zip) uses: actions/upload-artifact@v4 with: path: llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.zip name: llama-bin-macos-arm64.zip + - name: Upload artifacts (tar) + uses: actions/upload-artifact@v4 + with: + path: llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.tar.gz + name: llama-bin-macos-arm64.tar.gz + macOS-x64: runs-on: macos-15-intel @@ -120,14 +127,21 @@ jobs: id: pack_artifacts run: | cp LICENSE ./build/bin/ - zip -r llama-${{ steps.tag.outputs.name }}-bin-macos-x64.zip ./build/bin/* + zip -y -r llama-${{ steps.tag.outputs.name }}-bin-macos-x64.zip ./build/bin/* + tar -czvf llama-${{ steps.tag.outputs.name }}-bin-macos-x64.tar.gz -s ",./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin . - - name: Upload artifacts + - name: Upload artifacts (zip) uses: actions/upload-artifact@v4 with: path: llama-${{ steps.tag.outputs.name }}-bin-macos-x64.zip name: llama-bin-macos-x64.zip + - name: Upload artifacts (tar) + uses: actions/upload-artifact@v4 + with: + path: llama-${{ steps.tag.outputs.name }}-bin-macos-x64.tar.gz + name: llama-bin-macos-x64.tar.gz + ubuntu-22-cpu: strategy: matrix: @@ -182,14 +196,21 @@ jobs: id: pack_artifacts run: | cp LICENSE ./build/bin/ - zip -r llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.zip ./build/bin/* + zip -y -r llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.zip ./build/bin/* + tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin . - - name: Upload artifacts + - name: Upload artifacts (zip) uses: actions/upload-artifact@v4 with: path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.zip name: llama-bin-ubuntu-${{ matrix.build }}.zip + - name: Upload artifacts (tar) + uses: actions/upload-artifact@v4 + with: + path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.tar.gz + name: llama-bin-ubuntu-${{ matrix.build }}.tar.gz + ubuntu-22-vulkan: runs-on: ubuntu-22.04 @@ -235,14 +256,21 @@ jobs: id: pack_artifacts run: | cp LICENSE ./build/bin/ - zip -r llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.zip ./build/bin/* + zip -y -r llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.zip ./build/bin/* + tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin . - - name: Upload artifacts + - name: Upload artifacts (zip) uses: actions/upload-artifact@v4 with: path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.zip name: llama-bin-ubuntu-vulkan-x64.zip + - name: Upload artifacts (tar) + uses: actions/upload-artifact@v4 + with: + path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.tar.gz + name: llama-bin-ubuntu-vulkan-x64.tar.gz + windows-cpu: runs-on: windows-2025 @@ -298,7 +326,7 @@ jobs: run: | Copy-Item $env:CURL_PATH\bin\libcurl-${{ matrix.arch }}.dll .\build\bin\Release\ Copy-Item "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Redist\MSVC\14.44.35112\debug_nonredist\${{ matrix.arch }}\Microsoft.VC143.OpenMP.LLVM\libomp140.${{ matrix.arch == 'x64' && 'x86_64' || 'aarch64' }}.dll" .\build\bin\Release\ - 7z a llama-bin-win-cpu-${{ matrix.arch }}.zip .\build\bin\Release\* + 7z a -snl llama-bin-win-cpu-${{ matrix.arch }}.zip .\build\bin\Release\* - name: Upload artifacts uses: actions/upload-artifact@v4 @@ -380,7 +408,7 @@ jobs: - name: Pack artifacts id: pack_artifacts run: | - 7z a llama-bin-win-${{ matrix.backend }}-${{ matrix.arch }}.zip .\build\bin\Release\${{ matrix.target }}.dll + 7z a -snl llama-bin-win-${{ matrix.backend }}-${{ matrix.arch }}.zip .\build\bin\Release\${{ matrix.target }}.dll - name: Upload artifacts uses: actions/upload-artifact@v4 @@ -393,7 +421,7 @@ jobs: strategy: matrix: - cuda: ['12.4'] + cuda: ['12.4', '13.1'] steps: - name: Clone @@ -434,7 +462,7 @@ jobs: - name: Pack artifacts id: pack_artifacts run: | - 7z a llama-bin-win-cuda-${{ matrix.cuda }}-x64.zip .\build\bin\Release\ggml-cuda.dll + 7z a -snl llama-bin-win-cuda-${{ matrix.cuda }}-x64.zip .\build\bin\Release\ggml-cuda.dll - name: Upload artifacts uses: actions/upload-artifact@v4 @@ -448,6 +476,7 @@ jobs: $dst='.\build\bin\cudart\' robocopy "${{env.CUDA_PATH}}\bin" $dst cudart64_*.dll cublas64_*.dll cublasLt64_*.dll robocopy "${{env.CUDA_PATH}}\lib" $dst cudart64_*.dll cublas64_*.dll cublasLt64_*.dll + robocopy "${{env.CUDA_PATH}}\bin\x64" $dst cudart64_*.dll cublas64_*.dll cublasLt64_*.dll 7z a cudart-llama-bin-win-cuda-${{ matrix.cuda }}-x64.zip $dst\* - name: Upload Cuda runtime @@ -517,6 +546,8 @@ jobs: cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/libmmd.dll" ./build/bin cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/libiomp5md.dll" ./build/bin cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/sycl-ls.exe" ./build/bin + cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/libsycl-fallback-bfloat16.spv" ./build/bin + cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/libsycl-native-bfloat16.spv" ./build/bin cp "${{ env.ONEAPI_ROOT }}/dnnl/latest/bin/dnnl.dll" ./build/bin cp "${{ env.ONEAPI_ROOT }}/tbb/latest/bin/tbb12.dll" ./build/bin @@ -526,7 +557,7 @@ jobs: cp "${{ env.ONEAPI_ROOT }}/umf/latest/bin/umf.dll" ./build/bin echo "cp oneAPI running time dll files to ./build/bin done" - 7z a llama-bin-win-sycl-x64.zip ./build/bin/* + 7z a -snl llama-bin-win-sycl-x64.zip ./build/bin/* - name: Upload the release package uses: actions/upload-artifact@v4 @@ -632,7 +663,7 @@ jobs: - name: Pack artifacts id: pack_artifacts run: | - 7z a llama-bin-win-hip-${{ matrix.name }}-x64.zip .\build\bin\* + 7z a -snl llama-bin-win-hip-${{ matrix.name }}-x64.zip .\build\bin\* - name: Upload artifacts uses: actions/upload-artifact@v4 @@ -685,58 +716,20 @@ jobs: - name: Pack artifacts id: pack_artifacts run: | - zip --symlinks -r llama-${{ steps.tag.outputs.name }}-xcframework.zip build-apple/llama.xcframework + zip -y -r llama-${{ steps.tag.outputs.name }}-xcframework.zip build-apple/llama.xcframework + tar -czvf llama-${{ steps.tag.outputs.name }}-xcframework.tar.gz -C build-apple llama.xcframework - - name: Upload artifacts + - name: Upload artifacts (zip) uses: actions/upload-artifact@v4 with: path: llama-${{ steps.tag.outputs.name }}-xcframework.zip - name: llama-${{ steps.tag.outputs.name }}-xcframework + name: llama-${{ steps.tag.outputs.name }}-xcframework.zip - openEuler-cann: - strategy: - matrix: - arch: [x86, aarch64] - chip_type: ['910b', '310p'] - build: ['Release'] - runs-on: ${{ matrix.arch == 'aarch64' && 'ubuntu-24.04-arm' || 'ubuntu-24.04' }} - container: ascendai/cann:${{ matrix.chip_type == '910b' && '8.3.rc1.alpha001-910b-openeuler22.03-py3.11' || '8.2.rc1-310p-openeuler22.03-py3.11' }} - steps: - - name: Checkout - uses: actions/checkout@v4 - with: - fetch-depth: 0 - - - name: Dependencies - run: | - yum update -y - yum install -y git gcc gcc-c++ make cmake libcurl-devel - git config --global --add safe.directory "$GITHUB_WORKSPACE" - - - name: Build - run: | - export LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:${ASCEND_TOOLKIT_HOME}/$(uname -m)-linux/devlib/:${LD_LIBRARY_PATH} - - cmake -S . -B build \ - -DCMAKE_BUILD_TYPE=${{ matrix.build }} \ - -DGGML_CANN=on \ - -DSOC_TYPE=ascend${{ matrix.chip_type }} - cmake --build build -j $(nproc) - - - name: Determine tag name - id: tag - uses: ./.github/actions/get-tag-name - - - name: Pack artifacts - run: | - cp LICENSE ./build/bin/ - zip -r llama-${{ steps.tag.outputs.name }}-bin-${{ matrix.chip_type }}-openEuler-${{ matrix.arch }}.zip ./build/bin/* - - - name: Upload artifacts + - name: Upload artifacts (tar) uses: actions/upload-artifact@v4 with: - path: llama-${{ steps.tag.outputs.name }}-bin-${{ matrix.chip_type }}-openEuler-${{ matrix.arch }}.zip - name: llama-bin-${{ matrix.chip_type }}-openEuler-${{ matrix.arch }}.zip + path: llama-${{ steps.tag.outputs.name }}-xcframework.tar.gz + name: llama-${{ steps.tag.outputs.name }}-xcframework.tar.gz release: if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }} @@ -759,7 +752,6 @@ jobs: - macOS-arm64 - macOS-x64 - ios-xcode-build - - openEuler-cann steps: - name: Clone @@ -814,6 +806,7 @@ jobs: echo "Moving other artifacts..." mv -v artifact/*.zip release + mv -v artifact/*.tar.gz release - name: Create release id: create_release @@ -822,6 +815,34 @@ jobs: GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} with: tag_name: ${{ steps.tag.outputs.name }} + body: | + > [!WARNING] + > **Release Format Update**: Linux releases will soon use .tar.gz archives instead of .zip. Please make the necessary changes to your deployment scripts. + +
+ + ${{ github.event.head_commit.message }} + +
+ + **macOS/iOS:** + - [macOS Apple Silicon (arm64)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.tar.gz) + - [macOS Intel (x64)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-macos-x64.tar.gz) + - [iOS XCFramework](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-xcframework.tar.gz) + + **Linux:** + - [Ubuntu x64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-x64.tar.gz) + - [Ubuntu x64 (Vulkan)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.tar.gz) + - [Ubuntu s390x (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-s390x.tar.gz) + + **Windows:** + - [Windows x64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cpu-x64.zip) + - [Windows arm64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cpu-arm64.zip) + - [Windows x64 (CUDA 12)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cuda-12.4-x64.zip) + - [Windows x64 (CUDA 13)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cuda-13.1-x64.zip) + - [Windows x64 (Vulkan)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-vulkan-x64.zip) + - [Windows x64 (SYCL)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-sycl-x64.zip) + - [Windows x64 (HIP)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-hip-radeon-x64.zip) - name: Upload release id: upload_release @@ -833,7 +854,7 @@ jobs: const fs = require('fs'); const release_id = '${{ steps.create_release.outputs.id }}'; for (let file of await fs.readdirSync('./release')) { - if (path.extname(file) === '.zip') { + if (path.extname(file) === '.zip' || file.endsWith('.tar.gz')) { console.log('uploadReleaseAsset', file); await github.repos.uploadReleaseAsset({ owner: context.repo.owner, diff --git a/.github/workflows/winget.yml b/.github/workflows/winget.yml index 5c28615595..d3d9be23ce 100644 --- a/.github/workflows/winget.yml +++ b/.github/workflows/winget.yml @@ -9,6 +9,7 @@ jobs: update: name: Update Winget Package runs-on: ubuntu-latest + if: github.repository_owner == 'ggml-org' steps: - name: Install cargo binstall diff --git a/.gitignore b/.gitignore index 8575a141c4..428f084110 100644 --- a/.gitignore +++ b/.gitignore @@ -134,3 +134,5 @@ poetry.toml # IDE /*.code-workspace /.windsurf/ +# emscripten +a.out.* diff --git a/CMakeLists.txt b/CMakeLists.txt index 3278c4a72c..c231ec0e3f 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -33,10 +33,24 @@ endif() option(LLAMA_USE_SYSTEM_GGML "Use system libggml" OFF) +option(LLAMA_WASM_MEM64 "llama: use 64-bit memory in WASM builds" ON) + if (EMSCRIPTEN) set(BUILD_SHARED_LIBS_DEFAULT OFF) - option(LLAMA_WASM_SINGLE_FILE "llama: embed WASM inside the generated llama.js" ON) + # Use 64-bit memory to support backend_get_memory queries + # TODO: analyze performance impact, see https://spidermonkey.dev/blog/2025/01/15/is-memory64-actually-worth-using + if (LLAMA_WASM_MEM64) + add_compile_options("-sMEMORY64=1") + add_link_options("-sMEMORY64=1") + endif() + add_link_options("-sALLOW_MEMORY_GROWTH=1") + + option(LLAMA_WASM_SINGLE_FILE "llama: embed WASM inside the generated llama.js" OFF) + option(LLAMA_BUILD_HTML "llama: build HTML file" ON) + if (LLAMA_BUILD_HTML) + set(CMAKE_EXECUTABLE_SUFFIX ".html") + endif() else() if (MINGW) set(BUILD_SHARED_LIBS_DEFAULT OFF) @@ -58,6 +72,12 @@ if (MSVC) add_compile_options("$<$:/bigobj>") endif() +if (LLAMA_STANDALONE) + # enable parallel builds for msbuild + list(APPEND CMAKE_VS_GLOBALS UseMultiToolTask=true) + list(APPEND CMAKE_VS_GLOBALS EnforceProcessCountAcrossBuilds=true) +endif() + if (CMAKE_SYSTEM_NAME STREQUAL "iOS") set(LLAMA_TOOLS_INSTALL_DEFAULT OFF) else() @@ -179,11 +199,6 @@ if (NOT TARGET ggml AND NOT LLAMA_USE_SYSTEM_GGML) # ... otherwise assume ggml is added by a parent CMakeLists.txt endif() -if (MINGW) - # Target Windows 8 for PrefetchVirtualMemory - add_compile_definitions(_WIN32_WINNT=${GGML_WIN_VER}) -endif() - # # build the library # diff --git a/CODEOWNERS b/CODEOWNERS index 6ef6c0489f..8e62a36e81 100644 --- a/CODEOWNERS +++ b/CODEOWNERS @@ -7,16 +7,20 @@ /ci/ @ggerganov /cmake/ @ggerganov /common/CMakeLists.txt @ggerganov -/common/arg.* @ggerganov @ericcurtin +/common/arg.* @ggerganov /common/base64.hpp.* @ggerganov /common/build-info.* @ggerganov +/common/chat.* @pwilkin +/common/chat-peg-parser.* @aldehir /common/common.* @ggerganov /common/console.* @ggerganov /common/http.* @angt /common/llguidance.* @ggerganov /common/log.* @ggerganov +/common/peg-parser.* @aldehir /common/sampling.* @ggerganov /common/speculative.* @ggerganov +/common/unicode.* @aldehir /convert_*.py @CISC /examples/batched.swift/ @ggerganov /examples/batched/ @ggerganov @@ -81,14 +85,14 @@ /src/llama-vocab.* @CISC /src/models/ @CISC /tests/ @ggerganov +/tests/test-chat-.* @pwilkin /tools/batched-bench/ @ggerganov /tools/main/ @ggerganov /tools/mtmd/ @ngxson /tools/perplexity/ @ggerganov /tools/quantize/ @ggerganov /tools/rpc/ @rgerganov -/tools/run/ @ericcurtin -/tools/server/* @ngxson @ggerganov @ericcurtin # no subdir +/tools/server/* @ngxson @ggerganov # no subdir /tools/server/webui/ @allozaur /tools/tokenize/ @ggerganov /tools/tts/ @ggerganov diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 875eb766f3..e4f05258db 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -16,7 +16,7 @@ The project differentiates between 3 levels of contributors: - If you modified a `ggml` operator or added a new one, add the corresponding test cases to `test-backend-ops` - Create separate PRs for each feature or fix. Avoid combining unrelated changes in a single PR - Consider allowing write access to your branch for faster reviews, as reviewers can push commits directly -- If your PR becomes stale, don't hesitate to ping the maintainers in the comments +- If your PR becomes stale, rebase it on top of latest `master` to get maintainers attention - Maintainers will rely on your insights and approval when making a final decision to approve and merge a PR - Consider adding yourself to [CODEOWNERS](CODEOWNERS) to indicate your availability for reviewing related PRs - Using AI to generate PRs is permitted. However, you must (1) explicitly disclose how AI was used and (2) conduct a thorough manual review before publishing the PR. Note that trivial tab autocompletions do not require disclosure. diff --git a/README.md b/README.md index 2e44ae7d0c..7dd2bfd8a1 100644 --- a/README.md +++ b/README.md @@ -61,7 +61,7 @@ range of hardware - locally and in the cloud. - Plain C/C++ implementation without any dependencies - Apple silicon is a first-class citizen - optimized via ARM NEON, Accelerate and Metal frameworks - AVX, AVX2, AVX512 and AMX support for x86 architectures -- RVV, ZVFH, ZFH and ZICBOP support for RISC-V architectures +- RVV, ZVFH, ZFH, ZICBOP and ZIHINTPAUSE support for RISC-V architectures - 1.5-bit, 2-bit, 3-bit, 4-bit, 5-bit, 6-bit, and 8-bit integer quantization for faster inference and reduced memory use - Custom CUDA kernels for running LLMs on NVIDIA GPUs (support for AMD GPUs via HIP and Moore Threads GPUs via MUSA) - Vulkan and SYCL backend support @@ -276,6 +276,7 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo | [MUSA](docs/build.md#musa) | Moore Threads GPU | | [CUDA](docs/build.md#cuda) | Nvidia GPU | | [HIP](docs/build.md#hip) | AMD GPU | +| [ZenDNN](docs/build.md#zendnn) | AMD CPU | | [Vulkan](docs/build.md#vulkan) | GPU | | [CANN](docs/build.md#cann) | Ascend NPU | | [OpenCL](docs/backend/OPENCL.md) | Adreno GPU | diff --git a/ci/run.sh b/ci/run.sh index 1dd65adeaa..83b2603e82 100755 --- a/ci/run.sh +++ b/ci/run.sh @@ -45,7 +45,7 @@ sd=`dirname $0` cd $sd/../ SRC=`pwd` -CMAKE_EXTRA="-DLLAMA_FATAL_WARNINGS=ON -DLLAMA_CURL=ON -DGGML_SCHED_NO_REALLOC=ON" +CMAKE_EXTRA="-DLLAMA_FATAL_WARNINGS=${LLAMA_FATAL_WARNINGS:-ON} -DLLAMA_CURL=ON -DGGML_SCHED_NO_REALLOC=ON" if [ ! -z ${GG_BUILD_METAL} ]; then CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_METAL=ON" diff --git a/cmake/build-info.cmake b/cmake/build-info.cmake index 75c78222f2..c7005950c5 100644 --- a/cmake/build-info.cmake +++ b/cmake/build-info.cmake @@ -39,26 +39,10 @@ if(Git_FOUND) endif() endif() -if(MSVC) - set(BUILD_COMPILER "${CMAKE_C_COMPILER_ID} ${CMAKE_C_COMPILER_VERSION}") - if (CMAKE_VS_PLATFORM_NAME) - set(BUILD_TARGET ${CMAKE_VS_PLATFORM_NAME}) - else() - set(BUILD_TARGET "${CMAKE_SYSTEM_NAME} ${CMAKE_SYSTEM_PROCESSOR}") - endif() -else() - execute_process( - COMMAND ${CMAKE_C_COMPILER} --version - OUTPUT_VARIABLE OUT - OUTPUT_STRIP_TRAILING_WHITESPACE - ) - string(REGEX REPLACE " *\n.*" "" OUT "${OUT}") - set(BUILD_COMPILER ${OUT}) +set(BUILD_COMPILER "${CMAKE_C_COMPILER_ID} ${CMAKE_C_COMPILER_VERSION}") - execute_process( - COMMAND ${CMAKE_C_COMPILER} -dumpmachine - OUTPUT_VARIABLE OUT - OUTPUT_STRIP_TRAILING_WHITESPACE - ) - set(BUILD_TARGET ${OUT}) +if(CMAKE_VS_PLATFORM_NAME) + set(BUILD_TARGET ${CMAKE_VS_PLATFORM_NAME}) +else() + set(BUILD_TARGET "${CMAKE_SYSTEM_NAME} ${CMAKE_SYSTEM_PROCESSOR}") endif() diff --git a/common/CMakeLists.txt b/common/CMakeLists.txt index bb168e8358..377b26846b 100644 --- a/common/CMakeLists.txt +++ b/common/CMakeLists.txt @@ -52,6 +52,8 @@ add_library(${TARGET} STATIC chat-parser.h chat-parser-xml-toolcall.h chat-parser-xml-toolcall.cpp + chat-peg-parser.cpp + chat-peg-parser.h chat.cpp chat.h common.cpp @@ -69,12 +71,16 @@ add_library(${TARGET} STATIC log.h ngram-cache.cpp ngram-cache.h + peg-parser.cpp + peg-parser.h regex-partial.cpp regex-partial.h sampling.cpp sampling.h speculative.cpp speculative.h + unicode.cpp + unicode.h ) if (BUILD_SHARED_LIBS) diff --git a/common/arg.cpp b/common/arg.cpp index 52094e3f10..4203da4a0a 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -30,6 +30,7 @@ #include // for hardware_concurrency #include +#ifndef __EMSCRIPTEN__ #ifdef __linux__ #include #elif defined(_WIN32) @@ -41,6 +42,8 @@ #else #include #endif +#endif + #define LLAMA_MAX_URL_LENGTH 2084 // Maximum URL Length in Chrome: 2083 using json = nlohmann::ordered_json; @@ -424,7 +427,7 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context // model is required (except for server) // TODO @ngxson : maybe show a list of available models in CLI in this case - if (params.model.path.empty() && ctx_arg.ex != LLAMA_EXAMPLE_SERVER) { + if (params.model.path.empty() && ctx_arg.ex != LLAMA_EXAMPLE_SERVER && !params.usage) { throw std::invalid_argument("error: --model is required\n"); } @@ -705,6 +708,8 @@ common_params_context common_params_parser_init(common_params & params, llama_ex params.use_jinja = true; } + params.use_color = tty_can_use_colors(); + // load dynamic backends ggml_backend_load_all(); @@ -787,10 +792,20 @@ common_params_context common_params_parser_init(common_params & params, llama_ex } ).set_examples({LLAMA_EXAMPLE_MAIN})); add_opt(common_arg( - {"-co", "--color"}, - string_format("colorise output to distinguish prompt and user input from generations (default: %s)", params.use_color ? "true" : "false"), - [](common_params & params) { - params.use_color = true; + {"-co", "--color"}, "[on|off|auto]", + "Colorize output to distinguish prompt and user input from generations ('on', 'off', or 'auto', default: 'auto')\n" + "'auto' enables colors when output is to a terminal", + [](common_params & params, const std::string & value) { + if (is_truthy(value)) { + params.use_color = true; + } else if (is_falsey(value)) { + params.use_color = false; + } else if (is_autoy(value)) { + params.use_color = tty_can_use_colors(); + } else { + throw std::invalid_argument( + string_format("error: unknown value for --color: '%s'\n", value.c_str())); + } } ).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP})); add_opt(common_arg( @@ -1019,7 +1034,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex params.flash_attn_type = LLAMA_FLASH_ATTN_TYPE_AUTO; } else { throw std::runtime_error( - string_format("error: unkown value for --flash-attn: '%s'\n", value.c_str())); + string_format("error: unknown value for --flash-attn: '%s'\n", value.c_str())); } }).set_env("LLAMA_ARG_FLASH_ATTN")); add_opt(common_arg( @@ -1226,7 +1241,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex [](common_params & params) { params.warmup = false; } - ).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_EMBEDDING, LLAMA_EXAMPLE_RETRIEVAL, LLAMA_EXAMPLE_PERPLEXITY})); + ).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_MTMD, LLAMA_EXAMPLE_EMBEDDING, LLAMA_EXAMPLE_RETRIEVAL, LLAMA_EXAMPLE_PERPLEXITY})); add_opt(common_arg( {"--spm-infill"}, string_format( @@ -2488,12 +2503,29 @@ common_params_context common_params_parser_init(common_params & params, llama_ex "path to save slot kv cache (default: disabled)", [](common_params & params, const std::string & value) { params.slot_save_path = value; + if (!fs_is_directory(params.slot_save_path)) { + throw std::invalid_argument("not a directory: " + value); + } // if doesn't end with DIRECTORY_SEPARATOR, add it if (!params.slot_save_path.empty() && params.slot_save_path[params.slot_save_path.size() - 1] != DIRECTORY_SEPARATOR) { params.slot_save_path += DIRECTORY_SEPARATOR; } } ).set_examples({LLAMA_EXAMPLE_SERVER})); + add_opt(common_arg( + {"--media-path"}, "PATH", + "directory for loading local media files; files can be accessed via file:// URLs using relative paths (default: disabled)", + [](common_params & params, const std::string & value) { + params.media_path = value; + if (!fs_is_directory(params.media_path)) { + throw std::invalid_argument("not a directory: " + value); + } + // if doesn't end with DIRECTORY_SEPARATOR, add it + if (!params.media_path.empty() && params.media_path[params.media_path.size() - 1] != DIRECTORY_SEPARATOR) { + params.media_path += DIRECTORY_SEPARATOR; + } + } + ).set_examples({LLAMA_EXAMPLE_SERVER})); add_opt(common_arg( {"--models-dir"}, "PATH", "directory containing models for the router server (default: disabled)", @@ -2676,7 +2708,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex common_log_set_colors(common_log_main(), LOG_COLORS_AUTO); } else { throw std::invalid_argument( - string_format("error: unkown value for --log-colors: '%s'\n", value.c_str())); + string_format("error: unknown value for --log-colors: '%s'\n", value.c_str())); } } ).set_env("LLAMA_LOG_COLORS")); diff --git a/common/chat-parser.cpp b/common/chat-parser.cpp index b4e3a9c1f3..fa7c3134da 100644 --- a/common/chat-parser.cpp +++ b/common/chat-parser.cpp @@ -1,6 +1,8 @@ #include "chat-parser.h" +#include "chat-peg-parser.h" #include "common.h" #include "log.h" +#include "peg-parser.h" #include "regex-partial.h" #include @@ -1505,6 +1507,11 @@ static void common_chat_parse(common_chat_msg_parser & builder) { } common_chat_msg common_chat_parse(const std::string & input, bool is_partial, const common_chat_syntax & syntax) { + if (syntax.format == COMMON_CHAT_FORMAT_PEG_SIMPLE || + syntax.format == COMMON_CHAT_FORMAT_PEG_NATIVE || + syntax.format == COMMON_CHAT_FORMAT_PEG_CONSTRUCTED) { + return common_chat_peg_parse(syntax.parser, input, is_partial, syntax); + } common_chat_msg_parser builder(input, is_partial, syntax); try { common_chat_parse(builder); @@ -1522,3 +1529,36 @@ common_chat_msg common_chat_parse(const std::string & input, bool is_partial, co } return msg; } + +common_chat_msg common_chat_peg_parse(const common_peg_arena & parser, const std::string & input, bool is_partial, const common_chat_syntax & syntax) { + if (parser.empty()) { + throw std::runtime_error("Failed to parse due to missing parser definition."); + } + + LOG_DBG("Parsing input with format %s: %s\n", common_chat_format_name(syntax.format), input.c_str()); + + common_peg_parse_context ctx(input, is_partial); + auto result = parser.parse(ctx); + if (result.fail()) { + throw std::runtime_error(std::string("Failed to parse input at pos ") + std::to_string(result.end)); + } + + common_chat_msg msg; + msg.role = "assistant"; + + if (syntax.format == COMMON_CHAT_FORMAT_PEG_NATIVE) { + auto mapper = common_chat_peg_native_mapper(msg); + mapper.from_ast(ctx.ast, result); + } else if (syntax.format == COMMON_CHAT_FORMAT_PEG_CONSTRUCTED) { + auto mapper = common_chat_peg_constructed_mapper(msg); + mapper.from_ast(ctx.ast, result); + } else { + // Generic mapper + auto mapper = common_chat_peg_mapper(msg); + mapper.from_ast(ctx.ast, result); + } + if (!is_partial) { + LOG_DBG("Parsed message: %s\n", common_chat_msgs_to_json_oaicompat({msg}).at(0).dump().c_str()); + } + return msg; +} diff --git a/common/chat-peg-parser.cpp b/common/chat-peg-parser.cpp new file mode 100644 index 0000000000..74a7b6a46d --- /dev/null +++ b/common/chat-peg-parser.cpp @@ -0,0 +1,114 @@ +#include "chat-peg-parser.h" + +#include + +using json = nlohmann::json; + +static std::string_view trim_trailing_space(std::string_view sv) { + while (!sv.empty() && std::isspace(static_cast(sv.back()))) { + sv.remove_suffix(1); + } + return sv; +} + +void common_chat_peg_mapper::from_ast(const common_peg_ast_arena & arena, const common_peg_parse_result & result) { + arena.visit(result, [this](const common_peg_ast_node & node) { + map(node); + }); +} + +void common_chat_peg_mapper::map(const common_peg_ast_node & node) { + bool is_reasoning = node.tag == common_chat_peg_builder::REASONING; + bool is_content = node.tag == common_chat_peg_builder::CONTENT; + + if (is_reasoning) { + result.reasoning_content = std::string(trim_trailing_space(node.text)); + } + + if (is_content) { + result.content = std::string(trim_trailing_space(node.text)); + } +} + +void common_chat_peg_native_mapper::map(const common_peg_ast_node & node) { + common_chat_peg_mapper::map(node); + + bool is_tool_open = node.tag == common_chat_peg_native_builder::TOOL_OPEN; + bool is_tool_name = node.tag == common_chat_peg_native_builder::TOOL_NAME; + bool is_tool_id = node.tag == common_chat_peg_native_builder::TOOL_ID; + bool is_tool_args = node.tag == common_chat_peg_native_builder::TOOL_ARGS; + + if (is_tool_open) { + result.tool_calls.emplace_back(); + current_tool = &result.tool_calls.back(); + } + + if (is_tool_id && current_tool) { + current_tool->id = std::string(trim_trailing_space(node.text)); + } + + if (is_tool_name && current_tool) { + current_tool->name = std::string(trim_trailing_space(node.text)); + } + + if (is_tool_args && current_tool) { + current_tool->arguments = std::string(trim_trailing_space(node.text)); + } +} + +void common_chat_peg_constructed_mapper::map(const common_peg_ast_node & node) { + common_chat_peg_mapper::map(node); + + bool is_tool_open = node.tag == common_chat_peg_constructed_builder::TOOL_OPEN; + bool is_tool_name = node.tag == common_chat_peg_constructed_builder::TOOL_NAME; + bool is_tool_close = node.tag == common_chat_peg_constructed_builder::TOOL_CLOSE; + bool is_arg_open = node.tag == common_chat_peg_constructed_builder::TOOL_ARG_OPEN; + bool is_arg_close = node.tag == common_chat_peg_constructed_builder::TOOL_ARG_CLOSE; + bool is_arg_name = node.tag == common_chat_peg_constructed_builder::TOOL_ARG_NAME; + bool is_arg_string = node.tag == common_chat_peg_constructed_builder::TOOL_ARG_STRING_VALUE; + bool is_arg_json = node.tag == common_chat_peg_constructed_builder::TOOL_ARG_JSON_VALUE; + + if (is_tool_open) { + result.tool_calls.emplace_back(); + current_tool = &result.tool_calls.back(); + arg_count = 0; + } + + if (is_tool_name) { + current_tool->name = std::string(node.text); + current_tool->arguments = "{"; + } + + if (is_arg_open) { + needs_closing_quote = false; + } + + if (is_arg_name && current_tool) { + if (arg_count > 0) { + current_tool->arguments += ","; + } + current_tool->arguments += json(trim_trailing_space(node.text)).dump() + ":"; + ++arg_count; + } + + if (is_arg_string && current_tool) { + // Serialize to JSON, but exclude the end quote + std::string dumped = json(node.text).dump(); + current_tool->arguments += dumped.substr(0, dumped.size() - 1); + needs_closing_quote = true; + } + + if (is_arg_close && current_tool) { + if (needs_closing_quote) { + current_tool->arguments += "\""; + } + } + + if (is_arg_json && current_tool) { + current_tool->arguments += std::string(trim_trailing_space(node.text)); + } + + if (is_tool_close && current_tool) { + current_tool->arguments += "}"; + } +} diff --git a/common/chat-peg-parser.h b/common/chat-peg-parser.h new file mode 100644 index 0000000000..b84cbed206 --- /dev/null +++ b/common/chat-peg-parser.h @@ -0,0 +1,105 @@ +#pragma once + +#include "chat.h" +#include "peg-parser.h" + +class common_chat_peg_builder : public common_peg_parser_builder { + public: + static constexpr const char * REASONING_BLOCK = "reasoning-block"; + static constexpr const char * REASONING = "reasoning"; + static constexpr const char * CONTENT = "content"; + + common_peg_parser reasoning_block(const common_peg_parser & p) { return tag(REASONING_BLOCK, p); } + common_peg_parser reasoning(const common_peg_parser & p) { return tag(REASONING, p); } + common_peg_parser content(const common_peg_parser & p) { return tag(CONTENT, p); } +}; + +inline common_peg_arena build_chat_peg_parser(const std::function & fn) { + common_chat_peg_builder builder; + builder.set_root(fn(builder)); + return builder.build(); +} + +class common_chat_peg_mapper { + public: + common_chat_msg & result; + + common_chat_peg_mapper(common_chat_msg & msg) : result(msg) {} + + virtual void from_ast(const common_peg_ast_arena & arena, const common_peg_parse_result & result); + virtual void map(const common_peg_ast_node & node); +}; + +class common_chat_peg_native_builder : public common_chat_peg_builder { + public: + static constexpr const char * TOOL = "tool"; + static constexpr const char * TOOL_OPEN = "tool-open"; + static constexpr const char * TOOL_CLOSE = "tool-close"; + static constexpr const char * TOOL_ID = "tool-id"; + static constexpr const char * TOOL_NAME = "tool-name"; + static constexpr const char * TOOL_ARGS = "tool-args"; + + common_peg_parser tool(const common_peg_parser & p) { return tag(TOOL, p); } + common_peg_parser tool_open(const common_peg_parser & p) { return atomic(tag(TOOL_OPEN, p)); } + common_peg_parser tool_close(const common_peg_parser & p) { return atomic(tag(TOOL_CLOSE, p)); } + common_peg_parser tool_id(const common_peg_parser & p) { return atomic(tag(TOOL_ID, p)); } + common_peg_parser tool_name(const common_peg_parser & p) { return atomic(tag(TOOL_NAME, p)); } + common_peg_parser tool_args(const common_peg_parser & p) { return tag(TOOL_ARGS, p); } +}; + +class common_chat_peg_native_mapper : public common_chat_peg_mapper { + common_chat_tool_call * current_tool; + + public: + common_chat_peg_native_mapper(common_chat_msg & msg) : common_chat_peg_mapper(msg) {} + + void map(const common_peg_ast_node & node) override; +}; + +inline common_peg_arena build_chat_peg_native_parser(const std::function & fn) { + common_chat_peg_native_builder builder; + builder.set_root(fn(builder)); + return builder.build(); +} + +class common_chat_peg_constructed_builder : public common_chat_peg_builder { + public: + static constexpr const char * TOOL = "tool"; + static constexpr const char * TOOL_OPEN = "tool-open"; + static constexpr const char * TOOL_CLOSE = "tool-close"; + static constexpr const char * TOOL_NAME = "tool-name"; + static constexpr const char * TOOL_ARG = "tool-arg"; + static constexpr const char * TOOL_ARG_OPEN = "tool-arg-open"; + static constexpr const char * TOOL_ARG_CLOSE = "tool-arg-close"; + static constexpr const char * TOOL_ARG_NAME = "tool-arg-name"; + static constexpr const char * TOOL_ARG_STRING_VALUE = "tool-arg-string-value"; + static constexpr const char * TOOL_ARG_JSON_VALUE = "tool-arg-json-value"; + + common_peg_parser tool(const common_peg_parser & p) { return tag(TOOL, p); } + common_peg_parser tool_open(const common_peg_parser & p) { return atomic(tag(TOOL_OPEN, p)); } + common_peg_parser tool_close(const common_peg_parser & p) { return atomic(tag(TOOL_CLOSE, p)); } + common_peg_parser tool_name(const common_peg_parser & p) { return atomic(tag(TOOL_NAME, p)); } + common_peg_parser tool_arg(const common_peg_parser & p) { return tag(TOOL_ARG, p); } + common_peg_parser tool_arg_open(const common_peg_parser & p) { return atomic(tag(TOOL_ARG_OPEN, p)); } + common_peg_parser tool_arg_close(const common_peg_parser & p) { return atomic(tag(TOOL_ARG_CLOSE, p)); } + common_peg_parser tool_arg_name(const common_peg_parser & p) { return atomic(tag(TOOL_ARG_NAME, p)); } + common_peg_parser tool_arg_string_value(const common_peg_parser & p) { return tag(TOOL_ARG_STRING_VALUE, p); } + common_peg_parser tool_arg_json_value(const common_peg_parser & p) { return tag(TOOL_ARG_JSON_VALUE, p); } +}; + +class common_chat_peg_constructed_mapper : public common_chat_peg_mapper { + common_chat_tool_call * current_tool; + int arg_count = 0; + bool needs_closing_quote = false; + + public: + common_chat_peg_constructed_mapper(common_chat_msg & msg) : common_chat_peg_mapper(msg) {} + + void map(const common_peg_ast_node & node) override; +}; + +inline common_peg_arena build_chat_peg_constructed_parser(const std::function & fn) { + common_chat_peg_constructed_builder builder; + builder.set_root(fn(builder)); + return builder.build(); +} diff --git a/common/chat.cpp b/common/chat.cpp index aba64a23a3..d370b57703 100644 --- a/common/chat.cpp +++ b/common/chat.cpp @@ -85,29 +85,36 @@ json common_chat_msg::to_json_oaicompat() const return message; } -std::vector common_chat_msg_diff::compute_diffs(const common_chat_msg & previous_msg, const common_chat_msg & new_msg) { +std::vector common_chat_msg_diff::compute_diffs(const common_chat_msg & msg_prv, const common_chat_msg & msg_new) { std::vector diffs; - if (previous_msg.reasoning_content != new_msg.reasoning_content) { - auto & diff = diffs.emplace_back(); - diff.reasoning_content_delta = string_diff(previous_msg.reasoning_content, new_msg.reasoning_content); - } - if (previous_msg.content != new_msg.content) { - auto & diff = diffs.emplace_back(); - diff.content_delta = string_diff(previous_msg.content, new_msg.content); + if (msg_new.tool_calls.size() > msg_prv.tool_calls.size()) { + diffs.reserve(msg_new.tool_calls.size() - msg_prv.tool_calls.size() + 3); + } else { + diffs.reserve(3); } - if (new_msg.tool_calls.size() < previous_msg.tool_calls.size()) { + // TODO: these can become expensive for long messages - how to optimize? + if (msg_prv.reasoning_content != msg_new.reasoning_content) { + auto & diff = diffs.emplace_back(); + diff.reasoning_content_delta = string_diff(msg_prv.reasoning_content, msg_new.reasoning_content); + } + if (msg_prv.content != msg_new.content) { + auto & diff = diffs.emplace_back(); + diff.content_delta = string_diff(msg_prv.content, msg_new.content); + } + + if (msg_new.tool_calls.size() < msg_prv.tool_calls.size()) { throw std::runtime_error("Invalid diff: now finding less tool calls!"); } - if (!previous_msg.tool_calls.empty()) { - auto idx = previous_msg.tool_calls.size() - 1; - const auto & pref = previous_msg.tool_calls[idx]; - const auto & newf = new_msg.tool_calls[idx]; + if (!msg_prv.tool_calls.empty()) { + const auto idx = msg_prv.tool_calls.size() - 1; + const auto & pref = msg_prv.tool_calls[idx]; + const auto & newf = msg_new.tool_calls[idx]; if (pref.name != newf.name) { throw std::runtime_error("Invalid diff: tool call mismatch!"); } - auto args_diff = string_diff(pref.arguments, newf.arguments); + const auto args_diff = string_diff(pref.arguments, newf.arguments); if (!args_diff.empty() || pref.id != newf.id) { auto & diff = diffs.emplace_back(); diff.tool_call_index = idx; @@ -118,11 +125,12 @@ std::vector common_chat_msg_diff::compute_diffs(const comm diff.tool_call_delta.arguments = args_diff; } } - for (size_t idx = previous_msg.tool_calls.size(); idx < new_msg.tool_calls.size(); ++idx) { + for (size_t idx = msg_prv.tool_calls.size(); idx < msg_new.tool_calls.size(); ++idx) { auto & diff = diffs.emplace_back(); diff.tool_call_index = idx; - diff.tool_call_delta = new_msg.tool_calls[idx]; + diff.tool_call_delta = msg_new.tool_calls[idx]; } + return diffs; } @@ -163,7 +171,7 @@ common_chat_tool_choice common_chat_tool_choice_parse_oaicompat(const std::strin if (tool_choice == "required") { return COMMON_CHAT_TOOL_CHOICE_REQUIRED; } - throw std::runtime_error("Invalid tool_choice: " + tool_choice); + throw std::invalid_argument("Invalid tool_choice: " + tool_choice); } bool common_chat_templates_support_enable_thinking(const common_chat_templates * chat_templates) { @@ -186,17 +194,17 @@ std::vector common_chat_msgs_parse_oaicompat(const json & messa try { if (!messages.is_array()) { - throw std::runtime_error("Expected 'messages' to be an array, got " + messages.dump()); + throw std::invalid_argument("Expected 'messages' to be an array, got " + messages.dump()); } for (const auto & message : messages) { if (!message.is_object()) { - throw std::runtime_error("Expected 'message' to be an object, got " + message.dump()); + throw std::invalid_argument("Expected 'message' to be an object, got " + message.dump()); } common_chat_msg msg; if (!message.contains("role")) { - throw std::runtime_error("Missing 'role' in message: " + message.dump()); + throw std::invalid_argument("Missing 'role' in message: " + message.dump()); } msg.role = message.at("role"); @@ -209,11 +217,11 @@ std::vector common_chat_msgs_parse_oaicompat(const json & messa } else if (content.is_array()) { for (const auto & part : content) { if (!part.contains("type")) { - throw std::runtime_error("Missing content part type: " + part.dump()); + throw std::invalid_argument("Missing content part type: " + part.dump()); } const auto & type = part.at("type"); if (type != "text") { - throw std::runtime_error("Unsupported content part type: " + type.dump()); + throw std::invalid_argument("Unsupported content part type: " + type.dump()); } common_chat_msg_content_part msg_part; msg_part.type = type; @@ -221,25 +229,25 @@ std::vector common_chat_msgs_parse_oaicompat(const json & messa msg.content_parts.push_back(msg_part); } } else if (!content.is_null()) { - throw std::runtime_error("Invalid 'content' type: expected string or array, got " + content.dump() + " (ref: https://github.com/ggml-org/llama.cpp/issues/8367)"); + throw std::invalid_argument("Invalid 'content' type: expected string or array, got " + content.dump() + " (ref: https://github.com/ggml-org/llama.cpp/issues/8367)"); } } if (has_tool_calls) { for (const auto & tool_call : message.at("tool_calls")) { common_chat_tool_call tc; if (!tool_call.contains("type")) { - throw std::runtime_error("Missing tool call type: " + tool_call.dump()); + throw std::invalid_argument("Missing tool call type: " + tool_call.dump()); } const auto & type = tool_call.at("type"); if (type != "function") { - throw std::runtime_error("Unsupported tool call type: " + tool_call.dump()); + throw std::invalid_argument("Unsupported tool call type: " + tool_call.dump()); } if (!tool_call.contains("function")) { - throw std::runtime_error("Missing tool call function: " + tool_call.dump()); + throw std::invalid_argument("Missing tool call function: " + tool_call.dump()); } const auto & fc = tool_call.at("function"); if (!fc.contains("name")) { - throw std::runtime_error("Missing tool call name: " + tool_call.dump()); + throw std::invalid_argument("Missing tool call name: " + tool_call.dump()); } tc.name = fc.at("name"); tc.arguments = fc.at("arguments"); @@ -250,7 +258,7 @@ std::vector common_chat_msgs_parse_oaicompat(const json & messa } } if (!has_content && !has_tool_calls) { - throw std::runtime_error("Expected 'content' or 'tool_calls' (ref: https://github.com/ggml-org/llama.cpp/issues/8367 & https://github.com/ggml-org/llama.cpp/issues/12279)"); + throw std::invalid_argument("Expected 'content' or 'tool_calls' (ref: https://github.com/ggml-org/llama.cpp/issues/8367 & https://github.com/ggml-org/llama.cpp/issues/12279)"); } if (message.contains("reasoning_content")) { msg.reasoning_content = message.at("reasoning_content"); @@ -353,18 +361,18 @@ std::vector common_chat_tools_parse_oaicompat(const json & too try { if (!tools.is_null()) { if (!tools.is_array()) { - throw std::runtime_error("Expected 'tools' to be an array, got " + tools.dump()); + throw std::invalid_argument("Expected 'tools' to be an array, got " + tools.dump()); } for (const auto & tool : tools) { if (!tool.contains("type")) { - throw std::runtime_error("Missing tool type: " + tool.dump()); + throw std::invalid_argument("Missing tool type: " + tool.dump()); } const auto & type = tool.at("type"); if (!type.is_string() || type != "function") { - throw std::runtime_error("Unsupported tool type: " + tool.dump()); + throw std::invalid_argument("Unsupported tool type: " + tool.dump()); } if (!tool.contains("function")) { - throw std::runtime_error("Missing tool function: " + tool.dump()); + throw std::invalid_argument("Missing tool function: " + tool.dump()); } const auto & function = tool.at("function"); @@ -649,6 +657,9 @@ const char * common_chat_format_name(common_chat_format format) { case COMMON_CHAT_FORMAT_QWEN3_CODER_XML: return "Qwen3 Coder"; case COMMON_CHAT_FORMAT_APRIEL_1_5: return "Apriel 1.5"; case COMMON_CHAT_FORMAT_XIAOMI_MIMO: return "Xiaomi MiMo"; + case COMMON_CHAT_FORMAT_PEG_SIMPLE: return "peg-simple"; + case COMMON_CHAT_FORMAT_PEG_NATIVE: return "peg-native"; + case COMMON_CHAT_FORMAT_PEG_CONSTRUCTED: return "peg-constructed"; case COMMON_CHAT_FORMAT_DEEPSEEK_V3_2: return "DeepSeek V3.2"; default: throw std::runtime_error("Unknown chat format"); diff --git a/common/chat.h b/common/chat.h index 36f81cdca2..7e8e99e9a9 100644 --- a/common/chat.h +++ b/common/chat.h @@ -3,6 +3,7 @@ #pragma once #include "common.h" +#include "peg-parser.h" #include #include #include @@ -76,7 +77,7 @@ struct common_chat_msg_diff { size_t tool_call_index = std::string::npos; common_chat_tool_call tool_call_delta; - static std::vector compute_diffs(const common_chat_msg & previous_msg, const common_chat_msg & new_msg); + static std::vector compute_diffs(const common_chat_msg & msg_prv, const common_chat_msg & msg_new); bool operator==(const common_chat_msg_diff & other) const { return content_delta == other.content_delta @@ -125,6 +126,11 @@ enum common_chat_format { COMMON_CHAT_FORMAT_XIAOMI_MIMO, COMMON_CHAT_FORMAT_DEEPSEEK_V3_2, + // These are intended to be parsed by the PEG parser + COMMON_CHAT_FORMAT_PEG_SIMPLE, + COMMON_CHAT_FORMAT_PEG_NATIVE, + COMMON_CHAT_FORMAT_PEG_CONSTRUCTED, + COMMON_CHAT_FORMAT_COUNT, // Not a format, just the # formats }; @@ -155,6 +161,7 @@ struct common_chat_params { std::vector grammar_triggers; std::vector preserved_tokens; std::vector additional_stops; + std::string parser; }; struct common_chat_syntax { @@ -164,6 +171,7 @@ struct common_chat_syntax { bool reasoning_in_content = false; bool thinking_forced_open = false; bool parse_tool_calls = true; + common_peg_arena parser = {}; }; // Check if the template supplied via "--chat-template" is supported or not. Returns true if it's valid @@ -207,6 +215,7 @@ const char* common_chat_format_name(common_chat_format format); const char* common_reasoning_format_name(common_reasoning_format format); common_reasoning_format common_reasoning_format_from_name(const std::string & format); common_chat_msg common_chat_parse(const std::string & input, bool is_partial, const common_chat_syntax & syntax); +common_chat_msg common_chat_peg_parse(const common_peg_arena & parser, const std::string & input, bool is_partial, const common_chat_syntax & syntax); common_chat_tool_choice common_chat_tool_choice_parse_oaicompat(const std::string & tool_choice); diff --git a/common/common.cpp b/common/common.cpp index 10001f5469..0497f90a28 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -694,7 +694,7 @@ bool string_parse_kv_override(const char * data, std::vector= 0xD800 && c <= 0xDFFF) // UTF-16 surrogate pairs || c == 0xFFFD // Replacement Character (UTF-8) || c == 0xFEFF // Byte Order Mark (BOM) - || c == '/' || c == '\\' || c == ':' || c == '*' // Illegal characters + || c == ':' || c == '*' // Illegal characters || c == '?' || c == '"' || c == '<' || c == '>' || c == '|') { return false; } + if (!allow_subdirs && (c == '/' || c == '\\')) { + // Subdirectories not allowed, reject path separators + return false; + } } // Reject any leading or trailing ' ', or any trailing '.', these are stripped on Windows and will cause a different filename @@ -782,11 +786,29 @@ bool fs_validate_filename(const std::string & filename) { #include +#ifdef _WIN32 +static std::wstring utf8_to_wstring(const std::string & str) { + if (str.empty()) { + return std::wstring(); + } + + int size = MultiByteToWideChar(CP_UTF8, 0, str.c_str(), (int)str.size(), NULL, 0); + + if (size <= 0) { + return std::wstring(); + } + + std::wstring wstr(size, 0); + MultiByteToWideChar(CP_UTF8, 0, str.c_str(), (int)str.size(), &wstr[0], size); + + return wstr; +} +#endif + // returns true if successful, false otherwise bool fs_create_directory_with_parents(const std::string & path) { #ifdef _WIN32 - std::wstring_convert> converter; - std::wstring wpath = converter.from_bytes(path); + std::wstring wpath = utf8_to_wstring(path); // if the path already exists, check whether it's a directory const DWORD attributes = GetFileAttributesW(wpath.c_str()); @@ -859,6 +881,11 @@ bool fs_create_directory_with_parents(const std::string & path) { #endif // _WIN32 } +bool fs_is_directory(const std::string & path) { + std::filesystem::path dir(path); + return std::filesystem::exists(dir) && std::filesystem::is_directory(dir); +} + std::string fs_get_cache_directory() { std::string cache_directory = ""; auto ensure_trailing_slash = [](std::string p) { @@ -893,6 +920,8 @@ std::string fs_get_cache_directory() { cache_directory = std::getenv("HOME") + std::string("/Library/Caches/"); #elif defined(_WIN32) cache_directory = std::getenv("LOCALAPPDATA"); +#elif defined(__EMSCRIPTEN__) + GGML_ABORT("not implemented on this platform"); #else # error Unknown architecture #endif @@ -953,6 +982,32 @@ std::vector fs_list(const std::string & path, bool include_dir return files; } +// +// TTY utils +// + +bool tty_can_use_colors() { + // Check NO_COLOR environment variable (https://no-color.org/) + if (const char * no_color = std::getenv("NO_COLOR")) { + if (no_color[0] != '\0') { + return false; + } + } + + // Check TERM environment variable + if (const char * term = std::getenv("TERM")) { + if (std::strcmp(term, "dumb") == 0) { + return false; + } + } + + // Check if stdout and stderr are connected to a terminal + // We check both because log messages can go to either + bool stdout_is_tty = isatty(fileno(stdout)); + bool stderr_is_tty = isatty(fileno(stderr)); + + return stdout_is_tty || stderr_is_tty; +} // // Model utils diff --git a/common/common.h b/common/common.h index cdca5e26a2..d28e48991c 100644 --- a/common/common.h +++ b/common/common.h @@ -12,6 +12,10 @@ #include #include +#if defined(_WIN32) && !defined(_WIN32_WINNT) +#define _WIN32_WINNT 0x0A00 +#endif + #ifdef _WIN32 #define DIRECTORY_SEPARATOR '\\' #else @@ -485,6 +489,7 @@ struct common_params { bool log_json = false; std::string slot_save_path; + std::string media_path; // path to directory for loading media files float slot_prompt_similarity = 0.1f; @@ -635,8 +640,9 @@ std::string string_from(const struct llama_context * ctx, const struct llama_bat // Filesystem utils // -bool fs_validate_filename(const std::string & filename); +bool fs_validate_filename(const std::string & filename, bool allow_subdirs = false); bool fs_create_directory_with_parents(const std::string & path); +bool fs_is_directory(const std::string & path); std::string fs_get_cache_directory(); std::string fs_get_cache_file(const std::string & filename); @@ -649,6 +655,13 @@ struct common_file_info { }; std::vector fs_list(const std::string & path, bool include_directories); +// +// TTY utils +// + +// Auto-detect if colors can be enabled based on terminal and environment +bool tty_can_use_colors(); + // // Model utils // diff --git a/common/download.cpp b/common/download.cpp index e6ce7f11f5..ab68c53b43 100644 --- a/common/download.cpp +++ b/common/download.cpp @@ -24,6 +24,7 @@ #include "http.h" #endif +#ifndef __EMSCRIPTEN__ #ifdef __linux__ #include #elif defined(_WIN32) @@ -35,6 +36,8 @@ #else #include #endif +#endif + #define LLAMA_MAX_URL_LENGTH 2084 // Maximum URL Length in Chrome: 2083 // isatty diff --git a/common/json-schema-to-grammar.cpp b/common/json-schema-to-grammar.cpp index c8421e1e82..c3b4e5d9dc 100644 --- a/common/json-schema-to-grammar.cpp +++ b/common/json-schema-to-grammar.cpp @@ -974,7 +974,7 @@ public: void check_errors() { if (!_errors.empty()) { - throw std::runtime_error("JSON schema conversion failed:\n" + string_join(_errors, "\n")); + throw std::invalid_argument("JSON schema conversion failed:\n" + string_join(_errors, "\n")); } if (!_warnings.empty()) { fprintf(stderr, "WARNING: JSON schema conversion was incomplete: %s\n", string_join(_warnings, "; ").c_str()); diff --git a/common/log.cpp b/common/log.cpp index b6c9ff79a4..00a03f158d 100644 --- a/common/log.cpp +++ b/common/log.cpp @@ -1,3 +1,4 @@ +#include "common.h" #include "log.h" #include @@ -26,30 +27,6 @@ void common_log_set_verbosity_thold(int verbosity) { common_log_verbosity_thold = verbosity; } -// Auto-detect if colors should be enabled based on terminal and environment -static bool common_log_should_use_colors_auto() { - // Check NO_COLOR environment variable (https://no-color.org/) - if (const char * no_color = std::getenv("NO_COLOR")) { - if (no_color[0] != '\0') { - return false; - } - } - - // Check TERM environment variable - if (const char * term = std::getenv("TERM")) { - if (std::strcmp(term, "dumb") == 0) { - return false; - } - } - - // Check if stdout and stderr are connected to a terminal - // We check both because log messages can go to either - bool stdout_is_tty = isatty(fileno(stdout)); - bool stderr_is_tty = isatty(fileno(stderr)); - - return stdout_is_tty || stderr_is_tty; -} - static int64_t t_us() { return std::chrono::duration_cast(std::chrono::system_clock::now().time_since_epoch()).count(); } @@ -391,7 +368,7 @@ struct common_log * common_log_main() { static std::once_flag init_flag; std::call_once(init_flag, [&]() { // Set default to auto-detect colors - log.set_colors(common_log_should_use_colors_auto()); + log.set_colors(tty_can_use_colors()); }); return &log; @@ -422,7 +399,7 @@ void common_log_set_file(struct common_log * log, const char * file) { void common_log_set_colors(struct common_log * log, log_colors colors) { if (colors == LOG_COLORS_AUTO) { - log->set_colors(common_log_should_use_colors_auto()); + log->set_colors(tty_can_use_colors()); return; } diff --git a/common/peg-parser.cpp b/common/peg-parser.cpp new file mode 100644 index 0000000000..dec99e1820 --- /dev/null +++ b/common/peg-parser.cpp @@ -0,0 +1,1712 @@ +#include "common.h" +#include "peg-parser.h" +#include "json-schema-to-grammar.h" +#include "unicode.h" + +#include + +#include +#include +#include +#include +#include +#include +#include + +// Trick to catch missing branches +template +inline constexpr bool is_always_false_v = false; + +const char * common_peg_parse_result_type_name(common_peg_parse_result_type type) { + switch (type) { + case COMMON_PEG_PARSE_RESULT_FAIL: return "fail"; + case COMMON_PEG_PARSE_RESULT_SUCCESS: return "success"; + case COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT: return "need_more_input"; + default: return "unknown"; + } +} + +static bool is_hex_digit(const char c) { + return (c >= '0' && c <= '9') || (c >= 'a' && c <= 'f') || (c >= 'A' && c <= 'F'); +} + +// Trie for matching multiple literals. +// This is used in common_peg_until_parser and to build a GBNF exclusion grammar +struct trie { + struct node { + size_t depth = 0; + std::map children; + bool is_word; + }; + + std::vector nodes; + + trie(const std::vector & words) { + create_node(); // root node + for (const auto & w : words) { + insert(w); + } + } + + enum match_result { NO_MATCH, PARTIAL_MATCH, COMPLETE_MATCH }; + + // Check if a delimiter starts at the given position + match_result check_at(std::string_view sv, size_t start_pos) const { + size_t current = 0; // Start at root + size_t pos = start_pos; + + while (pos < sv.size()) { + auto it = nodes[current].children.find(sv[pos]); + if (it == nodes[current].children.end()) { + // Can't continue matching + return match_result{match_result::NO_MATCH}; + } + + current = it->second; + pos++; + + // Check if we've matched a complete word + if (nodes[current].is_word) { + return match_result{match_result::COMPLETE_MATCH}; + } + } + + // Reached end of input while still in the trie (not at root) + if (current != 0) { + // We're in the middle of a potential match + return match_result{match_result::PARTIAL_MATCH}; + } + + // Reached end at root (no match) + return match_result{match_result::NO_MATCH}; + } + + struct prefix_and_next { + std::string prefix; + std::string next_chars; + }; + + std::vector collect_prefix_and_next() { + std::string prefix; + std::vector result; + collect_prefix_and_next(0, prefix, result); + return result; + } + + private: + void collect_prefix_and_next(size_t index, std::string & prefix, std::vector & out) { + if (!nodes[index].is_word) { + if (!nodes[index].children.empty()) { + std::string chars; + chars.reserve(nodes[index].children.size()); + for (const auto & p : nodes[index].children) { + chars.push_back(p.first); + } + out.emplace_back(prefix_and_next{prefix, chars}); + } + } + + for (const auto & p : nodes[index].children) { + unsigned char ch = p.first; + auto child = p.second; + prefix.push_back(ch); + collect_prefix_and_next(child, prefix, out); + prefix.pop_back(); + } + } + + size_t create_node() { + size_t index = nodes.size(); + nodes.emplace_back(); + return index; + } + + void insert(const std::string & word) { + size_t current = 0; + for (unsigned char ch : word) { + auto it = nodes[current].children.find(ch); + if (it == nodes[current].children.end()) { + size_t child = create_node(); + nodes[child].depth = nodes[current].depth + 1; + nodes[current].children[ch] = child; + current = child; + } else { + current = it->second; + } + } + nodes[current].is_word = true; + } +}; + +static std::pair parse_hex_escape(const std::string & str, size_t pos, int hex_count) { + if (pos + hex_count > str.length()) { + return {0, 0}; + } + + uint32_t value = 0; + for (int i = 0; i < hex_count; i++) { + char c = str[pos + i]; + if (!is_hex_digit(c)) { + return {0, 0}; + } + value <<= 4; + if ('a' <= c && c <= 'f') { + value += c - 'a' + 10; + } else if ('A' <= c && c <= 'F') { + value += c - 'A' + 10; + } else if ('0' <= c && c <= '9') { + value += c - '0'; + } else { + break; + } + } + return {value, static_cast(hex_count)}; +} + +static std::pair parse_char_class_char(const std::string & content, size_t pos) { + if (content[pos] == '\\' && pos + 1 < content.length()) { + switch (content[pos + 1]) { + case 'x': { + auto result = parse_hex_escape(content, pos + 2, 2); + if (result.second > 0) { + return {result.first, 2 + result.second}; + } + // Invalid escape, treat as literal 'x' + return {static_cast('x'), 2}; + } + case 'u': { + auto result = parse_hex_escape(content, pos + 2, 4); + if (result.second > 0) { + return {result.first, 2 + result.second}; + } + // Invalid escape, treat as literal 'u' + return {static_cast('u'), 2}; + } + case 'U': { + auto result = parse_hex_escape(content, pos + 2, 8); + if (result.second > 0) { + return {result.first, 2 + result.second}; + } + // Invalid escape, treat as literal 'U' + return {static_cast('U'), 2}; + } + case 'n': return {'\n', 2}; + case 't': return {'\t', 2}; + case 'r': return {'\r', 2}; + case '\\': return {'\\', 2}; + case ']': return {']', 2}; + case '[': return {'[', 2}; + default: return {static_cast(content[pos + 1]), 2}; + } + } + + // Regular character - return as codepoint + return {static_cast(static_cast(content[pos])), 1}; +} + +static std::pair, bool> parse_char_classes(const std::string & classes) { + std::vector ranges; + bool negated = false; + + std::string content = classes; + if (content.front() == '[') { + content = content.substr(1); + } + + if (content.back() == ']') { + content.pop_back(); + } + + // Check for negation + if (!content.empty() && content.front() == '^') { + negated = true; + content = content.substr(1); + } + + size_t i = 0; + while (i < content.length()) { + auto [start, start_len] = parse_char_class_char(content, i); + i += start_len; + + if (i + 1 < content.length() && content[i] == '-') { + // Range detected + auto [end, end_len] = parse_char_class_char(content, i + 1); + ranges.push_back(common_peg_chars_parser::char_range{start, end}); + i += 1 + end_len; + } else { + ranges.push_back(common_peg_chars_parser::char_range{start, start}); + } + } + + return {ranges, negated}; +} + +void common_peg_ast_arena::visit(common_peg_ast_id id, const common_peg_ast_visitor & visitor) const { + if (id == COMMON_PEG_INVALID_AST_ID) { + return; + } + const auto & node = get(id); + visitor(node); + for (const auto & child : node.children) { + visit(child, visitor); + } +} + +void common_peg_ast_arena::visit(const common_peg_parse_result & result, const common_peg_ast_visitor & visitor) const { + for (const auto & node : result.nodes) { + visit(node, visitor); + } +} + +struct parser_executor; + +common_peg_parser_id common_peg_arena::add_parser(common_peg_parser_variant parser) { + common_peg_parser_id id = parsers_.size(); + parsers_.push_back(std::move(parser)); + return id; +} + +void common_peg_arena::add_rule(const std::string & name, common_peg_parser_id id) { + rules_[name] = id; +} + +common_peg_parser_id common_peg_arena::get_rule(const std::string & name) const { + auto it = rules_.find(name); + if (it == rules_.end()) { + throw std::runtime_error("Rule not found: " + name); + } + return it->second; +} + +struct parser_executor { + const common_peg_arena & arena; + common_peg_parse_context & ctx; + size_t start_pos; + + parser_executor(const common_peg_arena & arena, common_peg_parse_context & ctx, size_t start) + : arena(arena), ctx(ctx), start_pos(start) {} + + common_peg_parse_result operator()(const common_peg_epsilon_parser & /* p */) const { + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start_pos); + } + + common_peg_parse_result operator()(const common_peg_start_parser & /* p */) const { + return common_peg_parse_result( + start_pos == 0 ? COMMON_PEG_PARSE_RESULT_SUCCESS : COMMON_PEG_PARSE_RESULT_FAIL, + start_pos + ); + } + + common_peg_parse_result operator()(const common_peg_end_parser & /* p */) const { + return common_peg_parse_result( + start_pos >= ctx.input.size() ? COMMON_PEG_PARSE_RESULT_SUCCESS : COMMON_PEG_PARSE_RESULT_FAIL, + start_pos + ); + } + + common_peg_parse_result operator()(const common_peg_literal_parser & p) { + auto pos = start_pos; + for (auto i = 0u; i < p.literal.size(); ++i) { + if (pos >= ctx.input.size()) { + if (!ctx.is_partial) { + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos); + } + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, pos); + } + if (ctx.input[pos] != p.literal[i]) { + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos); + } + ++pos; + } + + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start_pos, pos); + } + + common_peg_parse_result operator()(const common_peg_sequence_parser & p) { + auto pos = start_pos; + std::vector nodes; + + for (const auto & child_id : p.children) { + auto result = arena.parse(child_id, ctx, pos); + if (result.fail()) { + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos, result.end); + } + + if (!result.nodes.empty()) { + nodes.insert(nodes.end(), result.nodes.begin(), result.nodes.end()); + } + + if (result.need_more_input()) { + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, result.end, std::move(nodes)); + } + + pos = result.end; + } + + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start_pos, pos, std::move(nodes)); + } + + common_peg_parse_result operator()(const common_peg_choice_parser & p) { + auto pos = start_pos; + for (const auto & child_id : p.children) { + auto result = arena.parse(child_id, ctx, pos); + if (!result.fail()) { + return result; + } + } + + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos); + } + + common_peg_parse_result operator()(const common_peg_repetition_parser & p) { + auto pos = start_pos; + int match_count = 0; + std::vector nodes; + + // Try to match up to max_count times (or unlimited if max_count is -1) + while (p.max_count == -1 || match_count < p.max_count) { + if (pos >= ctx.input.size()) { + break; + } + + auto result = arena.parse(p.child, ctx, pos); + + if (result.success()) { + // Prevent infinite loop on empty matches + if (result.end == pos) { + break; + } + + if (!result.nodes.empty()) { + nodes.insert(nodes.end(), result.nodes.begin(), result.nodes.end()); + } + + pos = result.end; + match_count++; + continue; + } + + if (result.need_more_input()) { + if (!result.nodes.empty()) { + nodes.insert(nodes.end(), result.nodes.begin(), result.nodes.end()); + } + + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, result.end, std::move(nodes)); + } + + // Child failed - stop trying + break; + } + + // Check if we got enough matches + if (p.min_count > 0 && match_count < p.min_count) { + if (pos >= ctx.input.size() && ctx.is_partial) { + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, pos, std::move(nodes)); + } + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos, pos); + } + + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start_pos, pos, std::move(nodes)); + } + + common_peg_parse_result operator()(const common_peg_and_parser & p) { + auto result = arena.parse(p.child, ctx, start_pos); + // Pass result but don't consume input + return common_peg_parse_result(result.type, start_pos); + } + + common_peg_parse_result operator()(const common_peg_not_parser & p) { + auto result = arena.parse(p.child, ctx, start_pos); + + if (result.success()) { + // Fail if the underlying parser matches + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos); + } + + if (result.need_more_input()) { + // Propagate - need to know what child would match before negating + return result; + } + + // Child failed, so negation succeeds + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start_pos); + } + + common_peg_parse_result operator()(const common_peg_any_parser & /* p */) const { + // Parse a single UTF-8 codepoint (not just a single byte) + auto result = parse_utf8_codepoint(ctx.input, start_pos); + + if (result.status == utf8_parse_result::INCOMPLETE) { + if (!ctx.is_partial) { + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos); + } + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos); + } + if (result.status == utf8_parse_result::INVALID) { + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos); + } + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start_pos, start_pos + result.bytes_consumed); + } + + common_peg_parse_result operator()(const common_peg_space_parser & /* p */) { + auto pos = start_pos; + while (pos < ctx.input.size()) { + auto c = static_cast(ctx.input[pos]); + if (std::isspace(c)) { + ++pos; + } else { + break; + } + } + + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start_pos, pos); + } + + common_peg_parse_result operator()(const common_peg_chars_parser & p) const { + auto pos = start_pos; + int match_count = 0; + + // Try to match up to max_count times (or unlimited if max_count is -1) + while (p.max_count == -1 || match_count < p.max_count) { + auto result = parse_utf8_codepoint(ctx.input, pos); + + if (result.status == utf8_parse_result::INCOMPLETE) { + if (match_count >= p.min_count) { + // We have enough matches, succeed with what we have + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start_pos, pos); + } + // Not enough matches yet + if (!ctx.is_partial) { + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos); + } + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, pos); + } + + if (result.status == utf8_parse_result::INVALID) { + // Malformed UTF-8 in input + if (match_count >= p.min_count) { + // We have enough matches, succeed up to here + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start_pos, pos); + } + // Not enough matches, fail + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos); + } + + // Check if this codepoint matches our character class + bool matches = false; + for (const auto & range : p.ranges) { + if (range.contains(result.codepoint)) { + matches = true; + break; + } + } + + // If negated, invert the match result + if (p.negated) { + matches = !matches; + } + + if (matches) { + pos += result.bytes_consumed; + ++match_count; + } else { + // Character doesn't match, stop matching + break; + } + } + + // Check if we got enough matches + if (match_count < p.min_count) { + if (pos >= ctx.input.size() && ctx.is_partial) { + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, pos); + } + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos, pos); + } + + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start_pos, pos); + } + + static common_peg_parse_result handle_escape_sequence(common_peg_parse_context & ctx, size_t start, size_t & pos) { + ++pos; // consume '\' + if (pos >= ctx.input.size()) { + if (!ctx.is_partial) { + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start); + } + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start, pos); + } + + switch (ctx.input[pos]) { + case '"': + case '\\': + case '/': + case 'b': + case 'f': + case 'n': + case 'r': + case 't': + ++pos; + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start, pos); + case 'u': + return handle_unicode_escape(ctx, start, pos); + default: + // Invalid escape sequence + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start); + } + } + + static common_peg_parse_result handle_unicode_escape(common_peg_parse_context & ctx, size_t start, size_t & pos) { + ++pos; // consume 'u' + for (int i = 0; i < 4; ++i) { + if (pos >= ctx.input.size()) { + if (!ctx.is_partial) { + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start); + } + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start, pos); + } + if (!is_hex_digit(ctx.input[pos])) { + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start); + } + ++pos; + } + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start, pos); + } + + common_peg_parse_result operator()(const common_peg_json_string_parser & /* p */) { + auto pos = start_pos; + + // Parse string content (without quotes) + while (pos < ctx.input.size()) { + char c = ctx.input[pos]; + + if (c == '"') { + // Found closing quote - success (don't consume it) + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start_pos, pos); + } + + if (c == '\\') { + auto result = handle_escape_sequence(ctx, start_pos, pos); + if (!result.success()) { + return result; + } + } else { + auto utf8_result = parse_utf8_codepoint(ctx.input, pos); + + if (utf8_result.status == utf8_parse_result::INCOMPLETE) { + if (!ctx.is_partial) { + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos); + } + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, pos); + } + + if (utf8_result.status == utf8_parse_result::INVALID) { + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos); + } + + pos += utf8_result.bytes_consumed; + } + } + + // Reached end without finding closing quote + if (!ctx.is_partial) { + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos, pos); + } + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, pos); + } + + common_peg_parse_result operator()(const common_peg_until_parser & p) const { + trie matcher(p.delimiters); + + // Scan input and check for delimiters + size_t pos = start_pos; + size_t last_valid_pos = start_pos; + + while (pos < ctx.input.size()) { + auto utf8_result = parse_utf8_codepoint(ctx.input, pos); + + if (utf8_result.status == utf8_parse_result::INCOMPLETE) { + // Incomplete UTF-8 sequence + if (!ctx.is_partial) { + // Input is complete but UTF-8 is incomplete = malformed + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos); + } + // Return what we have so far (before incomplete sequence) + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, last_valid_pos); + } + + if (utf8_result.status == utf8_parse_result::INVALID) { + // Malformed UTF-8 + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos); + } + + // Check if a delimiter starts at this position + auto match = matcher.check_at(ctx.input, pos); + + if (match == trie::COMPLETE_MATCH) { + // Found a complete delimiter, return everything before it + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start_pos, pos); + } + + if (match == trie::PARTIAL_MATCH) { + // Found a partial match extending to end of input, return everything before it + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start_pos, pos); + } + + pos += utf8_result.bytes_consumed; + last_valid_pos = pos; + } + + if (last_valid_pos == ctx.input.size() && ctx.is_partial) { + // Reached the end of a partial stream, there might still be more input that we need to consume. + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, last_valid_pos); + } + return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start_pos, last_valid_pos); + } + + common_peg_parse_result operator()(const common_peg_schema_parser & p) { + return arena.parse(p.child, ctx, start_pos); + } + + common_peg_parse_result operator()(const common_peg_rule_parser & p) { + // Parse the child + auto result = arena.parse(p.child, ctx, start_pos); + + if (!result.fail()) { + std::string_view text; + if (result.start < ctx.input.size()) { + text = std::string_view(ctx.input).substr(result.start, result.end - result.start); + } + + auto node_id = ctx.ast.add_node( + p.name, + "", + result.start, + result.end, + text, + std::move(result.nodes), + result.need_more_input() + ); + + return common_peg_parse_result(result.type, result.start, result.end, { node_id }); + } + + return result; + } + + common_peg_parse_result operator()(const common_peg_tag_parser & p) { + // Parse the child + auto result = arena.parse(p.child, ctx, start_pos); + + if (!result.fail()) { + std::string_view text; + if (result.start < ctx.input.size()) { + text = std::string_view(ctx.input).substr(result.start, result.end - result.start); + } + + auto node_id = ctx.ast.add_node( + "", + p.tag, + result.start, + result.end, + text, + std::move(result.nodes), + result.need_more_input() + ); + + return common_peg_parse_result(result.type, result.start, result.end, { node_id }); + } + + return result; + } + + common_peg_parse_result operator()(const common_peg_ref_parser & p) { + auto rule_id = arena.get_rule(p.name); + return arena.parse(rule_id, ctx, start_pos); + } + + common_peg_parse_result operator()(const common_peg_atomic_parser & p) { + auto result = arena.parse(p.child, ctx, start_pos); + if (result.need_more_input()) { + // Clear nodes so they don't propagate up. + result.nodes.clear(); + } + return result; + } +}; + +common_peg_parse_result common_peg_arena::parse(common_peg_parse_context & ctx, size_t start) const { + if (root_ == COMMON_PEG_INVALID_PARSER_ID) { + throw std::runtime_error("No root parser set"); + } + return parse(root_, ctx, start); +} + +common_peg_parse_result common_peg_arena::parse(common_peg_parser_id id, common_peg_parse_context & ctx, size_t start) const { + // Execute parser + const auto & parser = parsers_.at(id); + parser_executor exec(*this, ctx, start); + return std::visit(exec, parser); +} + +common_peg_parser_id common_peg_arena::resolve_ref(common_peg_parser_id id) { + const auto & parser = parsers_.at(id); + if (auto ref = std::get_if(&parser)) { + return get_rule(ref->name); + } + return id; +} + +void common_peg_arena::resolve_refs() { + // Walk through all parsers and replace refs with their corresponding rule IDs + for (auto & parser : parsers_) { + std::visit([this](auto & p) { + using T = std::decay_t; + + if constexpr (std::is_same_v) { + for (auto & child : p.children) { + child = resolve_ref(child); + } + } else if constexpr (std::is_same_v) { + for (auto & child : p.children) { + child = resolve_ref(child); + } + } else if constexpr (std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v) { + p.child = resolve_ref(p.child); + } else if constexpr (std::is_same_v) { + p.child = resolve_ref(p.child); + } else if constexpr (std::is_same_v) { + p.child = resolve_ref(p.child); + } else if constexpr (std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v) { + // These rules do not have children + } else { + static_assert(is_always_false_v); + } + }, parser); + } + + // Also flatten root if it's a ref + if (root_ != COMMON_PEG_INVALID_PARSER_ID) { + root_ = resolve_ref(root_); + } +} + +std::string common_peg_arena::dump(common_peg_parser_id id) const { + const auto & parser = parsers_.at(id); + + return std::visit([this](const auto & p) -> std::string { + using T = std::decay_t; + + if constexpr (std::is_same_v) { + return "Epsilon"; + } else if constexpr (std::is_same_v) { + return "Start"; + } else if constexpr (std::is_same_v) { + return "End"; + } else if constexpr (std::is_same_v) { + return "Literal(" + p.literal + ")"; + } else if constexpr (std::is_same_v) { + std::vector parts; + for (const auto & child : p.children) { + parts.push_back(dump(child)); + } + return "Sequence(" + string_join(parts, ", ") + ")"; + } else if constexpr (std::is_same_v) { + std::vector parts; + for (const auto & child : p.children) { + parts.push_back(dump(child)); + } + return "Choice(" + string_join(parts, ", ") + ")"; + } else if constexpr (std::is_same_v) { + if (p.max_count == -1) { + return "Repetition(" + dump(p.child) + ", " + std::to_string(p.min_count) + ", unbounded)"; + } + return "Repetition(" + dump(p.child) + ", " + std::to_string(p.min_count) + ", " + std::to_string(p.max_count) + ")"; + } else if constexpr (std::is_same_v) { + return "And(" + dump(p.child) + ")"; + } else if constexpr (std::is_same_v) { + return "Not(" + dump(p.child) + ")"; + } else if constexpr (std::is_same_v) { + return "Any"; + } else if constexpr (std::is_same_v) { + return "Space"; + } else if constexpr (std::is_same_v) { + if (p.max_count == -1) { + return "CharRepeat(" + p.pattern + ", " + std::to_string(p.min_count) + ", unbounded)"; + } + return "CharRepeat(" + p.pattern + ", " + std::to_string(p.min_count) + ", " + std::to_string(p.max_count) + ")"; + } else if constexpr (std::is_same_v) { + return "JsonString()"; + } else if constexpr (std::is_same_v) { + return "Until(" + string_join(p.delimiters, " | ") + ")"; + } else if constexpr (std::is_same_v) { + return "Schema(" + dump(p.child) + ", " + (p.schema ? p.schema->dump() : "null") + ")"; + } else if constexpr (std::is_same_v) { + return "Rule(" + p.name + ", " + dump(p.child) + ")"; + } else if constexpr (std::is_same_v) { + return "Ref(" + p.name + ")"; + } else { + return "Unknown"; + } + }, parser); +} + +common_peg_parser & common_peg_parser::operator=(const common_peg_parser & other) { + id_ = other.id_; + return *this; +} + +common_peg_parser & common_peg_parser::operator+=(const common_peg_parser & other) { + id_ = builder_.sequence({id_, other.id_}); + return *this; +} + +common_peg_parser & common_peg_parser::operator|=(const common_peg_parser & other) { + id_ = builder_.choice({id_, other.id_}); + return *this; +} + +common_peg_parser common_peg_parser::operator+(const common_peg_parser & other) const { + return builder_.sequence({id_, other.id_}); +} + +common_peg_parser common_peg_parser::operator|(const common_peg_parser & other) const { + return builder_.choice({id_, other.id_}); +} + +common_peg_parser common_peg_parser::operator<<(const common_peg_parser & other) const { + return builder_.sequence({id_, builder_.space(), other.id_}); +} + +common_peg_parser common_peg_parser::operator+(const char * str) const { + return *this + builder_.literal(str); +} + +common_peg_parser common_peg_parser::operator+(const std::string & str) const { + return *this + builder_.literal(str); +} + +common_peg_parser common_peg_parser::operator<<(const char * str) const { + return *this << builder_.literal(str); +} + +common_peg_parser common_peg_parser::operator<<(const std::string & str) const { + return *this << builder_.literal(str); +} + +common_peg_parser common_peg_parser::operator|(const char * str) const { + return *this | builder_.literal(str); +} + +common_peg_parser common_peg_parser::operator|(const std::string & str) const { + return *this | builder_.literal(str); +} + +common_peg_parser operator+(const char * str, const common_peg_parser & p) { + return p.builder().literal(str) + p; +} + +common_peg_parser operator+(const std::string & str, const common_peg_parser & p) { + return operator+(str.c_str(), p); +} + +common_peg_parser operator<<(const char * str, const common_peg_parser & p) { + return p.builder().literal(str) << p; +} + +common_peg_parser operator<<(const std::string & str, const common_peg_parser & p) { + return operator<<(str.c_str(), p); +} + +common_peg_parser operator|(const char * str, const common_peg_parser & p) { + return p.builder().literal(str) | p; +} + +common_peg_parser operator|(const std::string & str, const common_peg_parser & p) { + return operator|(str.c_str(), p); +} + +static std::string rule_name(const std::string & name) { + static const std::regex invalid_rule_chars_re("[^a-zA-Z0-9-]+"); + return std::regex_replace(name, invalid_rule_chars_re, "-"); +} + +common_peg_parser_builder::common_peg_parser_builder() {} + +common_peg_parser common_peg_parser_builder::sequence(const std::vector & parsers) { + // Flatten nested sequences + std::vector flattened; + for (const auto & p : parsers) { + const auto & parser = arena_.get(p); + if (auto seq = std::get_if(&parser)) { + flattened.insert(flattened.end(), seq->children.begin(), seq->children.end()); + } else { + flattened.push_back(p); + } + } + return wrap(arena_.add_parser(common_peg_sequence_parser{flattened})); +} + +common_peg_parser common_peg_parser_builder::sequence(const std::vector & parsers) { + std::vector ids; + ids.reserve(parsers.size()); + for (const auto & p : parsers) { + ids.push_back(p.id()); + } + return sequence(ids); +} + +common_peg_parser common_peg_parser_builder::sequence(std::initializer_list parsers) { + std::vector ids; + ids.reserve(parsers.size()); + for (const auto & p : parsers) { + ids.push_back(p.id()); + } + return sequence(ids); +} + +common_peg_parser common_peg_parser_builder::choice(const std::vector & parsers) { + // Flatten nested choices + std::vector flattened; + for (const auto & p : parsers) { + const auto & parser = arena_.get(p); + if (auto choice = std::get_if(&parser)) { + flattened.insert(flattened.end(), choice->children.begin(), choice->children.end()); + } else { + flattened.push_back(p); + } + } + return wrap(arena_.add_parser(common_peg_choice_parser{flattened})); +} + +common_peg_parser common_peg_parser_builder::choice(const std::vector & parsers) { + std::vector ids; + ids.reserve(parsers.size()); + for (const auto & p : parsers) { + ids.push_back(p.id()); + } + return choice(ids); +} + +common_peg_parser common_peg_parser_builder::choice(std::initializer_list parsers) { + std::vector ids; + ids.reserve(parsers.size()); + for (const auto & p : parsers) { + ids.push_back(p.id()); + } + return choice(ids); +} + +common_peg_parser common_peg_parser_builder::chars(const std::string & classes, int min, int max) { + auto [ranges, negated] = parse_char_classes(classes); + return wrap(arena_.add_parser(common_peg_chars_parser{classes, ranges, negated, min, max})); +} + +common_peg_parser common_peg_parser_builder::schema(const common_peg_parser & p, const std::string & name, const nlohmann::ordered_json & schema, bool raw) { + return wrap(arena_.add_parser(common_peg_schema_parser{p.id(), name, std::make_shared(schema), raw})); +} + +common_peg_parser common_peg_parser_builder::rule(const std::string & name, const common_peg_parser & p, bool trigger) { + auto clean_name = rule_name(name); + auto rule_id = arena_.add_parser(common_peg_rule_parser{clean_name, p.id(), trigger}); + arena_.add_rule(clean_name, rule_id); + return ref(clean_name); +} + +common_peg_parser common_peg_parser_builder::rule(const std::string & name, const std::function & builder_fn, bool trigger) { + auto clean_name = rule_name(name); + if (arena_.has_rule(clean_name)) { + return ref(clean_name); + } + + // Create placeholder rule to allow recursive references + auto placeholder = any(); // Temporary placeholder + auto placeholder_rule_id = arena_.add_parser(common_peg_rule_parser{clean_name, placeholder.id(), trigger}); + arena_.add_rule(clean_name, placeholder_rule_id); + + // Build the actual parser + auto parser = builder_fn(); + + // Replace placeholder with actual rule + auto rule_id = arena_.add_parser(common_peg_rule_parser{clean_name, parser.id(), trigger}); + arena_.rules_[clean_name] = rule_id; + + return ref(clean_name); +} + +void common_peg_parser_builder::set_root(const common_peg_parser & p) { + arena_.set_root(p.id()); +} + +common_peg_arena common_peg_parser_builder::build() { + arena_.resolve_refs(); + return std::move(arena_); +} + +// JSON parsers +common_peg_parser common_peg_parser_builder::json_number() { + return rule("json-number", [this]() { + auto digit1_9 = chars("[1-9]", 1, 1); + auto digits = chars("[0-9]"); + auto int_part = choice({literal("0"), sequence({digit1_9, chars("[0-9]", 0, -1)})}); + auto frac = sequence({literal("."), digits}); + auto exp = sequence({choice({literal("e"), literal("E")}), optional(chars("[+-]", 1, 1)), digits}); + return sequence({optional(literal("-")), int_part, optional(frac), optional(exp), space()}); + }); +} + +common_peg_parser common_peg_parser_builder::json_string() { + return rule("json-string", [this]() { + return sequence({literal("\""), json_string_content(), literal("\""), space()}); + }); +} + +common_peg_parser common_peg_parser_builder::json_bool() { + return rule("json-bool", [this]() { + return sequence({choice({literal("true"), literal("false")}), space()}); + }); +} + +common_peg_parser common_peg_parser_builder::json_null() { + return rule("json-null", [this]() { + return sequence({literal("null"), space()}); + }); +} + +common_peg_parser common_peg_parser_builder::json_object() { + return rule("json-object", [this]() { + auto ws = space(); + auto member = sequence({json_string(), ws, literal(":"), ws, json()}); + auto members = sequence({member, zero_or_more(sequence({ws, literal(","), ws, member}))}); + return sequence({ + literal("{"), + ws, + choice({ + literal("}"), + sequence({members, ws, literal("}")}) + }), + ws + }); + }); +} + +common_peg_parser common_peg_parser_builder::json_array() { + return rule("json-array", [this]() { + auto ws = space(); + auto elements = sequence({json(), zero_or_more(sequence({literal(","), ws, json()}))}); + return sequence({ + literal("["), + ws, + choice({ + literal("]"), + sequence({elements, ws, literal("]")}) + }), + ws + }); + }); +} + +common_peg_parser common_peg_parser_builder::json() { + return rule("json-value", [this]() { + return choice({ + json_object(), + json_array(), + json_string(), + json_number(), + json_bool(), + json_null() + }); + }); +} + +common_peg_parser common_peg_parser_builder::json_string_content() { + return wrap(arena_.add_parser(common_peg_json_string_parser{})); +} + +common_peg_parser common_peg_parser_builder::json_member(const std::string & key, const common_peg_parser & p) { + auto ws = space(); + return sequence({ + literal("\"" + key + "\""), + ws, + literal(":"), + ws, + p, + }); +} + + +static std::string gbnf_escape_char_class(char c) { + switch (c) { + case '\n': return "\\n"; + case '\t': return "\\t"; + case '\r': return "\\r"; + case '\\': return "\\\\"; + case ']': return "\\]"; + case '[': return "\\["; + default: return std::string(1, c); + } +} + +static std::string gbnf_excluding_pattern(const std::vector & strings) { + trie matcher(strings); + auto pieces = matcher.collect_prefix_and_next(); + + std::string pattern; + for (size_t i = 0; i < pieces.size(); ++i) { + if (i > 0) { + pattern += " | "; + } + + const auto & pre = pieces[i].prefix; + const auto & chars = pieces[i].next_chars; + + std::string cls; + cls.reserve(chars.size()); + for (const auto & ch : chars) { + cls += gbnf_escape_char_class(ch); + } + + if (!pre.empty()) { + pattern += gbnf_format_literal(pre) + " [^" + cls + "]"; + } else { + pattern += "[^" + cls + "]"; + } + } + + return "(" + pattern + ")*"; +} + +static std::unordered_set collect_reachable_rules( + const common_peg_arena & arena, + const common_peg_parser_id & rule +) { + std::unordered_set reachable; + std::unordered_set visited; + + std::function visit = [&](common_peg_parser_id id) { + const auto & parser = arena.get(id); + + std::visit([&](const auto & p) { + using T = std::decay_t; + + if constexpr (std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v) { + // These parsers do not have any children + } else if constexpr (std::is_same_v) { + for (auto child : p.children) { + visit(child); + } + } else if constexpr (std::is_same_v) { + for (auto child : p.children) { + visit(child); + } + } else if constexpr (std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v) { + visit(p.child); + } else if constexpr (std::is_same_v) { + if (visited.find(p.name) == visited.end()) { + visited.insert(p.name); + reachable.insert(p.name); + visit(p.child); + } + } else if constexpr (std::is_same_v) { + // Traverse rules so we pick up everything + auto referenced_rule = arena.get_rule(p.name); + visit(referenced_rule); + } else { + static_assert(is_always_false_v); + } + }, parser); + }; + + visit(rule); + return reachable; +} + +// GBNF generation implementation +void common_peg_arena::build_grammar(const common_grammar_builder & builder, bool lazy) const { + // Generate GBNF for a parser + std::function to_gbnf = [&](common_peg_parser_id id) -> std::string { + const auto & parser = parsers_.at(id); + + return std::visit([&](const auto & p) -> std::string { + using T = std::decay_t; + + if constexpr (std::is_same_v || + std::is_same_v || + std::is_same_v) { + return ""; + } else if constexpr (std::is_same_v) { + return gbnf_format_literal(p.literal); + } else if constexpr (std::is_same_v) { + std::string s; + for (const auto & child : p.children) { + if (!s.empty()) { + s += " "; + } + auto child_gbnf = to_gbnf(child); + const auto & child_parser = parsers_.at(child); + if (std::holds_alternative(child_parser) || + std::holds_alternative(child_parser)) { + s += "(" + child_gbnf + ")"; + } else { + s += child_gbnf; + } + } + return s; + } else if constexpr (std::is_same_v) { + std::string s; + for (const auto & child : p.children) { + if (!s.empty()) { + s += " | "; + } + auto child_gbnf = to_gbnf(child); + const auto & child_parser = parsers_.at(child); + if (std::holds_alternative(child_parser)) { + s += "(" + child_gbnf + ")"; + } else { + s += child_gbnf; + } + } + return s; + } else if constexpr (std::is_same_v) { + auto child_gbnf = to_gbnf(p.child); + const auto & child_parser = parsers_.at(p.child); + if (std::holds_alternative(child_parser) || + std::holds_alternative(child_parser)) { + child_gbnf = "(" + child_gbnf + ")"; + } + if (p.min_count == 0 && p.max_count == 1) { + return child_gbnf + "?"; + } + if (p.min_count == 0 && p.max_count == -1) { + return child_gbnf + "*"; + } + if (p.min_count == 1 && p.max_count == -1) { + return child_gbnf + "+"; + } + if (p.max_count == -1) { + return child_gbnf + "{" + std::to_string(p.min_count) + ",}"; + } + if (p.min_count == p.max_count) { + if (p.min_count == 1) { + return child_gbnf; + } + return child_gbnf + "{" + std::to_string(p.min_count) + "}"; + } + return child_gbnf + "{" + std::to_string(p.min_count) + "," + std::to_string(p.max_count) + "}"; + } else if constexpr (std::is_same_v || std::is_same_v) { + return ""; // Lookahead not supported in GBNF + } else if constexpr (std::is_same_v) { + return "."; + } else if constexpr (std::is_same_v) { + return "space"; + } else if constexpr (std::is_same_v) { + std::string result = p.pattern; + if (p.min_count == 0 && p.max_count == 1) { + return result + "?"; + } + if (p.min_count == 0 && p.max_count == -1) { + return result + "*"; + } + if (p.min_count == 1 && p.max_count == -1) { + return result + "+"; + } + if (p.max_count == -1) { + return result + "{" + std::to_string(p.min_count) + ",}"; + } + if (p.min_count == p.max_count) { + if (p.min_count == 1) { + return result; + } + return result + "{" + std::to_string(p.min_count) + "}"; + } + return result + "{" + std::to_string(p.min_count) + "," + std::to_string(p.max_count) + "}"; + } else if constexpr (std::is_same_v) { + return R"(( [^"\\] | "\\" ( ["\\/ bfnrt] | "u" [0-9a-fA-F]{4} ) )*)"; + } else if constexpr (std::is_same_v) { + if (p.delimiters.empty()) { + return ".*"; + } + return gbnf_excluding_pattern(p.delimiters); + } else if constexpr (std::is_same_v) { + if (p.schema) { + if (p.raw && p.schema->contains("type") && p.schema->at("type").is_string() && p.schema->at("type") == "string") { + // TODO: Implement more comprehensive grammar generation for raw strings. + // For now, use the grammar emitted from the underlying parser. + return to_gbnf(p.child); + } + return builder.add_schema(p.name, *p.schema); + } + return to_gbnf(p.child); + } else if constexpr (std::is_same_v) { + return p.name; + } else if constexpr (std::is_same_v) { + // Refs should not exist after flattening, but kept just in case + return p.name; + } else if constexpr (std::is_same_v) { + return to_gbnf(p.child); + } else if constexpr (std::is_same_v) { + return to_gbnf(p.child); + } else { + static_assert(is_always_false_v); + } + }, parser); + }; + + // Collect reachable rules + std::unordered_set reachable_rules; + + if (lazy) { + // Collect rules reachable from trigger rules + for (const auto & [name, id] : rules_) { + const auto & parser = parsers_.at(id); + if (auto rule = std::get_if(&parser)) { + if (rule->trigger) { + // Mark trigger as reachable and visit it + reachable_rules.insert(name); + auto add_rules = collect_reachable_rules(*this, id); + reachable_rules.insert(add_rules.begin(), add_rules.end()); + } + } + } + } else { + // Collect rules reachable from root + reachable_rules = collect_reachable_rules(*this, root_); + } + + // Create GBNF rules for all reachable rules + for (const auto & [name, rule_id] : rules_) { + if (reachable_rules.find(name) == reachable_rules.end()) { + continue; + } + + const auto & parser = parsers_.at(rule_id); + if (auto rule = std::get_if(&parser)) { + builder.add_rule(rule->name, to_gbnf(rule->child)); + } + } + + if (lazy) { + // Generate root rule from trigger rules only + std::vector trigger_names; + for (const auto & [name, rule_id] : rules_) { + const auto & parser = parsers_.at(rule_id); + if (auto rule = std::get_if(&parser)) { + if (rule->trigger) { + trigger_names.push_back(rule->name); + } + } + } + + // Sort for predictable order + std::sort(trigger_names.begin(), trigger_names.end()); + builder.add_rule("root", string_join(trigger_names, " | ")); + } else if (root_ != COMMON_PEG_INVALID_PARSER_ID) { + builder.add_rule("root", to_gbnf(root_)); + } +} + +static nlohmann::json serialize_parser_variant(const common_peg_parser_variant & variant) { + using json = nlohmann::json; + + return std::visit([](const auto & p) -> json { + using T = std::decay_t; + + if constexpr (std::is_same_v) { + return json{{"type", "epsilon"}}; + } else if constexpr (std::is_same_v) { + return json{{"type", "start"}}; + } else if constexpr (std::is_same_v) { + return json{{"type", "end"}}; + } else if constexpr (std::is_same_v) { + return json{{"type", "literal"}, {"literal", p.literal}}; + } else if constexpr (std::is_same_v) { + return json{{"type", "sequence"}, {"children", p.children}}; + } else if constexpr (std::is_same_v) { + return json{{"type", "choice"}, {"children", p.children}}; + } else if constexpr (std::is_same_v) { + return json{ + {"type", "repetition"}, + {"child", p.child}, + {"min_count", p.min_count}, + {"max_count", p.max_count} + }; + } else if constexpr (std::is_same_v) { + return json{{"type", "and"}, {"child", p.child}}; + } else if constexpr (std::is_same_v) { + return json{{"type", "not"}, {"child", p.child}}; + } else if constexpr (std::is_same_v) { + return json{{"type", "any"}}; + } else if constexpr (std::is_same_v) { + return json{{"type", "space"}}; + } else if constexpr (std::is_same_v) { + json ranges = json::array(); + for (const auto & range : p.ranges) { + ranges.push_back({{"start", range.start}, {"end", range.end}}); + } + return json{ + {"type", "chars"}, + {"pattern", p.pattern}, + {"ranges", ranges}, + {"negated", p.negated}, + {"min_count", p.min_count}, + {"max_count", p.max_count} + }; + } else if constexpr (std::is_same_v) { + return json{{"type", "json_string"}}; + } else if constexpr (std::is_same_v) { + return json{{"type", "until"}, {"delimiters", p.delimiters}}; + } else if constexpr (std::is_same_v) { + return json{ + {"type", "schema"}, + {"child", p.child}, + {"name", p.name}, + {"schema", p.schema ? *p.schema : nullptr}, + {"raw", p.raw} + }; + } else if constexpr (std::is_same_v) { + return json{ + {"type", "rule"}, + {"name", p.name}, + {"child", p.child}, + {"trigger", p.trigger} + }; + } else if constexpr (std::is_same_v) { + return json{{"type", "ref"}, {"name", p.name}}; + } else if constexpr (std::is_same_v) { + return json{{"type", "atomic"}, {"child", p.child}}; + } else if constexpr (std::is_same_v) { + return json{ + {"type", "tag"}, + {"child", p.child}, + {"tag", p.tag} + }; + } + }, variant); +} + +nlohmann::json common_peg_arena::to_json() const { + auto parsers = nlohmann::json::array(); + for (const auto & parser : parsers_) { + parsers.push_back(serialize_parser_variant(parser)); + } + return nlohmann::json{ + {"parsers", parsers}, + {"rules", rules_}, + {"root", root_} + }; +} + +static common_peg_parser_variant deserialize_parser_variant(const nlohmann::json & j) { + if (!j.contains("type") || !j["type"].is_string()) { + throw std::runtime_error("Parser variant JSON missing or invalid 'type' field"); + } + + std::string type = j["type"]; + + if (type == "epsilon") { + return common_peg_epsilon_parser{}; + } + if (type == "start") { + return common_peg_start_parser{}; + } + if (type == "end") { + return common_peg_end_parser{}; + } + if (type == "literal") { + if (!j.contains("literal") || !j["literal"].is_string()) { + throw std::runtime_error("literal parser missing or invalid 'literal' field"); + } + return common_peg_literal_parser{j["literal"]}; + } + if (type == "sequence") { + if (!j.contains("children") || !j["children"].is_array()) { + throw std::runtime_error("sequence parser missing or invalid 'children' field"); + } + return common_peg_sequence_parser{j["children"].get>()}; + } + if (type == "choice") { + if (!j.contains("children") || !j["children"].is_array()) { + throw std::runtime_error("choice parser missing or invalid 'children' field"); + } + return common_peg_choice_parser{j["children"].get>()}; + } + if (type == "repetition") { + if (!j.contains("child") || !j.contains("min_count") || !j.contains("max_count")) { + throw std::runtime_error("repetition parser missing required fields"); + } + return common_peg_repetition_parser{ + j["child"].get(), + j["min_count"].get(), + j["max_count"].get() + }; + } + if (type == "and") { + if (!j.contains("child")) { + throw std::runtime_error("and parser missing 'child' field"); + } + return common_peg_and_parser{j["child"].get()}; + } + if (type == "not") { + if (!j.contains("child")) { + throw std::runtime_error("not parser missing 'child' field"); + } + return common_peg_not_parser{j["child"].get()}; + } + if (type == "any") { + return common_peg_any_parser{}; + } + if (type == "space") { + return common_peg_space_parser{}; + } + if (type == "chars") { + if (!j.contains("pattern") || !j.contains("ranges") || !j.contains("negated") || + !j.contains("min_count") || !j.contains("max_count")) { + throw std::runtime_error("chars parser missing required fields"); + } + common_peg_chars_parser parser; + parser.pattern = j["pattern"]; + parser.negated = j["negated"]; + parser.min_count = j["min_count"]; + parser.max_count = j["max_count"]; + for (const auto & range_json : j["ranges"]) { + if (!range_json.contains("start") || !range_json.contains("end")) { + throw std::runtime_error("char_range missing 'start' or 'end' field"); + } + parser.ranges.push_back({ + range_json["start"].get(), + range_json["end"].get() + }); + } + return parser; + } + if (type == "json_string") { + return common_peg_json_string_parser{}; + } + if (type == "until") { + if (!j.contains("delimiters") || !j["delimiters"].is_array()) { + throw std::runtime_error("until parser missing or invalid 'delimiters' field"); + } + return common_peg_until_parser{j["delimiters"].get>()}; + } + if (type == "schema") { + if (!j.contains("child") || !j.contains("name") || !j.contains("schema") || !j.contains("raw")) { + throw std::runtime_error("schema parser missing required fields"); + } + common_peg_schema_parser parser; + parser.child = j["child"].get(); + parser.name = j["name"]; + if (!j["schema"].is_null()) { + parser.schema = std::make_shared(j["schema"]); + } + parser.raw = j["raw"].get(); + return parser; + } + if (type == "rule") { + if (!j.contains("name") || !j.contains("child") || !j.contains("trigger")) { + throw std::runtime_error("rule parser missing required fields"); + } + return common_peg_rule_parser{ + j["name"].get(), + j["child"].get(), + j["trigger"].get() + }; + } + if (type == "ref") { + if (!j.contains("name") || !j["name"].is_string()) { + throw std::runtime_error("ref parser missing or invalid 'name' field"); + } + return common_peg_ref_parser{j["name"]}; + } + if (type == "atomic") { + if (!j.contains("child")) { + throw std::runtime_error("tag parser missing required fields"); + } + return common_peg_atomic_parser{ + j["child"].get(), + }; + } + if (type == "tag") { + if (!j.contains("child") || !j.contains("tag")) { + throw std::runtime_error("tag parser missing required fields"); + } + return common_peg_tag_parser{ + j["child"].get(), + j["tag"].get(), + }; + } + + throw std::runtime_error("Unknown parser type: " + type); +} + +common_peg_arena common_peg_arena::from_json(const nlohmann::json & j) { + if (!j.contains("parsers") || !j["parsers"].is_array()) { + throw std::runtime_error("JSON missing or invalid 'parsers' array"); + } + if (!j.contains("rules") || !j["rules"].is_object()) { + throw std::runtime_error("JSON missing or invalid 'rules' object"); + } + if (!j.contains("root")) { + throw std::runtime_error("JSON missing 'root' field"); + } + + common_peg_arena arena; + + const auto & parsers_json = j["parsers"]; + arena.parsers_.reserve(parsers_json.size()); + for (const auto & parser_json : parsers_json) { + arena.parsers_.push_back(deserialize_parser_variant(parser_json)); + } + + arena.rules_ = j["rules"].get>(); + + for (const auto & [name, id] : arena.rules_) { + if (id >= arena.parsers_.size()) { + throw std::runtime_error("Rule '" + name + "' references invalid parser ID: " + std::to_string(id)); + } + } + + arena.root_ = j["root"].get(); + if (arena.root_ != COMMON_PEG_INVALID_PARSER_ID && arena.root_ >= arena.parsers_.size()) { + throw std::runtime_error("Root references invalid parser ID: " + std::to_string(arena.root_)); + } + + return arena; +} + +std::string common_peg_arena::save() const { + return to_json().dump(); +} + +void common_peg_arena::load(const std::string & data) { + *this = from_json(nlohmann::json::parse(data)); +} + +common_peg_arena build_peg_parser(const std::function & fn) { + common_peg_parser_builder builder; + builder.set_root(fn(builder)); + return builder.build(); +} diff --git a/common/peg-parser.h b/common/peg-parser.h new file mode 100644 index 0000000000..1cd640365f --- /dev/null +++ b/common/peg-parser.h @@ -0,0 +1,459 @@ +#pragma once + +#include + +#include +#include +#include +#include +#include +#include +#include + +struct common_grammar_builder; + +class common_peg_parser_builder; + +using common_peg_parser_id = size_t; +constexpr common_peg_parser_id COMMON_PEG_INVALID_PARSER_ID = static_cast(-1); + +using common_peg_ast_id = size_t; +constexpr common_peg_ast_id COMMON_PEG_INVALID_AST_ID = static_cast(-1); + +// Lightweight wrapper around common_peg_parser_id for convenience +class common_peg_parser { + common_peg_parser_id id_; + common_peg_parser_builder & builder_; + + public: + common_peg_parser(const common_peg_parser & other) : id_(other.id_), builder_(other.builder_) {} + common_peg_parser(common_peg_parser_id id, common_peg_parser_builder & builder) : id_(id), builder_(builder) {} + + common_peg_parser & operator=(const common_peg_parser & other); + common_peg_parser & operator+=(const common_peg_parser & other); + common_peg_parser & operator|=(const common_peg_parser & other); + + operator common_peg_parser_id() const { return id_; } + common_peg_parser_id id() const { return id_; } + + common_peg_parser_builder & builder() const { return builder_; } + + // Creates a sequence + common_peg_parser operator+(const common_peg_parser & other) const; + + // Creates a sequence separated by spaces. + common_peg_parser operator<<(const common_peg_parser & other) const; + + // Creates a choice + common_peg_parser operator|(const common_peg_parser & other) const; + + common_peg_parser operator+(const char * str) const; + common_peg_parser operator+(const std::string & str) const; + common_peg_parser operator<<(const char * str) const; + common_peg_parser operator<<(const std::string & str) const; + common_peg_parser operator|(const char * str) const; + common_peg_parser operator|(const std::string & str) const; +}; + +common_peg_parser operator+(const char * str, const common_peg_parser & p); +common_peg_parser operator+(const std::string & str, const common_peg_parser & p); +common_peg_parser operator<<(const char * str, const common_peg_parser & p); +common_peg_parser operator<<(const std::string & str, const common_peg_parser & p); +common_peg_parser operator|(const char * str, const common_peg_parser & p); +common_peg_parser operator|(const std::string & str, const common_peg_parser & p); + +enum common_peg_parse_result_type { + COMMON_PEG_PARSE_RESULT_FAIL = 0, + COMMON_PEG_PARSE_RESULT_SUCCESS = 1, + COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT = 2, +}; + +const char * common_peg_parse_result_type_name(common_peg_parse_result_type type); + +struct common_peg_ast_node { + common_peg_ast_id id; + std::string rule; + std::string tag; + size_t start; + size_t end; + std::string_view text; + std::vector children; + + bool is_partial = false; +}; + +struct common_peg_parse_result; + +using common_peg_ast_visitor = std::function; + +class common_peg_ast_arena { + std::vector nodes_; + public: + common_peg_ast_id add_node( + const std::string & rule, + const std::string & tag, + size_t start, + size_t end, + std::string_view text, + std::vector children, + bool is_partial = false + ) { + common_peg_ast_id id = nodes_.size(); + nodes_.push_back({id, rule, tag, start, end, text, std::move(children), is_partial}); + return id; + } + + const common_peg_ast_node & get(common_peg_ast_id id) const { return nodes_.at(id); } + + size_t size() const { return nodes_.size(); } + + void clear() { nodes_.clear(); } + + void visit(common_peg_ast_id id, const common_peg_ast_visitor & visitor) const; + void visit(const common_peg_parse_result & result, const common_peg_ast_visitor & visitor) const; +}; + +struct common_peg_parse_result { + common_peg_parse_result_type type = COMMON_PEG_PARSE_RESULT_FAIL; + size_t start = 0; + size_t end = 0; + + std::vector nodes; + + common_peg_parse_result() = default; + + common_peg_parse_result(common_peg_parse_result_type type, size_t start) + : type(type), start(start), end(start) {} + + common_peg_parse_result(common_peg_parse_result_type type, size_t start, size_t end) + : type(type), start(start), end(end) {} + + common_peg_parse_result(common_peg_parse_result_type type, size_t start, size_t end, std::vector nodes) + : type(type), start(start), end(end), nodes(std::move(nodes)) {} + + bool fail() const { return type == COMMON_PEG_PARSE_RESULT_FAIL; } + bool need_more_input() const { return type == COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT; } + bool success() const { return type == COMMON_PEG_PARSE_RESULT_SUCCESS; } +}; + +struct common_peg_parse_context { + std::string input; + bool is_partial; + common_peg_ast_arena ast; + + int parse_depth; + + common_peg_parse_context() + : is_partial(false), parse_depth(0) {} + + common_peg_parse_context(const std::string & input) + : input(input), is_partial(false), parse_depth(0) {} + + common_peg_parse_context(const std::string & input, bool is_partial) + : input(input), is_partial(is_partial), parse_depth(0) {} +}; + +class common_peg_arena; + +// Parser variants +struct common_peg_epsilon_parser {}; + +struct common_peg_start_parser {}; + +struct common_peg_end_parser {}; + +struct common_peg_literal_parser { + std::string literal; +}; + +struct common_peg_sequence_parser { + std::vector children; +}; + +struct common_peg_choice_parser { + std::vector children; +}; + +struct common_peg_repetition_parser { + common_peg_parser_id child; + int min_count; + int max_count; // -1 for unbounded +}; + +struct common_peg_and_parser { + common_peg_parser_id child; +}; + +struct common_peg_not_parser { + common_peg_parser_id child; +}; + +struct common_peg_any_parser {}; + +struct common_peg_space_parser {}; + +struct common_peg_chars_parser { + struct char_range { + uint32_t start; + uint32_t end; + bool contains(uint32_t codepoint) const { return codepoint >= start && codepoint <= end; } + }; + + std::string pattern; + std::vector ranges; + bool negated; + int min_count; + int max_count; // -1 for unbounded +}; + +struct common_peg_json_string_parser {}; + +struct common_peg_until_parser { + std::vector delimiters; +}; + +struct common_peg_schema_parser { + common_peg_parser_id child; + std::string name; + std::shared_ptr schema; + + // Indicates if the GBNF should accept a raw string that matches the schema. + bool raw; +}; + +struct common_peg_rule_parser { + std::string name; + common_peg_parser_id child; + bool trigger; +}; + +struct common_peg_ref_parser { + std::string name; +}; + +struct common_peg_atomic_parser { + common_peg_parser_id child; +}; + +struct common_peg_tag_parser { + common_peg_parser_id child; + std::string tag; +}; + +// Variant holding all parser types +using common_peg_parser_variant = std::variant< + common_peg_epsilon_parser, + common_peg_start_parser, + common_peg_end_parser, + common_peg_literal_parser, + common_peg_sequence_parser, + common_peg_choice_parser, + common_peg_repetition_parser, + common_peg_and_parser, + common_peg_not_parser, + common_peg_any_parser, + common_peg_space_parser, + common_peg_chars_parser, + common_peg_json_string_parser, + common_peg_until_parser, + common_peg_schema_parser, + common_peg_rule_parser, + common_peg_ref_parser, + common_peg_atomic_parser, + common_peg_tag_parser +>; + +class common_peg_arena { + std::vector parsers_; + std::unordered_map rules_; + common_peg_parser_id root_ = COMMON_PEG_INVALID_PARSER_ID; + + public: + const common_peg_parser_variant & get(common_peg_parser_id id) const { return parsers_.at(id); } + common_peg_parser_variant & get(common_peg_parser_id id) { return parsers_.at(id); } + + size_t size() const { return parsers_.size(); } + bool empty() const { return parsers_.empty(); } + + common_peg_parser_id get_rule(const std::string & name) const; + bool has_rule(const std::string & name) const { return rules_.find(name) != rules_.end(); } + + common_peg_parser_id root() const { return root_; } + void set_root(common_peg_parser_id id) { root_ = id; } + + common_peg_parse_result parse(common_peg_parse_context & ctx, size_t start = 0) const; + common_peg_parse_result parse(common_peg_parser_id id, common_peg_parse_context & ctx, size_t start) const; + + void resolve_refs(); + + void build_grammar(const common_grammar_builder & builder, bool lazy = false) const; + + std::string dump(common_peg_parser_id id) const; + + nlohmann::json to_json() const; + static common_peg_arena from_json(const nlohmann::json & j); + + std::string save() const; + void load(const std::string & data); + + friend class common_peg_parser_builder; + + private: + common_peg_parser_id add_parser(common_peg_parser_variant parser); + void add_rule(const std::string & name, common_peg_parser_id id); + + common_peg_parser_id resolve_ref(common_peg_parser_id id); +}; + +class common_peg_parser_builder { + common_peg_arena arena_; + + common_peg_parser wrap(common_peg_parser_id id) { return common_peg_parser(id, *this); } + common_peg_parser add(const common_peg_parser_variant & p) { return wrap(arena_.add_parser(p)); } + + public: + common_peg_parser_builder(); + + // Match nothing, always succeed. + // S -> ε + common_peg_parser eps() { return add(common_peg_epsilon_parser{}); } + + // Matches the start of the input. + // S -> ^ + common_peg_parser start() { return add(common_peg_start_parser{}); } + + // Matches the end of the input. + // S -> $ + common_peg_parser end() { return add(common_peg_end_parser{}); } + + // Matches an exact literal string. + // S -> "hello" + common_peg_parser literal(const std::string & literal) { return add(common_peg_literal_parser{literal}); } + + // Matches a sequence of parsers in order, all must succeed. + // S -> A B C + common_peg_parser sequence() { return add(common_peg_sequence_parser{}); } + common_peg_parser sequence(const std::vector & parsers); + common_peg_parser sequence(const std::vector & parsers); + common_peg_parser sequence(std::initializer_list parsers); + + // Matches the first parser that succeeds from a list of alternatives. + // S -> A | B | C + common_peg_parser choice() { return add(common_peg_choice_parser{}); } + common_peg_parser choice(const std::vector & parsers); + common_peg_parser choice(const std::vector & parsers); + common_peg_parser choice(std::initializer_list parsers); + + // Matches one or more repetitions of a parser. + // S -> A+ + common_peg_parser one_or_more(const common_peg_parser & p) { return repeat(p, 1, -1); } + + // Matches zero or more repetitions of a parser, always succeeds. + // S -> A* + common_peg_parser zero_or_more(const common_peg_parser & p) { return repeat(p, 0, -1); } + + // Matches zero or one occurrence of a parser, always succeeds. + // S -> A? + common_peg_parser optional(const common_peg_parser & p) { return repeat(p, 0, 1); } + + // Positive lookahead: succeeds if child parser succeeds, consumes no input. + // S -> &A + common_peg_parser peek(const common_peg_parser & p) { return add(common_peg_and_parser{p}); } + + // Negative lookahead: succeeds if child parser fails, consumes no input. + // S -> !A + common_peg_parser negate(const common_peg_parser & p) { return add(common_peg_not_parser{p}); } + + // Matches any single character. + // S -> . + common_peg_parser any() { return add(common_peg_any_parser{}); } + + // Matches between min and max repetitions of characters from a character class. + // S -> [a-z]{m,n} + // + // Use -1 for max to represent unbounded repetition (equivalent to {m,}) + common_peg_parser chars(const std::string & classes, int min = 1, int max = -1); + + // Creates a lightweight reference to a named rule (resolved during build()). + // Use this for forward references in recursive grammars. + // expr_ref -> expr + common_peg_parser ref(const std::string & name) { return add(common_peg_ref_parser{name}); } + + // Matches zero or more whitespace characters (space, tab, newline). + // S -> [ \t\n]* + common_peg_parser space() { return add(common_peg_space_parser{}); } + + // Matches all characters until a delimiter is found (delimiter not consumed). + // S -> (!delim .)* + common_peg_parser until(const std::string & delimiter) { return add(common_peg_until_parser{{delimiter}}); } + + // Matches all characters until one of the delimiters in the list is found (delimiter not consumed). + // S -> (!delim .)* + common_peg_parser until_one_of(const std::vector & delimiters) { return add(common_peg_until_parser{delimiters}); } + + // Matches everything + // S -> .* + common_peg_parser rest() { return until_one_of({}); } + + // Matches between min and max repetitions of a parser (inclusive). + // S -> A{m,n} + // Use -1 for max to represent unbounded repetition (equivalent to {m,}) + common_peg_parser repeat(const common_peg_parser & p, int min, int max) { return add(common_peg_repetition_parser{p, min,max}); } + + // Matches exactly n repetitions of a parser. + // S -> A{n} + common_peg_parser repeat(const common_peg_parser & p, int n) { return repeat(p, n, n); } + + // Creates a complete JSON parser supporting objects, arrays, strings, numbers, booleans, and null. + // value -> object | array | string | number | true | false | null + common_peg_parser json(); + common_peg_parser json_object(); + common_peg_parser json_string(); + common_peg_parser json_array(); + common_peg_parser json_number(); + common_peg_parser json_bool(); + common_peg_parser json_null(); + + // Matches JSON string content without the surrounding quotes. + // Useful for extracting content within a JSON string. + common_peg_parser json_string_content(); + + // Matches a JSON object member with a key and associated parser as the + // value. + common_peg_parser json_member(const std::string & key, const common_peg_parser & p); + + // Wraps a parser with JSON schema metadata for grammar generation. + // Used internally to convert JSON schemas to GBNF grammar rules. + common_peg_parser schema(const common_peg_parser & p, const std::string & name, const nlohmann::ordered_json & schema, bool raw = false); + + // Creates a named rule, stores it in the grammar, and returns a ref. + // If trigger=true, marks this rule as an entry point for lazy grammar generation. + // auto json = p.rule("json", json_obj | json_arr | ...) + common_peg_parser rule(const std::string & name, const common_peg_parser & p, bool trigger = false); + + // Creates a named rule using a builder function, and returns a ref. + // If trigger=true, marks this rule as an entry point for lazy grammar generation. + // auto json = p.rule("json", [&]() { return json_object() | json_array() | ... }) + common_peg_parser rule(const std::string & name, const std::function & builder, bool trigger = false); + + // Creates a trigger rule. When generating a lazy grammar from the parser, + // only trigger rules and descendents are emitted. + common_peg_parser trigger_rule(const std::string & name, const common_peg_parser & p) { return rule(name, p, true); } + common_peg_parser trigger_rule(const std::string & name, const std::function & builder) { return rule(name, builder, true); } + + // Creates an atomic parser. Atomic parsers do not create an AST node if + // the child results in a partial parse, i.e. NEEDS_MORE_INPUT. This is + // intended for situations where partial output is undesirable. + common_peg_parser atomic(const common_peg_parser & p) { return add(common_peg_atomic_parser{p}); } + + // Tags create nodes in the generated AST for semantic purposes. + // Unlike rules, you can tag multiple nodes with the same tag. + common_peg_parser tag(const std::string & tag, const common_peg_parser & p) { return add(common_peg_tag_parser{p.id(), tag}); } + + void set_root(const common_peg_parser & p); + + common_peg_arena build(); +}; + +// Helper function for building parsers +common_peg_arena build_peg_parser(const std::function & fn); diff --git a/common/unicode.cpp b/common/unicode.cpp new file mode 100644 index 0000000000..56ab0f468e --- /dev/null +++ b/common/unicode.cpp @@ -0,0 +1,64 @@ +#include "unicode.h" + +// implementation adopted from src/unicode.cpp + +size_t utf8_sequence_length(unsigned char first_byte) { + const size_t lookup[] = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 3, 4 }; + uint8_t highbits = static_cast(first_byte) >> 4; + return lookup[highbits]; +} + +utf8_parse_result parse_utf8_codepoint(std::string_view input, size_t offset) { + if (offset >= input.size()) { + return utf8_parse_result(utf8_parse_result::INCOMPLETE); + } + + // ASCII fast path + if (!(input[offset] & 0x80)) { + return utf8_parse_result(utf8_parse_result::SUCCESS, input[offset], 1); + } + + // Invalid: continuation byte as first byte + if (!(input[offset] & 0x40)) { + return utf8_parse_result(utf8_parse_result::INVALID); + } + + // 2-byte sequence + if (!(input[offset] & 0x20)) { + if (offset + 1 >= input.size()) { + return utf8_parse_result(utf8_parse_result::INCOMPLETE); + } + if ((input[offset + 1] & 0xc0) != 0x80) { + return utf8_parse_result(utf8_parse_result::INVALID); + } + auto result = ((input[offset] & 0x1f) << 6) | (input[offset + 1] & 0x3f); + return utf8_parse_result(utf8_parse_result::SUCCESS, result, 2); + } + + // 3-byte sequence + if (!(input[offset] & 0x10)) { + if (offset + 2 >= input.size()) { + return utf8_parse_result(utf8_parse_result::INCOMPLETE); + } + if ((input[offset + 1] & 0xc0) != 0x80 || (input[offset + 2] & 0xc0) != 0x80) { + return utf8_parse_result(utf8_parse_result::INVALID); + } + auto result = ((input[offset] & 0x0f) << 12) | ((input[offset + 1] & 0x3f) << 6) | (input[offset + 2] & 0x3f); + return utf8_parse_result(utf8_parse_result::SUCCESS, result, 3); + } + + // 4-byte sequence + if (!(input[offset] & 0x08)) { + if (offset + 3 >= input.size()) { + return utf8_parse_result(utf8_parse_result::INCOMPLETE); + } + if ((input[offset + 1] & 0xc0) != 0x80 || (input[offset + 2] & 0xc0) != 0x80 || (input[offset + 3] & 0xc0) != 0x80) { + return utf8_parse_result(utf8_parse_result::INVALID); + } + auto result = ((input[offset] & 0x07) << 18) | ((input[offset + 1] & 0x3f) << 12) | ((input[offset + 2] & 0x3f) << 6) | (input[offset + 3] & 0x3f); + return utf8_parse_result(utf8_parse_result::SUCCESS, result, 4); + } + + // Invalid first byte + return utf8_parse_result(utf8_parse_result::INVALID); +} diff --git a/common/unicode.h b/common/unicode.h new file mode 100644 index 0000000000..9d9e8e1227 --- /dev/null +++ b/common/unicode.h @@ -0,0 +1,22 @@ +#pragma once + +#include +#include + +// UTF-8 parsing utilities for streaming-aware unicode support + +struct utf8_parse_result { + uint32_t codepoint; // Decoded codepoint (only valid if status == SUCCESS) + size_t bytes_consumed; // How many bytes this codepoint uses (1-4) + enum status { SUCCESS, INCOMPLETE, INVALID } status; + + utf8_parse_result(enum status s, uint32_t cp = 0, size_t bytes = 0) + : codepoint(cp), bytes_consumed(bytes), status(s) {} +}; + +// Determine the expected length of a UTF-8 sequence from its first byte +// Returns 0 for invalid first bytes +size_t utf8_sequence_length(unsigned char first_byte); + +// Parse a single UTF-8 codepoint from input +utf8_parse_result parse_utf8_codepoint(std::string_view input, size_t offset); diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py index a54cce887b..c641989c19 100755 --- a/convert_hf_to_gguf.py +++ b/convert_hf_to_gguf.py @@ -1524,6 +1524,79 @@ class TextModel(ModelBase): special_vocab._set_special_token("bos", 151643) special_vocab.add_to_gguf(self.gguf_writer) + def _set_vocab_mistral(self): + if not _mistral_common_installed: + raise ImportError(_mistral_import_error_msg) + + vocab = MistralVocab(self.dir_model) + logger.info( + f"Converting tokenizer {vocab.tokenizer_type} of size {vocab.vocab_size}." + ) + + self.gguf_writer.add_tokenizer_model(vocab.gguf_tokenizer_model) + + tokens = [] + scores = [] + toktypes = [] + + for text, score, toktype in vocab.all_tokens(): + tokens.append(text) + scores.append(score) + toktypes.append(toktype) + + assert len(tokens) == vocab.vocab_size, ( + f"token count ({len(tokens)}) != vocab size ({vocab.vocab_size})" + ) + + if vocab.tokenizer_type == MistralTokenizerType.tekken: + self.gguf_writer.add_tokenizer_pre("tekken") + self.gguf_writer.add_token_merges( + vocab.extract_vocab_merges_from_model() + ) + + logger.info( + f"Setting bos, eos, unk and pad token IDs to {vocab.bos_id}, {vocab.eos_id}, {vocab.unk_id}, {vocab.pad_id}." + ) + + self.gguf_writer.add_bos_token_id(vocab.bos_id) + self.gguf_writer.add_eos_token_id(vocab.eos_id) + self.gguf_writer.add_unk_token_id(vocab.unk_id) + self.gguf_writer.add_pad_token_id(vocab.pad_id) + + self.gguf_writer.add_token_list(tokens) + self.gguf_writer.add_token_scores(scores) + self.gguf_writer.add_token_types(toktypes) + self.gguf_writer.add_vocab_size(vocab.vocab_size) + + self.gguf_writer.add_add_bos_token(True) + self.gguf_writer.add_add_eos_token(False) + + local_template_file_path = self.dir_model / "chat_template.jinja" + + if self.is_mistral_format and local_template_file_path.is_file(): + # Ministral-3 and other new Mistral models come with chat templates. + # ref: https://huggingface.co/mistralai/Ministral-3-14B-Instruct-2512/tree/main + logger.info("Using an existing Mistral local chat template.") + + with open(local_template_file_path, "r", encoding="utf-8") as f: + template = f.read() + elif not self.is_mistral_format or not self.disable_mistral_community_chat_template: + template_dir = Path(__file__).parent / "models/templates/" + + # Log only for Mistral format that the official tokenization and detokenization is via `mistral-common`. + if self.is_mistral_format: + logger.info( + "Using a Mistral community chat template. These templates can be subject to errors in early days or weeks after a release. " + "Mistral recommends to use `mistral-common` to perform tokenization and detokenization." + ) + template = MistralModel.get_community_chat_template(vocab, template_dir, self.is_mistral_format) + else: + logger.info("Not using a Mistral local or community chat template. Ensure to perform the tokenization and detokenization via `mistral-common`.") + template = None + + if template is not None: + self.gguf_writer.add_chat_template(template) + class MmprojModel(ModelBase): model_type = ModelType.MMPROJ @@ -2294,67 +2367,6 @@ class LlamaModel(TextModel): if self.hf_arch == "VLlama3ForCausalLM": self.hparams["num_attention_heads"] = self.hparams.get("num_attention_heads", 32) - def _set_vocab_mistral(self): - if not _mistral_common_installed: - raise ImportError(_mistral_import_error_msg) - - vocab = MistralVocab(self.dir_model) - logger.info( - f"Converting tokenizer {vocab.tokenizer_type} of size {vocab.vocab_size}." - ) - - self.gguf_writer.add_tokenizer_model(vocab.gguf_tokenizer_model) - - tokens = [] - scores = [] - toktypes = [] - - for text, score, toktype in vocab.all_tokens(): - tokens.append(text) - scores.append(score) - toktypes.append(toktype) - - assert len(tokens) == vocab.vocab_size, ( - f"token count ({len(tokens)}) != vocab size ({vocab.vocab_size})" - ) - - if vocab.tokenizer_type == MistralTokenizerType.tekken: - self.gguf_writer.add_tokenizer_pre("tekken") - self.gguf_writer.add_token_merges( - vocab.extract_vocab_merges_from_model() - ) - - logger.info( - f"Setting bos, eos, unk and pad token IDs to {vocab.bos_id}, {vocab.eos_id}, {vocab.unk_id}, {vocab.pad_id}." - ) - - self.gguf_writer.add_bos_token_id(vocab.bos_id) - self.gguf_writer.add_eos_token_id(vocab.eos_id) - self.gguf_writer.add_unk_token_id(vocab.unk_id) - self.gguf_writer.add_pad_token_id(vocab.pad_id) - - self.gguf_writer.add_token_list(tokens) - self.gguf_writer.add_token_scores(scores) - self.gguf_writer.add_token_types(toktypes) - self.gguf_writer.add_vocab_size(vocab.vocab_size) - - self.gguf_writer.add_add_bos_token(True) - self.gguf_writer.add_add_eos_token(False) - - template_dir = Path(__file__).parent / "models/templates/" - - if not self.is_mistral_format or not self.disable_mistral_community_chat_template: - # Log only for Mistral format that the official tokenization and detokenization is via `mistral-common`. - if self.is_mistral_format: - logger.info( - "Using a Mistral community chat template. These templates can be subject to errors in early days or weeks after a release. " - "Mistral recommends to use `mistral-common` to perform tokenization and detokenization." - ) - template = MistralModel.get_community_chat_template(vocab, template_dir, self.is_mistral_format) - self.gguf_writer.add_chat_template(template) - else: - logger.info("Not using a Mistral community chat template. Ensure to perform the tokenization and detokenization via `mistral-common`.") - def set_vocab(self): if self.is_mistral_format: return self._set_vocab_mistral() @@ -2842,6 +2854,10 @@ class Mistral3Model(LlamaModel): self.gguf_writer.add_attn_temperature_scale(rope_params["llama_4_scaling_beta"]) def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None): + # TODO: probably not worth supporting quantized weight, as official BF16 is also available + if name.endswith("weight_scale_inv"): + raise ValueError("This is a quantized weight, please use BF16 weight instead") + name = name.replace("language_model.", "") if "multi_modal_projector" in name or "vision_tower" in name: return [] @@ -9908,17 +9924,109 @@ class MistralModel(LlamaModel): def set_gguf_parameters(self): super().set_gguf_parameters() - if "yarn" in self.hparams: - yarn_params = self.hparams["yarn"] - self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.YARN) - self.gguf_writer.add_rope_scaling_factor(yarn_params["factor"]) - self.gguf_writer.add_rope_scaling_yarn_beta_fast(yarn_params["beta"]) - self.gguf_writer.add_rope_scaling_yarn_beta_slow(yarn_params["alpha"]) - self.gguf_writer.add_rope_scaling_yarn_log_mul(1.0) # mscale_all_dim - self.gguf_writer.add_rope_scaling_orig_ctx_len(yarn_params["original_max_position_embeddings"]) + MistralModel.set_mistral_config(self.gguf_writer, self.hparams) - if "llama_4_scaling" in self.hparams: - self.gguf_writer.add_attn_temperature_scale(self.hparams["llama_4_scaling"]["beta"]) + @staticmethod + def set_mistral_config(gguf_writer: gguf.GGUFWriter, hparams: dict): + if "yarn" in hparams: + yarn_params = hparams["yarn"] + gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.YARN) + gguf_writer.add_rope_scaling_factor(yarn_params["factor"]) + gguf_writer.add_rope_scaling_yarn_beta_fast(yarn_params["beta"]) + gguf_writer.add_rope_scaling_yarn_beta_slow(yarn_params["alpha"]) + gguf_writer.add_rope_scaling_yarn_log_mul(1.0) # mscale_all_dim + gguf_writer.add_rope_scaling_orig_ctx_len(yarn_params["original_max_position_embeddings"]) + + if "llama_4_scaling" in hparams: + gguf_writer.add_attn_temperature_scale(hparams["llama_4_scaling"]["beta"]) + + +class MistralMoeModel(DeepseekV2Model): + model_arch = gguf.MODEL_ARCH.DEEPSEEK2 + model_name = "Mistral" + hf_arch = "" + is_mistral_format = True + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + logger.info("Using MistralMoeModel") + # remap hparams from Mistral MoE format to DeepseekV2 format + # we do this way to be able to reuse DeepseekV2Model set_gguf_parameters logic + # ref: https://github.com/vllm-project/vllm/blob/b294e28db2c5dee61bc25157664edcada8b90b31/vllm/transformers_utils/configs/mistral.py + config = self.hparams + # Mistral key -> HF key + config_mapping = { + "dim": "hidden_size", + "norm_eps": "rms_norm_eps", + "n_kv_heads": "num_key_value_heads", + "n_layers": "num_hidden_layers", + "n_heads": "num_attention_heads", + "hidden_dim": "intermediate_size", + } + # HF key -> (Mistral key, default value) + top_level_mapping_with_default = { + "model_type": ("model_type", "transformer"), + "hidden_act": ("activation", "silu"), + "tie_word_embeddings": ("tied_embeddings", False), + "max_seq_len": ("max_seq_len", config.get("max_position_embeddings", 128_000)), + "max_position_embeddings": ("max_position_embeddings", 128_000), + } + # mapping top-level keys + for key, new_key in config_mapping.items(): + if key in config: + config[new_key] = config[key] + for new_key, (key, default_value) in top_level_mapping_with_default.items(): + config[new_key] = config.get(key, default_value) + # mapping MoE-specific keys + moe_config_map = { + "route_every_n": "moe_layer_freq", + "first_k_dense_replace": "first_k_dense_replace", + "num_experts_per_tok": "num_experts_per_tok", + "num_experts": "n_routed_experts", + "expert_hidden_dim": "moe_intermediate_size", + "routed_scale": "routed_scaling_factor", + "num_shared_experts": "n_shared_experts", + "num_expert_groups": "n_group", + "num_expert_groups_per_tok": "topk_group", + } + moe = config["moe"] + for key, new_key in moe_config_map.items(): + if key in moe: + config[new_key] = moe[key] + # provide missing values + config["topk_method"] = None + config["norm_topk_prob"] = True + config["scoring_func"] = "softmax" + + def set_vocab(self): + self._set_vocab_mistral() + + def set_gguf_parameters(self): + super().set_gguf_parameters() + MistralModel.set_mistral_config(self.gguf_writer, self.hparams) + yarn_params = self.hparams["yarn"] + self.gguf_writer.add_attn_temperature_length(yarn_params["original_max_position_embeddings"]) + self.gguf_writer.add_rope_scaling_yarn_log_mul(0.1) # mscale_all_dim * 0.1 + + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None): + if name.startswith("vision_") or name.startswith("patch_merger.") or "mm_projector" in name: + return [] + + # rename certain tensors so that we can reuse DeepseekV2Model modify_tensors logic + if name.endswith(".qscale_act"): + name = name.replace(".qscale_act", ".input_scale") + if name.endswith(".qscale_weight"): + name = name.replace(".qscale_weight", ".weight_scale") + if ".wkv_b." in name: + name = name.replace(".wkv_b.", ".kv_b_proj.") + if ".experts." in name: + name = name.replace(".experts.", ".mlp.experts.") + name = name.replace(".w1.", ".gate_proj.") + name = name.replace(".w2.", ".down_proj.") + name = name.replace(".w3.", ".up_proj.") + name = "model." + name + + return super().modify_tensors(data_torch, name, bid) class PixtralModel(LlavaVisionModel): @@ -10474,6 +10582,8 @@ def main() -> None: elif args.mmproj: assert hparams.get("vision_encoder") is not None, "This model does not support multimodal" model_class = PixtralModel + elif "moe" in hparams: + model_class = MistralMoeModel else: model_class = MistralModel diff --git a/docs/backend/ZenDNN.md b/docs/backend/ZenDNN.md new file mode 100644 index 0000000000..b57fd97b69 --- /dev/null +++ b/docs/backend/ZenDNN.md @@ -0,0 +1,258 @@ +# llama.cpp for AMD ZenDNN + +> [!WARNING] +> **Note:** ZenDNN is **not** the same as zDNN. +> - **ZenDNN** (this page): AMD's deep learning library for AMD EPYC CPUs +> - **zDNN**: IBM's Deep Neural Network acceleration library for IBM Z & LinuxONE Mainframes ([see zDNN documentation](zDNN.md)) + +- [Background](#background) +- [OS](#os) +- [Hardware](#hardware) +- [Supported Operations](#supported-operations) +- [DataType Supports](#datatype-supports) +- [Linux](#linux) +- [Environment Variable](#environment-variable) +- [Performance Optimization](#performance-optimization) +- [Known Issues](#known-issues) +- [TODO](#todo) + +## Background + +**ZenDNN** (Zen Deep Neural Network Library) is AMD's high-performance deep learning inference library optimized for AMD EPYC™ CPUs. It provides optimized implementations of key deep learning primitives and operations, delivering significant performance improvements for neural network workloads on AMD Zen-based processor architectures. + +**Llama.cpp + ZenDNN** + +The llama.cpp ZenDNN backend leverages AMD's optimized matrix multiplication primitives to accelerate inference on AMD CPUs. It utilizes ZenDNN's **LowOHA (Low Overhead Hardware Accelerated)** MatMul operator for efficient GEMM operations with minimal execution overhead, built-in weight caching, and direct access to backend libraries (AOCL BLIS, LibXSMM, OneDNN). + +For more information about ZenDNN, visit: https://www.amd.com/en/developer/zendnn.html + +## OS + +| OS | Status | Verified | +|:-------:|:-------:|:----------------------------------------------:| +| Linux | Support | Ubuntu 20.04, 22.04, 24.04 | + +For the latest list of supported operating systems, see the [ZenDNN Supported OS](https://github.com/amd/ZenDNN/blob/zendnnl/README.md#15-supported-os). + +## Hardware + +### AMD CPUs + +**Recommended Processors** + +ZenDNN is optimized for AMD EPYC™ processors and AMD Ryzen™ processors based on "Zen" microarchitecture and newer. + +| CPU Family | Status | Notes | +|:-----------------------------:|:-------:|:----------------------------------:| +| AMD EPYC™ 9005 Series (Turin)| Support | 5th Gen - Zen 5 architecture | +| AMD EPYC™ 9004 Series (Genoa)| Support | 4th Gen - Zen 4 architecture | +| AMD EPYC™ 7003 Series (Milan)| Support | 3rd Gen - Zen 3 architecture | +| AMD Ryzen™ AI MAX (Strix Halo)| Support | High-performance mobile processors | + +*Notes:* + +- Best performance is achieved on AMD EPYC™ processors with high core counts (e.g., EPYC 9005 series). +- ZenDNN leverages AMD's advanced CPU features including AVX2 and AVX-512 instruction sets. +- For optimal performance, ensure your system has sufficient memory bandwidth. + +## Supported Operations + +The ZenDNN backend currently accelerates **matrix multiplication (MUL_MAT)** operations only. Other operations are handled by the standard CPU backend. + +| Operation | Status | Notes | +|:-------------|:-------:|:----------------------------------------------:| +| MUL_MAT | ✓ | Accelerated via ZenDNN LowOHA MatMul | + +*Note:* Since only MUL_MAT is accelerated, models will benefit most from ZenDNN when matrix multiplications dominate the computational workload (which is typical for transformer-based LLMs). + +## DataType Supports + +| DataType | Status | Notes | +|:----------------------:|:-------:|:---------------------------------------------:| +| FP32 | Support | Full precision floating point | +| BF16 | Support | BFloat16 (best performance on Zen 4/Zen 5) | + +*Notes:* + +- **BF16** provides best performance on Zen 4 and Zen 5 EPYC™ processors (Genoa, Turin). + +## Linux + +### I. Setup Environment + +You have two options to set up ZenDNN: + +#### Option 1: Automatic Download and Build (Recommended) + +CMake will automatically download and build ZenDNN for you: + +```sh +# Build llama.cpp - ZenDNN will be automatically downloaded and built +cmake -B build -DGGML_ZENDNN=ON -DCMAKE_BUILD_TYPE=Release +cmake --build build --config Release -j $(nproc) +``` + +No manual ZenDNN installation required. CMake will handle everything automatically. + +#### Option 2: Use Custom ZenDNN Installation + +If you want to build ZenDNN yourself or use a specific version: + +**Step 1: Build ZenDNN from source** + +```sh +# Clone ZenDNN repository +git clone https://github.com/amd/ZenDNN.git +cd ZenDNN +git checkout zendnnl + +# Build and install (requires CMake >= 3.25) +mkdir build && cd build +cmake .. +cmake --build . --target all +``` + +Default installation path: `ZenDNN/build/install` + +**For detailed build instructions**, refer to the [ZenDNN README](https://github.com/amd/ZenDNN/blob/zendnnl/README.md). + +**Step 2: Build llama.cpp with custom ZenDNN path** + +```sh +# Using environment variable +export ZENDNN_ROOT=/path/to/ZenDNN/build/install +cmake -B build -DGGML_ZENDNN=ON -DCMAKE_BUILD_TYPE=Release +cmake --build build --config Release -j $(nproc) + +# OR specify path directly in CMake +cmake -B build -DGGML_ZENDNN=ON -DZENDNN_ROOT=/path/to/ZenDNN/build/install -DCMAKE_BUILD_TYPE=Release +cmake --build build --config Release -j $(nproc) +``` + +### II. Run the Server + +#### 1. Download Model + +Download LLaMA 3.1 8B Instruct BF16 model: + +```sh +# Download from Hugging Face +huggingface-cli download meta-llama/Llama-3.1-8B-Instruct-GGUF --local-dir models/ +``` + +#### 2. Start Server + +Run llama.cpp server with ZenDNN acceleration: + +```sh +# Set optimal configuration +export OMP_NUM_THREADS=64 # Adjust to your CPU core count +export ZENDNNL_MATMUL_ALGO=2 # Blocked AOCL BLIS for best performance + +# Start server +./build/bin/llama-server \ + -m models/Llama-3.1-8B-Instruct.BF16.gguf \ + --host 0.0.0.0 \ + --port 8080 \ + -t 64 +``` + +Access the server at `http://localhost:8080`. + +**Performance tips**: +- Set `OMP_NUM_THREADS` to match your physical core count +- Use `ZENDNNL_MATMUL_ALGO=2` for optimal performance +- For NUMA systems: `numactl --cpunodebind=0 --membind=0 ./build/bin/llama-server ...` + +## Environment Variable + +### Build Time + +| Name | Value | Function | +|--------------------|---------------------------------------|---------------------------------------------| +| GGML_ZENDNN | ON/OFF | Enable ZenDNN backend support | +| ZENDNN_ROOT | Path to ZenDNN installation | Set ZenDNN installation directory | +| GGML_OPENMP | ON/OFF (recommended: ON) | Enable OpenMP for multi-threading | + +### Runtime + +| Name | Value | Function | +|-------------------------|--------------------------|-------------------------------------------------------------------| +| OMP_NUM_THREADS | Number (e.g., 64) | Set number of OpenMP threads (recommended: physical core count) | +| ZENDNNL_MATMUL_ALGO | 0-5 | Select MatMul backend algorithm (see Performance Optimization) | +| ZENDNNL_PROFILE_LOG_LEVEL | 0-4 | Profiling log level (0=disabled, 4=verbose) | +| ZENDNNL_ENABLE_PROFILER | 0 or 1 | Enable detailed profiling (1=enabled) | +| ZENDNNL_API_LOG_LEVEL | 0-4 | API log level (0=disabled, 4=verbose) | + +**Example**: + +```sh +export OMP_NUM_THREADS=64 +export ZENDNNL_MATMUL_ALGO=2 # Use Blocked AOCL BLIS for best performance +./build/bin/llama-cli -m models/llama-2-7b.Q4_0.gguf -p "Test" -n 100 +``` + +## Performance Optimization + +### MatMul Algorithm Selection + +ZenDNN's LowOHA MatMul supports multiple backend algorithms. For **best performance**, use the **Blocked AOCL BLIS** algorithm: + +```sh +export ZENDNNL_MATMUL_ALGO=2 # Blocked AOCL BLIS (recommended) +``` + +**Available algorithms**: + +| Value | Algorithm | Description | +|:-----:|:-----------------------|:----------------------------------------------| +| 0 | Dynamic Dispatch | Automatic backend selection (default) | +| 1 | AOCL BLIS | AOCL BLIS backend | +| 2 | AOCL BLIS Blocked | **Blocked AOCL BLIS (recommended)** | +| 3 | OneDNN | OneDNN backend | +| 4 | OneDNN Blocked | Blocked OneDNN | +| 5 | LibXSMM | LibXSMM backend | + +### Profiling and Debugging + +For detailed profiling and logging options, refer to the [ZenDNN Logging Documentation](https://github.com/amd/ZenDNN/blob/zendnnl/docs/logging.md). + +## Known Issues + +- **Limited operation support**: Currently only matrix multiplication (MUL_MAT) is accelerated via ZenDNN. Other operations fall back to the standard CPU backend. +- **BF16 support**: BF16 operations require AMD Zen 4 or Zen 5 architecture (EPYC 9004/9005 series). On older CPUs, operations will use FP32. +- **NUMA awareness**: For multi-socket systems, manual NUMA binding may be required for optimal performance. + +## Q&A + +**Q: How do I verify that ZenDNN backend is being used?** + +A: Check the log output when running llama.cpp. You should see messages indicating the ZenDNN backend is initialized. You can also check the backend name in the output. + +**Q: What performance improvement can I expect?** + +A: Performance gains vary depending on the model size, batch size, and CPU architecture. On AMD EPYC processors, you can typically expect 1.1x-2x speedup compared to standard CPU inference for matrix multiplication operations. + +**Q: Can I use ZenDNN on non-AMD processors?** + +A: ZenDNN is optimized specifically for AMD processors. While it may work on other x86-64 CPUs, performance benefits are only guaranteed on AMD Zen-based architectures. + +**Q: Does ZenDNN support quantized models?** + +A: Currently, ZenDNN primarily supports FP32 and BF16 data types. Quantized model support is not available at this time. + +**Q: Why is my inference not faster with ZenDNN?** + +A: Ensure: +1. You're using an AMD EPYC or Ryzen processor (Zen 2 or newer) +2. `OMP_NUM_THREADS` is set appropriately (physical core count) +3. `ZENDNNL_MATMUL_ALGO=2` is set for best performance (Blocked AOCL BLIS) +4. You're using a sufficiently large model (small models may not benefit as much) +5. Enable profiling to verify ZenDNN MatMul is being called + +### **GitHub Contribution**: +Please add the **[ZenDNN]** prefix/tag in issues/PRs titles to help the ZenDNN-team check/address them without delay. + +## TODO + +- Expand operation support beyond MUL_MAT (attention operations, activations, etc.) diff --git a/docs/backend/zDNN.md b/docs/backend/zDNN.md index 8d2e111772..94108f5ef4 100644 --- a/docs/backend/zDNN.md +++ b/docs/backend/zDNN.md @@ -1,5 +1,10 @@ # llama.cpp for IBM zDNN Accelerator +> [!WARNING] +> **Note:** zDNN is **not** the same as ZenDNN. +> - **zDNN** (this page): IBM's Deep Neural Network acceleration library for IBM Z & LinuxONE Mainframes +> - **ZenDNN**: AMD's deep learning library for AMD EPYC CPUs ([see ZenDNN documentation](ZenDNN.md)) + ## Background IBM zDNN (Z Deep Neural Network) is a hardware acceleration library designed specifically to leverage the IBM NNPA (Neural Network Processor Assist) accelerator located within IBM Telum I and II processors. It provides significant performance improvements for neural network inference operations. diff --git a/docs/build-riscv64-spacemit.md b/docs/build-riscv64-spacemit.md index eaa6532546..79bd4de63a 100644 --- a/docs/build-riscv64-spacemit.md +++ b/docs/build-riscv64-spacemit.md @@ -19,6 +19,7 @@ cmake -B build \ -DGGML_RVV=ON \ -DGGML_RV_ZFH=ON \ -DGGML_RV_ZICBOP=ON \ + -DGGML_RV_ZIHINTPAUSE=ON \ -DRISCV64_SPACEMIT_IME_SPEC=RISCV64_SPACEMIT_IME1 \ -DCMAKE_TOOLCHAIN_FILE=${PWD}/cmake/riscv64-spacemit-linux-gnu-gcc.cmake \ -DCMAKE_INSTALL_PREFIX=build/installed diff --git a/docs/build.md b/docs/build.md index 7d244ff013..4a6911778c 100644 --- a/docs/build.md +++ b/docs/build.md @@ -431,11 +431,22 @@ docker run -it --rm -v "$(pwd):/app:Z" --device /dev/dri/renderD128:/dev/dri/ren ### For Linux users: +#### Using the LunarG Vulkan SDK + First, follow the official LunarG instructions for the installation and setup of the Vulkan SDK in the [Getting Started with the Linux Tarball Vulkan SDK](https://vulkan.lunarg.com/doc/sdk/latest/linux/getting_started.html) guide. > [!IMPORTANT] > After completing the first step, ensure that you have used the `source` command on the `setup_env.sh` file inside of the Vulkan SDK in your current terminal session. Otherwise, the build won't work. Additionally, if you close out of your terminal, you must perform this step again if you intend to perform a build. However, there are ways to make this persistent. Refer to the Vulkan SDK guide linked in the first step for more information about any of this. +#### Using system packages + +On Debian / Ubuntu, you can install the required dependencies using: +```sh +sudo apt-get install libvulkan-dev glslc +``` + +#### Common steps + Second, after verifying that you have followed all of the SDK installation/setup steps, use this command to make sure before proceeding: ```bash vulkaninfo @@ -484,6 +495,38 @@ llama_new_context_with_model: CANN compute buffer size = 1260.81 MiB For detailed info, such as model/device supports, CANN install, please refer to [llama.cpp for CANN](./backend/CANN.md). +## ZenDNN + +ZenDNN provides optimized deep learning primitives for AMD EPYC™ CPUs. It accelerates matrix multiplication operations for inference workloads. + +### Compilation + +- Using `CMake` on Linux (automatic build): + + ```bash + cmake -B build -DGGML_ZENDNN=ON + cmake --build build --config Release + ``` + + The first build will automatically download and build ZenDNN, which may take 5-10 minutes. Subsequent builds will be much faster. + +- Using `CMake` with custom ZenDNN installation: + + ```bash + cmake -B build -DGGML_ZENDNN=ON -DZENDNN_ROOT=/path/to/zendnn/install + cmake --build build --config Release + ``` + +### Testing + +You can test with: + +```bash +./build/bin/llama-cli -m PATH_TO_MODEL -p "Building a website can be done in 10 steps:" -n 50 +``` + +For detailed information about hardware support, setup instructions, and performance optimization, refer to [llama.cpp for ZenDNN](./backend/ZenDNN.md). + ## Arm® KleidiAI™ KleidiAI is a library of optimized microkernels for AI workloads, specifically designed for Arm CPUs. These microkernels enhance performance and can be enabled for use by the CPU backend. diff --git a/docs/development/parsing.md b/docs/development/parsing.md new file mode 100644 index 0000000000..113ab2e2ee --- /dev/null +++ b/docs/development/parsing.md @@ -0,0 +1,288 @@ +# Parsing Model Output + +The `common` library contains a PEG parser implementation suitable for parsing +model output. + +Types with the prefix `common_peg_*` are intended for general use and may have +applications beyond parsing model output, such as parsing user-provided regex +patterns. + +Types with the prefix `common_chat_peg_*` are specialized helpers for model +output. + +The parser features: + +- Partial parsing of streaming input +- Built-in JSON parsers +- AST generation with semantics via "tagged" nodes + +## Example + +Below is a contrived example demonstrating how to use the PEG parser to parse +output from a model that emits arguments as JSON. + +```cpp +auto parser = build_chat_peg_native_parser([&](common_chat_peg_native_builder & p) { + // Build a choice of all available tools + auto tool_choice = p.choice(); + for (const auto & tool : tools) { + const auto & function = tool.at("function"); + std::string name = function.at("name"); + const auto & schema = function.at("parameters"); + + auto tool_name = p.json_member("name", "\"" + p.literal(name) + "\""); + auto tool_args = p.json_member("arguments", p.schema(p.json(), "tool-" + name + "-schema", schema)); + + tool_choice |= p.rule("tool-" + name, "{" << tool_name << "," << tool_args << "}"); + } + + // Define the tool call structure: [{tool}] + auto tool_call = p.trigger_rule("tool-call", + p.sequence({ + p.literal("["), + tool_choice, + p.literal("]") + }) + ); + + // Parser accepts content, optionally followed by a tool call + return p.sequence({ + p.content(p.until("")), + p.optional(tool_call), + p.end() + }); +}); +``` + +For a more complete example, see `test_example_native()` in +[tests/test-chat-peg-parser.cpp](tests/test-chat-peg-parser.cpp). + +## Parsers/Combinators + +### Basic Matchers + +- **`eps()`** - Matches nothing and always succeeds (epsilon/empty match) +- **`start()`** - Matches the start of input (anchor `^`) +- **`end()`** - Matches the end of input (anchor `$`) +- **`literal(string)`** - Matches an exact literal string +- **`any()`** - Matches any single character (`.`) + +### Combinators + +- **`sequence(...)`** - Matches parsers in order; all must succeed +- **`choice(...)`** - Matches the first parser that succeeds from alternatives (ordered choice) +- **`one_or_more(p)`** - Matches one or more repetitions (`+`) +- **`zero_or_more(p)`** - Matches zero or more repetitions (`*`) +- **`optional(p)`** - Matches zero or one occurrence (`?`) +- **`repeat(p, min, max)`** - Matches between min and max repetitions (use `-1` for unbounded) +- **`repeat(p, n)`** - Matches exactly n repetitions + +### Lookahead + +- **`peek(p)`** - Positive lookahead: succeeds if parser succeeds without consuming input (`&`) +- **`negate(p)`** - Negative lookahead: succeeds if parser fails without consuming input (`!`) + +### Character Classes & Utilities + +- **`chars(classes, min, max)`** - Matches repetitions of characters from a character class +- **`space()`** - Matches zero or more whitespace characters (space, tab, newline) +- **`until(delimiter)`** - Matches characters until delimiter is found (delimiter not consumed) +- **`until_one_of(delimiters)`** - Matches characters until any delimiter in the list is found +- **`rest()`** - Matches everything remaining (`.*`) + +### JSON Parsers + +- **`json()`** - Complete JSON parser (objects, arrays, strings, numbers, booleans, null) +- **`json_object()`** - JSON object parser +- **`json_array()`** - JSON array parser +- **`json_string()`** - JSON string parser +- **`json_number()`** - JSON number parser +- **`json_bool()`** - JSON boolean parser +- **`json_null()`** - JSON null parser +- **`json_string_content()`** - JSON string content without surrounding quotes +- **`json_member(key, p)`** - JSON object member with specific key and value parser + +### Grammar Building + +- **`ref(name)`** - Creates a lightweight reference to a named rule (for recursive grammars) +- **`rule(name, p, trigger)`** - Creates a named rule and returns a reference +- **`trigger_rule(name, p)`** - Creates a trigger rule (entry point for lazy grammar generation) +- **`schema(p, name, schema, raw)`** - Wraps parser with JSON schema metadata for grammar generation + +### AST Control + +- **`atomic(p)`** - Prevents AST node creation for partial parses +- **`tag(tag, p)`** - Creates AST nodes with semantic tags (multiple nodes can share tags) + +## GBNF Grammar Generation + +The PEG parser also acts as a convenient DSL for generating GBNF grammars, with +some exceptions. + +```cpp +data.grammar = build_grammar([&](const common_grammar_builder & builder) { + foreach_function(params.tools, [&](const json & fn) { + builder.resolve_refs(fn.at("parameters")); + }); + parser.build_grammar(builder, data.grammar_lazy); +}); +``` + +The notable exception is the `negate(p)` lookahead parser, which cannot be +defined as a CFG grammar and therefore does not produce a rule. Its usage +should be limited and preferably hidden behind a `schema()` parser. In many +cases, `until(delimiter)` or `until_one_of(delimiters)` is a better choice. + +Another limitation is that the PEG parser requires an unambiguous grammar. In +contrast, the `llama-grammar` implementation can support ambiguous grammars, +though they are difficult to parse. + +### Lazy Grammars + +During lazy grammar generation, only rules reachable from a `trigger_rule(p)` +are emitted in the grammar. All trigger rules are added as alternations in the +root rule. It is still necessary to define trigger patterns, as the parser has +no interaction with the grammar sampling. + +### JSON Schema + +The `schema(p, name, schema, raw)` parser will use the `json-schema-to-grammar` +implementation to generate the grammar instead of the underlying parser. + +The `raw` option emits a grammar suitable for a raw string instead of a JSON +string. In other words, it won't be wrapped in quotes or require escaping +quotes. It should only be used when `type == "string"`. + +The downside is that it can potentially lead to ambiguous grammars. For +example, if a user provides the pattern `^.*$`, the following grammar may be +generated: + +``` +root ::= "" .* "" +``` + +This creates an ambiguous grammar that cannot be parsed by the PEG parser. To +help mitigate this, if `.*` is found in the pattern, the grammar from the +underlying parser will be emitted instead. + +## Common AST Shapes for Chat Parsing + +Most model output can be placed in one of the following categories: + +- Content only +- Tool calling with arguments emitted as a single JSON object +- Tool calling with arguments emitted as separate entities, either XML + (Qwen3-Coder, MiniMax M2) or pseudo-function calls (LFM2) + +To provide broad coverage, +[`common/chat-peg-parser.h`](common/chat-peg-parser.h) contains builders and +mappers that help create parsers and visitors/extractors for these types. They +require parsers to tag nodes to conform to an AST "shape". This normalization +makes it easy to extract information and generalize parsing. + +### Simple + +The `common_chat_peg_builder` builds a `simple` parser that supports +content-only models with optional reasoning. + +- **`reasoning(p)`** - Tag node for extracting `reasoning_content` +- **`content(p)`** - Tag node for extracting `content` + +```cpp +build_chat_peg_parser([&](common_chat_peg_parser & p) { + return p.sequence({ + p.optional("" + p.reasoning(p.until("")) + ""), + p.content(p.until("")), + p.end() + }); +}); +``` + +Use `common_chat_peg_mapper` to extract the content. Note that this is already +done for you in `common_chat_peg_parser` when +`chat_format == COMMON_CHAT_FORMAT_PEG_SIMPLE`. + +```cpp +auto result = parser.parse(ctx); + +common_chat_msg msg; +auto mapper = common_chat_peg_mapper(msg); +mapper.from_ast(ctx.ast, result); +``` + +### Native + +The `common_chat_peg_native_builder` builds a `native` parser suitable for +models that emit tool arguments as a direct JSON object. + +- **`reasoning(p)`** - Tag node for `reasoning_content` +- **`content(p)`** - Tag node for `content` +- **`tool(p)`** - Tag entirety of a single tool call +- **`tool_open(p)`** - Tag start of a tool call +- **`tool_close(p)`** - Tag end of a tool call +- **`tool_id(p)`** - Tag the tool call ID (optional) +- **`tool_name(p)`** - Tag the tool name +- **`tool_args(p)`** - Tag the tool arguments + +```cpp +build_chat_peg_native_parser([&](common_chat_peg_native_parser & p) { + auto get_weather_tool = p.tool(p.sequence({ + p.tool_open(p.literal("{")), + p.json_member("name", "\"" + p.tool_name(p.literal("get_weather")) + "\""), + p.literal(","), + p.json_member("arguments", p.tool_args(p.json())), + p.tool_close(p.literal("}")) + })); + + return p.sequence({ + p.content(p.until("")), + p.literal(""), + get_weather_tool, + p.literal(""), + p.end() + }); +}); +``` + +### Constructed + +The `common_chat_peg_constructed_builder` builds a `constructed` parser +suitable for models that emit tool arguments as separate entities, such as XML +tags. + +- **`reasoning(p)`** - Tag node for `reasoning_content` +- **`content(p)`** - Tag node for `content` +- **`tool(p)`** - Tag entirety of a single tool call +- **`tool_open(p)`** - Tag start of a tool call +- **`tool_close(p)`** - Tag end of a tool call +- **`tool_name(p)`** - Tag the tool name +- **`tool_arg(p)`** - Tag a complete tool argument (name + value) +- **`tool_arg_open(p)`** - Tag start of a tool argument +- **`tool_arg_close(p)`** - Tag end of a tool argument +- **`tool_arg_name(p)`** - Tag the argument name +- **`tool_arg_string_value(p)`** - Tag string value for the argument +- **`tool_arg_json_value(p)`** - Tag JSON value for the argument + +```cpp +build_chat_peg_constructed_parser([&](common_chat_peg_constructed_builder & p) { + auto location_arg = p.tool_arg( + p.tool_arg_open(""), + p.tool_arg_string_value(p.until("")), + p.tool_arg_close(p.literal("")) + ); + + auto get_weather_tool = p.tool(p.sequence({ + p.tool_open(""), + location_arg, + p.tool_close(p.literal("")) + })); + + return p.sequence({ + p.content(p.until("")), + p.literal(""), + get_weather_tool, + p.literal(""), + p.end() + }); +}); +``` diff --git a/docs/ops.md b/docs/ops.md index fe5e6c1819..ef1febccae 100644 --- a/docs/ops.md +++ b/docs/ops.md @@ -12,111 +12,111 @@ Legend: - 🟡 Partially supported by this backend - ❌ Not supported by this backend -| Operation | BLAS | CANN | CPU | CUDA | Metal | OpenCL | SYCL | Vulkan | zDNN | -|-----------|------|------|------|------|------|------|------|------|------| -| ABS | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ❌ | -| ACC | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | -| ADD | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ✅ | ❌ | -| ADD1 | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ✅ | ❌ | -| ADD_ID | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | -| ARANGE | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | -| ARGMAX | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | -| ARGSORT | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | -| CEIL | ❌ | ❌ | ✅ | 🟡 | ❌ | ❌ | 🟡 | 🟡 | ❌ | -| CLAMP | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | 🟡 | ❌ | -| CONCAT | ❌ | ✅ | ✅ | 🟡 | ✅ | 🟡 | ✅ | ✅ | ❌ | -| CONT | ❌ | 🟡 | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ❌ | -| CONV_2D | ❌ | ❌ | ✅ | ✅ | ❌ | ✅ | ❌ | ✅ | ❌ | -| CONV_2D_DW | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | -| CONV_3D | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | -| CONV_TRANSPOSE_1D | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | -| CONV_TRANSPOSE_2D | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | -| COS | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | 🟡 | 🟡 | ❌ | -| COUNT_EQUAL | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ✅ | ❌ | -| CPY | ❌ | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | ❌ | -| CROSS_ENTROPY_LOSS | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | -| CROSS_ENTROPY_LOSS_BACK | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | -| CUMSUM | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ✅ | ❌ | -| DIAG_MASK_INF | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ✅ | ❌ | -| DIV | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ✅ | ❌ | -| DUP | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | ✅ | ❌ | -| ELU | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | ❌ | ❌ | -| EXP | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ❌ | -| EXPM1 | ❌ | ❌ | ✅ | 🟡 | ❌ | ❌ | ❌ | ❌ | ❌ | -| FILL | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ✅ | ❌ | -| FLASH_ATTN_EXT | ❌ | 🟡 | ✅ | 🟡 | 🟡 | ❌ | ❌ | 🟡 | ❌ | -| FLOOR | ❌ | ❌ | ✅ | 🟡 | ❌ | ❌ | 🟡 | 🟡 | ❌ | -| GATED_LINEAR_ATTN | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | -| GEGLU | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ❌ | -| GEGLU_ERF | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ❌ | -| GEGLU_QUICK | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ❌ | -| GELU | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ❌ | -| GELU_ERF | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ❌ | -| GELU_QUICK | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ❌ | -| GET_ROWS | ❌ | 🟡 | ✅ | 🟡 | ✅ | 🟡 | 🟡 | 🟡 | ❌ | -| GET_ROWS_BACK | ❌ | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ | ❌ | ❌ | -| GROUP_NORM | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | -| GROUP_NORM_MUL_ADD | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | -| HARDSIGMOID | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ❌ | -| HARDSWISH | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ❌ | -| IM2COL | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | ✅ | ❌ | -| IM2COL_3D | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | -| L2_NORM | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | -| LEAKY_RELU | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | 🟡 | ❌ | -| LOG | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | 🟡 | ✅ | ❌ | -| MEAN | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | -| MUL | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ✅ | ❌ | -| MUL_MAT | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | -| MUL_MAT_ID | ❌ | 🟡 | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ❌ | -| NEG | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ❌ | -| NORM | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ❌ | -| NORM_MUL_ADD | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | -| OPT_STEP_ADAMW | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | -| OPT_STEP_SGD | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | -| OUT_PROD | 🟡 | ❌ | 🟡 | 🟡 | ❌ | ❌ | 🟡 | ❌ | ❌ | -| PAD | ❌ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ✅ | ❌ | -| PAD_REFLECT_1D | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ❌ | ❌ | -| POOL_2D | ❌ | 🟡 | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | -| REGLU | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ❌ | -| RELU | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ❌ | -| REPEAT | ❌ | ✅ | ✅ | 🟡 | ✅ | 🟡 | ✅ | 🟡 | ❌ | -| REPEAT_BACK | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ✅ | ✅ | ❌ | -| RMS_NORM | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | ✅ | ❌ | -| RMS_NORM_BACK | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ✅ | ✅ | ❌ | -| RMS_NORM_MUL_ADD | ❌ | ✅ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | -| ROLL | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ✅ | ✅ | ❌ | -| ROPE | ❌ | 🟡 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | -| ROPE_BACK | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | -| ROUND | ❌ | ❌ | ✅ | 🟡 | ❌ | ❌ | 🟡 | 🟡 | ❌ | -| RWKV_WKV6 | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | -| RWKV_WKV7 | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | -| SCALE | ❌ | 🟡 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | -| SET | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | 🟡 | ❌ | ❌ | -| SET_ROWS | ❌ | ❌ | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | ❌ | -| SGN | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | ❌ | ❌ | -| SIGMOID | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ❌ | -| SILU | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ❌ | -| SILU_BACK | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | -| SIN | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | 🟡 | 🟡 | ❌ | -| SOFTCAP | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | -| SOFTPLUS | ❌ | ❌ | ✅ | 🟡 | ❌ | ❌ | ❌ | 🟡 | ❌ | -| SOFT_MAX | ❌ | 🟡 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | -| SOFT_MAX_BACK | ❌ | ❌ | 🟡 | 🟡 | ❌ | ❌ | 🟡 | ✅ | ❌ | -| SOLVE_TRI | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | 🟡 | ❌ | -| SQR | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | 🟡 | 🟡 | ❌ | -| SQRT | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | 🟡 | 🟡 | ❌ | -| SSM_CONV | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | -| SSM_SCAN | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | 🟡 | ❌ | -| STEP | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ❌ | -| SUB | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ✅ | ❌ | -| SUM | ❌ | ✅ | ✅ | 🟡 | ❌ | ❌ | 🟡 | 🟡 | ❌ | -| SUM_ROWS | ❌ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ✅ | ❌ | -| SWIGLU | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ❌ | -| SWIGLU_OAI | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | 🟡 | ❌ | -| TANH | ❌ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ✅ | 🟡 | ❌ | -| TIMESTEP_EMBEDDING | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | -| TOP_K | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | 🟡 | ❌ | -| TRI | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ✅ | ❌ | -| TRUNC | ❌ | ❌ | ✅ | 🟡 | ❌ | ❌ | 🟡 | 🟡 | ❌ | -| UPSCALE | ❌ | 🟡 | ✅ | ✅ | 🟡 | ✅ | 🟡 | 🟡 | ❌ | -| XIELU | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | +| Operation | BLAS | CANN | CPU | CUDA | Metal | OpenCL | SYCL | Vulkan | WebGPU | ZenDNN | zDNN | +|-----------|------|------|------|------|------|------|------|------|------|------|------| +| ABS | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ | +| ACC | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | +| ADD | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ✅ | ✅ | ❌ | ❌ | +| ADD1 | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | +| ADD_ID | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | +| ARANGE | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | +| ARGMAX | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | +| ARGSORT | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ | +| CEIL | ❌ | ❌ | ✅ | 🟡 | ❌ | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ | +| CLAMP | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | 🟡 | ❌ | ❌ | ❌ | +| CONCAT | ❌ | ✅ | ✅ | 🟡 | ✅ | 🟡 | ✅ | ✅ | ❌ | ❌ | ❌ | +| CONT | ❌ | 🟡 | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | 🟡 | ❌ | ❌ | +| CONV_2D | ❌ | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ❌ | ❌ | ❌ | +| CONV_2D_DW | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | +| CONV_3D | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | +| CONV_TRANSPOSE_1D | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | +| CONV_TRANSPOSE_2D | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | +| COS | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ | +| COUNT_EQUAL | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | +| CPY | ❌ | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | ❌ | ❌ | +| CROSS_ENTROPY_LOSS | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | +| CROSS_ENTROPY_LOSS_BACK | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | +| CUMSUM | ❌ | ❌ | ✅ | ❌ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | +| DIAG_MASK_INF | ❌ | ✅ | ✅ | ✅ | ❌ | 🟡 | ✅ | ✅ | ❌ | ❌ | ❌ | +| DIV | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ✅ | ✅ | ❌ | ❌ | +| DUP | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | ✅ | ❌ | ❌ | ❌ | +| ELU | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | ❌ | ✅ | ❌ | ❌ | +| EXP | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ | +| EXPM1 | ❌ | ❌ | ✅ | 🟡 | 🟡 | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | +| FILL | ❌ | ❌ | ✅ | ❌ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | +| FLASH_ATTN_EXT | ❌ | 🟡 | ✅ | 🟡 | 🟡 | ❌ | ❌ | 🟡 | ❌ | ❌ | ❌ | +| FLOOR | ❌ | ❌ | ✅ | 🟡 | ❌ | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ | +| GATED_LINEAR_ATTN | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | +| GEGLU | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ✅ | ❌ | ❌ | +| GEGLU_ERF | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ✅ | ❌ | ❌ | +| GEGLU_QUICK | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ✅ | ❌ | ❌ | +| GELU | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ✅ | ❌ | ❌ | +| GELU_ERF | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ✅ | ❌ | ❌ | +| GELU_QUICK | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ✅ | ❌ | ❌ | +| GET_ROWS | ❌ | 🟡 | ✅ | 🟡 | ✅ | 🟡 | 🟡 | 🟡 | 🟡 | ❌ | ❌ | +| GET_ROWS_BACK | ❌ | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | +| GROUP_NORM | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ | +| GROUP_NORM_MUL_ADD | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | +| HARDSIGMOID | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ | +| HARDSWISH | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ | +| IM2COL | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ | +| IM2COL_3D | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | +| L2_NORM | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | +| LEAKY_RELU | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | ✅ | 🟡 | ❌ | ❌ | ❌ | +| LOG | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | 🟡 | ✅ | ❌ | ❌ | ❌ | +| MEAN | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | +| MUL | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ✅ | ✅ | ❌ | ❌ | +| MUL_MAT | 🟡 | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | +| MUL_MAT_ID | ❌ | 🟡 | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ❌ | ❌ | ❌ | +| NEG | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ | +| NORM | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | 🟡 | ❌ | ❌ | ❌ | +| NORM_MUL_ADD | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | +| OPT_STEP_ADAMW | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | +| OPT_STEP_SGD | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | +| OUT_PROD | 🟡 | ❌ | 🟡 | 🟡 | ❌ | ❌ | 🟡 | ❌ | ❌ | ❌ | ❌ | +| PAD | ❌ | ✅ | ✅ | 🟡 | 🟡 | ✅ | 🟡 | ✅ | ❌ | ❌ | ❌ | +| PAD_REFLECT_1D | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | +| POOL_2D | ❌ | 🟡 | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | +| REGLU | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ✅ | ❌ | ❌ | +| RELU | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ✅ | ❌ | ❌ | +| REPEAT | ❌ | ✅ | ✅ | 🟡 | ✅ | 🟡 | ✅ | 🟡 | ❌ | ❌ | ❌ | +| REPEAT_BACK | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | +| RMS_NORM | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | +| RMS_NORM_BACK | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | +| RMS_NORM_MUL_ADD | ❌ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | +| ROLL | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | +| ROPE | ❌ | 🟡 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | +| ROPE_BACK | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | +| ROUND | ❌ | ❌ | ✅ | 🟡 | ❌ | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ | +| RWKV_WKV6 | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | +| RWKV_WKV7 | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | +| SCALE | ❌ | 🟡 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | +| SET | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | 🟡 | ❌ | ❌ | ❌ | ❌ | +| SET_ROWS | ❌ | ❌ | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | ❌ | ❌ | +| SGN | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | ❌ | ✅ | ❌ | ❌ | +| SIGMOID | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ✅ | ❌ | ❌ | +| SILU | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ✅ | ❌ | ❌ | +| SILU_BACK | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | +| SIN | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ | +| SOFTCAP | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | +| SOFTPLUS | ❌ | ❌ | ✅ | 🟡 | 🟡 | ❌ | ❌ | 🟡 | ❌ | ❌ | ❌ | +| SOFT_MAX | ❌ | 🟡 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | +| SOFT_MAX_BACK | ❌ | ❌ | 🟡 | 🟡 | ❌ | ❌ | 🟡 | ✅ | ❌ | ❌ | ❌ | +| SOLVE_TRI | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | 🟡 | ❌ | ❌ | ❌ | +| SQR | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ | +| SQRT | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ | +| SSM_CONV | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | +| SSM_SCAN | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | 🟡 | ❌ | ❌ | ❌ | +| STEP | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ | +| SUB | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ✅ | ✅ | ❌ | ❌ | +| SUM | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ | +| SUM_ROWS | ❌ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ✅ | ❌ | ❌ | ❌ | +| SWIGLU | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ✅ | ❌ | ❌ | +| SWIGLU_OAI | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | 🟡 | ✅ | ❌ | ❌ | +| TANH | ❌ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ✅ | 🟡 | ✅ | ❌ | ❌ | +| TIMESTEP_EMBEDDING | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ | +| TOP_K | ❌ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | 🟡 | ❌ | ❌ | ❌ | +| TRI | ❌ | ❌ | ✅ | ❌ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | +| TRUNC | ❌ | ❌ | ✅ | 🟡 | ❌ | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ | +| UPSCALE | ❌ | 🟡 | ✅ | ✅ | 🟡 | ✅ | 🟡 | 🟡 | ❌ | ❌ | ❌ | +| XIELU | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | diff --git a/docs/ops/BLAS.csv b/docs/ops/BLAS.csv index 74c767cf29..0b7042aa8a 100644 --- a/docs/ops/BLAS.csv +++ b/docs/ops/BLAS.csv @@ -27,8 +27,20 @@ "BLAS","HARDSIGMOID","type=f16,ne_a=[5,7,11,13],v=0","support","0","no","BLAS" "BLAS","EXP","type=f16,ne_a=[128,2,2,2],v=0","support","0","no","BLAS" "BLAS","EXP","type=f16,ne_a=[5,7,11,13],v=0","support","0","no","BLAS" +"BLAS","EXPM1","type=f16,ne_a=[128,2,2,2],v=0","support","0","no","BLAS" +"BLAS","EXPM1","type=f16,ne_a=[5,7,11,13],v=0","support","0","no","BLAS" +"BLAS","SOFTPLUS","type=f16,ne_a=[128,2,2,2],v=0","support","0","no","BLAS" +"BLAS","SOFTPLUS","type=f16,ne_a=[5,7,11,13],v=0","support","0","no","BLAS" "BLAS","GELU_ERF","type=f16,ne_a=[128,2,2,2],v=0","support","0","no","BLAS" "BLAS","GELU_ERF","type=f16,ne_a=[5,7,11,13],v=0","support","0","no","BLAS" +"BLAS","FLOOR","type=f16,ne_a=[128,2,2,2],v=0","support","0","no","BLAS" +"BLAS","FLOOR","type=f16,ne_a=[5,7,11,13],v=0","support","0","no","BLAS" +"BLAS","CEIL","type=f16,ne_a=[128,2,2,2],v=0","support","0","no","BLAS" +"BLAS","CEIL","type=f16,ne_a=[5,7,11,13],v=0","support","0","no","BLAS" +"BLAS","ROUND","type=f16,ne_a=[128,2,2,2],v=0","support","0","no","BLAS" +"BLAS","ROUND","type=f16,ne_a=[5,7,11,13],v=0","support","0","no","BLAS" +"BLAS","TRUNC","type=f16,ne_a=[128,2,2,2],v=0","support","0","no","BLAS" +"BLAS","TRUNC","type=f16,ne_a=[5,7,11,13],v=0","support","0","no","BLAS" "BLAS","ABS","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" "BLAS","ABS","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" "BLAS","SGN","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" @@ -57,8 +69,20 @@ "BLAS","HARDSIGMOID","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" "BLAS","EXP","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" "BLAS","EXP","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" +"BLAS","EXPM1","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" +"BLAS","EXPM1","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" +"BLAS","SOFTPLUS","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" +"BLAS","SOFTPLUS","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" "BLAS","GELU_ERF","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" "BLAS","GELU_ERF","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" +"BLAS","FLOOR","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" +"BLAS","FLOOR","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" +"BLAS","CEIL","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" +"BLAS","CEIL","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" +"BLAS","ROUND","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" +"BLAS","ROUND","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" +"BLAS","TRUNC","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" +"BLAS","TRUNC","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" "BLAS","ABS","type=f32,ne_a=[128,2,2,2],v=0","support","0","no","BLAS" "BLAS","ABS","type=f32,ne_a=[5,7,11,13],v=0","support","0","no","BLAS" "BLAS","SGN","type=f32,ne_a=[128,2,2,2],v=0","support","0","no","BLAS" @@ -87,8 +111,20 @@ "BLAS","HARDSIGMOID","type=f32,ne_a=[5,7,11,13],v=0","support","0","no","BLAS" "BLAS","EXP","type=f32,ne_a=[128,2,2,2],v=0","support","0","no","BLAS" "BLAS","EXP","type=f32,ne_a=[5,7,11,13],v=0","support","0","no","BLAS" +"BLAS","EXPM1","type=f32,ne_a=[128,2,2,2],v=0","support","0","no","BLAS" +"BLAS","EXPM1","type=f32,ne_a=[5,7,11,13],v=0","support","0","no","BLAS" +"BLAS","SOFTPLUS","type=f32,ne_a=[128,2,2,2],v=0","support","0","no","BLAS" +"BLAS","SOFTPLUS","type=f32,ne_a=[5,7,11,13],v=0","support","0","no","BLAS" "BLAS","GELU_ERF","type=f32,ne_a=[128,2,2,2],v=0","support","0","no","BLAS" "BLAS","GELU_ERF","type=f32,ne_a=[5,7,11,13],v=0","support","0","no","BLAS" +"BLAS","FLOOR","type=f32,ne_a=[128,2,2,2],v=0","support","0","no","BLAS" +"BLAS","FLOOR","type=f32,ne_a=[5,7,11,13],v=0","support","0","no","BLAS" +"BLAS","CEIL","type=f32,ne_a=[128,2,2,2],v=0","support","0","no","BLAS" +"BLAS","CEIL","type=f32,ne_a=[5,7,11,13],v=0","support","0","no","BLAS" +"BLAS","ROUND","type=f32,ne_a=[128,2,2,2],v=0","support","0","no","BLAS" +"BLAS","ROUND","type=f32,ne_a=[5,7,11,13],v=0","support","0","no","BLAS" +"BLAS","TRUNC","type=f32,ne_a=[128,2,2,2],v=0","support","0","no","BLAS" +"BLAS","TRUNC","type=f32,ne_a=[5,7,11,13],v=0","support","0","no","BLAS" "BLAS","ABS","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" "BLAS","ABS","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" "BLAS","SGN","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" @@ -117,8 +153,20 @@ "BLAS","HARDSIGMOID","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" "BLAS","EXP","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" "BLAS","EXP","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" +"BLAS","EXPM1","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" +"BLAS","EXPM1","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" +"BLAS","SOFTPLUS","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" +"BLAS","SOFTPLUS","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" "BLAS","GELU_ERF","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" "BLAS","GELU_ERF","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" +"BLAS","FLOOR","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" +"BLAS","FLOOR","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" +"BLAS","CEIL","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" +"BLAS","CEIL","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" +"BLAS","ROUND","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" +"BLAS","ROUND","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" +"BLAS","TRUNC","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","BLAS" +"BLAS","TRUNC","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","BLAS" "BLAS","REGLU","type=f16,ne_a=[128,2,2,2],v=0,swapped=0","support","0","no","BLAS" "BLAS","REGLU","type=f16,ne_a=[5,7,11,13],v=0,swapped=0","support","0","no","BLAS" "BLAS","REGLU","type=f16,ne_a=[128,2,2,2],v=0,swapped=1","support","0","no","BLAS" @@ -239,99 +287,117 @@ "BLAS","GEGLU_QUICK","type=f32,ne_a=[5,7,11,13],v=1,swapped=1","support","0","no","BLAS" "BLAS","GEGLU_QUICK","type=f32,ne_a=[128,2,2,2],v=1,split","support","0","no","BLAS" "BLAS","GEGLU_QUICK","type=f32,ne_a=[5,7,11,13],v=1,split","support","0","no","BLAS" -"BLAS","GET_ROWS","type=f32,n=1,m=8,r=2,b=1,v=0","support","0","no","BLAS" -"BLAS","GET_ROWS","type=f32,n=256,m=5,r=4,b=1,v=0","support","0","no","BLAS" -"BLAS","GET_ROWS","type=f32,n=256,m=5,r=4,b=1,v=1","support","0","no","BLAS" -"BLAS","GET_ROWS","type=f32,n=256,m=5,r=4,b=7,v=0","support","0","no","BLAS" -"BLAS","GET_ROWS","type=f32,n=256,m=5,r=4,b=7,v=1","support","0","no","BLAS" -"BLAS","GET_ROWS","type=f16,n=256,m=5,r=4,b=1,v=0","support","0","no","BLAS" -"BLAS","GET_ROWS","type=f16,n=256,m=5,r=4,b=1,v=1","support","0","no","BLAS" -"BLAS","GET_ROWS","type=f16,n=256,m=5,r=4,b=7,v=0","support","0","no","BLAS" -"BLAS","GET_ROWS","type=f16,n=256,m=5,r=4,b=7,v=1","support","0","no","BLAS" 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+"BLAS","CONV_3D","N=2,IC=3,ID=18,IH=22,IW=20,OC=4,KD=3,KH=1,KW=5,s0=2,s1=1,s2=1,p0=2,p1=0,p2=1,d0=1,d1=1,d2=2,type_kernel=f16","support","0","no","BLAS" +"BLAS","CONV_3D","N=1,IC=4,ID=8,IH=8,IW=8,OC=8,KD=1,KH=1,KW=1,s0=1,s1=1,s2=1,p0=0,p1=0,p2=0,d0=1,d1=1,d2=1,type_kernel=f16","support","0","no","BLAS" "BLAS","CONV_TRANSPOSE_1D","ne_input=[1,1,1,1],ne_kernel=[1,1,1,1],s0=1,p0=0,d0=1","support","0","no","BLAS" "BLAS","CONV_TRANSPOSE_1D","ne_input=[1,1,1,1],ne_kernel=[1,1,1,1],s0=2,p0=0,d0=1","support","0","no","BLAS" "BLAS","CONV_TRANSPOSE_1D","ne_input=[1,1,1,1],ne_kernel=[1,1,1,1],s0=3,p0=0,d0=1","support","0","no","BLAS" @@ -2576,6 +4967,7 @@ "BLAS","COUNT_EQUAL","type=f32,ne=[4,500,1,1]","support","0","no","BLAS" "BLAS","COUNT_EQUAL","type=f32,ne=[4,5000,1,1]","support","0","no","BLAS" "BLAS","ARGMAX","type=f32,ne=[32,1,1,1]","support","0","no","BLAS" +"BLAS","ARGMAX","type=f32,ne=[32,513,1,1]","support","0","no","BLAS" "BLAS","ARGMAX","type=f32,ne=[100,10,1,1]","support","0","no","BLAS" "BLAS","ARGMAX","type=f32,ne=[1024,10,1,1]","support","0","no","BLAS" "BLAS","ARGMAX","type=f32,ne=[1024,12,1,1]","support","0","no","BLAS" @@ -2621,394 +5013,451 @@ "BLAS","SET","type_src=i32,type_dst=i32,ne=[6,5,4,3],dim=1","support","0","no","BLAS" "BLAS","SET","type_src=i32,type_dst=i32,ne=[6,5,4,3],dim=2","support","0","no","BLAS" "BLAS","SET","type_src=i32,type_dst=i32,ne=[6,5,4,3],dim=3","support","0","no","BLAS" -"BLAS","CPY","type_src=f32,type_dst=f32,ne=[1,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","BLAS" -"BLAS","CPY","type_src=f32,type_dst=f32,ne=[1,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","BLAS" -"BLAS","CPY","type_src=f32,type_dst=f32,ne=[1,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","BLAS" -"BLAS","CPY","type_src=f32,type_dst=f32,ne=[2,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","BLAS" 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"BLAS","MUL","type=f16,ne=[10,5,4,3],nr=[2,2,2,2],nf=1","support","0","no","BLAS" "BLAS","DIV","type=f16,ne=[10,5,4,3],nr=[2,2,2,2],nf=1","support","0","no","BLAS" +"BLAS","ADD","type=f16,ne=[1,1,65536,1],nr=[256,1,1,1],nf=1","support","0","no","BLAS" +"BLAS","SUB","type=f16,ne=[1,1,65536,1],nr=[256,1,1,1],nf=1","support","0","no","BLAS" +"BLAS","MUL","type=f16,ne=[1,1,65536,1],nr=[256,1,1,1],nf=1","support","0","no","BLAS" +"BLAS","DIV","type=f16,ne=[1,1,65536,1],nr=[256,1,1,1],nf=1","support","0","no","BLAS" "BLAS","ADD","type=f16,ne=[1280,1,1,1],nr=[1,1,1,1],nf=1","support","0","no","BLAS" "BLAS","SUB","type=f16,ne=[1280,1,1,1],nr=[1,1,1,1],nf=1","support","0","no","BLAS" "BLAS","MUL","type=f16,ne=[1280,1,1,1],nr=[1,1,1,1],nf=1","support","0","no","BLAS" @@ -3113,6 +5566,10 @@ "BLAS","SUB","type=f16,ne=[640,1,1,1],nr=[1,1,1,1],nf=1","support","0","no","BLAS" "BLAS","MUL","type=f16,ne=[640,1,1,1],nr=[1,1,1,1],nf=1","support","0","no","BLAS" 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"BLAS","CROSS_ENTROPY_LOSS","type=f32,ne=[10,5,4,3]","support","0","no","BLAS" "BLAS","CROSS_ENTROPY_LOSS","type=f32,ne=[30000,1,1,1]","support","0","no","BLAS" "BLAS","CROSS_ENTROPY_LOSS_BACK","type=f32,ne=[10,5,4,3]","support","0","no","BLAS" "BLAS","CROSS_ENTROPY_LOSS_BACK","type=f32,ne=[30000,1,1,1]","support","0","no","BLAS" "BLAS","OPT_STEP_ADAMW","type=f32,ne=[10,5,4,3]","support","0","no","BLAS" +"BLAS","OPT_STEP_SGD","type=f32,ne=[10,5,4,3]","support","0","no","BLAS" diff --git a/docs/ops/Metal.csv b/docs/ops/Metal.csv index 65fa0d6573..5f7450e91f 100644 --- a/docs/ops/Metal.csv +++ b/docs/ops/Metal.csv @@ -27,8 +27,20 @@ "Metal","HARDSIGMOID","type=f16,ne_a=[5,7,11,13],v=0","support","0","no","Metal" "Metal","EXP","type=f16,ne_a=[128,2,2,2],v=0","support","0","no","Metal" "Metal","EXP","type=f16,ne_a=[5,7,11,13],v=0","support","0","no","Metal" +"Metal","EXPM1","type=f16,ne_a=[128,2,2,2],v=0","support","0","no","Metal" +"Metal","EXPM1","type=f16,ne_a=[5,7,11,13],v=0","support","0","no","Metal" +"Metal","SOFTPLUS","type=f16,ne_a=[128,2,2,2],v=0","support","0","no","Metal" +"Metal","SOFTPLUS","type=f16,ne_a=[5,7,11,13],v=0","support","0","no","Metal" "Metal","GELU_ERF","type=f16,ne_a=[128,2,2,2],v=0","support","0","no","Metal" "Metal","GELU_ERF","type=f16,ne_a=[5,7,11,13],v=0","support","0","no","Metal" +"Metal","FLOOR","type=f16,ne_a=[128,2,2,2],v=0","support","0","no","Metal" +"Metal","FLOOR","type=f16,ne_a=[5,7,11,13],v=0","support","0","no","Metal" +"Metal","CEIL","type=f16,ne_a=[128,2,2,2],v=0","support","0","no","Metal" +"Metal","CEIL","type=f16,ne_a=[5,7,11,13],v=0","support","0","no","Metal" +"Metal","ROUND","type=f16,ne_a=[128,2,2,2],v=0","support","0","no","Metal" +"Metal","ROUND","type=f16,ne_a=[5,7,11,13],v=0","support","0","no","Metal" +"Metal","TRUNC","type=f16,ne_a=[128,2,2,2],v=0","support","0","no","Metal" +"Metal","TRUNC","type=f16,ne_a=[5,7,11,13],v=0","support","0","no","Metal" "Metal","ABS","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","Metal" "Metal","ABS","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","Metal" "Metal","SGN","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","Metal" @@ -57,8 +69,20 @@ "Metal","HARDSIGMOID","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","Metal" "Metal","EXP","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","Metal" "Metal","EXP","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","Metal" +"Metal","EXPM1","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","Metal" +"Metal","EXPM1","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","Metal" +"Metal","SOFTPLUS","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","Metal" +"Metal","SOFTPLUS","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","Metal" "Metal","GELU_ERF","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","Metal" "Metal","GELU_ERF","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","Metal" +"Metal","FLOOR","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","Metal" +"Metal","FLOOR","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","Metal" +"Metal","CEIL","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","Metal" +"Metal","CEIL","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","Metal" +"Metal","ROUND","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","Metal" +"Metal","ROUND","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","Metal" +"Metal","TRUNC","type=f16,ne_a=[128,2,2,2],v=1","support","0","no","Metal" +"Metal","TRUNC","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","Metal" "Metal","ABS","type=f32,ne_a=[128,2,2,2],v=0","support","1","yes","Metal" "Metal","ABS","type=f32,ne_a=[5,7,11,13],v=0","support","1","yes","Metal" "Metal","SGN","type=f32,ne_a=[128,2,2,2],v=0","support","1","yes","Metal" @@ -87,8 +111,20 @@ "Metal","HARDSIGMOID","type=f32,ne_a=[5,7,11,13],v=0","support","1","yes","Metal" "Metal","EXP","type=f32,ne_a=[128,2,2,2],v=0","support","1","yes","Metal" "Metal","EXP","type=f32,ne_a=[5,7,11,13],v=0","support","1","yes","Metal" +"Metal","EXPM1","type=f32,ne_a=[128,2,2,2],v=0","support","1","yes","Metal" +"Metal","EXPM1","type=f32,ne_a=[5,7,11,13],v=0","support","1","yes","Metal" +"Metal","SOFTPLUS","type=f32,ne_a=[128,2,2,2],v=0","support","1","yes","Metal" +"Metal","SOFTPLUS","type=f32,ne_a=[5,7,11,13],v=0","support","1","yes","Metal" "Metal","GELU_ERF","type=f32,ne_a=[128,2,2,2],v=0","support","1","yes","Metal" "Metal","GELU_ERF","type=f32,ne_a=[5,7,11,13],v=0","support","1","yes","Metal" +"Metal","FLOOR","type=f32,ne_a=[128,2,2,2],v=0","support","0","no","Metal" +"Metal","FLOOR","type=f32,ne_a=[5,7,11,13],v=0","support","0","no","Metal" +"Metal","CEIL","type=f32,ne_a=[128,2,2,2],v=0","support","0","no","Metal" +"Metal","CEIL","type=f32,ne_a=[5,7,11,13],v=0","support","0","no","Metal" +"Metal","ROUND","type=f32,ne_a=[128,2,2,2],v=0","support","0","no","Metal" +"Metal","ROUND","type=f32,ne_a=[5,7,11,13],v=0","support","0","no","Metal" +"Metal","TRUNC","type=f32,ne_a=[128,2,2,2],v=0","support","0","no","Metal" +"Metal","TRUNC","type=f32,ne_a=[5,7,11,13],v=0","support","0","no","Metal" "Metal","ABS","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","Metal" "Metal","ABS","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","Metal" "Metal","SGN","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","Metal" @@ -117,8 +153,20 @@ "Metal","HARDSIGMOID","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","Metal" "Metal","EXP","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","Metal" "Metal","EXP","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","Metal" +"Metal","EXPM1","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","Metal" +"Metal","EXPM1","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","Metal" +"Metal","SOFTPLUS","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","Metal" +"Metal","SOFTPLUS","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","Metal" "Metal","GELU_ERF","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","Metal" "Metal","GELU_ERF","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","Metal" +"Metal","FLOOR","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","Metal" +"Metal","FLOOR","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","Metal" +"Metal","CEIL","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","Metal" +"Metal","CEIL","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","Metal" +"Metal","ROUND","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","Metal" +"Metal","ROUND","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","Metal" +"Metal","TRUNC","type=f32,ne_a=[128,2,2,2],v=1","support","0","no","Metal" +"Metal","TRUNC","type=f32,ne_a=[5,7,11,13],v=1","support","0","no","Metal" "Metal","REGLU","type=f16,ne_a=[128,2,2,2],v=0,swapped=0","support","0","no","Metal" "Metal","REGLU","type=f16,ne_a=[5,7,11,13],v=0,swapped=0","support","0","no","Metal" "Metal","REGLU","type=f16,ne_a=[128,2,2,2],v=0,swapped=1","support","0","no","Metal" @@ -239,99 +287,117 @@ "Metal","GEGLU_QUICK","type=f32,ne_a=[5,7,11,13],v=1,swapped=1","support","1","yes","Metal" "Metal","GEGLU_QUICK","type=f32,ne_a=[128,2,2,2],v=1,split","support","1","yes","Metal" "Metal","GEGLU_QUICK","type=f32,ne_a=[5,7,11,13],v=1,split","support","1","yes","Metal" -"Metal","GET_ROWS","type=f32,n=1,m=8,r=2,b=1,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=f32,n=256,m=5,r=4,b=1,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=f32,n=256,m=5,r=4,b=1,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=f32,n=256,m=5,r=4,b=7,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=f32,n=256,m=5,r=4,b=7,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=f16,n=256,m=5,r=4,b=1,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=f16,n=256,m=5,r=4,b=1,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=f16,n=256,m=5,r=4,b=7,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=f16,n=256,m=5,r=4,b=7,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=bf16,n=256,m=5,r=4,b=1,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=bf16,n=256,m=5,r=4,b=1,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=bf16,n=256,m=5,r=4,b=7,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=bf16,n=256,m=5,r=4,b=7,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q4_0,n=256,m=5,r=4,b=1,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q4_0,n=256,m=5,r=4,b=1,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q4_0,n=256,m=5,r=4,b=7,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q4_0,n=256,m=5,r=4,b=7,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q4_1,n=256,m=5,r=4,b=1,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q4_1,n=256,m=5,r=4,b=1,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q4_1,n=256,m=5,r=4,b=7,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q4_1,n=256,m=5,r=4,b=7,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q5_0,n=256,m=5,r=4,b=1,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q5_0,n=256,m=5,r=4,b=1,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q5_0,n=256,m=5,r=4,b=7,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q5_0,n=256,m=5,r=4,b=7,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q5_1,n=256,m=5,r=4,b=1,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q5_1,n=256,m=5,r=4,b=1,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q5_1,n=256,m=5,r=4,b=7,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q5_1,n=256,m=5,r=4,b=7,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q8_0,n=256,m=5,r=4,b=1,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q8_0,n=256,m=5,r=4,b=1,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q8_0,n=256,m=5,r=4,b=7,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q8_0,n=256,m=5,r=4,b=7,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q2_K,n=256,m=5,r=4,b=1,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q2_K,n=256,m=5,r=4,b=1,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q2_K,n=256,m=5,r=4,b=7,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q2_K,n=256,m=5,r=4,b=7,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q3_K,n=256,m=5,r=4,b=1,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q3_K,n=256,m=5,r=4,b=1,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q3_K,n=256,m=5,r=4,b=7,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q3_K,n=256,m=5,r=4,b=7,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q4_K,n=256,m=5,r=4,b=1,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q4_K,n=256,m=5,r=4,b=1,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q4_K,n=256,m=5,r=4,b=7,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q4_K,n=256,m=5,r=4,b=7,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q5_K,n=256,m=5,r=4,b=1,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q5_K,n=256,m=5,r=4,b=1,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q5_K,n=256,m=5,r=4,b=7,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q5_K,n=256,m=5,r=4,b=7,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q6_K,n=256,m=5,r=4,b=1,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q6_K,n=256,m=5,r=4,b=1,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=q6_K,n=256,m=5,r=4,b=7,v=0","support","1","yes","Metal" -"Metal","GET_ROWS","type=q6_K,n=256,m=5,r=4,b=7,v=1","support","1","yes","Metal" -"Metal","GET_ROWS","type=iq2_xxs,n=256,m=5,r=4,b=1,v=0","support","1","yes","Metal" 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+"Metal","GET_ROWS","type=i32,n=256,m=5,r=4,be1=1,be2=1,v=1","support","1","yes","Metal" +"Metal","GET_ROWS","type=i32,n=256,m=5,r=4,be1=7,be2=1,v=0","support","1","yes","Metal" +"Metal","GET_ROWS","type=i32,n=256,m=5,r=4,be1=7,be2=1,v=1","support","1","yes","Metal" "Metal","GET_ROWS_BACK","type=f32,n=1,m=8,r=2,b=1,v=0","support","0","no","Metal" "Metal","GET_ROWS_BACK","type=f32,n=256,m=5,r=4,b=1,v=0","support","0","no","Metal" "Metal","GET_ROWS_BACK","type=f32,n=256,m=5,r=4,b=1,v=1","support","0","no","Metal" @@ -349,6 +415,8 @@ "Metal","GET_ROWS_BACK","type=q5_1,n=256,m=5,r=4,b=1,v=1","support","0","no","Metal" "Metal","GET_ROWS_BACK","type=q8_0,n=256,m=5,r=4,b=1,v=0","support","0","no","Metal" "Metal","GET_ROWS_BACK","type=q8_0,n=256,m=5,r=4,b=1,v=1","support","0","no","Metal" +"Metal","GET_ROWS_BACK","type=mxfp4,n=256,m=5,r=4,b=1,v=0","support","0","no","Metal" +"Metal","GET_ROWS_BACK","type=mxfp4,n=256,m=5,r=4,b=1,v=1","support","0","no","Metal" "Metal","GET_ROWS_BACK","type=q2_K,n=256,m=5,r=4,b=1,v=0","support","0","no","Metal" "Metal","GET_ROWS_BACK","type=q2_K,n=256,m=5,r=4,b=1,v=1","support","0","no","Metal" "Metal","GET_ROWS_BACK","type=q3_K,n=256,m=5,r=4,b=1,v=0","support","0","no","Metal" @@ -379,295 +447,309 @@ "Metal","GET_ROWS_BACK","type=iq4_xs,n=256,m=5,r=4,b=1,v=1","support","0","no","Metal" "Metal","GET_ROWS_BACK","type=i32,n=256,m=5,r=4,b=1,v=0","support","0","no","Metal" "Metal","GET_ROWS_BACK","type=i32,n=256,m=5,r=4,b=1,v=1","support","0","no","Metal" -"Metal","SET_ROWS","type=f32,ne=[1,8,1,3],nr23=[1,1],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[256,5,1,3],nr23=[1,1],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[256,11,1,1],nr23=[2,3],r=7,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[3,3,1,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[31,3,1,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[33,5,1,1],nr23=[2,3],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[256,5,1,3],nr23=[1,1],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[256,11,1,1],nr23=[2,3],r=7,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[3,3,1,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[31,3,1,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[33,5,1,1],nr23=[2,3],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[256,5,7,3],nr23=[1,1],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[256,11,1,7],nr23=[2,3],r=7,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[3,3,7,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[31,3,7,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[33,5,1,7],nr23=[2,3],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[256,5,7,3],nr23=[1,1],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[256,11,1,7],nr23=[2,3],r=7,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[3,3,7,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[31,3,7,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=f32,ne=[33,5,1,7],nr23=[2,3],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[256,5,1,3],nr23=[1,1],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[256,11,1,1],nr23=[2,3],r=7,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[3,3,1,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[31,3,1,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[33,5,1,1],nr23=[2,3],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[256,5,1,3],nr23=[1,1],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[256,11,1,1],nr23=[2,3],r=7,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[3,3,1,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[31,3,1,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[33,5,1,1],nr23=[2,3],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[256,5,7,3],nr23=[1,1],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[256,11,1,7],nr23=[2,3],r=7,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[3,3,7,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[31,3,7,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[33,5,1,7],nr23=[2,3],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[256,5,7,3],nr23=[1,1],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[256,11,1,7],nr23=[2,3],r=7,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[3,3,7,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[31,3,7,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=f16,ne=[33,5,1,7],nr23=[2,3],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[256,5,1,3],nr23=[1,1],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[256,11,1,1],nr23=[2,3],r=7,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[3,3,1,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[31,3,1,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[33,5,1,1],nr23=[2,3],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[256,5,1,3],nr23=[1,1],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[256,11,1,1],nr23=[2,3],r=7,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[3,3,1,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[31,3,1,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[33,5,1,1],nr23=[2,3],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[256,5,7,3],nr23=[1,1],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[256,11,1,7],nr23=[2,3],r=7,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[3,3,7,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[31,3,7,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[33,5,1,7],nr23=[2,3],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[256,5,7,3],nr23=[1,1],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[256,11,1,7],nr23=[2,3],r=7,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[3,3,7,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[31,3,7,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=bf16,ne=[33,5,1,7],nr23=[2,3],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_0,ne=[256,5,1,3],nr23=[1,1],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_0,ne=[256,11,1,1],nr23=[2,3],r=7,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_0,ne=[96,3,1,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_0,ne=[256,5,1,3],nr23=[1,1],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_0,ne=[256,11,1,1],nr23=[2,3],r=7,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_0,ne=[96,3,1,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_0,ne=[256,5,7,3],nr23=[1,1],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_0,ne=[256,11,1,7],nr23=[2,3],r=7,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_0,ne=[96,3,7,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_0,ne=[256,5,7,3],nr23=[1,1],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_0,ne=[256,11,1,7],nr23=[2,3],r=7,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_0,ne=[96,3,7,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_1,ne=[256,5,1,3],nr23=[1,1],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_1,ne=[256,11,1,1],nr23=[2,3],r=7,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_1,ne=[96,3,1,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_1,ne=[256,5,1,3],nr23=[1,1],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_1,ne=[256,11,1,1],nr23=[2,3],r=7,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_1,ne=[96,3,1,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_1,ne=[256,5,7,3],nr23=[1,1],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_1,ne=[256,11,1,7],nr23=[2,3],r=7,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_1,ne=[96,3,7,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_1,ne=[256,5,7,3],nr23=[1,1],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_1,ne=[256,11,1,7],nr23=[2,3],r=7,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q4_1,ne=[96,3,7,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_0,ne=[256,5,1,3],nr23=[1,1],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_0,ne=[256,11,1,1],nr23=[2,3],r=7,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_0,ne=[96,3,1,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_0,ne=[256,5,1,3],nr23=[1,1],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_0,ne=[256,11,1,1],nr23=[2,3],r=7,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_0,ne=[96,3,1,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_0,ne=[256,5,7,3],nr23=[1,1],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_0,ne=[256,11,1,7],nr23=[2,3],r=7,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_0,ne=[96,3,7,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_0,ne=[256,5,7,3],nr23=[1,1],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_0,ne=[256,11,1,7],nr23=[2,3],r=7,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_0,ne=[96,3,7,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_1,ne=[256,5,1,3],nr23=[1,1],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_1,ne=[256,11,1,1],nr23=[2,3],r=7,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_1,ne=[96,3,1,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_1,ne=[256,5,1,3],nr23=[1,1],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_1,ne=[256,11,1,1],nr23=[2,3],r=7,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_1,ne=[96,3,1,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_1,ne=[256,5,7,3],nr23=[1,1],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_1,ne=[256,11,1,7],nr23=[2,3],r=7,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_1,ne=[96,3,7,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_1,ne=[256,5,7,3],nr23=[1,1],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_1,ne=[256,11,1,7],nr23=[2,3],r=7,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q5_1,ne=[96,3,7,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q8_0,ne=[256,5,1,3],nr23=[1,1],r=1,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q8_0,ne=[256,11,1,1],nr23=[2,3],r=7,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q8_0,ne=[96,3,1,1],nr23=[2,3],r=2,v=0","support","1","yes","Metal" -"Metal","SET_ROWS","type=q8_0,ne=[256,5,1,3],nr23=[1,1],r=1,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q8_0,ne=[256,11,1,1],nr23=[2,3],r=7,v=1","support","1","yes","Metal" -"Metal","SET_ROWS","type=q8_0,ne=[96,3,1,1],nr23=[2,3],r=2,v=1","support","1","yes","Metal" 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-"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=3,s1=3,p0=3,p1=0,d0=1,d1=1,is_2D=1","support","0","no","Metal" -"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=3,s1=3,p0=3,p1=0,d0=1,d1=3,is_2D=1","support","0","no","Metal" -"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=3,s1=3,p0=3,p1=0,d0=3,d1=1,is_2D=1","support","0","no","Metal" -"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=3,s1=3,p0=3,p1=0,d0=3,d1=3,is_2D=1","support","0","no","Metal" -"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=3,s1=3,p0=3,p1=3,d0=1,d1=1,is_2D=1","support","0","no","Metal" -"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=3,s1=3,p0=3,p1=3,d0=1,d1=3,is_2D=1","support","0","no","Metal" -"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=3,s1=3,p0=3,p1=3,d0=3,d1=1,is_2D=1","support","0","no","Metal" -"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=3,s1=3,p0=3,p1=3,d0=3,d1=3,is_2D=1","support","0","no","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=1,p0=0,p1=0,d0=1,d1=1,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=1,p0=0,p1=0,d0=1,d1=3,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=1,p0=0,p1=0,d0=3,d1=1,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=1,p0=0,p1=0,d0=3,d1=3,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=1,p0=0,p1=3,d0=1,d1=1,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=1,p0=0,p1=3,d0=1,d1=3,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=1,p0=0,p1=3,d0=3,d1=1,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=1,p0=0,p1=3,d0=3,d1=3,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=1,p0=3,p1=0,d0=1,d1=1,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=1,p0=3,p1=0,d0=1,d1=3,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=1,p0=3,p1=0,d0=3,d1=1,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=1,p0=3,p1=0,d0=3,d1=3,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=1,p0=3,p1=3,d0=1,d1=1,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=1,p0=3,p1=3,d0=1,d1=3,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=1,p0=3,p1=3,d0=3,d1=1,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=1,p0=3,p1=3,d0=3,d1=3,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=3,p0=0,p1=0,d0=1,d1=1,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=3,p0=0,p1=0,d0=1,d1=3,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=3,p0=0,p1=0,d0=3,d1=1,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=3,p0=0,p1=0,d0=3,d1=3,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=3,p0=0,p1=3,d0=1,d1=1,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=3,p0=0,p1=3,d0=1,d1=3,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=3,p0=0,p1=3,d0=3,d1=1,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=3,p0=0,p1=3,d0=3,d1=3,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=3,p0=3,p1=0,d0=1,d1=1,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=3,p0=3,p1=0,d0=1,d1=3,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=3,p0=3,p1=0,d0=3,d1=1,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=3,p0=3,p1=0,d0=3,d1=3,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=3,p0=3,p1=3,d0=1,d1=1,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=3,p0=3,p1=3,d0=1,d1=3,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=3,p0=3,p1=3,d0=3,d1=1,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=3,p0=3,p1=3,d0=3,d1=3,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=3,s1=1,p0=0,p1=0,d0=1,d1=1,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=3,s1=1,p0=0,p1=0,d0=1,d1=3,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=3,s1=1,p0=0,p1=0,d0=3,d1=1,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=3,s1=1,p0=0,p1=0,d0=3,d1=3,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=3,s1=1,p0=0,p1=3,d0=1,d1=1,is_2D=1","support","1","yes","Metal" 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+"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=3,s1=3,p0=3,p1=3,d0=3,d1=1,is_2D=1","support","1","yes","Metal" +"Metal","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=3,s1=3,p0=3,p1=3,d0=3,d1=3,is_2D=1","support","1","yes","Metal" "Metal","IM2COL","type_input=f32,type_kernel=f16,dst_type=f16,ne_input=[12,12,1,32],ne_kernel=[3,3,1,32],s0=1,s1=1,p0=1,p1=1,d0=1,d1=1,is_2D=1","support","1","yes","Metal" "Metal","IM2COL","type_input=f32,type_kernel=f16,dst_type=f16,ne_input=[12,12,2,32],ne_kernel=[3,3,2,32],s0=1,s1=1,p0=1,p1=1,d0=1,d1=1,is_2D=1","support","1","yes","Metal" "Metal","IM2COL","type_input=f32,type_kernel=f16,dst_type=f16,ne_input=[12,12,1,1024],ne_kernel=[3,3,1,1024],s0=1,s1=1,p0=1,p1=1,d0=1,d1=1,is_2D=1","support","1","yes","Metal" @@ -883,1578 +965,3887 @@ "Metal","IM2COL","type_input=f32,type_kernel=f16,dst_type=f16,ne_input=[12,12,1,2560],ne_kernel=[3,3,1,2560],s0=1,s1=1,p0=1,p1=1,d0=1,d1=1,is_2D=1","support","1","yes","Metal" "Metal","IM2COL","type_input=f32,type_kernel=f16,dst_type=f16,ne_input=[12,12,2,2560],ne_kernel=[3,3,2,2560],s0=1,s1=1,p0=1,p1=1,d0=1,d1=1,is_2D=1","support","1","yes","Metal" "Metal","IM2COL","type_input=f32,type_kernel=f16,dst_type=f16,ne_input=[5,5,1,32],ne_kernel=[3,4,1,32],s0=1,s1=1,p0=0,p1=0,d0=1,d1=1,is_2D=1","support","1","yes","Metal" -"Metal","CONV_2D","ne_input=[1,1,1,2],ne_kernel=[1,1,1,1],type_kernel=f32,stride0=1,stride1=5,padding0=5,padding1=2,dilation0=2,dilation1=4,cwhn=0","support","0","no","Metal" -"Metal","CONV_2D","ne_input=[1,1,1,2],ne_kernel=[1,1,1,1],type_kernel=f16,stride0=1,stride1=5,padding0=5,padding1=2,dilation0=2,dilation1=4,cwhn=0","support","0","no","Metal" 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+"Metal","CONV_3D","N=2,IC=3,ID=18,IH=22,IW=20,OC=4,KD=3,KH=3,KW=3,s0=2,s1=2,s2=2,p0=1,p1=1,p2=1,d0=2,d1=2,d2=2,type_kernel=f16","support","0","no","Metal" +"Metal","CONV_3D","N=2,IC=3,ID=18,IH=22,IW=20,OC=4,KD=3,KH=1,KW=5,s0=2,s1=1,s2=1,p0=2,p1=0,p2=1,d0=1,d1=1,d2=2,type_kernel=f16","support","0","no","Metal" +"Metal","CONV_3D","N=1,IC=4,ID=8,IH=8,IW=8,OC=8,KD=1,KH=1,KW=1,s0=1,s1=1,s2=1,p0=0,p1=0,p2=0,d0=1,d1=1,d2=1,type_kernel=f16","support","0","no","Metal" "Metal","CONV_TRANSPOSE_1D","ne_input=[1,1,1,1],ne_kernel=[1,1,1,1],s0=1,p0=0,d0=1","support","1","yes","Metal" "Metal","CONV_TRANSPOSE_1D","ne_input=[1,1,1,1],ne_kernel=[1,1,1,1],s0=2,p0=0,d0=1","support","1","yes","Metal" "Metal","CONV_TRANSPOSE_1D","ne_input=[1,1,1,1],ne_kernel=[1,1,1,1],s0=3,p0=0,d0=1","support","1","yes","Metal" @@ -2571,11 +4962,12 @@ "Metal","CONV_TRANSPOSE_1D","ne_input=[3,2,1,1],ne_kernel=[3,2,2,1],s0=1,p0=0,d0=1","support","1","yes","Metal" "Metal","CONV_TRANSPOSE_1D","ne_input=[3,2,1,1],ne_kernel=[3,1,2,1],s0=1,p0=0,d0=1","support","1","yes","Metal" "Metal","CONV_TRANSPOSE_1D","ne_input=[2,1,1,1],ne_kernel=[3,1,1,1],s0=1,p0=0,d0=1","support","1","yes","Metal" -"Metal","CONV_TRANSPOSE_2D","ne_input=[3,2,3,1],ne_kernel=[2,2,1,3],stride=1","support","0","no","Metal" -"Metal","CONV_TRANSPOSE_2D","ne_input=[10,10,9,1],ne_kernel=[3,3,1,9],stride=2","support","0","no","Metal" +"Metal","CONV_TRANSPOSE_2D","ne_input=[3,2,3,1],ne_kernel=[2,2,1,3],stride=1","support","1","yes","Metal" +"Metal","CONV_TRANSPOSE_2D","ne_input=[10,10,9,1],ne_kernel=[3,3,1,9],stride=2","support","1","yes","Metal" "Metal","COUNT_EQUAL","type=f32,ne=[4,500,1,1]","support","0","no","Metal" "Metal","COUNT_EQUAL","type=f32,ne=[4,5000,1,1]","support","0","no","Metal" "Metal","ARGMAX","type=f32,ne=[32,1,1,1]","support","1","yes","Metal" +"Metal","ARGMAX","type=f32,ne=[32,513,1,1]","support","1","yes","Metal" "Metal","ARGMAX","type=f32,ne=[100,10,1,1]","support","1","yes","Metal" "Metal","ARGMAX","type=f32,ne=[1024,10,1,1]","support","1","yes","Metal" "Metal","ARGMAX","type=f32,ne=[1024,12,1,1]","support","1","yes","Metal" @@ -2607,7 +4999,7 @@ "Metal","REPEAT_BACK","type=f32,ne=[8,6,4,2],nr=[1,1,1,2],v=1","support","0","no","Metal" "Metal","DUP","type=f32,ne=[10,10,20,1]","support","1","yes","Metal" "Metal","DUP","type=f16,ne=[10,10,20,1]","support","1","yes","Metal" -"Metal","DUP","type=i32,ne=[10,10,20,1]","support","0","no","Metal" +"Metal","DUP","type=i32,ne=[10,10,20,1]","support","1","yes","Metal" "Metal","DUP","type=i16,ne=[10,10,20,1]","support","0","no","Metal" "Metal","DUP","type=f32,ne=[10,10,5,1],permute=[0,2,1,3]","support","1","yes","Metal" "Metal","DUP","type=f16,ne=[10,10,5,1],permute=[0,2,1,3]","support","1","yes","Metal" @@ -2615,400 +5007,457 @@ "Metal","DUP","type=f16,ne=[10,10,5,1],permute=[1,0,2,3]","support","1","yes","Metal" "Metal","DUP","type=i16,ne=[10,8,3,1],permute=[0,2,1,3]","support","0","no","Metal" "Metal","DUP","type=i16,ne=[10,8,3,1],permute=[1,2,0,3]","support","0","no","Metal" -"Metal","SET","type_src=f32,type_dst=f32,ne=[6,5,4,3],dim=1","support","1","yes","Metal" -"Metal","SET","type_src=f32,type_dst=f32,ne=[6,5,4,3],dim=2","support","1","yes","Metal" -"Metal","SET","type_src=f32,type_dst=f32,ne=[6,5,4,3],dim=3","support","1","yes","Metal" -"Metal","SET","type_src=i32,type_dst=i32,ne=[6,5,4,3],dim=1","support","1","yes","Metal" -"Metal","SET","type_src=i32,type_dst=i32,ne=[6,5,4,3],dim=2","support","1","yes","Metal" -"Metal","SET","type_src=i32,type_dst=i32,ne=[6,5,4,3],dim=3","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=f32,ne=[1,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=f32,ne=[1,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=f32,ne=[1,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=f32,ne=[2,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=f32,ne=[2,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=f32,ne=[2,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=f32,ne=[3,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=f32,ne=[3,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=f32,ne=[3,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","1","yes","Metal" -"Metal","CPY","type_src=f16,type_dst=f16,ne=[1,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f16,type_dst=f16,ne=[1,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f16,type_dst=f16,ne=[1,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","1","yes","Metal" -"Metal","CPY","type_src=f16,type_dst=f16,ne=[2,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f16,type_dst=f16,ne=[2,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f16,type_dst=f16,ne=[2,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","1","yes","Metal" -"Metal","CPY","type_src=f16,type_dst=f16,ne=[3,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f16,type_dst=f16,ne=[3,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f16,type_dst=f16,ne=[3,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","1","yes","Metal" -"Metal","CPY","type_src=bf16,type_dst=bf16,ne=[1,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=bf16,type_dst=bf16,ne=[1,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=bf16,type_dst=bf16,ne=[1,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","1","yes","Metal" -"Metal","CPY","type_src=bf16,type_dst=bf16,ne=[2,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=bf16,type_dst=bf16,ne=[2,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=bf16,type_dst=bf16,ne=[2,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","1","yes","Metal" -"Metal","CPY","type_src=bf16,type_dst=bf16,ne=[3,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=bf16,type_dst=bf16,ne=[3,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=bf16,type_dst=bf16,ne=[3,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","1","yes","Metal" -"Metal","CPY","type_src=q4_0,type_dst=q4_0,ne=[32,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q4_0,type_dst=q4_0,ne=[32,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q4_0,type_dst=q4_0,ne=[32,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q4_0,type_dst=q4_0,ne=[64,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q4_0,type_dst=q4_0,ne=[64,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q4_0,type_dst=q4_0,ne=[64,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q4_0,type_dst=q4_0,ne=[96,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q4_0,type_dst=q4_0,ne=[96,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q4_0,type_dst=q4_0,ne=[96,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q4_1,type_dst=q4_1,ne=[32,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q4_1,type_dst=q4_1,ne=[32,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q4_1,type_dst=q4_1,ne=[32,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q4_1,type_dst=q4_1,ne=[64,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q4_1,type_dst=q4_1,ne=[64,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q4_1,type_dst=q4_1,ne=[64,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q4_1,type_dst=q4_1,ne=[96,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q4_1,type_dst=q4_1,ne=[96,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q4_1,type_dst=q4_1,ne=[96,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q5_0,type_dst=q5_0,ne=[32,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q5_0,type_dst=q5_0,ne=[32,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q5_0,type_dst=q5_0,ne=[32,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q5_0,type_dst=q5_0,ne=[64,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q5_0,type_dst=q5_0,ne=[64,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q5_0,type_dst=q5_0,ne=[64,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q5_0,type_dst=q5_0,ne=[96,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q5_0,type_dst=q5_0,ne=[96,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q5_0,type_dst=q5_0,ne=[96,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q5_1,type_dst=q5_1,ne=[32,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q5_1,type_dst=q5_1,ne=[32,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q5_1,type_dst=q5_1,ne=[32,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q5_1,type_dst=q5_1,ne=[64,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q5_1,type_dst=q5_1,ne=[64,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q5_1,type_dst=q5_1,ne=[64,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q5_1,type_dst=q5_1,ne=[96,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q5_1,type_dst=q5_1,ne=[96,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q5_1,type_dst=q5_1,ne=[96,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q8_0,type_dst=q8_0,ne=[32,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q8_0,type_dst=q8_0,ne=[32,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q8_0,type_dst=q8_0,ne=[32,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q8_0,type_dst=q8_0,ne=[64,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q8_0,type_dst=q8_0,ne=[64,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q8_0,type_dst=q8_0,ne=[64,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q8_0,type_dst=q8_0,ne=[96,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q8_0,type_dst=q8_0,ne=[96,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q8_0,type_dst=q8_0,ne=[96,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q2_K,type_dst=q2_K,ne=[256,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q2_K,type_dst=q2_K,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q2_K,type_dst=q2_K,ne=[256,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q2_K,type_dst=q2_K,ne=[512,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q2_K,type_dst=q2_K,ne=[512,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q2_K,type_dst=q2_K,ne=[512,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q2_K,type_dst=q2_K,ne=[768,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q2_K,type_dst=q2_K,ne=[768,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q2_K,type_dst=q2_K,ne=[768,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q3_K,type_dst=q3_K,ne=[256,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q3_K,type_dst=q3_K,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q3_K,type_dst=q3_K,ne=[256,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q3_K,type_dst=q3_K,ne=[512,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q3_K,type_dst=q3_K,ne=[512,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q3_K,type_dst=q3_K,ne=[512,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q3_K,type_dst=q3_K,ne=[768,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q3_K,type_dst=q3_K,ne=[768,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q3_K,type_dst=q3_K,ne=[768,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" -"Metal","CPY","type_src=q4_K,type_dst=q4_K,ne=[256,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q4_K,type_dst=q4_K,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q4_K,type_dst=q4_K,ne=[256,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3]","support","0","no","Metal" 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-"Metal","CPY","type_src=f32,type_dst=f16,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=bf16,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=bf16,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=q4_0,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=q4_0,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=q4_1,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=q4_1,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=q5_0,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=q5_0,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=q5_1,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=q5_1,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=q8_0,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=q8_0,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=q2_K,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=q2_K,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=q3_K,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=q3_K,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=q4_K,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=q4_K,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=q5_K,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=q5_K,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=q6_K,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=q6_K,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=iq2_xxs,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=iq2_xxs,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=iq2_xs,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=iq2_xs,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=iq2_s,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=iq2_s,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=iq3_xxs,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=iq3_xxs,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=iq1_s,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=iq1_s,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=iq1_m,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=iq1_m,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=iq4_nl,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=iq4_nl,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=iq3_s,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=iq3_s,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=iq4_xs,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=iq4_xs,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=f32,type_dst=f32,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f32,type_dst=f32,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f16,type_dst=f32,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=f16,type_dst=f32,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=bf16,type_dst=f32,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=bf16,type_dst=f32,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=q4_0,type_dst=f32,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=q4_0,type_dst=f32,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=q4_1,type_dst=f32,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=q4_1,type_dst=f32,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=q5_0,type_dst=f32,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=q5_0,type_dst=f32,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=q5_1,type_dst=f32,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=q5_1,type_dst=f32,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","1","yes","Metal" -"Metal","CPY","type_src=q8_0,type_dst=f32,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","1","yes","Metal" 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-"Metal","CPY","type_src=q5_K,type_dst=f32,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q5_K,type_dst=f32,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q6_K,type_dst=f32,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=q6_K,type_dst=f32,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=iq2_xxs,type_dst=f32,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=iq2_xxs,type_dst=f32,ne=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0]","support","0","no","Metal" -"Metal","CPY","type_src=iq2_xs,type_dst=f32,ne=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0]","support","0","no","Metal" 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+"Metal","CONT","type=i32,ne=[1,4,4,1],use_view_slice=0","support","1","yes","Metal" +"Metal","CONT","type=i32,ne=[1,8,17,1],use_view_slice=0","support","1","yes","Metal" +"Metal","CONT","type=i32,ne=[10,10,10,1],use_view_slice=0","support","1","yes","Metal" +"Metal","CONT","type=f16,ne=[2,1,1,1],use_view_slice=0","support","1","yes","Metal" +"Metal","CONT","type=f16,ne=[2,1,3,5],use_view_slice=0","support","1","yes","Metal" +"Metal","CONT","type=f16,ne=[2,3,5,7],use_view_slice=0","support","1","yes","Metal" +"Metal","CONT","type=f16,ne=[1,4,4,1],use_view_slice=0","support","1","yes","Metal" +"Metal","CONT","type=f16,ne=[1,8,17,1],use_view_slice=0","support","1","yes","Metal" +"Metal","CONT","type=f16,ne=[10,10,10,1],use_view_slice=0","support","1","yes","Metal" +"Metal","CONT","type=bf16,ne=[2,1,1,1],use_view_slice=0","support","1","yes","Metal" +"Metal","CONT","type=bf16,ne=[2,1,3,5],use_view_slice=0","support","1","yes","Metal" +"Metal","CONT","type=bf16,ne=[2,3,5,7],use_view_slice=0","support","1","yes","Metal" +"Metal","CONT","type=bf16,ne=[1,4,4,1],use_view_slice=0","support","1","yes","Metal" +"Metal","CONT","type=bf16,ne=[1,8,17,1],use_view_slice=0","support","1","yes","Metal" +"Metal","CONT","type=bf16,ne=[10,10,10,1],use_view_slice=0","support","1","yes","Metal" "Metal","ADD","type=f16,ne=[1,1,8,1],nr=[1,1,1,1],nf=1","support","0","no","Metal" "Metal","SUB","type=f16,ne=[1,1,8,1],nr=[1,1,1,1],nf=1","support","0","no","Metal" "Metal","MUL","type=f16,ne=[1,1,8,1],nr=[1,1,1,1],nf=1","support","0","no","Metal" @@ -3061,6 +5510,10 @@ "Metal","SUB","type=f16,ne=[10,5,4,3],nr=[2,2,2,2],nf=1","support","0","no","Metal" "Metal","MUL","type=f16,ne=[10,5,4,3],nr=[2,2,2,2],nf=1","support","0","no","Metal" "Metal","DIV","type=f16,ne=[10,5,4,3],nr=[2,2,2,2],nf=1","support","0","no","Metal" +"Metal","ADD","type=f16,ne=[1,1,65536,1],nr=[256,1,1,1],nf=1","support","0","no","Metal" +"Metal","SUB","type=f16,ne=[1,1,65536,1],nr=[256,1,1,1],nf=1","support","0","no","Metal" +"Metal","MUL","type=f16,ne=[1,1,65536,1],nr=[256,1,1,1],nf=1","support","0","no","Metal" +"Metal","DIV","type=f16,ne=[1,1,65536,1],nr=[256,1,1,1],nf=1","support","0","no","Metal" "Metal","ADD","type=f16,ne=[1280,1,1,1],nr=[1,1,1,1],nf=1","support","0","no","Metal" "Metal","SUB","type=f16,ne=[1280,1,1,1],nr=[1,1,1,1],nf=1","support","0","no","Metal" "Metal","MUL","type=f16,ne=[1280,1,1,1],nr=[1,1,1,1],nf=1","support","0","no","Metal" @@ -3113,6 +5566,10 @@ "Metal","SUB","type=f16,ne=[640,1,1,1],nr=[1,1,1,1],nf=1","support","0","no","Metal" "Metal","MUL","type=f16,ne=[640,1,1,1],nr=[1,1,1,1],nf=1","support","0","no","Metal" "Metal","DIV","type=f16,ne=[640,1,1,1],nr=[1,1,1,1],nf=1","support","0","no","Metal" +"Metal","ADD","type=f16,ne=[64,262144,1,1],nr=[1,1,1,1],nf=1","support","0","no","Metal" +"Metal","SUB","type=f16,ne=[64,262144,1,1],nr=[1,1,1,1],nf=1","support","0","no","Metal" +"Metal","MUL","type=f16,ne=[64,262144,1,1],nr=[1,1,1,1],nf=1","support","0","no","Metal" +"Metal","DIV","type=f16,ne=[64,262144,1,1],nr=[1,1,1,1],nf=1","support","0","no","Metal" "Metal","ADD","type=f32,ne=[1,1,8,1],nr=[1,1,1,1],nf=1","support","1","yes","Metal" "Metal","SUB","type=f32,ne=[1,1,8,1],nr=[1,1,1,1],nf=1","support","1","yes","Metal" "Metal","MUL","type=f32,ne=[1,1,8,1],nr=[1,1,1,1],nf=1","support","1","yes","Metal" @@ -3165,6 +5622,10 @@ "Metal","SUB","type=f32,ne=[10,5,4,3],nr=[2,2,2,2],nf=1","support","1","yes","Metal" "Metal","MUL","type=f32,ne=[10,5,4,3],nr=[2,2,2,2],nf=1","support","1","yes","Metal" "Metal","DIV","type=f32,ne=[10,5,4,3],nr=[2,2,2,2],nf=1","support","1","yes","Metal" +"Metal","ADD","type=f32,ne=[1,1,65536,1],nr=[256,1,1,1],nf=1","support","1","yes","Metal" +"Metal","SUB","type=f32,ne=[1,1,65536,1],nr=[256,1,1,1],nf=1","support","1","yes","Metal" +"Metal","MUL","type=f32,ne=[1,1,65536,1],nr=[256,1,1,1],nf=1","support","1","yes","Metal" +"Metal","DIV","type=f32,ne=[1,1,65536,1],nr=[256,1,1,1],nf=1","support","1","yes","Metal" "Metal","ADD","type=f32,ne=[1280,1,1,1],nr=[1,1,1,1],nf=1","support","1","yes","Metal" "Metal","SUB","type=f32,ne=[1280,1,1,1],nr=[1,1,1,1],nf=1","support","1","yes","Metal" "Metal","MUL","type=f32,ne=[1280,1,1,1],nr=[1,1,1,1],nf=1","support","1","yes","Metal" @@ -3217,51 +5678,42 @@ "Metal","SUB","type=f32,ne=[640,1,1,1],nr=[1,1,1,1],nf=1","support","1","yes","Metal" "Metal","MUL","type=f32,ne=[640,1,1,1],nr=[1,1,1,1],nf=1","support","1","yes","Metal" "Metal","DIV","type=f32,ne=[640,1,1,1],nr=[1,1,1,1],nf=1","support","1","yes","Metal" -"Metal","ADD","type=f32,ne=[10,5,4,3],nr=[2,1,1,1],nf=2","support","1","yes","Metal" -"Metal","ADD","type=f32,ne=[16,5,4,3],nr=[1,2,1,1],nf=3","support","1","yes","Metal" -"Metal","ADD","type=f32,ne=[10,5,4,3],nr=[1,1,2,1],nf=4","support","1","yes","Metal" -"Metal","ADD","type=f32,ne=[16,5,4,3],nr=[1,1,1,2],nf=5","support","1","yes","Metal" -"Metal","ADD","type=f32,ne=[10,5,4,3],nr=[1,1,2,2],nf=6","support","1","yes","Metal" -"Metal","ADD","type=f32,ne=[10,5,4,3],nr=[1,2,2,2],nf=7","support","1","yes","Metal" -"Metal","ADD","type=f32,ne=[16,5,4,3],nr=[2,2,2,2],nf=8","support","1","yes","Metal" +"Metal","ADD","type=f32,ne=[64,262144,1,1],nr=[1,1,1,1],nf=1","support","1","yes","Metal" +"Metal","SUB","type=f32,ne=[64,262144,1,1],nr=[1,1,1,1],nf=1","support","1","yes","Metal" +"Metal","MUL","type=f32,ne=[64,262144,1,1],nr=[1,1,1,1],nf=1","support","1","yes","Metal" +"Metal","DIV","type=f32,ne=[64,262144,1,1],nr=[1,1,1,1],nf=1","support","1","yes","Metal" "Metal","ADD1","type=f32,ne=[10,5,4,3]","support","0","no","Metal" -"Metal","SCALE","type=f32,ne=[10,10,10,10],scale=2.000000,bias=0.000000","support","1","yes","Metal" -"Metal","SCALE","type=f32,ne=[10,10,10,10],scale=2.000000,bias=1.000000","support","1","yes","Metal" +"Metal","ADD1","type=f32,ne=[1024,1024,1,1]","support","0","no","Metal" +"Metal","SCALE","type=f32,ne=[10,10,10,10],scale=2.000000,bias=0.000000,inplace=0","support","1","yes","Metal" +"Metal","SCALE","type=f32,ne=[10,10,10,10],scale=2.000000,bias=1.000000,inplace=0","support","1","yes","Metal" +"Metal","SCALE","type=f32,ne=[10,10,10,10],scale=2.000000,bias=1.000000,inplace=1","support","1","yes","Metal" +"Metal","SCALE","type=f32,ne=[100,10,10,10],scale=2.000000,bias=1.000000,inplace=0","support","1","yes","Metal" "Metal","SILU_BACK","type=f32,ne=[64,5,4,3],eps=0.000001","support","0","no","Metal" "Metal","NORM","type=f32,ne=[64,5,4,3],v=0,eps=0.000000","support","1","yes","Metal" -"Metal","RMS_NORM","type=f32,ne=[64,5,4,3],v=0,eps=0.000000","support","1","yes","Metal" -"Metal","NORM","type=f32,ne=[64,5,4,3],v=1,eps=0.000000","support","0","no","Metal" -"Metal","RMS_NORM","type=f32,ne=[64,5,4,3],v=1,eps=0.000000","support","0","no","Metal" +"Metal","RMS_NORM","type=f32,ne=[64,5,4,3],v=0,eps=0.000000,inplace=0","support","1","yes","Metal" +"Metal","NORM","type=f32,ne=[64,5,4,3],v=1,eps=0.000000","support","1","yes","Metal" +"Metal","RMS_NORM","type=f32,ne=[64,5,4,3],v=1,eps=0.000000,inplace=0","support","1","yes","Metal" "Metal","RMS_NORM_BACK","type=f32,ne=[64,5,4,3],eps=0.000000","support","0","no","Metal" "Metal","L2_NORM","type=f32,ne=[64,5,4,3]","support","1","yes","Metal" "Metal","NORM","type=f32,ne=[64,5,4,3],v=0,eps=0.000001","support","1","yes","Metal" -"Metal","RMS_NORM","type=f32,ne=[64,5,4,3],v=0,eps=0.000001","support","1","yes","Metal" -"Metal","NORM","type=f32,ne=[64,5,4,3],v=1,eps=0.000001","support","0","no","Metal" -"Metal","RMS_NORM","type=f32,ne=[64,5,4,3],v=1,eps=0.000001","support","0","no","Metal" +"Metal","RMS_NORM","type=f32,ne=[64,5,4,3],v=0,eps=0.000001,inplace=0","support","1","yes","Metal" +"Metal","NORM","type=f32,ne=[64,5,4,3],v=1,eps=0.000001","support","1","yes","Metal" +"Metal","RMS_NORM","type=f32,ne=[64,5,4,3],v=1,eps=0.000001,inplace=0","support","1","yes","Metal" "Metal","RMS_NORM_BACK","type=f32,ne=[64,5,4,3],eps=0.000001","support","0","no","Metal" "Metal","L2_NORM","type=f32,ne=[64,5,4,3]","support","1","yes","Metal" "Metal","NORM","type=f32,ne=[64,5,4,3],v=0,eps=0.000100","support","1","yes","Metal" -"Metal","RMS_NORM","type=f32,ne=[64,5,4,3],v=0,eps=0.000100","support","1","yes","Metal" -"Metal","NORM","type=f32,ne=[64,5,4,3],v=1,eps=0.000100","support","0","no","Metal" -"Metal","RMS_NORM","type=f32,ne=[64,5,4,3],v=1,eps=0.000100","support","0","no","Metal" +"Metal","RMS_NORM","type=f32,ne=[64,5,4,3],v=0,eps=0.000100,inplace=0","support","1","yes","Metal" +"Metal","NORM","type=f32,ne=[64,5,4,3],v=1,eps=0.000100","support","1","yes","Metal" +"Metal","RMS_NORM","type=f32,ne=[64,5,4,3],v=1,eps=0.000100,inplace=0","support","1","yes","Metal" "Metal","RMS_NORM_BACK","type=f32,ne=[64,5,4,3],eps=0.000100","support","0","no","Metal" "Metal","L2_NORM","type=f32,ne=[64,5,4,3]","support","1","yes","Metal" "Metal","NORM","type=f32,ne=[64,5,4,3],v=0,eps=0.100000","support","1","yes","Metal" -"Metal","RMS_NORM","type=f32,ne=[64,5,4,3],v=0,eps=0.100000","support","1","yes","Metal" -"Metal","NORM","type=f32,ne=[64,5,4,3],v=1,eps=0.100000","support","0","no","Metal" -"Metal","RMS_NORM","type=f32,ne=[64,5,4,3],v=1,eps=0.100000","support","0","no","Metal" +"Metal","RMS_NORM","type=f32,ne=[64,5,4,3],v=0,eps=0.100000,inplace=0","support","1","yes","Metal" +"Metal","NORM","type=f32,ne=[64,5,4,3],v=1,eps=0.100000","support","1","yes","Metal" +"Metal","RMS_NORM","type=f32,ne=[64,5,4,3],v=1,eps=0.100000,inplace=0","support","1","yes","Metal" "Metal","RMS_NORM_BACK","type=f32,ne=[64,5,4,3],eps=0.100000","support","0","no","Metal" "Metal","L2_NORM","type=f32,ne=[64,5,4,3]","support","1","yes","Metal" -"Metal","RMS_NORM_MUL_ADD","type=f32,ne=[64,5,4,3],eps=0.000000,broadcast=0","support","1","yes","Metal" -"Metal","RMS_NORM_MUL_ADD","type=f32,ne=[64,5,4,3],eps=0.000000,broadcast=1","support","1","yes","Metal" -"Metal","RMS_NORM_MUL_ADD","type=f32,ne=[64,5,4,3],eps=0.000001,broadcast=0","support","1","yes","Metal" -"Metal","RMS_NORM_MUL_ADD","type=f32,ne=[64,5,4,3],eps=0.000001,broadcast=1","support","1","yes","Metal" -"Metal","RMS_NORM_MUL_ADD","type=f32,ne=[64,5,4,3],eps=0.000100,broadcast=0","support","1","yes","Metal" -"Metal","RMS_NORM_MUL_ADD","type=f32,ne=[64,5,4,3],eps=0.000100,broadcast=1","support","1","yes","Metal" -"Metal","RMS_NORM_MUL_ADD","type=f32,ne=[64,5,4,3],eps=0.100000,broadcast=0","support","1","yes","Metal" -"Metal","RMS_NORM_MUL_ADD","type=f32,ne=[64,5,4,3],eps=0.100000,broadcast=1","support","1","yes","Metal" -"Metal","RMS_NORM_MUL_ADD","type=f32,ne=[64,5,4,3],eps=1.000000,broadcast=0","support","1","yes","Metal" -"Metal","RMS_NORM_MUL_ADD","type=f32,ne=[64,5,4,3],eps=1.000000,broadcast=1","support","1","yes","Metal" +"Metal","RMS_NORM","type=f32,ne=[64,5,4,3],v=0,eps=0.000001,inplace=1","support","1","yes","Metal" "Metal","L2_NORM","type=f32,ne=[64,5,4,3]","support","1","yes","Metal" "Metal","SSM_CONV","type=f32,ne_a=[4,1024,1,1],ne_b=[3,1024,1,1]","support","1","yes","Metal" "Metal","SSM_CONV","type=f32,ne_a=[8,1024,1,1],ne_b=[3,1024,1,1]","support","1","yes","Metal" @@ -3296,1207 +5748,1816 @@ "Metal","GATED_LINEAR_ATTN","type=f32,head_count=32,head_size=64,n_seq_tokens=32,n_seqs=1","support","0","no","Metal" "Metal","GATED_LINEAR_ATTN","type=f32,head_count=32,head_size=64,n_seq_tokens=32,n_seqs=4","support","0","no","Metal" "Metal","GATED_LINEAR_ATTN","type=f32,head_count=32,head_size=64,n_seq_tokens=128,n_seqs=4","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_0,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_0,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_0,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_0,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_0,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_0,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_0,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_0,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_0,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_1,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_1,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_1,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_1,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_1,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_1,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_1,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_1,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_1,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q2_K,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q2_K,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q2_K,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q2_K,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q2_K,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q2_K,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q2_K,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q2_K,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q2_K,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q3_K,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q3_K,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q3_K,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q3_K,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q3_K,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q3_K,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q3_K,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q3_K,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q3_K,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_K,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_K,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_K,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_K,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_K,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_K,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_K,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_K,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_K,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q6_K,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q6_K,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q6_K,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q6_K,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q6_K,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q6_K,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q6_K,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q6_K,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q6_K,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xs,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xs,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xs,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xs,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xs,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xs,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xs,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xs,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xs,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_s,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_s,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_s,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_s,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_s,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_s,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_s,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_s,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_s,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_xxs,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_xxs,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_xxs,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_xxs,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_xxs,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_xxs,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_xxs,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_xxs,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_xxs,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_s,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_s,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_s,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_s,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_s,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_s,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_s,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_s,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_s,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_m,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_m,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_m,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_m,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_m,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_m,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_m,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_m,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_m,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_nl,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_nl,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_nl,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_nl,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_nl,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_nl,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_nl,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_nl,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_nl,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_s,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_s,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_s,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_s,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_s,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_s,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_s,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_s,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_s,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_xs,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_xs,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_xs,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_xs,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_xs,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_xs,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_xs,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_xs,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_xs,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=4,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=4,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=4,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=4,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=4,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=4,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=4,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=4,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=4,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=4,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=4,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=4,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=4,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=4,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=4,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=4,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=4,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=4,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=4,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=4,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=4,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=8,k=4,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=8,k=4,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=8,k=4,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=4,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=4,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=4,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=8,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=16,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=4,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=4,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=4,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=4,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=4,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=4,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=4,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=4,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=4,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=4,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=4,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=4,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=4,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=4,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=4,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=4,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=4,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=4,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=4,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=4,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=4,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=8,k=4,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=8,k=4,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=8,k=4,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=4,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=4,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=4,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=1,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=8,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f16,m=16,n=16,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","0","no","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=4,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=4,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=4,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=4,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=4,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=4,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=4,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=4,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=4,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=4,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=4,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=4,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=4,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=4,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=4,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=4,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=4,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=4,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=4,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=4,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=4,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=8,k=4,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=8,k=4,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=8,k=4,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=4,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=4,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=4,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=8,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=16,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=4,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=4,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=4,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=4,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=4,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=4,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=4,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=4,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=4,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=4,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=4,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=4,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=4,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=4,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=4,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=4,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=4,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=4,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=4,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=4,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=4,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=8,k=4,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=8,k=4,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=8,k=4,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=4,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=4,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=4,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=1,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=8,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f16,m=16,n=16,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=1,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=1,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=16,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=16,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=1,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=8,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=16,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=1,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=1,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=16,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=16,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=1,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=8,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f16,m=16,n=16,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=1,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=1,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=16,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=16,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=1,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=8,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=16,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=1,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=1,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=16,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=16,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=1,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=8,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_0,type_b=f16,m=16,n=16,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=1,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=1,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=16,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=16,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=1,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=8,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=16,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=1,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=1,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=16,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=16,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=1,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=8,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f16,m=16,n=16,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=1,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=1,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=16,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=16,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=1,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=8,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f32,m=16,n=16,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=1,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=1,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=16,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=16,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=1,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=8,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_K,type_b=f16,m=16,n=16,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=1,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=1,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=1,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=16,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=16,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=16,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=16,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=1,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=8,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f32,m=16,n=16,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=1,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=1,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=1,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=1,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=16,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=16,k=256,bs=[3,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=16,k=256,bs=[3,1],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[2,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[1,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=16,k=256,bs=[3,2],nr=[2,2],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=1,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=8,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,1,3,2],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=16,k=256,bs=[2,3],nr=[1,1],per=[0,3,2,1],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=1,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=8,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xxs,type_b=f16,m=16,n=16,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=1,k=32,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_0,type_b=f32,m=16,n=1,k=32,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_0,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_1,type_b=f32,m=16,n=1,k=32,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_1,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=1,k=32,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q2_K,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q3_K,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q5_K,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=q6_K,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_xs,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq2_s,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_xxs,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_s,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq1_m,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_nl,type_b=f32,m=16,n=1,k=32,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_nl,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq3_s,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=iq4_xs,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=1,k=1,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=64,n=2,k=128,bs=[8,1],nr=[1,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=83,n=2,k=128,bs=[8,1],nr=[4,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=64,n=2,k=64,bs=[8,1],nr=[4,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=83,n=2,k=64,bs=[8,1],nr=[4,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=64,n=45,k=128,bs=[8,1],nr=[4,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=45,k=64,bs=[8,1],nr=[4,1],per=[0,1,2,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=193,bs=[1,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=67,bs=[1,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=128,bs=[1,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=1,k=1056,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1056,n=1,k=128,bs=[1,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=128,n=1,k=1056,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1056,n=1,k=128,bs=[1,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=128,n=1,k=1056,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=129,bs=[1,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=1,k=1057,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1056,n=1,k=129,bs=[1,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=128,n=1,k=1057,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1056,n=1,k=129,bs=[1,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=128,n=1,k=1057,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1057,n=1,k=128,bs=[1,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=129,n=1,k=1056,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1057,n=1,k=128,bs=[1,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=129,n=1,k=1056,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1057,n=1,k=128,bs=[1,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=129,n=1,k=1056,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1057,n=1,k=129,bs=[1,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=129,n=1,k=1057,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1057,n=1,k=129,bs=[1,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=129,n=1,k=1057,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1057,n=1,k=129,bs=[1,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=129,n=1,k=1057,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=128,bs=[1,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=1,k=1056,bs=[1,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1056,n=1,k=128,bs=[1,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=128,n=1,k=1056,bs=[1,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1056,n=1,k=128,bs=[1,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=128,n=1,k=1056,bs=[1,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=129,bs=[1,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=1,k=1057,bs=[1,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1056,n=1,k=129,bs=[1,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=128,n=1,k=1057,bs=[1,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1056,n=1,k=129,bs=[1,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=128,n=1,k=1057,bs=[1,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1057,n=1,k=128,bs=[1,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=129,n=1,k=1056,bs=[1,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1057,n=1,k=128,bs=[1,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=129,n=1,k=1056,bs=[1,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1057,n=1,k=128,bs=[1,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=129,n=1,k=1056,bs=[1,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1057,n=1,k=129,bs=[1,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=129,n=1,k=1057,bs=[1,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1057,n=1,k=129,bs=[1,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=129,n=1,k=1057,bs=[1,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1057,n=1,k=129,bs=[1,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=129,n=1,k=1057,bs=[1,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=128,bs=[2,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=1,k=1056,bs=[2,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1056,n=1,k=128,bs=[2,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=128,n=1,k=1056,bs=[2,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1056,n=1,k=128,bs=[2,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=128,n=1,k=1056,bs=[2,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=129,bs=[2,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=1,k=1057,bs=[2,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1056,n=1,k=129,bs=[2,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=128,n=1,k=1057,bs=[2,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1056,n=1,k=129,bs=[2,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=128,n=1,k=1057,bs=[2,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1057,n=1,k=128,bs=[2,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=129,n=1,k=1056,bs=[2,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1057,n=1,k=128,bs=[2,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=129,n=1,k=1056,bs=[2,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1057,n=1,k=128,bs=[2,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=129,n=1,k=1056,bs=[2,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1057,n=1,k=129,bs=[2,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=129,n=1,k=1057,bs=[2,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1057,n=1,k=129,bs=[2,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=129,n=1,k=1057,bs=[2,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1057,n=1,k=129,bs=[2,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=129,n=1,k=1057,bs=[2,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=128,bs=[2,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=1,k=1056,bs=[2,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1056,n=1,k=128,bs=[2,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=128,n=1,k=1056,bs=[2,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1056,n=1,k=128,bs=[2,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=128,n=1,k=1056,bs=[2,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=129,bs=[2,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=1,k=1057,bs=[2,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1056,n=1,k=129,bs=[2,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=128,n=1,k=1057,bs=[2,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1056,n=1,k=129,bs=[2,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=128,n=1,k=1057,bs=[2,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1057,n=1,k=128,bs=[2,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=129,n=1,k=1056,bs=[2,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1057,n=1,k=128,bs=[2,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=129,n=1,k=1056,bs=[2,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1057,n=1,k=128,bs=[2,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=129,n=1,k=1056,bs=[2,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1057,n=1,k=129,bs=[2,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=129,n=1,k=1057,bs=[2,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1057,n=1,k=129,bs=[2,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=129,n=1,k=1057,bs=[2,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1057,n=1,k=129,bs=[2,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=129,n=1,k=1057,bs=[2,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=128,bs=[4,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=1,k=1056,bs=[4,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1056,n=1,k=128,bs=[4,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=128,n=1,k=1056,bs=[4,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1056,n=1,k=128,bs=[4,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=128,n=1,k=1056,bs=[4,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=129,bs=[4,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=1,k=1057,bs=[4,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1056,n=1,k=129,bs=[4,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=128,n=1,k=1057,bs=[4,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1056,n=1,k=129,bs=[4,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=128,n=1,k=1057,bs=[4,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1057,n=1,k=128,bs=[4,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=129,n=1,k=1056,bs=[4,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1057,n=1,k=128,bs=[4,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=129,n=1,k=1056,bs=[4,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1057,n=1,k=128,bs=[4,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=129,n=1,k=1056,bs=[4,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1057,n=1,k=129,bs=[4,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=129,n=1,k=1057,bs=[4,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1057,n=1,k=129,bs=[4,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=129,n=1,k=1057,bs=[4,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1057,n=1,k=129,bs=[4,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=129,n=1,k=1057,bs=[4,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=128,bs=[4,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=1,k=1056,bs=[4,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1056,n=1,k=128,bs=[4,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=128,n=1,k=1056,bs=[4,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1056,n=1,k=128,bs=[4,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=128,n=1,k=1056,bs=[4,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=129,bs=[4,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=1,k=1057,bs=[4,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1056,n=1,k=129,bs=[4,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=128,n=1,k=1057,bs=[4,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1056,n=1,k=129,bs=[4,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=128,n=1,k=1057,bs=[4,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1057,n=1,k=128,bs=[4,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=129,n=1,k=1056,bs=[4,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1057,n=1,k=128,bs=[4,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=129,n=1,k=1056,bs=[4,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1057,n=1,k=128,bs=[4,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=129,n=1,k=1056,bs=[4,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1057,n=1,k=129,bs=[4,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=129,n=1,k=1057,bs=[4,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1057,n=1,k=129,bs=[4,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=129,n=1,k=1057,bs=[4,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1057,n=1,k=129,bs=[4,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=129,n=1,k=1057,bs=[4,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=128,bs=[8,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=1,k=1056,bs=[8,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1056,n=1,k=128,bs=[8,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=128,n=1,k=1056,bs=[8,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1056,n=1,k=128,bs=[8,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=128,n=1,k=1056,bs=[8,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=129,bs=[8,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=1,k=1057,bs=[8,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1056,n=1,k=129,bs=[8,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=128,n=1,k=1057,bs=[8,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1056,n=1,k=129,bs=[8,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=128,n=1,k=1057,bs=[8,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1057,n=1,k=128,bs=[8,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=129,n=1,k=1056,bs=[8,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1057,n=1,k=128,bs=[8,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=129,n=1,k=1056,bs=[8,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1057,n=1,k=128,bs=[8,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=129,n=1,k=1056,bs=[8,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1057,n=1,k=129,bs=[8,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=129,n=1,k=1057,bs=[8,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1057,n=1,k=129,bs=[8,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=129,n=1,k=1057,bs=[8,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1057,n=1,k=129,bs=[8,1],nr=[1,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=129,n=1,k=1057,bs=[8,1],nr=[1,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=128,bs=[8,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=1,k=1056,bs=[8,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1056,n=1,k=128,bs=[8,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=128,n=1,k=1056,bs=[8,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1056,n=1,k=128,bs=[8,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=128,n=1,k=1056,bs=[8,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=129,bs=[8,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=1,k=1057,bs=[8,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1056,n=1,k=129,bs=[8,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=128,n=1,k=1057,bs=[8,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1056,n=1,k=129,bs=[8,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=128,n=1,k=1057,bs=[8,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1057,n=1,k=128,bs=[8,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=129,n=1,k=1056,bs=[8,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1057,n=1,k=128,bs=[8,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=129,n=1,k=1056,bs=[8,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1057,n=1,k=128,bs=[8,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=129,n=1,k=1056,bs=[8,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1057,n=1,k=129,bs=[8,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f16,type_b=f32,m=129,n=1,k=1057,bs=[8,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1057,n=1,k=129,bs=[8,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=129,n=1,k=1057,bs=[8,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1057,n=1,k=129,bs=[8,1],nr=[4,1],per=[0,2,1,3],v=0","support","1","yes","Metal" -"Metal","MUL_MAT","type_a=f32,type_b=f32,m=129,n=1,k=1057,bs=[8,1],nr=[4,1],per=[0,1,2,3],v=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f32,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q4_1,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" 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+"Metal","MUL_MAT","type_a=q5_0,type_b=f32,m=16,n=1,k=32,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q5_0,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q5_1,type_b=f32,m=16,n=1,k=32,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q5_1,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=1,k=32,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q8_0,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q2_K,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q3_K,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q5_K,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q6_K,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=iq2_xs,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=iq2_s,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=iq3_xxs,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=iq1_s,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=iq1_m,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=iq4_nl,type_b=f32,m=16,n=1,k=32,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=iq4_nl,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=iq3_s,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=iq4_xs,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=1,k=1,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=64,n=2,k=128,bs=[8,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=83,n=2,k=128,bs=[8,1],nr=[4,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=64,n=2,k=64,bs=[8,1],nr=[4,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=83,n=2,k=64,bs=[8,1],nr=[4,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=64,n=45,k=128,bs=[8,1],nr=[4,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=45,k=64,bs=[8,1],nr=[4,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=193,bs=[1,1],nr=[4,1],per=[0,2,1,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=67,bs=[1,1],nr=[4,1],per=[0,2,1,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f32,type_b=f32,m=64,n=77,k=77,bs=[12,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=q4_0,type_b=f32,m=576,n=512,k=576,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=128,bs=[1,1],nr=[1,1],per=[0,2,1,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=1,k=1056,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=2112,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1056,n=1,k=128,bs=[1,1],nr=[1,1],per=[0,2,1,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=128,n=1,k=1056,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=2112,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1056,n=1,k=128,bs=[1,1],nr=[1,1],per=[0,2,1,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f32,type_b=f32,m=128,n=1,k=1056,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=2112,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=129,bs=[1,1],nr=[1,1],per=[0,2,1,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f16,type_b=f32,m=128,n=1,k=1057,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=2113,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=1056,n=1,k=129,bs=[1,1],nr=[1,1],per=[0,2,1,3],k_v=0,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=bf16,type_b=f32,m=128,n=1,k=1057,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=2113,o=1","support","1","yes","Metal" +"Metal","MUL_MAT","type_a=f32,type_b=f32,m=1056,n=1,k=129,bs=[1,1],nr=[1,1],per=[0,2,1,3],k_v=0,o=1","support","1","yes","Metal" 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+"Metal","SOFT_MAX_BACK","type=f32,ne=[1024,1024,2,3],scale=1.000000,max_bias=8.000000","support","0","no","Metal" "Metal","SOFT_MAX_BACK","type=f32,ne=[16,16,1,1],scale=0.100000,max_bias=8.000000","support","0","no","Metal" "Metal","SOFT_MAX_BACK","type=f32,ne=[15,15,1,1],scale=0.100000,max_bias=8.000000","support","0","no","Metal" +"Metal","SOFT_MAX_BACK","type=f32,ne=[16,16,2,3],scale=0.100000,max_bias=8.000000","support","0","no","Metal" "Metal","SOFT_MAX_BACK","type=f32,ne=[16,1024,1,1],scale=0.100000,max_bias=8.000000","support","0","no","Metal" "Metal","SOFT_MAX_BACK","type=f32,ne=[15,1023,1,1],scale=0.100000,max_bias=8.000000","support","0","no","Metal" +"Metal","SOFT_MAX_BACK","type=f32,ne=[16,1024,2,3],scale=0.100000,max_bias=8.000000","support","0","no","Metal" "Metal","SOFT_MAX_BACK","type=f32,ne=[1024,16,1,1],scale=0.100000,max_bias=8.000000","support","0","no","Metal" "Metal","SOFT_MAX_BACK","type=f32,ne=[1023,15,1,1],scale=0.100000,max_bias=8.000000","support","0","no","Metal" +"Metal","SOFT_MAX_BACK","type=f32,ne=[1024,16,2,3],scale=0.100000,max_bias=8.000000","support","0","no","Metal" "Metal","SOFT_MAX_BACK","type=f32,ne=[1024,1024,1,1],scale=0.100000,max_bias=8.000000","support","0","no","Metal" "Metal","SOFT_MAX_BACK","type=f32,ne=[1023,1023,1,1],scale=0.100000,max_bias=8.000000","support","0","no","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,40,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,52,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,64,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,1,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,71,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,8,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=20,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=32,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,4,1],n_dims=32,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=20,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=32,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,4,1],n_dims=32,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,12,2,1],n_dims=128,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,28,2,1],n_dims=128,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,12,2,1],n_dims=20,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,28,2,1],n_dims=32,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,16,2,1],n_dims=80,mode=24,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,40,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,52,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,64,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,1,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,71,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,8,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=20,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=32,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,4,1],n_dims=32,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=20,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=32,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,4,1],n_dims=32,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,12,2,1],n_dims=128,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,28,2,1],n_dims=128,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,12,2,1],n_dims=20,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,28,2,1],n_dims=32,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,16,2,1],n_dims=80,mode=24,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,40,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,52,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,64,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,1,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,71,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,8,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=20,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=32,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,4,1],n_dims=32,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=20,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=32,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,4,1],n_dims=32,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,12,2,1],n_dims=128,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,28,2,1],n_dims=128,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,12,2,1],n_dims=20,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,28,2,1],n_dims=32,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,16,2,1],n_dims=80,mode=24,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,40,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,52,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,64,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,1,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,71,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,8,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=20,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=32,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,4,1],n_dims=32,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=20,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=32,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,32,4,1],n_dims=32,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,12,2,1],n_dims=128,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,28,2,1],n_dims=128,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,12,2,1],n_dims=20,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,28,2,1],n_dims=32,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[80,16,2,1],n_dims=80,mode=24,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.424500,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.424500,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.424500,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.424500,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.424500,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.424500,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.424500,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.424500,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.424500,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.424500,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.424500,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.424500,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.424500,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.424500,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.424500,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.424500,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.746500,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.746500,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.746500,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.746500,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.746500,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.746500,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.746500,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.746500,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.746500,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.746500,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.746500,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.746500,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.746500,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.746500,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.746500,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.746500,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.746500,af=1.424500,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.746500,af=1.424500,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.746500,af=1.424500,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.746500,af=1.424500,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.746500,af=1.424500,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.746500,af=1.424500,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.746500,af=1.424500,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.746500,af=1.424500,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.746500,af=1.424500,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.746500,af=1.424500,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.746500,af=1.424500,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.746500,af=1.424500,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.746500,af=1.424500,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.746500,af=1.424500,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.746500,af=1.424500,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.746500,af=1.424500,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=0","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=1","support","1","yes","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,40,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,52,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,64,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,1,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,71,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,8,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,2,1],n_dims=20,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,2,1],n_dims=32,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,4,1],n_dims=32,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,2,1],n_dims=20,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,2,1],n_dims=32,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,4,1],n_dims=32,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,12,2,1],n_dims=128,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,28,2,1],n_dims=128,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,12,2,1],n_dims=20,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,28,2,1],n_dims=32,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,16,2,1],n_dims=80,mode=24,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,40,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,52,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,64,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,1,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,71,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,8,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,2,1],n_dims=20,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,2,1],n_dims=32,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,4,1],n_dims=32,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,2,1],n_dims=20,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,2,1],n_dims=32,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,4,1],n_dims=32,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,12,2,1],n_dims=128,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,28,2,1],n_dims=128,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,12,2,1],n_dims=20,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,28,2,1],n_dims=32,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,16,2,1],n_dims=80,mode=24,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,40,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,52,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,64,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,1,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,71,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,8,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,2,1],n_dims=20,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,2,1],n_dims=32,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,4,1],n_dims=32,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,2,1],n_dims=20,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,2,1],n_dims=32,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,4,1],n_dims=32,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,12,2,1],n_dims=128,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,28,2,1],n_dims=128,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,12,2,1],n_dims=20,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,28,2,1],n_dims=32,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,16,2,1],n_dims=80,mode=24,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,40,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,52,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,64,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,1,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,71,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,8,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,2,1],n_dims=20,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,2,1],n_dims=32,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,4,1],n_dims=32,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,2,1],n_dims=20,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,2,1],n_dims=32,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[80,32,4,1],n_dims=32,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,12,2,1],n_dims=128,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=1,v=1","support","0","no","Metal" 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-"Metal","ROPE_BACK","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.000000,af=1.424500,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.000000,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=0","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=1","support","0","no","Metal" -"Metal","ROPE_BACK","type=f16,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=1","support","0","no","Metal" +"Metal","SOFT_MAX_BACK","type=f32,ne=[1024,1024,2,3],scale=0.100000,max_bias=8.000000","support","0","no","Metal" +"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[128,40,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[128,52,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[128,64,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[64,1,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[64,71,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[64,8,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=20,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=32,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[80,32,4,1],n_dims=32,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=20,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[80,32,2,1],n_dims=32,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[80,32,4,1],n_dims=32,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[128,12,2,1],n_dims=128,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[128,28,2,1],n_dims=128,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[128,12,2,1],n_dims=20,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[128,28,2,1],n_dims=32,mode=8,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[128,12,2,1],n_dims=128,mode=40,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[128,28,2,1],n_dims=128,mode=40,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[128,12,2,1],n_dims=20,mode=40,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[128,28,2,1],n_dims=32,mode=40,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[80,16,2,1],n_dims=80,mode=24,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[128,16,2,1],n_dims=128,mode=40,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[64,128,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=0,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[128,32,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[128,40,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[128,52,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[128,64,2,1],n_dims=128,mode=0,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[64,1,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1,inplace=0","support","1","yes","Metal" +"Metal","ROPE","type=f32,ne_a=[64,71,2,1],n_dims=64,mode=2,n_ctx=512,fs=1.000000,ef=0.000000,af=1.000000,ff=0,v=1,inplace=0","support","1","yes","Metal" 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+"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=0,inplace=1","support","1","yes","Metal" +"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=2,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=0,inplace=1","support","1","yes","Metal" +"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=8,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=0,inplace=1","support","1","yes","Metal" +"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=8,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=0,inplace=1","support","1","yes","Metal" +"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=40,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=0,inplace=1","support","1","yes","Metal" +"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=40,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=0,inplace=1","support","1","yes","Metal" +"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=24,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=0,inplace=1","support","1","yes","Metal" +"Metal","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=24,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=0,inplace=1","support","1","yes","Metal" "Metal","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=0,v=0","support","1","yes","Metal" "Metal","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=0,v=0","support","1","yes","Metal" "Metal","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=1,v=0","support","1","yes","Metal" @@ -6003,2131 +9448,9295 @@ "Metal","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=2,v=3","support","1","yes","Metal" "Metal","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=3","support","1","yes","Metal" "Metal","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=3","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[3,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[4,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[7,1,1,1],order=0","support","1","yes","Metal" "Metal","ARGSORT","type=f32,ne=[8,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[15,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[16,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[31,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[32,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[63,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[64,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[127,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[128,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[255,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[256,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[511,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[512,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[1023,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[1024,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[2047,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[2048,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[4095,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[4096,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[8191,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[8192,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[16383,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[16384,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[32767,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[32768,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[65535,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[65536,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[131071,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[131072,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[262143,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[262144,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[524287,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[524288,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[1048575,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[1048576,1,1,1],order=0","support","1","yes","Metal" "Metal","ARGSORT","type=f32,ne=[16,10,10,10],order=0","support","1","yes","Metal" "Metal","ARGSORT","type=f32,ne=[60,10,10,10],order=0","support","1","yes","Metal" -"Metal","ARGSORT","type=f32,ne=[8,1,1,1],order=1","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[1023,2,1,3],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[1024,2,1,3],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[1025,2,1,3],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[2047,2,1,3],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[2048,2,1,3],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[2049,2,1,3],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[2,8,8192,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[3,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[4,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[7,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[8,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[15,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[16,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[31,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[32,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[63,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[64,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[127,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[128,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[255,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[256,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[511,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[512,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[1023,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[1024,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[2047,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[2048,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[4095,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[4096,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[8191,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[8192,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[16383,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[16384,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[32767,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[32768,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[65535,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[65536,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[131071,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[131072,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[262143,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[262144,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[524287,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[524288,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[1048575,1,1,1],order=0","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[1048576,1,1,1],order=0","support","1","yes","Metal" "Metal","ARGSORT","type=f32,ne=[16,10,10,10],order=1","support","1","yes","Metal" "Metal","ARGSORT","type=f32,ne=[60,10,10,10],order=1","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[1023,2,1,3],order=1","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[1024,2,1,3],order=1","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[1025,2,1,3],order=1","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[2047,2,1,3],order=1","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[2048,2,1,3],order=1","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[2049,2,1,3],order=1","support","1","yes","Metal" +"Metal","ARGSORT","type=f32,ne=[2,8,8192,1],order=1","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[1,1,1,1],k=1","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[12,1,2,1],k=1","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[2,1,1,1],k=1","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[13,1,2,1],k=1","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[2,1,1,1],k=2","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[13,1,2,1],k=2","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[4,1,1,1],k=1","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[15,1,2,1],k=1","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[4,1,1,1],k=2","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[15,1,2,1],k=2","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[4,1,1,1],k=3","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[15,1,2,1],k=3","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[8,1,1,1],k=1","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[19,1,2,1],k=1","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[8,1,1,1],k=2","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[19,1,2,1],k=2","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[8,1,1,1],k=3","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[19,1,2,1],k=3","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[8,1,1,1],k=7","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[19,1,2,1],k=7","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[16,1,1,1],k=1","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[27,1,2,1],k=1","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[16,1,1,1],k=2","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[27,1,2,1],k=2","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[16,1,1,1],k=3","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[27,1,2,1],k=3","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[16,1,1,1],k=7","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[27,1,2,1],k=7","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[16,1,1,1],k=15","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[27,1,2,1],k=15","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[32,1,1,1],k=1","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[43,1,2,1],k=1","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[32,1,1,1],k=2","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[43,1,2,1],k=2","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[32,1,1,1],k=3","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[43,1,2,1],k=3","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[32,1,1,1],k=7","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[43,1,2,1],k=7","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[32,1,1,1],k=15","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[43,1,2,1],k=15","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[64,1,1,1],k=1","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[75,1,2,1],k=1","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[64,1,1,1],k=2","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[75,1,2,1],k=2","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[64,1,1,1],k=3","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[75,1,2,1],k=3","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[64,1,1,1],k=7","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[75,1,2,1],k=7","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[64,1,1,1],k=15","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[75,1,2,1],k=15","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[128,1,1,1],k=1","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[139,1,2,1],k=1","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[128,1,1,1],k=2","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[139,1,2,1],k=2","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[128,1,1,1],k=3","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[139,1,2,1],k=3","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[128,1,1,1],k=7","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[139,1,2,1],k=7","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[128,1,1,1],k=15","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[139,1,2,1],k=15","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[128,1,1,1],k=100","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[139,1,2,1],k=100","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[256,1,1,1],k=1","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[267,1,2,1],k=1","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[256,1,1,1],k=2","support","1","yes","Metal" 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+"Metal","TOP_K","type=f32,ne=[16,10,10,10],k=7","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[60,10,10,10],k=7","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[1023,2,1,3],k=7","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[1024,2,1,3],k=7","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[1025,2,1,3],k=7","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[16384,1,1,1],k=7","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[2047,2,1,3],k=7","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[2048,2,1,3],k=7","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[2049,2,1,3],k=7","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[16,10,10,10],k=15","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[60,10,10,10],k=15","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[1023,2,1,3],k=15","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[1024,2,1,3],k=15","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[1025,2,1,3],k=15","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[16384,1,1,1],k=15","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[2047,2,1,3],k=15","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[2048,2,1,3],k=15","support","1","yes","Metal" +"Metal","TOP_K","type=f32,ne=[2049,2,1,3],k=15","support","1","yes","Metal" "Metal","UPSCALE","type=f32,ne=[512,512,3,2],scale_factor=2,mode=nearest,transpose=0","support","1","yes","Metal" "Metal","UPSCALE","type=f32,ne=[512,512,3,2],scale_factor=2,mode=nearest,transpose=1","support","1","yes","Metal" -"Metal","UPSCALE","type=f32,ne=[2,5,7,11],ne_tgt=[5,7,11,13],mode=0","support","1","yes","Metal" -"Metal","UPSCALE","type=f32,ne=[5,7,11,13],ne_tgt=[2,5,7,11],mode=0","support","1","yes","Metal" +"Metal","UPSCALE","type=f32,ne=[2,5,7,11],ne_tgt=[5,7,11,13],mode=nearest,flags=none","support","1","yes","Metal" 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+"Metal","UPSCALE","type=f32,ne=[5,7,11,13],ne_tgt=[2,5,7,11],mode=bilinear,flags=none","support","0","no","Metal" +"Metal","UPSCALE","type=f32,ne=[2,5,7,11],ne_tgt=[5,7,11,13],mode=bilinear,flags=align_corners","support","0","no","Metal" +"Metal","UPSCALE","type=f32,ne=[1,4,3,2],ne_tgt=[2,8,3,2],mode=bilinear,flags=align_corners","support","0","no","Metal" +"Metal","UPSCALE","type=f32,ne=[4,1,3,2],ne_tgt=[1,1,3,2],mode=bilinear,flags=align_corners","support","0","no","Metal" +"Metal","UPSCALE","type=f32,ne=[2,5,7,11],ne_tgt=[5,7,11,13],mode=bicubic,flags=align_corners","support","0","no","Metal" +"Metal","UPSCALE","type=f32,ne=[1,4,3,2],ne_tgt=[2,8,3,2],mode=bicubic,flags=align_corners","support","0","no","Metal" +"Metal","UPSCALE","type=f32,ne=[4,1,3,2],ne_tgt=[1,1,3,2],mode=bicubic,flags=align_corners","support","0","no","Metal" +"Metal","SUM","type=f32,ne=[10,5,4,3]","support","1","yes","Metal" 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+"Metal","SUM_ROWS","type=f32,ne=[33,1024,1,1],permute=0,slice=0","support","1","yes","Metal" +"Metal","SUM","type=f32,ne=[33,256,1,1]","support","1","yes","Metal" +"Metal","SUM","type=f32,ne=[33,256,1,1],permute=[1,0,2,3]","support","0","no","Metal" +"Metal","SUM_ROWS","type=f32,ne=[33,256,1,1],permute=0,slice=0","support","1","yes","Metal" +"Metal","MEAN","type=f32,ne=[33,256,1,1]","support","1","yes","Metal" +"Metal","MEAN","type=f32,ne=[32769,1,1,1]","support","1","yes","Metal" "Metal","GROUP_NORM","type=f32,ne=[64,64,320,1],num_groups=32,eps=0.000001","support","1","yes","Metal" "Metal","GROUP_NORM","type=f32,ne=[9,9,1280,1],num_groups=32,eps=0.000001","support","1","yes","Metal" "Metal","ACC","type=f32,ne_a=[256,17,1,1],ne_b=[256,16,1,1]","support","1","yes","Metal" "Metal","PAD","type=f32,ne_a=[512,512,1,1],pad_0=1,pad_1=1","support","1","yes","Metal" +"Metal","PAD","type=f32,ne_a=[512,512,3,1],lp0=1,rp0=1,lp1=1,rp1=1,lp2=1,rp2=1,lp3=1,rp3=1,v=0","support","0","no","Metal" "Metal","PAD_REFLECT_1D","type=f32,ne_a=[512,34,2,1],pad_0=10,pad_1=9","support","1","yes","Metal" +"Metal","PAD_REFLECT_1D","type=f32,ne_a=[3000,384,4,1],pad_0=10,pad_1=9","support","1","yes","Metal" "Metal","ROLL","shift0=3,shift1=-2,shift3=1,shift4=-1","support","0","no","Metal" "Metal","ARANGE","type=f32,start=0.000000,stop=10.000000,step=1.000000","support","1","yes","Metal" +"Metal","ARANGE","type=f32,start=0.000000,stop=1048576.000000,step=1.000000","support","1","yes","Metal" "Metal","TIMESTEP_EMBEDDING","type=f32,ne_a=[2,1,1,1],dim=320,max_period=10000","support","1","yes","Metal" "Metal","LEAKY_RELU","type=f32,ne_a=[10,5,4,3],negative_slope=0.100000","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" 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-"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=80,hsv=80,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[16,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=10.000000,prec=def,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=128,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=192,hsv=192,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[1,1],kv=1024,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","1","yes","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=35,mask=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,2,1,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=512,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[1,1],kv=1024,nb=35,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","Metal" -"Metal","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","Metal" 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+"ZenDNN","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","ZenDNN" +"ZenDNN","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","ZenDNN" +"ZenDNN","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","ZenDNN" +"ZenDNN","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","ZenDNN" +"ZenDNN","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f32,permute=[0,1,2,3]","support","0","no","ZenDNN" +"ZenDNN","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","ZenDNN" +"ZenDNN","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","ZenDNN" +"ZenDNN","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","ZenDNN" +"ZenDNN","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","ZenDNN" +"ZenDNN","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f32,permute=[0,1,2,3]","support","0","no","ZenDNN" +"ZenDNN","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","0","no","ZenDNN" +"ZenDNN","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","ZenDNN" +"ZenDNN","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q8_0,permute=[0,1,2,3]","support","0","no","ZenDNN" +"ZenDNN","FLASH_ATTN_EXT","hsk=576,hsv=512,nh=4,nr23=[4,1],kv=512,nb=35,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=q4_0,permute=[0,1,2,3]","support","0","no","ZenDNN" +"ZenDNN","CROSS_ENTROPY_LOSS","type=f32,ne=[10,5,4,3]","support","0","no","ZenDNN" +"ZenDNN","CROSS_ENTROPY_LOSS","type=f32,ne=[30000,1,1,1]","support","0","no","ZenDNN" +"ZenDNN","CROSS_ENTROPY_LOSS_BACK","type=f32,ne=[10,5,4,3]","support","0","no","ZenDNN" +"ZenDNN","CROSS_ENTROPY_LOSS_BACK","type=f32,ne=[30000,1,1,1]","support","0","no","ZenDNN" +"ZenDNN","OPT_STEP_ADAMW","type=f32,ne=[10,5,4,3]","support","0","no","ZenDNN" +"ZenDNN","OPT_STEP_SGD","type=f32,ne=[10,5,4,3]","support","0","no","ZenDNN" diff --git a/examples/CMakeLists.txt b/examples/CMakeLists.txt index dab795fb90..91797cf78a 100644 --- a/examples/CMakeLists.txt +++ b/examples/CMakeLists.txt @@ -20,6 +20,7 @@ else() add_subdirectory(gguf-hash) add_subdirectory(gguf) + add_subdirectory(idle) add_subdirectory(lookahead) add_subdirectory(lookup) add_subdirectory(parallel) diff --git a/examples/idle/CMakeLists.txt b/examples/idle/CMakeLists.txt new file mode 100644 index 0000000000..d5018fec4b --- /dev/null +++ b/examples/idle/CMakeLists.txt @@ -0,0 +1,5 @@ +set(TARGET llama-idle) +add_executable(${TARGET} idle.cpp) +install(TARGETS ${TARGET} RUNTIME) +target_link_libraries(${TARGET} PRIVATE llama common ${CMAKE_THREAD_LIBS_INIT}) +target_compile_features(${TARGET} PRIVATE cxx_std_11) diff --git a/examples/idle/README.md b/examples/idle/README.md new file mode 100644 index 0000000000..d38e607994 --- /dev/null +++ b/examples/idle/README.md @@ -0,0 +1,3 @@ +# llama.cpp/example/idle + +https://github.com/ggml-org/llama.cpp/pull/17766 diff --git a/examples/idle/idle.cpp b/examples/idle/idle.cpp new file mode 100644 index 0000000000..000427143d --- /dev/null +++ b/examples/idle/idle.cpp @@ -0,0 +1,110 @@ +#include "arg.h" +#include "common.h" +#include "log.h" +#include "llama.h" + +#include +#include +#include +#include +#include +#include + +static void print_usage(int /*argc*/, char ** argv) { + printf("\nexample usage:\n"); + printf("\n %s -m model.gguf [-ngl n_gpu_layers]\n", argv[0]); + printf("\n"); +} + +int main(int argc, char ** argv) { + common_params params; + + if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_COMMON, print_usage)) { + return 1; + } + + common_init(); + + // init LLM + + llama_backend_init(); + llama_numa_init(params.numa); + + // initialize the model + + llama_model_params model_params = common_model_params_to_llama(params); + + llama_model * model = llama_model_load_from_file(params.model.path.c_str(), model_params); + + if (model == NULL) { + LOG_ERR("%s: error: unable to load model\n" , __func__); + return 1; + } + + const llama_vocab * vocab = llama_model_get_vocab(model); + + // we need just a dummy token to evaluate + std::vector prompt_tokens(1, llama_vocab_bos(vocab)); + + llama_context_params ctx_params = llama_context_default_params(); + ctx_params.n_ctx = 512; + ctx_params.n_batch = 512; + ctx_params.no_perf = false; + + llama_context * ctx = llama_init_from_model(model, ctx_params); + if (ctx == NULL) { + fprintf(stderr , "%s: error: failed to create the llama_context\n" , __func__); + return 1; + } + + llama_batch batch = llama_batch_get_one(prompt_tokens.data(), prompt_tokens.size()); + + const int n_iters = 3; + + // warm-up + llama_decode(ctx, batch); + llama_memory_clear(llama_get_memory(ctx), true); + llama_synchronize(ctx); + + for (int64_t t_pause_ms = 0; t_pause_ms <= 4000; t_pause_ms += 800) { + double t_sum_us = 0.0; + double t_sum2_us = 0.0; + + for (int i = 0; i < n_iters; i++) { + // this pause is important - it simulates "idle GPU" + std::this_thread::sleep_for(std::chrono::milliseconds(t_pause_ms)); + + const int64_t t_start_us = llama_time_us(); + + // this should take constant time + llama_decode(ctx, batch); + llama_synchronize(ctx); + + const int64_t t_end_us = llama_time_us(); + + const double t_cur_us = t_end_us - t_start_us; + +#if 1 + // print individual decode times + printf(" - decode time: %8.2f ms\n", t_cur_us / 1000); +#endif + + t_sum_us += t_cur_us; + t_sum2_us += t_cur_us * t_cur_us; + + llama_memory_clear(llama_get_memory(ctx), true); + llama_synchronize(ctx); // just in case + } + + const double t_avg_us = t_sum_us / n_iters; + const double t_dev_us = sqrt((t_sum2_us / (n_iters - 1)) - (t_avg_us * t_avg_us * n_iters) / (n_iters - 1)); + + printf("iters: %4d, pause: %5d ms, avg decode time: %8.2f +/- %4.2f ms\n", n_iters, (int) t_pause_ms, t_avg_us / 1000, t_dev_us / 1000); + fflush(stdout); + } + + llama_free(ctx); + llama_model_free(model); + + return 0; +} diff --git a/examples/model-conversion/logits.cpp b/examples/model-conversion/logits.cpp index bbd095e603..5bcf063267 100644 --- a/examples/model-conversion/logits.cpp +++ b/examples/model-conversion/logits.cpp @@ -144,7 +144,7 @@ int main(int argc, char ** argv) { return 1; } std::string s(buf, n); - printf("%s", s.c_str()); + printf("%s (%d)", s.c_str(), id); } printf("\n"); diff --git a/examples/save-load-state/save-load-state.cpp b/examples/save-load-state/save-load-state.cpp index 1065ec6bb0..4cd3071f76 100644 --- a/examples/save-load-state/save-load-state.cpp +++ b/examples/save-load-state/save-load-state.cpp @@ -241,6 +241,12 @@ int main(int argc, char ** argv) { llama_batch_free(batch); + // this one is managed by common_init_result + //llama_free(ctx); + + llama_free(ctx2); + llama_free(ctx3); + if (result0 != result2) { fprintf(stderr, "\n%s : error : the seq restore generation is different\n", __func__); return 1; diff --git a/examples/simple-cmake-pkg/README.md b/examples/simple-cmake-pkg/README.md index d7430cc9c2..0cabc2e775 100644 --- a/examples/simple-cmake-pkg/README.md +++ b/examples/simple-cmake-pkg/README.md @@ -18,6 +18,7 @@ cd llama.cpp cmake -S . -B build cmake --build build cmake --install build --prefix inst +``` ### Build simple-cmake-pkg diff --git a/ggml/CMakeLists.txt b/ggml/CMakeLists.txt index 9b10df00da..ab5b4760e2 100644 --- a/ggml/CMakeLists.txt +++ b/ggml/CMakeLists.txt @@ -168,6 +168,7 @@ option(GGML_RVV "ggml: enable rvv" ON) option(GGML_RV_ZFH "ggml: enable riscv zfh" ON) option(GGML_RV_ZVFH "ggml: enable riscv zvfh" ON) option(GGML_RV_ZICBOP "ggml: enable riscv zicbop" ON) +option(GGML_RV_ZIHINTPAUSE "ggml: enable riscv zihintpause " ON) option(GGML_XTHEADVECTOR "ggml: enable xtheadvector" OFF) option(GGML_VXE "ggml: enable vxe" ${GGML_NATIVE}) @@ -175,11 +176,6 @@ option(GGML_CPU_ALL_VARIANTS "ggml: build all variants of the CPU backend (requi set(GGML_CPU_ARM_ARCH "" CACHE STRING "ggml: CPU architecture for ARM") set(GGML_CPU_POWERPC_CPUTYPE "" CACHE STRING "ggml: CPU type for PowerPC") - -if (MINGW) - set(GGML_WIN_VER "0xA00" CACHE STRING "ggml: Windows version") -endif() - # ggml core set(GGML_SCHED_MAX_COPIES "4" CACHE STRING "ggml: max input copies for pipeline parallelism") option(GGML_CPU "ggml: enable CPU backend" ON) @@ -226,7 +222,7 @@ option(GGML_WEBGPU "ggml: use WebGPU" option(GGML_WEBGPU_DEBUG "ggml: enable WebGPU debug output" OFF) option(GGML_WEBGPU_CPU_PROFILE "ggml: enable WebGPU profiling (CPU)" OFF) option(GGML_WEBGPU_GPU_PROFILE "ggml: enable WebGPU profiling (GPU)" OFF) - +option(GGML_WEBGPU_JSPI "ggml: use JSPI for WebGPU" ON) option(GGML_ZDNN "ggml: use zDNN" OFF) option(GGML_METAL "ggml: use Metal" ${GGML_METAL_DEFAULT}) option(GGML_METAL_NDEBUG "ggml: disable Metal debugging" OFF) @@ -258,6 +254,9 @@ option(GGML_HEXAGON "ggml: enable Hexagon backend" # toolchain for vulkan-shaders-gen set (GGML_VULKAN_SHADERS_GEN_TOOLCHAIN "" CACHE FILEPATH "ggml: toolchain file for vulkan-shaders-gen") +option(GGML_ZENDNN "ggml: use ZenDNN" OFF) +option(ZENDNN_ROOT "ggml: path to ZenDNN installation" "") + # extra artifacts option(GGML_BUILD_TESTS "ggml: build tests" ${GGML_STANDALONE}) option(GGML_BUILD_EXAMPLES "ggml: build examples" ${GGML_STANDALONE}) @@ -319,6 +318,7 @@ set(GGML_PUBLIC_HEADERS include/ggml-sycl.h include/ggml-vulkan.h include/ggml-webgpu.h + include/ggml-zendnn.h include/gguf.h) set_target_properties(ggml PROPERTIES PUBLIC_HEADER "${GGML_PUBLIC_HEADERS}") @@ -408,62 +408,67 @@ if (MSVC) /wd4996 # Disable POSIX deprecation warnings /wd4702 # Unreachable code warnings ) - function(disable_msvc_warnings target_name) + set(MSVC_COMPILE_OPTIONS + "$<$:/utf-8>" + "$<$:/utf-8>" + ) + function(configure_msvc_target target_name) if(TARGET ${target_name}) target_compile_options(${target_name} PRIVATE ${MSVC_WARNING_FLAGS}) + target_compile_options(${target_name} PRIVATE ${MSVC_COMPILE_OPTIONS}) endif() endfunction() - disable_msvc_warnings(ggml-base) - disable_msvc_warnings(ggml) - disable_msvc_warnings(ggml-cpu) - disable_msvc_warnings(ggml-cpu-x64) - disable_msvc_warnings(ggml-cpu-sse42) - disable_msvc_warnings(ggml-cpu-sandybridge) - disable_msvc_warnings(ggml-cpu-haswell) - disable_msvc_warnings(ggml-cpu-skylakex) - disable_msvc_warnings(ggml-cpu-icelake) - disable_msvc_warnings(ggml-cpu-alderlake) + configure_msvc_target(ggml-base) + configure_msvc_target(ggml) + configure_msvc_target(ggml-cpu) + configure_msvc_target(ggml-cpu-x64) + configure_msvc_target(ggml-cpu-sse42) + configure_msvc_target(ggml-cpu-sandybridge) + configure_msvc_target(ggml-cpu-haswell) + configure_msvc_target(ggml-cpu-skylakex) + configure_msvc_target(ggml-cpu-icelake) + configure_msvc_target(ggml-cpu-alderlake) if (GGML_BUILD_EXAMPLES) - disable_msvc_warnings(common-ggml) - disable_msvc_warnings(common) + configure_msvc_target(common-ggml) + configure_msvc_target(common) - disable_msvc_warnings(mnist-common) - disable_msvc_warnings(mnist-eval) - disable_msvc_warnings(mnist-train) + configure_msvc_target(mnist-common) + configure_msvc_target(mnist-eval) + configure_msvc_target(mnist-train) - disable_msvc_warnings(gpt-2-ctx) - disable_msvc_warnings(gpt-2-alloc) - disable_msvc_warnings(gpt-2-backend) - disable_msvc_warnings(gpt-2-sched) - disable_msvc_warnings(gpt-2-quantize) - disable_msvc_warnings(gpt-2-batched) + configure_msvc_target(gpt-2-ctx) + configure_msvc_target(gpt-2-alloc) + configure_msvc_target(gpt-2-backend) + configure_msvc_target(gpt-2-sched) + configure_msvc_target(gpt-2-quantize) + configure_msvc_target(gpt-2-batched) - disable_msvc_warnings(gpt-j) - disable_msvc_warnings(gpt-j-quantize) + configure_msvc_target(gpt-j) + configure_msvc_target(gpt-j-quantize) - disable_msvc_warnings(magika) - disable_msvc_warnings(yolov3-tiny) - disable_msvc_warnings(sam) + configure_msvc_target(magika) + configure_msvc_target(yolov3-tiny) + configure_msvc_target(sam) - disable_msvc_warnings(simple-ctx) - disable_msvc_warnings(simple-backend) + configure_msvc_target(simple-ctx) + configure_msvc_target(simple-backend) endif() if (GGML_BUILD_TESTS) - disable_msvc_warnings(test-mul-mat) - disable_msvc_warnings(test-arange) - disable_msvc_warnings(test-backend-ops) - disable_msvc_warnings(test-cont) - disable_msvc_warnings(test-conv-transpose) - disable_msvc_warnings(test-conv-transpose-1d) - disable_msvc_warnings(test-conv1d) - disable_msvc_warnings(test-conv2d) - disable_msvc_warnings(test-conv2d-dw) - disable_msvc_warnings(test-customop) - disable_msvc_warnings(test-dup) - disable_msvc_warnings(test-opt) - disable_msvc_warnings(test-pool) + configure_msvc_target(test-mul-mat) + configure_msvc_target(test-arange) + configure_msvc_target(test-backend-ops) + configure_msvc_target(test-cont) + configure_msvc_target(test-conv-transpose) + configure_msvc_target(test-conv-transpose-1d) + configure_msvc_target(test-conv1d) + configure_msvc_target(test-conv2d) + configure_msvc_target(test-conv2d-dw) + configure_msvc_target(test-customop) + configure_msvc_target(test-dup) + configure_msvc_target(test-opt) + configure_msvc_target(test-pool) endif () endif() diff --git a/ggml/include/ggml-rpc.h b/ggml/include/ggml-rpc.h index 832c26c61d..df1ad2a516 100644 --- a/ggml/include/ggml-rpc.h +++ b/ggml/include/ggml-rpc.h @@ -1,6 +1,5 @@ #pragma once -#include "ggml.h" #include "ggml-backend.h" #ifdef __cplusplus @@ -8,7 +7,7 @@ extern "C" { #endif #define RPC_PROTO_MAJOR_VERSION 3 -#define RPC_PROTO_MINOR_VERSION 5 +#define RPC_PROTO_MINOR_VERSION 6 #define RPC_PROTO_PATCH_VERSION 0 #define GGML_RPC_MAX_SERVERS 16 diff --git a/ggml/include/ggml-zendnn.h b/ggml/include/ggml-zendnn.h new file mode 100644 index 0000000000..a30a3a9808 --- /dev/null +++ b/ggml/include/ggml-zendnn.h @@ -0,0 +1,22 @@ +#pragma once + +#include "ggml-backend.h" +#include "ggml.h" + +#ifdef __cplusplus +extern "C" { +#endif + +// backend API +GGML_BACKEND_API ggml_backend_t ggml_backend_zendnn_init(void); + +GGML_BACKEND_API bool ggml_backend_is_zendnn(ggml_backend_t backend); + +// number of threads used for zendnn operations +GGML_BACKEND_API void ggml_backend_zendnn_set_n_threads(ggml_backend_t backend_zendnn, int n_threads); + +GGML_BACKEND_API ggml_backend_reg_t ggml_backend_zendnn_reg(void); + +#ifdef __cplusplus +} +#endif diff --git a/ggml/include/ggml.h b/ggml/include/ggml.h index 48da68fe7e..6bc762c069 100644 --- a/ggml/include/ggml.h +++ b/ggml/include/ggml.h @@ -204,6 +204,10 @@ # define GGML_ATTRIBUTE_FORMAT(...) __attribute__((format(printf, __VA_ARGS__))) #endif +#if defined(_WIN32) && !defined(_WIN32_WINNT) +# define _WIN32_WINNT 0x0A00 +#endif + #include #include #include @@ -2192,6 +2196,15 @@ extern "C" { int p2, int p3); + // pad each dimension with values on the other side of the torus (looping around) + GGML_API struct ggml_tensor * ggml_pad_circular( + struct ggml_context * ctx, + struct ggml_tensor * a, + int p0, + int p1, + int p2, + int p3); + GGML_API struct ggml_tensor * ggml_pad_ext( struct ggml_context * ctx, struct ggml_tensor * a, @@ -2205,6 +2218,19 @@ extern "C" { int rp3 ); + // pad each dimension with values on the other side of the torus (looping around) + GGML_API struct ggml_tensor * ggml_pad_ext_circular( + struct ggml_context * ctx, + struct ggml_tensor * a, + int lp0, + int rp0, + int lp1, + int rp1, + int lp2, + int rp2, + int lp3, + int rp3); + // pad each dimension with reflection: [a, b, c, d] -> [b, a, b, c, d, c] GGML_API struct ggml_tensor * ggml_pad_reflect_1d( struct ggml_context * ctx, @@ -2279,7 +2305,7 @@ extern "C" { float stop, float step); -#define GGML_KQ_MASK_PAD 64 +#define GGML_KQ_MASK_PAD 1 // q: [n_embd_k, n_batch, n_head, ne3 ] // k: [n_embd_k, n_kv, n_head_kv, ne3 ] diff --git a/ggml/src/CMakeLists.txt b/ggml/src/CMakeLists.txt index d93664b8b5..4c04c33003 100644 --- a/ggml/src/CMakeLists.txt +++ b/ggml/src/CMakeLists.txt @@ -127,10 +127,6 @@ if (NOT MSVC) endif() endif() -if (MINGW) - add_compile_definitions(_WIN32_WINNT=${GGML_WIN_VER}) -endif() - # # POSIX conformance # @@ -444,6 +440,7 @@ ggml_add_backend(WebGPU) ggml_add_backend(zDNN) ggml_add_backend(OpenCL) ggml_add_backend(Hexagon) +ggml_add_backend(ZenDNN) foreach (target ggml-base ggml) target_include_directories(${target} PUBLIC $ $) diff --git a/ggml/src/ggml-backend-reg.cpp b/ggml/src/ggml-backend-reg.cpp index e96b5c403d..4181a714ad 100644 --- a/ggml/src/ggml-backend-reg.cpp +++ b/ggml/src/ggml-backend-reg.cpp @@ -73,6 +73,10 @@ #include "ggml-cann.h" #endif +#ifdef GGML_USE_ZENDNN +#include "ggml-zendnn.h" +#endif + // disable C++17 deprecation warning for std::codecvt_utf8 #if defined(__clang__) # pragma clang diagnostic push @@ -203,6 +207,9 @@ struct ggml_backend_registry { #ifdef GGML_USE_OPENCL register_backend(ggml_backend_opencl_reg()); #endif +#ifdef GGML_USE_ZENDNN + register_backend(ggml_backend_zendnn_reg()); +#endif #ifdef GGML_USE_HEXAGON register_backend(ggml_backend_hexagon_reg()); #endif @@ -534,8 +541,12 @@ static ggml_backend_reg_t ggml_backend_load_best(const char * name, bool silent, fs::path best_path; for (const auto & search_path : search_paths) { - if (!fs::exists(search_path)) { - GGML_LOG_DEBUG("%s: search path %s does not exist\n", __func__, path_str(search_path).c_str()); + if (std::error_code ec; !fs::exists(search_path, ec)) { + if (ec) { + GGML_LOG_DEBUG("%s: posix_stat(%s) failure, error-message: %s\n", __func__, path_str(search_path).c_str(), ec.message().c_str()); + } else { + GGML_LOG_DEBUG("%s: search path %s does not exist\n", __func__, path_str(search_path).c_str()); + } continue; } fs::directory_iterator dir_it(search_path, fs::directory_options::skip_permission_denied); @@ -575,8 +586,12 @@ static ggml_backend_reg_t ggml_backend_load_best(const char * name, bool silent, for (const auto & search_path : search_paths) { fs::path filename = backend_filename_prefix().native() + name_path.native() + backend_filename_extension().native(); fs::path path = search_path / filename; - if (fs::exists(path)) { + if (std::error_code ec; fs::exists(path, ec)) { return get_reg().load_backend(path, silent); + } else { + if (ec) { + GGML_LOG_DEBUG("%s: posix_stat(%s) failure, error-message: %s\n", __func__, path_str(path).c_str(), ec.message().c_str()); + } } } return nullptr; @@ -597,6 +612,7 @@ void ggml_backend_load_all_from_path(const char * dir_path) { #endif ggml_backend_load_best("blas", silent, dir_path); + ggml_backend_load_best("zendnn", silent, dir_path); ggml_backend_load_best("cann", silent, dir_path); ggml_backend_load_best("cuda", silent, dir_path); ggml_backend_load_best("hip", silent, dir_path); diff --git a/ggml/src/ggml-backend.cpp b/ggml/src/ggml-backend.cpp index 1d88c826bb..08681f35e3 100644 --- a/ggml/src/ggml-backend.cpp +++ b/ggml/src/ggml-backend.cpp @@ -1240,10 +1240,8 @@ void ggml_backend_sched_split_graph(ggml_backend_sched_t sched, struct ggml_cgra tensor_copy = ggml_dup_tensor_layout(sched->ctx, src); ggml_format_name(tensor_copy, "%s#%s#%d", ggml_backend_name(backend), src->name, c); } - if (sched->n_copies > 1) { - ggml_set_input(tensor_copy); - ggml_set_output(tensor_copy); // prevent ggml-alloc from overwriting the tensor - } + ggml_set_input(tensor_copy); + ggml_set_output(tensor_copy); // prevent ggml-alloc from overwriting the tensor tensor_id_copy(src_id, src_backend_id, c) = tensor_copy; SET_CAUSE(tensor_copy, "4.cpy"); } diff --git a/ggml/src/ggml-cann/ggml-cann.cpp b/ggml/src/ggml-cann/ggml-cann.cpp index cd1b5e5b94..23dc0433c1 100644 --- a/ggml/src/ggml-cann/ggml-cann.cpp +++ b/ggml/src/ggml-cann/ggml-cann.cpp @@ -2551,6 +2551,8 @@ static bool ggml_backend_cann_supports_op(ggml_backend_dev_t dev, const ggml_ten case GGML_OP_ACC: case GGML_OP_GROUP_NORM: case GGML_OP_PAD: + // TODO: add circular padding support for cann, see https://github.com/ggml-org/llama.cpp/pull/16985 + return ggml_get_op_params_i32(op, 8) == 0; case GGML_OP_ARANGE: case GGML_OP_TIMESTEP_EMBEDDING: case GGML_OP_LEAKY_RELU: @@ -2564,6 +2566,10 @@ static bool ggml_backend_cann_supports_op(ggml_backend_dev_t dev, const ggml_ten return true; case GGML_OP_OUT_PROD: { +#ifdef ASCEND_310P + // Ger is not supported on 310p device + return false; +#endif switch (op->src[0]->type) { case GGML_TYPE_F16: case GGML_TYPE_F32: diff --git a/ggml/src/ggml-cpu/CMakeLists.txt b/ggml/src/ggml-cpu/CMakeLists.txt index 7e53a57b7b..fc31089f3e 100644 --- a/ggml/src/ggml-cpu/CMakeLists.txt +++ b/ggml/src/ggml-cpu/CMakeLists.txt @@ -469,6 +469,9 @@ function(ggml_add_cpu_backend_variant_impl tag_name) if (GGML_RV_ZICBOP) string(APPEND MARCH_STR "_zicbop") endif() + if (GGML_RV_ZIHINTPAUSE) + string(APPEND MARCH_STR "_zihintpause") + endif() list(APPEND ARCH_FLAGS "-march=${MARCH_STR}" -mabi=lp64d) else() # Begin with the lowest baseline diff --git a/ggml/src/ggml-cpu/arch/arm/cpu-feats.cpp b/ggml/src/ggml-cpu/arch/arm/cpu-feats.cpp index 67369147ce..c460c54911 100644 --- a/ggml/src/ggml-cpu/arch/arm/cpu-feats.cpp +++ b/ggml/src/ggml-cpu/arch/arm/cpu-feats.cpp @@ -8,6 +8,10 @@ #include #endif +#if !defined(HWCAP2_SVE2) +#define HWCAP2_SVE2 (1 << 1) +#endif + #if !defined(HWCAP2_I8MM) #define HWCAP2_I8MM (1 << 13) #endif diff --git a/ggml/src/ggml-cpu/arch/arm/repack.cpp b/ggml/src/ggml-cpu/arch/arm/repack.cpp index 082bd2bf04..683ed8d2df 100644 --- a/ggml/src/ggml-cpu/arch/arm/repack.cpp +++ b/ggml/src/ggml-cpu/arch/arm/repack.cpp @@ -505,7 +505,6 @@ void ggml_gemv_q4_K_8x4_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo constexpr int blocklen = 8; assert(n % qk == 0); - assert(nr % 4 == 0); assert(nc % ncols_interleaved == 0); UNUSED(nb); @@ -645,7 +644,6 @@ void ggml_gemv_q4_K_8x8_q8_K(int n, constexpr int blocklen = 8; assert(n % qk == 0); - assert(nr % 4 == 0); assert(nc % ncols_interleaved == 0); UNUSED(nb); diff --git a/ggml/src/ggml-cpu/ggml-cpu.c b/ggml/src/ggml-cpu/ggml-cpu.c index 3247af8bb0..b468b115a1 100644 --- a/ggml/src/ggml-cpu/ggml-cpu.c +++ b/ggml/src/ggml-cpu/ggml-cpu.c @@ -490,6 +490,15 @@ static inline void ggml_thread_cpu_relax(void) { static inline void ggml_thread_cpu_relax(void) { _mm_pause(); } +#elif defined(__riscv) +static inline void ggml_thread_cpu_relax(void) { + #ifdef __riscv_zihintpause + __asm__ __volatile__ ("pause"); + #else + /* Encoding of the pause instruction */ + __asm__ __volatile__ (".4byte 0x100000F"); + #endif +} #else static inline void ggml_thread_cpu_relax(void) {;} #endif @@ -683,22 +692,14 @@ bool ggml_is_numa(void) { } #if defined(__ARM_ARCH) - -#if defined(__linux__) && defined(__aarch64__) -#include -#endif - -static void ggml_init_arm_arch_features(void) { #if defined(__aarch64__) && defined(__ARM_FEATURE_SVE) -#if defined(__linux__) - ggml_arm_arch_features.sve_cnt = PR_SVE_VL_LEN_MASK & prctl(PR_SVE_GET_VL); -#else - // TODO: add support of SVE for non-linux systems -#error "TODO: SVE is not supported on this platform. To use SVE, sve_cnt needs to be initialized here." -#endif -#endif +#include +static void ggml_init_arm_arch_features(void) { + ggml_arm_arch_features.sve_cnt = svcntb(); } - +#else +static void ggml_init_arm_arch_features(void) {} +#endif #endif // __ARM_ARCH struct ggml_tensor * ggml_new_i32(struct ggml_context * ctx, int32_t value) { @@ -2706,6 +2707,11 @@ struct ggml_cplan ggml_graph_plan( n_threads = threadpool ? threadpool->n_threads_max : GGML_DEFAULT_N_THREADS; } +#if defined(__EMSCRIPTEN__) && !defined(__EMSCRIPTEN_PTHREADS__) + // Emscripten without pthreads support can only use a single thread + n_threads = 1; +#endif + size_t work_size = 0; struct ggml_cplan cplan; diff --git a/ggml/src/ggml-cpu/llamafile/sgemm-ppc.h b/ggml/src/ggml-cpu/llamafile/sgemm-ppc.h new file mode 100644 index 0000000000..a707868728 --- /dev/null +++ b/ggml/src/ggml-cpu/llamafile/sgemm-ppc.h @@ -0,0 +1,333 @@ +#pragma once + +typedef vector unsigned char vec_t; +typedef __vector_quad acc_t; + +template +class tinyBLAS_Q0_PPC { + public: + tinyBLAS_Q0_PPC(int64_t k, + const TA *A, int64_t lda, + const block_q8_0 *B, int64_t ldb, + float *C, int64_t ldc, + int ith, int nth); + + void matmul(int64_t m, int64_t n); + void matmul_tiled_q0(int64_t m, int64_t n, int64_t mc, int64_t nc, int64_t kc) { + vec_t A_pack[mc*kc*2]; + vec_t B_pack[nc*kc*2]; + int comparray[mc*kc]; + constexpr bool is_Ablock_q4 = std::is_same_v; + int64_t ytiles = m / mc; + int64_t xtiles = n / nc; + int64_t tiles = xtiles * ytiles; + int64_t duty = (tiles + nth - 1) / nth; + int64_t start = duty * ith; + int64_t end = start + duty; + if (end > tiles) { + end = tiles; + } + for (int64_t job = start; job < end; ++job) { + int64_t ii = (job / xtiles) * mc; + int64_t jj = (job % xtiles) * nc; + for (int64_t kk = 0; kk < k; kk += kc) { + if constexpr(is_Ablock_q4) { + packNormalInt4_large(A + ii*lda + kk, lda, mc, 4, (int8_t*)A_pack, comparray); + } else { + packNormal_large(A + ii*lda + kk, lda, mc, 8, (int8_t*)A_pack, false, comparray); + } + packNormal_large(B + jj*ldb + kk, ldb, nc, 8, (uint8_t*)B_pack, true); + KERNEL_Q0(ii, jj, mc, nc, kc, kk, A_pack, B_pack, comparray); + } + } + } + + private: + inline void save_res(int ii, int jj, int idx, vector float* fin_res, int RM=4, int RN=4) { + for (int I = 0; I < RM; I++) { + for (int J = 0; J < RN; J++) { + *((float*)(C+ii+((jj+J)*ldc)+I)) = *((float*)&fin_res[idx+I]+J); + } + } + } + + inline void add_save_res(int ii, int jj, int idx, vector float* fin_res, int RM=4, int RN=4) { + for (int I = 0; I < RM; I++) { + for (int J = 0; J < RN; J++) { + float * c_ptr = (float *)(C+ii+((jj+J)*ldc)+I); + *c_ptr += *((float*)&fin_res[idx+I]+J); + } + } + } + + template + inline void compute(acc_t* ACC, int c_idx, int s_idx, ArrayType& comparray, vector float* vs, vector float* fin_res) { + vector signed int vec_C[4]; + vector float CA[4] = {0}; + vector float res[4] = {0}; + __builtin_mma_disassemble_acc(vec_C, ACC); + for (int i = 0; i < 4; i++) { + CA[i] = vec_splats((float)(((double)comparray[c_idx+i]) * -128.0)); + res[i] = vec_add(vec_ctf(vec_C[i], 0), CA[i]); + fin_res[s_idx+i] = vec_madd(res[i], vs[s_idx+i], fin_res[s_idx+i]); + } + } + + inline void process_q4_elements(vector signed char (&c)[2], int* ca) { + const vector signed char lowMask = vec_splats((signed char)0xF); + const vector unsigned char v4 = vec_splats((unsigned char)0x4); + const vector signed char v8 = vec_splats((signed char)0x8); + vector signed int vsum = {0}; + vector signed int vsum2 = {0}; + c[0] = vec_and(c[1], lowMask); + c[1] = vec_sr(c[1], v4); + c[0] = vec_sub(c[0], v8); + c[1] = vec_sub(c[1], v8); + vsum = vec_sum4s(c[0], vsum); + vsum2 = vec_sum4s(c[1], vsum2); + vsum = vec_add(vsum, vsum2); + *(ca) = vsum[0] + vsum[1] + vsum[2] + vsum[3]; + } + + template + inline void vector_permute_store(V2 &s1, V2 &s2, V2 &s3, V2 &s4, V1 *vecOffset, bool flip) { + vector unsigned char swiz1 = {0, 1, 2, 3, 4, 5, 6, 7, 16, 17, 18, 19, 20, 21, 22, 23}; + vector unsigned char swiz2 = {8, 9, 10, 11, 12, 13, 14, 15, 24, 25, 26, 27, 28, 29, 30, 31}; + vector unsigned char swiz3 = {0, 1, 2, 3, 8, 9, 10, 11, 16, 17, 18, 19, 24, 25, 26, 27}; + vector unsigned char swiz4 = {4, 5, 6, 7, 12, 13, 14, 15, 20, 21, 22, 23, 28, 29, 30, 31}; + V2 t1, t2, t3, t4, t5, t6, t7, t8; + vector unsigned char xor_vector; + uint8_t flip_vec = 0x80; + xor_vector = vec_splats(flip_vec); + t1 = vec_perm(s1, s2, swiz1); + t2 = vec_perm(s1, s2, swiz2); + t3 = vec_perm(s3, s4, swiz1); + t4 = vec_perm(s3, s4, swiz2); + t5 = vec_perm(t1, t3, swiz3); + t6 = vec_perm(t1, t3, swiz4); + t7 = vec_perm(t2, t4, swiz3); + t8 = vec_perm(t2, t4, swiz4); + if (flip == true) { + t5 = vec_xor(t5, xor_vector); + t6 = vec_xor(t6, xor_vector); + t7 = vec_xor(t7, xor_vector); + t8 = vec_xor(t8, xor_vector); + } + vec_xst(t5, 0, vecOffset); + vec_xst(t6, 0, vecOffset+16); + vec_xst(t7, 0, vecOffset+32); + vec_xst(t8, 0, vecOffset+48); + } + + template + inline void kernel(int64_t ii, int64_t jj) { + if constexpr(RM == 4 && RN == 8) { + KERNEL_4x8(ii,jj); + } else if constexpr(RM == 8 && RN == 4) { + KERNEL_8x4(ii,jj); + } else if constexpr(RM == 8 && RN == 8) { + KERNEL_8x8(ii,jj); + } else { + assert(false && "RN/RM values not supported"); + } + } + template + void packNormalInt4(const TA* a, int64_t lda, int rows, int cols, int8_t* vec, std::array& comparray); + template + void packNormal(const block_q8_0* a, int64_t lda, int rows, int cols, VA* vec, bool flip); + void mnpack(int64_t m0, int64_t m, int64_t n0, int64_t n); + void KERNEL_4x8(int64_t ii, int64_t jj); + void KERNEL_8x4(int64_t ii, int64_t jj); + void KERNEL_8x8(int64_t ii, int64_t jj); + void gemm_small(int64_t m0, int64_t m, int64_t n0, int64_t n, int RM, int RN); + template + void gemm(int64_t m0, int64_t m, int64_t n0, int64_t n); + + void compute_scale(int64_t ii, int64_t jj, int blk, vector float* vs){ + for (int I = 0; I<8; I++) { + float a_scale = unhalf((A+((ii+I)*lda)+blk)->d); + for (int J = 0; J<4; J++) { + *((float*)&vs[I]+J) = (a_scale * unhalf((B+((jj+J)*ldb)+blk)->d)); + *((float*)&vs[I+8]+J) = (a_scale * unhalf((B+((jj+J+4)*ldb)+blk)->d)); + } + } + } + + inline void process_q8_elements(const int8_t *qs, int *ca) { + vector signed char c1 = vec_xl(0, qs); + vector signed char c2 = vec_xl(16, qs); + vector signed int vsum1 = {0}; + vector signed int vsum2 = {0}; + vsum1 = vec_sum4s(c1, vsum1); + vsum2 = vec_sum4s(c2, vsum2); + vector signed int vsum = vec_add(vsum1, vsum2); + *ca = vsum[0] + vsum[1] + vsum[2] + vsum[3]; + } + + template + void packNormal_large(const block_q8_0* a, int64_t lda, int rows, int cols, VA* vec, bool flip, int* comparray=nullptr) { + int64_t i, j; + block_q8_0 *aoffset = NULL; + VA *vecOffset = NULL; + block_q8_0* aoffsets[8]; + __vector_pair arr[8]; + VB c[8][2] = {0}; + VB c1[8] = {0}; VB c2[8] = {0}; + aoffset = const_cast(a); + vecOffset = vec; + j = (rows >> 3); + int index = 0; + if (j > 0) { + do { + for (int it = 0; it < 8; it++) + aoffsets[it] = aoffset + it*lda; + aoffset += 8 * lda; + for (int blk = 0; blk < kc; blk++) { + for (int it = 0; it < 8; it++) { + arr[it] = __builtin_vsx_lxvp(0, (__vector_pair*)(aoffsets[it]+blk)->qs); + __builtin_vsx_disassemble_pair(c[it], &arr[it]); + c1[it] = c[it][0]; + c2[it] = c[it][1]; + if (comparray){ + process_q8_elements((aoffsets[it]+ blk)->qs, &comparray[index + 8*blk + it]); + } + } + vector_permute_store(c1[0], c1[1], c1[2], c1[3], vecOffset, flip); + vector_permute_store(c2[0], c2[1], c2[2], c2[3], vecOffset+64, flip); + vector_permute_store(c1[4], c1[5], c1[6], c1[7], vecOffset+128, flip); + vector_permute_store(c2[4], c2[5], c2[6], c2[7], vecOffset+192, flip); + vecOffset += 256; + } + j--; + index += 8*kc; + } while(j > 0); + } + + } + + void packNormalInt4_large(const TA* a, int64_t lda, int rows, int cols, int8_t* vec, int*comparray) { + int64_t i, j; + TA *aoffset = NULL; + int8_t *vecOffset = NULL; + TA *aoffset1 = NULL, *aoffset2 = NULL, *aoffset3 = NULL, *aoffset4 = NULL; + TA *aoffset5 = NULL, *aoffset6 = NULL, *aoffset7 = NULL, *aoffset8 = NULL; + vector signed char c1[2] = {0}, c2[2] = {0}, c3[2] = {0}, c4[2] = {0}; + vector signed char c5[2] = {0}, c6[2] = {0}, c7[2] = {0}, c8[2] = {0}; + aoffset = const_cast(a); + vecOffset = vec; + int index = 0; + j = (rows >> 3); + if (j > 0) { + do { + aoffset1 = aoffset; + aoffset2 = aoffset1 + lda; + aoffset3 = aoffset2 + lda; + aoffset4 = aoffset3 + lda; + aoffset5 = aoffset4 + lda; + aoffset6 = aoffset5 + lda; + aoffset7 = aoffset6 + lda; + aoffset8 = aoffset7 + lda; + aoffset += 8 * lda; + for (int blk = 0; blk < kc; blk++) { + c1[1] = reinterpret_cast(vec_xl(0, (aoffset1+blk)->qs)); + c2[1] = reinterpret_cast(vec_xl(0, (aoffset2+blk)->qs)); + c3[1] = reinterpret_cast(vec_xl(0, (aoffset3+blk)->qs)); + c4[1] = reinterpret_cast(vec_xl(0, (aoffset4+blk)->qs)); + c5[1] = reinterpret_cast(vec_xl(0, (aoffset5+blk)->qs)); + c6[1] = reinterpret_cast(vec_xl(0, (aoffset6+blk)->qs)); + c7[1] = reinterpret_cast(vec_xl(0, (aoffset7+blk)->qs)); + c8[1] = reinterpret_cast(vec_xl(0, (aoffset8+blk)->qs)); + + process_q4_elements(c1, &comparray[index + 8*blk+0]); + process_q4_elements(c2, &comparray[index + 8*blk+1]); + process_q4_elements(c3, &comparray[index + 8*blk+2]); + process_q4_elements(c4, &comparray[index + 8*blk+3]); + process_q4_elements(c5, &comparray[index + 8*blk+4]); + process_q4_elements(c6, &comparray[index + 8*blk+5]); + process_q4_elements(c7, &comparray[index + 8*blk+6]); + process_q4_elements(c8, &comparray[index + 8*blk+7]); + vector_permute_store(c1[0], c2[0], c3[0], c4[0], vecOffset, false); + vector_permute_store(c1[1], c2[1], c3[1], c4[1], vecOffset+64, false); + vector_permute_store(c5[0], c6[0], c7[0], c8[0], vecOffset+128, false); + vector_permute_store(c5[1], c6[1], c7[1], c8[1], vecOffset+192, false); + vecOffset += 256; + } + j--; + index += 8*kc; + } while (j > 0); + } + } + + void KERNEL_Q0(int64_t ii, int64_t jj, int64_t mc, int64_t nc, int64_t kc, int64_t l, vec_t *vec_A, vec_t *vec_B, int *comparray) { + acc_t acc[8]; + for (int i = 0; i < mc ; i += 8) { + for (int j = 0; j < nc; j += 8) { + vector float fin_res[16] = {0}; + vector float vs[16] = {0}; + for (int64_t kk = 0; kk < kc; kk+=2) { + for (int x = 0; x < 8; x++) { + __builtin_mma_xxsetaccz(&acc[x]); + } + int A_block_idx = (i/8)*(16*kc) + kk*16; + int B_block_idx = (j/8)*(16*kc)+ kk*16; + vec_t *A_block = &vec_A[A_block_idx]; + vec_t *B_block = &vec_B[B_block_idx]; + for (int x = 0; x < 8; x++) { + __builtin_mma_xvi8ger4pp(&acc[0], A_block[x], B_block[x]); + __builtin_mma_xvi8ger4pp(&acc[1], A_block[x + 8], B_block[x]); + __builtin_mma_xvi8ger4pp(&acc[2], A_block[x], B_block[x+8]); + __builtin_mma_xvi8ger4pp(&acc[3], A_block[x+8], B_block[x+8]); + } + compute_scale(ii+i, jj+j, l+kk, vs); + int c_index = (i/8)*(8*kc)+ kk*8; + int* c_block = &comparray[c_index]; + compute(&acc[0], 0, 0, c_block, vs, fin_res); + compute(&acc[1], 4, 4, c_block, vs, fin_res); + compute(&acc[2], 0, 8, c_block, vs, fin_res); + compute(&acc[3], 4, 12, c_block, vs, fin_res); + + A_block_idx = (i/8)*(16*kc) + (kk+1)*16; + B_block_idx = (j/8)*(16*kc)+ (kk+1)*16; + A_block = &vec_A[A_block_idx]; + B_block = &vec_B[B_block_idx]; + for (int x = 0; x < 8; x++) { + __builtin_mma_xvi8ger4pp(&acc[4], A_block[x], B_block[x]); + __builtin_mma_xvi8ger4pp(&acc[5], A_block[x + 8], B_block[x]); + __builtin_mma_xvi8ger4pp(&acc[6], A_block[x], B_block[x+8]); + __builtin_mma_xvi8ger4pp(&acc[7], A_block[x+8], B_block[x+8]); + } + compute_scale(ii+i, jj+j, l+kk+1, vs); + c_index = (i/8)*(8*kc)+ (kk+1)*8; + c_block = &comparray[c_index]; + compute(&acc[4], 0, 0, c_block, vs, fin_res); + compute(&acc[5], 4, 4, c_block, vs, fin_res); + compute(&acc[6], 0, 8, c_block, vs, fin_res); + compute(&acc[7], 4, 12, c_block, vs, fin_res); + + } + if (l == 0) { + save_res(ii+i, jj+j, 0, fin_res); + save_res(ii+i+4, jj+j, 4, fin_res); + save_res(ii+i, jj+j+4, 8, fin_res); + save_res(ii+i+4, jj+j+4, 12, fin_res); + } else { + add_save_res(ii+i, jj+j, 0, fin_res); + add_save_res(ii+i+4, jj+j, 4, fin_res); + add_save_res(ii+i, jj+j+4, 8, fin_res); + add_save_res(ii+i+4, jj+j+4, 12, fin_res); + } + } + } + } + + const TA *const A; + const block_q8_0 *const B; + float *C; + const int64_t k; + int64_t kc; + const int64_t lda; + const int64_t ldb; + const int64_t ldc; + const int ith; + const int nth; +}; diff --git a/ggml/src/ggml-cpu/llamafile/sgemm.cpp b/ggml/src/ggml-cpu/llamafile/sgemm.cpp index 2c4ad9d58b..a0cce10aa7 100644 --- a/ggml/src/ggml-cpu/llamafile/sgemm.cpp +++ b/ggml/src/ggml-cpu/llamafile/sgemm.cpp @@ -117,8 +117,7 @@ inline float32x4_t mul(float32x4_t x, float32x4_t y) { return vec_mul(x, y); } #endif #if defined(__MMA__) -typedef vector unsigned char vec_t; -typedef __vector_quad acc_t; +#include "sgemm-ppc.h" #endif //////////////////////////////////////////////////////////////////////////////////////////////////// // VECTORIZED FUSED MULTIPLY ADD @@ -1573,95 +1572,35 @@ class tinyBLAS_BF16_PPC { const int nth; }; -template -class tinyBLAS_Q0_PPC { - public: - tinyBLAS_Q0_PPC(int64_t k, - const TA *A, int64_t lda, - const block_q8_0 *B, int64_t ldb, - float *C, int64_t ldc, - int ith, int nth) + template + tinyBLAS_Q0_PPC::tinyBLAS_Q0_PPC(int64_t k, + const TA *A, int64_t lda, + const block_q8_0 *B, int64_t ldb, + float *C, int64_t ldc, + int ith, int nth) : A(A), B(B), C(C), k(k), lda(lda), ldb(ldb), ldc(ldc), ith(ith), nth(nth) { + kc = 64; } - void matmul(int64_t m, int64_t n) { - mnpack(0, m, 0, n); - } - - private: - - inline void save_res(int ii, int jj, int idx, vector float* fin_res, int RM=4, int RN=4) { - for (int I = 0; I < RM; I++) { - for (int J = 0; J < RN; J++) { - *((float*)(C+ii+((jj+J)*ldc)+I)) = *((float*)&fin_res[idx+I]+J); - } - } - } - - template - inline void compute(acc_t* ACC, int c_idx, int s_idx, std::array& comparray, vector float* vs, vector float* fin_res) { - vector signed int vec_C[4]; - vector float CA[4] = {0}; - vector float res[4] = {0}; - __builtin_mma_disassemble_acc(vec_C, ACC); - for (int i = 0; i < 4; i++) { - CA[i] = vec_splats((float)(((double)comparray[c_idx+i]) * -128.0)); - res[i] = vec_add(vec_ctf(vec_C[i], 0), CA[i]); - fin_res[s_idx+i] = vec_madd(res[i], vs[s_idx+i], fin_res[s_idx+i]); - } - } - /* This function processes quantized data from block_q4_0 elements. - * First the we try to extract the two int4 values stored in single int8_t into two signed int8. - * And then we subtract each of the resultant element with 8, to convert signed int8 to unsigned int8. - * Also compute the rowsum which is required to compensate the above conversion. */ - inline void process_q4_elements(vector signed char (&c)[2], int* ca) { - const vector signed char lowMask = vec_splats((signed char)0xF); - const vector unsigned char v4 = vec_splats((unsigned char)0x4); - const vector signed char v8 = vec_splats((signed char)0x8); - vector signed int vsum = {0}; - vector signed int vsum2 = {0}; - c[0] = vec_and(c[1], lowMask); - c[1] = vec_sr(c[1], v4); - c[0] = vec_sub(c[0], v8); - c[1] = vec_sub(c[1], v8); - vsum = vec_sum4s(c[0], vsum); - vsum2 = vec_sum4s(c[1], vsum2); - vsum = vec_add(vsum, vsum2); - *(ca) = vsum[0] + vsum[1] + vsum[2] + vsum[3]; - } - - template - inline void vector_permute_store(V2 &s1, V2 &s2, V2 &s3, V2 &s4, V1 *vecOffset, bool flip) { - vector unsigned char swiz1 = {0, 1, 2, 3, 4, 5, 6, 7, 16, 17, 18, 19, 20, 21, 22, 23}; - vector unsigned char swiz2 = {8, 9, 10, 11, 12, 13, 14, 15, 24, 25, 26, 27, 28, 29, 30, 31}; - vector unsigned char swiz3 = {0, 1, 2, 3, 8, 9, 10, 11, 16, 17, 18, 19, 24, 25, 26, 27}; - vector unsigned char swiz4 = {4, 5, 6, 7, 12, 13, 14, 15, 20, 21, 22, 23, 28, 29, 30, 31}; - V2 t1, t2, t3, t4, t5, t6, t7, t8; - vector unsigned char xor_vector; - uint8_t flip_vec = 0x80; - xor_vector = vec_splats(flip_vec); - t1 = vec_perm(s1, s2, swiz1); - t2 = vec_perm(s1, s2, swiz2); - t3 = vec_perm(s3, s4, swiz1); - t4 = vec_perm(s3, s4, swiz2); - t5 = vec_perm(t1, t3, swiz3); - t6 = vec_perm(t1, t3, swiz4); - t7 = vec_perm(t2, t4, swiz3); - t8 = vec_perm(t2, t4, swiz4); - if (flip == true) { - t5 = vec_xor(t5, xor_vector); - t6 = vec_xor(t6, xor_vector); - t7 = vec_xor(t7, xor_vector); - t8 = vec_xor(t8, xor_vector); + template + void tinyBLAS_Q0_PPC::matmul(int64_t m, int64_t n) { + int mc = 64; int nc = 64; + if (n % 8 == 0 && n < nc) { + nc = n; + mc = 32 ; + kc = 32; + } + const bool is_aligned = ((m & (mc - 1)) == 0) & ((n & (nc - 1)) == 0) & ((k & (kc - 1)) == 0); + if (is_aligned) { + this->matmul_tiled_q0(m, n, mc, nc, kc); + } else { + mnpack(0, m, 0, n); } - vec_xst(t5, 0, vecOffset); - vec_xst(t6, 0, vecOffset+16); - vec_xst(t7, 0, vecOffset+32); - vec_xst(t8, 0, vecOffset+48); } - template - void packNormalInt4(const TA* a, int64_t lda, int rows, int cols, int8_t* vec, std::array& comparray) { + template + template + void tinyBLAS_Q0_PPC::packNormalInt4(const TA* a, int64_t lda, int rows, int cols, int8_t* vec, std::array& comparray) { int64_t i, j; TA *aoffset = NULL; int8_t *vecOffset = NULL; @@ -1781,8 +1720,10 @@ class tinyBLAS_Q0_PPC { } } } + + template template - void packNormal(const block_q8_0* a, int64_t lda, int rows, int cols, VA* vec, bool flip) { + void tinyBLAS_Q0_PPC::packNormal(const block_q8_0* a, int64_t lda, int rows, int cols, VA* vec, bool flip) { int64_t i, j; block_q8_0 *aoffset = NULL; VA *vecOffset = NULL; @@ -1822,7 +1763,6 @@ class tinyBLAS_Q0_PPC { j--; } while(j > 0); } - if (rows & 4) { aoffsets[0] = aoffset; for (int it = 1; it < 4; it++ ) @@ -1878,7 +1818,8 @@ class tinyBLAS_Q0_PPC { } } - void mnpack(int64_t m0, int64_t m, int64_t n0, int64_t n) { + template + void tinyBLAS_Q0_PPC::mnpack(int64_t m0, int64_t m, int64_t n0, int64_t n) { int m_rem = MIN(m - m0, 16); int n_rem = MIN(n - n0, 16); @@ -1915,7 +1856,8 @@ class tinyBLAS_Q0_PPC { } - void KERNEL_4x8(int64_t ii, int64_t jj) { + template + void tinyBLAS_Q0_PPC::KERNEL_4x8(int64_t ii, int64_t jj) { vec_t vec_A[8], vec_B[16] = {0}; acc_t acc_0, acc_1; std::array comparray {}; @@ -1953,14 +1895,15 @@ class tinyBLAS_Q0_PPC { aoffset += lda; } } - compute<4>(&acc_0, 0, 0, comparray, vs, fin_res); - compute<4>(&acc_1, 0, 4, comparray, vs, fin_res); + compute(&acc_0, 0, 0, comparray, vs, fin_res); + compute(&acc_1, 0, 4, comparray, vs, fin_res); } save_res(ii, jj, 0, fin_res); save_res(ii, jj+4, 4, fin_res); } - void KERNEL_8x4(int64_t ii, int64_t jj) { + template + void tinyBLAS_Q0_PPC::KERNEL_8x4(int64_t ii, int64_t jj) { vec_t vec_A[16], vec_B[8] = {0}; acc_t acc_0, acc_1; std::array comparray {}; @@ -1997,16 +1940,18 @@ class tinyBLAS_Q0_PPC { aoffset += lda; } } - compute<8>(&acc_0, 0, 0, comparray, vs, fin_res); - compute<8>(&acc_1, 4, 4, comparray, vs, fin_res); + compute(&acc_0, 0, 0, comparray, vs, fin_res); + compute(&acc_1, 4, 4, comparray, vs, fin_res); } save_res(ii, jj, 0, fin_res); save_res(ii+4, jj, 4, fin_res); } - void KERNEL_8x8(int64_t ii, int64_t jj) { + template + void tinyBLAS_Q0_PPC::KERNEL_8x8(int64_t ii, int64_t jj) { vec_t vec_A[16], vec_B[16] = {0}; acc_t acc_0, acc_1, acc_2, acc_3; + acc_t acc_4, acc_5, acc_6, acc_7; std::array comparray {}; vector float fin_res[16] = {0}; vector float vs[16] = {0}; @@ -2046,10 +1991,10 @@ class tinyBLAS_Q0_PPC { aoffset += lda; } } - compute<8>(&acc_0, 0, 0, comparray, vs, fin_res); - compute<8>(&acc_1, 4, 4, comparray, vs, fin_res); - compute<8>(&acc_2, 0, 8, comparray, vs, fin_res); - compute<8>(&acc_3, 4, 12, comparray, vs, fin_res); + compute(&acc_0, 0, 0, comparray, vs, fin_res); + compute(&acc_1, 4, 4, comparray, vs, fin_res); + compute(&acc_2, 0, 8, comparray, vs, fin_res); + compute(&acc_3, 4, 12, comparray, vs, fin_res); } save_res(ii, jj, 0, fin_res); save_res(ii+4, jj, 4, fin_res); @@ -2057,7 +2002,8 @@ class tinyBLAS_Q0_PPC { save_res(ii+4, jj+4, 12, fin_res); } - void gemm_small(int64_t m0, int64_t m, int64_t n0, int64_t n, int RM, int RN) { + template + void tinyBLAS_Q0_PPC::gemm_small(int64_t m0, int64_t m, int64_t n0, int64_t n, int RM, int RN) { int64_t ytiles = (m - m0) / RM; int64_t xtiles = (n - n0) / RN; int64_t tiles = xtiles * ytiles; @@ -2125,21 +2071,9 @@ class tinyBLAS_Q0_PPC { } } - template - inline void kernel(int64_t ii, int64_t jj) { - if constexpr(RM == 4 && RN == 8) { - KERNEL_4x8(ii,jj); - } else if constexpr(RM == 8 && RN == 4) { - KERNEL_8x4(ii,jj); - } else if constexpr(RM == 8 && RN == 8) { - KERNEL_8x8(ii,jj); - } else { - assert(false && "RN/RM values not supported"); - } - } - + template template - NOINLINE void gemm(int64_t m0, int64_t m, int64_t n0, int64_t n) { + NOINLINE void tinyBLAS_Q0_PPC::gemm(int64_t m0, int64_t m, int64_t n0, int64_t n) { int64_t ytiles = (m - m0) / RM; int64_t xtiles = (n - n0) / RN; int64_t tiles = xtiles * ytiles; @@ -2151,20 +2085,12 @@ class tinyBLAS_Q0_PPC { for (int64_t job = start; job < end; ++job) { int64_t ii = m0 + job / xtiles * RM; int64_t jj = n0 + job % xtiles * RN; - kernel(ii, jj); + this->kernel(ii, jj); } } - const TA *const A; - const block_q8_0 *const B; - float *C; - const int64_t k; - const int64_t lda; - const int64_t ldb; - const int64_t ldc; - const int ith; - const int nth; -}; +template class tinyBLAS_Q0_PPC; +template class tinyBLAS_Q0_PPC; class tinyBLAS_PPC { public: diff --git a/ggml/src/ggml-cpu/llamafile/sgemm.h b/ggml/src/ggml-cpu/llamafile/sgemm.h index 729e8853d5..867b0c04ae 100644 --- a/ggml/src/ggml-cpu/llamafile/sgemm.h +++ b/ggml/src/ggml-cpu/llamafile/sgemm.h @@ -6,6 +6,12 @@ #include #endif +#ifdef _MSC_VER +#define NOINLINE __declspec(noinline) +#else +#define NOINLINE __attribute__((__noinline__)) +#endif + #ifdef __cplusplus extern "C" { #endif diff --git a/ggml/src/ggml-cpu/ops.cpp b/ggml/src/ggml-cpu/ops.cpp index 608e82af69..3032783971 100644 --- a/ggml/src/ggml-cpu/ops.cpp +++ b/ggml/src/ggml-cpu/ops.cpp @@ -6383,7 +6383,7 @@ static void ggml_compute_forward_im2col_3d_f16( const int64_t iih = ioh*s1 + ikh*d1 - p1; const int64_t iid = iod*s2 + ikd*d2 - p2; - if (iid < 0 || iid >= ID || iih < 0 || iih >= IH || iiw < 0 || iiw >= IW || iid < 0 || iid >= ID) { + if (iid < 0 || iid >= ID || iih < 0 || iih >= IH || iiw < 0 || iiw >= IW) { dst_data[iic*KD_KH_KW + ikd * KH_KW + ikh*KW + ikw] = 0; } else { const float * const s = (const float *) ((const char *)src_data + iid*nb12 + iih*nb11 + iiw*nb10); // [ID, IH, IW] @@ -6554,8 +6554,13 @@ static void ggml_call_mul_mat(ggml_type type, const ggml_compute_params * params ggml_compute_forward_mul_mat(params, &dst); } +static inline int64_t ggml_wrap_around(int64_t coord, int64_t size) { + return (coord + size) % size; // adding size avoids negative number weirdness +} + // ggml_compute_forward_conv_2d + static void ggml_compute_forward_conv_2d_impl(const ggml_compute_params * params, const ggml_tensor * kernel, // [KW, KH, IC, OC] const ggml_tensor * src, // [W, H, C, N] @@ -7591,6 +7596,7 @@ void ggml_compute_forward_upscale( // ggml_compute_forward_pad +template static void ggml_compute_forward_pad_f32( const ggml_compute_params * params, ggml_tensor * dst) { @@ -7615,23 +7621,40 @@ static void ggml_compute_forward_pad_f32( const int32_t lp3 = ggml_get_op_params_i32(dst, 6); const int32_t rp3 = ggml_get_op_params_i32(dst, 7); - // TODO: optimize for (int64_t i2 = 0; i2 < ne2; ++i2) { for (int64_t i1 = ith; i1 < ne1; i1 += nth) { for (int64_t i0 = 0; i0 < ne0; ++i0) { for (int64_t i3 = 0; i3 < ne3; ++i3) { - const int64_t dst_idx = i3*(ne0*ne1*ne2) + i2*(ne0*ne1) + i1*ne0 + i0; - if ((i0 >= lp0 && i0 < ne0 - rp0) \ - && (i1 >= lp1 && i1 < ne1 - rp1) \ - && (i2 >= lp2 && i2 < ne2 - rp2) \ - && (i3 >= lp3 && i3 < ne3 - rp3)) { - const int64_t src_idx = (i3 - lp3)*nb03 + (i2 - lp2)*nb02 + (i1 - lp1)*nb01 + (i0 - lp0)*nb00; + // circular means wrap around on a torus, so x and y loop around + if constexpr (circular_t) { + const int64_t dst_idx = i3*(ne0*ne1*ne2) + i2*(ne0*ne1) + i1*ne0 + i0; + const int64_t src_i0 = ggml_wrap_around(i0 - lp0, ne00); + const int64_t src_i1 = ggml_wrap_around(i1 - lp1, ne01); + const int64_t src_i2 = ggml_wrap_around(i2 - lp2, ne02); + const int64_t src_i3 = ggml_wrap_around(i3 - lp3, ne03); + + const int64_t src_idx = + src_i3*nb03 + + src_i2*nb02 + + src_i1*nb01 + + src_i0*nb00; + const float * src_ptr = (const float *)((char *) src0->data + src_idx); dst_ptr[dst_idx] = *src_ptr; } else { - dst_ptr[dst_idx] = 0; + const int64_t dst_idx = i3*(ne0*ne1*ne2) + i2*(ne0*ne1) + i1*ne0 + i0; + if ((i0 >= lp0 && i0 < ne0 - rp0) \ + && (i1 >= lp1 && i1 < ne1 - rp1) \ + && (i2 >= lp2 && i2 < ne2 - rp2) \ + && (i3 >= lp3 && i3 < ne3 - rp3)) { + const int64_t src_idx = (i3 - lp3)*nb03 + (i2 - lp2)*nb02 + (i1 - lp1)*nb01 + (i0 - lp0)*nb00; + const float * src_ptr = (const float *)((char *) src0->data + src_idx); + dst_ptr[dst_idx] = *src_ptr; + } else { + dst_ptr[dst_idx] = 0; + } } } } @@ -7639,16 +7662,20 @@ static void ggml_compute_forward_pad_f32( } } + void ggml_compute_forward_pad( const ggml_compute_params * params, ggml_tensor * dst) { - const ggml_tensor * src0 = dst->src[0]; - + const bool circular = (bool) ggml_get_op_params_i32(dst, 8); switch (src0->type) { case GGML_TYPE_F32: { - ggml_compute_forward_pad_f32(params, dst); + if (circular) { + ggml_compute_forward_pad_f32(params, dst); + } else { + ggml_compute_forward_pad_f32(params, dst); + } } break; default: { diff --git a/ggml/src/ggml-cuda/common.cuh b/ggml/src/ggml-cuda/common.cuh index 611341deb0..c4529f5d94 100644 --- a/ggml/src/ggml-cuda/common.cuh +++ b/ggml/src/ggml-cuda/common.cuh @@ -226,7 +226,7 @@ static const char * cu_get_error_str(CUresult err) { #define AMD_MFMA_AVAILABLE #endif // defined(GGML_USE_HIP) && defined(CDNA) && !defined(GGML_HIP_NO_MMQ_MFMA) -#if defined(GGML_USE_HIP) && defined(RDNA4) +#if defined(GGML_USE_HIP) && (defined(RDNA4) || defined(RDNA3)) #define AMD_WMMA_AVAILABLE #endif // defined(GGML_USE_HIP) && defined(RDNA4) @@ -294,7 +294,7 @@ static bool amd_mfma_available(const int cc) { } static bool amd_wmma_available(const int cc) { - return GGML_CUDA_CC_IS_RDNA4(cc); + return (GGML_CUDA_CC_IS_RDNA4(cc) || GGML_CUDA_CC_IS_RDNA3(cc)); } static bool volta_mma_available(const int cc) { @@ -463,6 +463,53 @@ static __device__ __forceinline__ float warp_reduce_max(float x) { return x; } +template +static __device__ __forceinline__ T warp_prefix_inclusive_sum(T x) { + const int lane_id = threadIdx.x % width; +#pragma unroll + for (int offset = 1; offset < width; offset <<= 1) { + const T t = __shfl_up_sync(0xffffffff, x, offset, width); + if (lane_id >= offset) { + x += t; + } + } + return x; +} + +template +static __device__ __forceinline__ float2 warp_prefix_inclusive_sum(float2 a) { + const int lane_id = threadIdx.x % width; +#pragma unroll + for (int offset = 1; offset < width; offset <<= 1) { + const float t_x = __shfl_up_sync(0xffffffff, a.x, offset, width); + const float t_y = __shfl_up_sync(0xffffffff, a.y, offset, width); + if (lane_id >= offset) { + a.x += t_x; + a.y += t_y; + } + } + return a; +} + +template +static __device__ __forceinline__ half2 warp_prefix_inclusive_sum(half2 a) { +#ifdef FP16_AVAILABLE + const int lane_id = threadIdx.x % width; +#pragma unroll + for (int offset = 1; offset < width; offset <<= 1) { + const half2 t = __shfl_up_sync(0xffffffff, a, offset, width); + if (lane_id >= offset) { + a = __hadd2(a, t); + } + } + return a; + +#else + NO_DEVICE_CODE; + return a; +#endif // FP16_AVAILABLE +} + static __device__ __forceinline__ half ggml_cuda_hmax(const half a, const half b) { #ifdef FP16_AVAILABLE @@ -989,6 +1036,10 @@ struct ggml_cuda_concurrent_event { int n_streams = 0; std::unordered_map stream_mapping; + // Original order of nodes in this concurrent region (before interleaving) + // Used to restore grouping for fusion within streams + std::vector original_order; + const ggml_tensor * join_node; ggml_cuda_concurrent_event() = default; @@ -1011,6 +1062,7 @@ struct ggml_cuda_concurrent_event { , fork_event(other.fork_event) , n_streams(other.n_streams) , stream_mapping(std::move(other.stream_mapping)) + , original_order(std::move(other.original_order)) , join_node(other.join_node) { other.fork_event = nullptr; } @@ -1121,11 +1173,9 @@ struct ggml_cuda_concurrent_event { }; struct ggml_cuda_stream_context { - std::vector original_nodes; std::unordered_map concurrent_events; void reset() { - original_nodes.clear(); concurrent_events.clear(); } }; diff --git a/ggml/src/ggml-cuda/cumsum.cu b/ggml/src/ggml-cuda/cumsum.cu new file mode 100644 index 0000000000..d2f2def8bd --- /dev/null +++ b/ggml/src/ggml-cuda/cumsum.cu @@ -0,0 +1,237 @@ +#include +#include "cumsum.cuh" +#include "convert.cuh" +#include "ggml-cuda/common.cuh" +#include "ggml.h" + +#ifdef GGML_CUDA_USE_CUB +# include +#endif // GGML_CUDA_USE_CUB + +template +static __global__ void cumsum_cub_kernel( + const T * __restrict__ src, + T * __restrict__ dst, + const int64_t ne00, const int64_t ne01, const int64_t ne02, const int64_t ne03, + const int64_t s01, const int64_t s02, const int64_t s03, + const int64_t s1, const int64_t s2, const int64_t s3) { +#ifdef GGML_CUDA_USE_CUB + using BlockScan = cub::BlockScan; + + __shared__ typename BlockScan::TempStorage temp_storage; + __shared__ T block_carry; // carry from previous tile + + const int tid = threadIdx.x; + + const int64_t i1 = blockIdx.x; + const int64_t i2 = blockIdx.y; + const int64_t i3 = blockIdx.z; + + if (i1 >= ne01 || i2 >= ne02 || i3 >= ne03) { + return; + } + + const T * src_row = src + i1 * s01 + i2 * s02 + i3 * s03; + T * dst_row = dst + i1 * s1 + i2 * s2 + i3 * s3; + + if (tid == 0) { + block_carry = 0; + } + __syncthreads(); + + for (int64_t start = 0; start < ne00; start += BLOCK_SIZE) { + int64_t idx = start + tid; + T x = (idx < ne00) ? src_row[idx] : T(0); + + T inclusive; + T block_total; + BlockScan(temp_storage).InclusiveSum(x, inclusive, block_total); + + __syncthreads(); + + T final_val = inclusive + block_carry; + + // store result + if (idx < ne00) { + dst_row[idx] = final_val; + } + + __syncthreads(); + + if (tid == 0) { + block_carry += block_total; + } + + __syncthreads(); + } +#else + NO_DEVICE_CODE; +#endif // GGML_CUDA_USE_CUB +} + +// Fallback kernel implementation (original) +template +static __global__ void cumsum_kernel( + const T * src, T * dst, + const int64_t ne00, const int64_t ne01, const int64_t ne02, const int64_t ne03, + const int64_t s00, const int64_t s01, const int64_t s02, const int64_t s03, + const int64_t s0, const int64_t s1, const int64_t s2, const int64_t s3) { + + GGML_UNUSED_VARS(s00, s0); + + const int tid = threadIdx.x; + constexpr int warp_size = ggml_cuda_get_physical_warp_size(); + const int lane = tid % warp_size; + const int warp = tid / warp_size; + const int warps_per_block = blockDim.x / warp_size; + + extern __shared__ float smem[]; + float * s_vals = smem; + float * s_warp_sums = smem + blockDim.x; + float * s_carry = smem + blockDim.x + warps_per_block; + float * s_chunk_total = s_carry + 1; + + // Initialize carry + if (tid == 0) { + *s_carry = 0.0f; + } + __syncthreads(); + + const int64_t i3 = blockIdx.z; + const int64_t i2 = blockIdx.y; + const int64_t i1 = blockIdx.x; + if (i3 >= ne03 || i2 >= ne02 || i1 >= ne01) { + return; + } + + const T * src_row = src + i1 * s01 + i2 * s02 + i3 * s03; + T * dst_row = dst + i1 * s1 + i2 * s2 + i3 * s3; + + for (int64_t start = 0; start < ne00; start += blockDim.x) { + int64_t idx = start + tid; + float val = (idx < ne00) ? ggml_cuda_cast(src_row[idx]) : 0.0f; + + // 1. Warp inclusive scan + val = warp_prefix_inclusive_sum(val); + s_vals[tid] = val; + + // Store warp total + if (lane == warp_size - 1) { + s_warp_sums[warp] = val; + } + __syncthreads(); + + // 2. Exclusive scan of warp sums (warp 0 only) + if (warp == 0) { + float w = (tid < warps_per_block) ? s_warp_sums[tid] : 0.0f; + float inc = warp_prefix_inclusive_sum(w); + if (tid < warps_per_block) { + s_warp_sums[tid] = inc - w; // exclusive sum + } + if (tid == warps_per_block - 1) { + *s_chunk_total = inc; // total sum of this chunk + } + } + __syncthreads(); + + float carry = *s_carry; + float final_val = s_vals[tid] + s_warp_sums[warp] + carry; + if (idx < ne00) { + dst_row[idx] = ggml_cuda_cast(final_val); + } + __syncthreads(); + + // Update carry for next chunk + if (tid == 0) { + *s_carry += *s_chunk_total; + } + __syncthreads(); + } +} + +template +static void cumsum_cuda( + const T * src, T * dst, + const int64_t ne00, const int64_t ne01, const int64_t ne02, const int64_t ne03, + const int64_t nb00, const int64_t nb01, const int64_t nb02, const int64_t nb03, + const int64_t nb0, const int64_t nb1, const int64_t nb2, const int64_t nb3, + cudaStream_t stream) { + + const size_t type_size = sizeof(T); + bool use_cub = false; +#ifdef GGML_CUDA_USE_CUB + // Check if we can use CUB (data must be contiguous along innermost dimension) + const bool is_contiguous = (nb00 == type_size) && (nb0 == type_size); + + if (is_contiguous) { + use_cub = true; + } +#endif // GGML_CUDA_USE_CUB + dim3 grid_dims(ne01, ne02, ne03); + const auto &info = ggml_cuda_info().devices[ggml_cuda_get_device()]; + const int warp_size = info.warp_size; + const int num_warps = (ne00 + warp_size - 1) / warp_size; + int block_size = num_warps * warp_size; + block_size = std::min(block_size, CUDA_CUMSUM_BLOCK_SIZE); + dim3 block_dims(block_size, 1, 1); + const int warps_per_block = block_size / warp_size; + const size_t shmem_size = (block_size + warps_per_block + 2) * sizeof(float); + + if (use_cub) { + cumsum_cub_kernel<<>>( + src, dst, + ne00, ne01, ne02, ne03, + nb01 / type_size, nb02 / type_size, nb03 / type_size, + nb1 / type_size, nb2 / type_size, nb3 / type_size + ); + } else { + cumsum_kernel<<>>( + src, dst, + ne00, ne01, ne02, ne03, + nb00 / type_size, nb01 / type_size, nb02 / type_size, nb03 / type_size, + nb0 / type_size, nb1 / type_size, nb2 / type_size, nb3 / type_size + ); + } +} + +void ggml_cuda_op_cumsum(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { + const ggml_tensor * src0 = dst->src[0]; + cudaStream_t stream = ctx.stream(); + + GGML_ASSERT(src0->type == dst->type); + switch(src0->type) { + case GGML_TYPE_F32: + { + cumsum_cuda( + (const float *)src0->data, (float *)dst->data, + src0->ne[0], src0->ne[1], src0->ne[2], src0->ne[3], + src0->nb[0], src0->nb[1], src0->nb[2], src0->nb[3], + dst->nb[0], dst->nb[1], dst->nb[2], dst->nb[3], + stream + ); + } break; + // We do not support those on CPU for now anyway, so comment them out because they cause errors on some CI platforms + /*case GGML_TYPE_F16: + { + cumsum_cuda( + (const half *)src0->data, (half *)dst->data, + src0->ne[0], src0->ne[1], src0->ne[2], src0->ne[3], + src0->nb[0], src0->nb[1], src0->nb[2], src0->nb[3], + dst->nb[0], dst->nb[1], dst->nb[2], dst->nb[3], + stream + ); + } break; + case GGML_TYPE_BF16: + { + cumsum_cuda( + (const nv_bfloat16 *)src0->data, (nv_bfloat16 *)dst->data, + src0->ne[0], src0->ne[1], src0->ne[2], src0->ne[3], + src0->nb[0], src0->nb[1], src0->nb[2], src0->nb[3], + dst->nb[0], dst->nb[1], dst->nb[2], dst->nb[3], + stream + ); + } break;*/ + default: + GGML_ABORT("fatal error"); + } +} diff --git a/ggml/src/ggml-cuda/cumsum.cuh b/ggml/src/ggml-cuda/cumsum.cuh new file mode 100644 index 0000000000..782d1d92e9 --- /dev/null +++ b/ggml/src/ggml-cuda/cumsum.cuh @@ -0,0 +1,5 @@ +#include "common.cuh" + +#define CUDA_CUMSUM_BLOCK_SIZE 256 + +void ggml_cuda_op_cumsum(ggml_backend_cuda_context & ctx, ggml_tensor * dst); diff --git a/ggml/src/ggml-cuda/fattn-common.cuh b/ggml/src/ggml-cuda/fattn-common.cuh index 5cdd4bb211..2750117aa9 100644 --- a/ggml/src/ggml-cuda/fattn-common.cuh +++ b/ggml/src/ggml-cuda/fattn-common.cuh @@ -10,6 +10,12 @@ #define HALF_MAX_HALF __float2half(65504.0f/2) // Use neg. of this instead of -INFINITY to initialize KQ max vals to avoid NaN upon subtraction. #define SOFTMAX_FTZ_THRESHOLD -20.0f // Softmax exp. of values smaller than this are flushed to zero to avoid NaNs. +// log(2) = 0.6931, by adding this to the KQ maximum used for the softmax the numerical range representable +// by the VKQ accumulators is effectively being shifted up by a factor of 8. +// This reduces issues with numerical overflow but also causes larger values to be flushed to zero. +// However, as the output from FlashAttention will usually be used as an input for a matrix multiplication this should be negligible. +#define FATTN_KQ_MAX_OFFSET 0.6931f + typedef void (* fattn_kernel_t)( const char * __restrict__ Q, const char * __restrict__ K, @@ -25,7 +31,7 @@ typedef void (* fattn_kernel_t)( const float m1, const uint32_t n_head_log2, const float logit_softcap, - const int32_t ne00, const int32_t ne01, const int32_t ne02, const int32_t ne03, + const int32_t ne00, const uint3 ne01, const int32_t ne02, const int32_t ne03, const int32_t nb01, const int32_t nb02, const int32_t nb03, const int32_t ne10, const int32_t ne11, const int32_t ne12, const int32_t ne13, const int32_t nb11, const int32_t nb12, const int64_t nb13, @@ -621,7 +627,8 @@ static __global__ void flash_attn_mask_to_KV_max( template // D == head size __launch_bounds__(D, 1) static __global__ void flash_attn_stream_k_fixup( - float * __restrict__ dst, const float2 * __restrict__ dst_fixup, const int ne01, const int ne02, const int ne03, const int ne11) { + float * __restrict__ dst, const float2 * __restrict__ dst_fixup, const int ne01, const int ne02, const int ne03, const int ne11, + const int nbatch_fa) { constexpr int ncols = ncols1*ncols2; const int bidx0 = blockIdx.x; @@ -632,8 +639,8 @@ static __global__ void flash_attn_stream_k_fixup( const float * dst_fixup_data = ((const float *) dst_fixup) + gridDim.x*(2*2*ncols); - const int iter_k = ne11 / FATTN_KQ_STRIDE; - const int iter_j = (ne01 + (ncols1 - 1)) / ncols1; + const int iter_k = (ne11 + (nbatch_fa - 1)) / nbatch_fa; + const int iter_j = (ne01 + (ncols1 - 1)) / ncols1; const int kbc0 = (bidx0 + 0)*(iter_k*iter_j*(ne02/ncols2)*ne03) / gridDim.x; const int kbc0_stop = (bidx0 + 1)*(iter_k*iter_j*(ne02/ncols2)*ne03) / gridDim.x; @@ -765,7 +772,7 @@ static __global__ void flash_attn_combine_results( template void launch_fattn( ggml_backend_cuda_context & ctx, ggml_tensor * dst, fattn_kernel_t fattn_kernel, const int nwarps, const size_t nbytes_shared, - const int KQ_row_granularity, const bool need_f16_K, const bool need_f16_V, const bool stream_k, const int warp_size = WARP_SIZE + const int nbatch_fa, const bool need_f16_K, const bool need_f16_V, const bool stream_k, const int warp_size = WARP_SIZE ) { constexpr int ncols = ncols1 * ncols2; @@ -790,8 +797,6 @@ void launch_fattn( GGML_ASSERT(!V || V->nb[0] == ggml_element_size(V)); GGML_ASSERT(!mask || mask->type == GGML_TYPE_F16); - GGML_ASSERT(!mask || mask->ne[1] >= GGML_PAD(Q->ne[1], 16) && - "the Flash-Attention CUDA kernel requires the mask to be padded to 16 and at least n_queries big"); ggml_cuda_pool & pool = ctx.pool(); cudaStream_t main_stream = ctx.stream(); @@ -915,7 +920,7 @@ void launch_fattn( dst_tmp_meta.alloc(blocks_num.x*ncols * (2*2 + DV) * sizeof(float)); } else { - const int ntiles_KQ = (K->ne[1] + KQ_row_granularity - 1) / KQ_row_granularity; // Max. number of parallel blocks limited by tensor size. + const int ntiles_KQ = (K->ne[1] + nbatch_fa - 1) / nbatch_fa; // Max. number of parallel blocks limited by tensor size. // parallel_blocks must not be larger than what the tensor size allows: parallel_blocks = std::min(parallel_blocks, ntiles_KQ); @@ -970,6 +975,9 @@ void launch_fattn( const float m0 = powf(2.0f, -(max_bias ) / n_head_log2); const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2); + // TODO other tensor dimensions after removal of WMMA kernel: + const uint3 ne01 = init_fastdiv_values(Q->ne[1]); + GGML_ASSERT(block_dim.x % warp_size == 0); fattn_kernel<<>>( (const char *) Q->data, @@ -980,7 +988,7 @@ void launch_fattn( KV_max.ptr, !stream_k && parallel_blocks > 1 ? dst_tmp.ptr : (float *) KQV->data, dst_tmp_meta.ptr, scale, max_bias, m0, m1, n_head_log2, logit_softcap, - Q->ne[0], Q->ne[1], Q->ne[2], Q->ne[3], Q->nb[1], Q->nb[2], Q->nb[3], + Q->ne[0], ne01, Q->ne[2], Q->ne[3], Q->nb[1], Q->nb[2], Q->nb[3], K->ne[0], K->ne[1], K->ne[2], K->ne[3], nb11, nb12, nb13, nb21, nb22, nb23, mask ? mask->ne[1] : 0, mask ? mask->ne[2] : 0, mask ? mask->ne[3] : 0, @@ -995,7 +1003,7 @@ void launch_fattn( flash_attn_stream_k_fixup <<>> - ((float *) KQV->data, dst_tmp_meta.ptr, Q->ne[1], Q->ne[2], Q->ne[3], K->ne[1]); + ((float *) KQV->data, dst_tmp_meta.ptr, Q->ne[1], Q->ne[2], Q->ne[3], K->ne[1], nbatch_fa); } } else if (parallel_blocks > 1) { const dim3 block_dim_combine(DV, 1, 1); diff --git a/ggml/src/ggml-cuda/fattn-mma-f16.cuh b/ggml/src/ggml-cuda/fattn-mma-f16.cuh index 57defb0c62..ade0773dad 100644 --- a/ggml/src/ggml-cuda/fattn-mma-f16.cuh +++ b/ggml/src/ggml-cuda/fattn-mma-f16.cuh @@ -5,284 +5,211 @@ using namespace ggml_cuda_mma; -typedef tile<16, 8, half2> tile_A; -typedef tile< 8, 8, half2> tile_B; -typedef tile<16, 8, half2> tile_B_16; -typedef tile<16, 8, float> tile_C_KQ; -typedef tile<16, 16, float> tile_C_KQ_16; -typedef tile<16, 4, half2> tile_C_VKQ; -typedef tile<16, 8, half2> tile_C_VKQ_16; - -// Config options for specific head sizes. +// Config options for the MMA kernel. // Should not affect results, only speed/register pressure/shared memory use. -// -// nbatch_fa: number of KV rows per softmax rescaling of KQ rowsums and VKQ accumulators. -// nwarps_max: maximum number of warps per CUDA block, up to 8 warps in total can run per SM (given enough shared memory). -// Q_in_reg: whether the Q values should be kept permanently in registers. -// nstages_target: targeted number of pipeline stages for cp_async (if available), 0 means synchronous data loading. -// nbatch_K2: number of K half2 values in direction of DKQ to load in parallel. -// nbatch_V2: number of V half2 values in direction of DV to load in parallel. -// nbatch_combine: number of VKQ half2 values in direction of DV to combine in parallel. +struct fattn_mma_config { + int nthreads; // Number of threads per CUDA block. + int occupancy; // Targeted occupancy for the MMA kernel. + int nbatch_fa; // Number of KV rows per softmax rescaling of KQ rowsums and VKQ accumulators. + int nbatch_K2; // Number of K half2 values in direction of DKQ to load in parallel. + int nbatch_V2; // Number of V half2 values in direction of DV to load in parallel. + int nbatch_combine; // Number of VKQ half2 values in direction of DV to combine in parallel. + int nstages_target; // Number of pipeline stages to use ideally, 1 == always load data synchronously, 2 == preload data if there is hardware support. + bool Q_in_reg; // Whether the Q values should be kept permanently in registers. -template -struct fattn_mma_f16_config; - -template <> -struct fattn_mma_f16_config< 64, 64> { - static constexpr int nbatch_fa = 64; - static constexpr int nwarps_max = 4; - static constexpr bool Q_in_reg = true; - static constexpr int nstages_target = 2; - - static int get_nbatch_K2_host(const int /*cc*/, const int /*ncols*/) { - return 32; - } - - static constexpr __device__ int get_nbatch_K2_device(int /*ncols*/) { - return 32; - } - - static int get_nbatch_V2_host(const int /*cc*/, const int /*ncols*/) { - return 32; - } - - static constexpr __device__ int get_nbatch_V2_device(int /*ncols*/) { - return 32; - } - - static int get_nbatch_combine_host(const int /*cc*/, const int /*ncols*/) { - return 32; - } - - static constexpr __device__ int get_nbatch_combine_device(int /*ncols*/) { - return 32; - } + constexpr __host__ __device__ fattn_mma_config( + int nthreads, int occupancy, int nbatch_fa, int nbatch_K2, int nbatch_V2, int nbatch_combine, int nstages_target, bool Q_in_reg) : + nthreads(nthreads), occupancy(occupancy), nbatch_fa(nbatch_fa), nbatch_K2(nbatch_K2), nbatch_V2(nbatch_V2), nbatch_combine(nbatch_combine), + nstages_target(nstages_target), Q_in_reg(Q_in_reg) {} }; -template <> -struct fattn_mma_f16_config< 80, 80> { - static constexpr int nbatch_fa = 64; - static constexpr int nwarps_max = 4; - static constexpr bool Q_in_reg = true; - static constexpr int nstages_target = 2; +#define GGML_CUDA_FATTN_MMA_CONFIG_CASE(DKQ_, DV_, ncols_, nthreads_, occupancy_, nbatch_fa_, nbatch_K2_, nbatch_V2_, nbatch_combine_, nstages_target_, Q_in_reg_) \ + if (DKQ == (DKQ_) && DV == (DV_) && ncols == (ncols_)) { \ + static_assert((nthreads_) % 32 == 0 && (nthreads_) <= 512, "bad nthreads"); \ + static_assert( (occupancy_) <= 8, "bad occupancy"); \ + static_assert((nbatch_fa_) % 32 == 0 && (nbatch_fa_) <= 256, "bad nbatch_fa"); \ + static_assert((nbatch_K2_) % 4 == 0 && (nbatch_K2_) <= 512, "bad nbatch_K2"); \ + static_assert((nbatch_V2_) % 4 == 0 && (nbatch_V2_) <= 256, "bad nbatch_V2"); \ + static_assert((nbatch_combine_) % 4 == 0 && (nbatch_combine_) <= 128, "bad nbatch_combine"); \ + static_assert((nstages_target_) >= 1 && (nstages_target_) <= 2, "bad nstages_target"); \ + return fattn_mma_config{(nthreads_), (occupancy_), (nbatch_fa_), (nbatch_K2_), (nbatch_V2_), (nbatch_combine_), (nstages_target_), (Q_in_reg_)}; \ + } \ - static int get_nbatch_K2_host(const int /*cc*/, const int /*ncols*/) { - return 40; +static constexpr __host__ __device__ fattn_mma_config ggml_cuda_fattn_mma_get_config_ampere(const int DKQ, const int DV, const int ncols) { + GGML_CUDA_FATTN_MMA_CONFIG_CASE( 64, 64, 8, 128, 2, 128, 32, 32, 32, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE( 64, 64, 16, 128, 2, 64, 32, 32, 32, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE( 64, 64, 32, 128, 2, 64, 32, 32, 32, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE( 64, 64, 64, 128, 2, 64, 32, 32, 32, 2, true); + + GGML_CUDA_FATTN_MMA_CONFIG_CASE( 80, 80, 8, 128, 2, 128, 40, 40, 40, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE( 80, 80, 16, 128, 2, 64, 40, 40, 40, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE( 80, 80, 32, 128, 2, 64, 40, 40, 40, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE( 80, 80, 64, 128, 2, 64, 40, 40, 40, 2, true); + + GGML_CUDA_FATTN_MMA_CONFIG_CASE( 96, 96, 8, 128, 2, 128, 48, 48, 48, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE( 96, 96, 16, 128, 2, 64, 48, 48, 48, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE( 96, 96, 32, 128, 2, 64, 48, 48, 48, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE( 96, 96, 64, 128, 2, 64, 48, 48, 48, 2, true); + + GGML_CUDA_FATTN_MMA_CONFIG_CASE(112, 112, 8, 128, 2, 128, 56, 56, 56, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(112, 112, 16, 128, 2, 64, 56, 56, 56, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(112, 112, 32, 128, 2, 64, 56, 56, 56, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(112, 112, 64, 128, 2, 64, 56, 56, 56, 2, true); + + GGML_CUDA_FATTN_MMA_CONFIG_CASE(128, 128, 8, 128, 2, 128, 64, 64, 64, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(128, 128, 16, 128, 2, 64, 64, 64, 64, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(128, 128, 32, 128, 2, 64, 64, 64, 64, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(128, 128, 64, 128, 2, 64, 64, 64, 64, 2, true); + + GGML_CUDA_FATTN_MMA_CONFIG_CASE(256, 256, 8, 64, 4, 64, 128, 128, 128, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(256, 256, 16, 64, 4, 32, 128, 128, 128, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(256, 256, 32, 128, 2, 32, 128, 128, 128, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(256, 256, 64, 128, 2, 32, 128, 128, 128, 2, true); + + GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 8, 64, 4, 32, 288, 256, 128, 1, false); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 16, 64, 4, 32, 288, 256, 128, 1, false); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 32, 128, 2, 32, 160, 128, 128, 1, false); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 64, 256, 1, 32, 160, 128, 128, 1, false); + + return fattn_mma_config(32, 1, 0, 0, 0, 0, 0, false); +} + +static constexpr __host__ __device__ fattn_mma_config ggml_cuda_fattn_mma_get_config_turing(const int DKQ, const int DV, const int ncols) { + GGML_CUDA_FATTN_MMA_CONFIG_CASE(256, 256, 8, 128, 2, 64, 128, 128, 128, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(256, 256, 16, 128, 2, 64, 128, 128, 128, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(256, 256, 32, 128, 2, 64, 128, 128, 64, 2, true); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(256, 256, 64, 128, 2, 64, 128, 128, 64, 2, true); + + GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 8, 64, 4, 32, 96, 64, 128, 1, false); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 16, 64, 4, 32, 96, 64, 128, 1, false); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 32, 128, 2, 32, 160, 128, 128, 1, false); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 64, 256, 1, 32, 160, 128, 128, 1, false); + + return ggml_cuda_fattn_mma_get_config_ampere(DKQ, DV, ncols); +} + +static constexpr __host__ __device__ fattn_mma_config ggml_cuda_fattn_mma_get_config_volta(const int DKQ, const int DV, const int ncols) { + GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 8, 64, 4, 32, 288, 256, 64, 1, false); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 16, 64, 4, 32, 288, 256, 64, 1, false); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 32, 128, 2, 32, 160, 128, 64, 1, false); + GGML_CUDA_FATTN_MMA_CONFIG_CASE(576, 512, 64, 256, 1, 32, 160, 128, 64, 1, false); + + // TODO tune specifically for Volta + return ggml_cuda_fattn_mma_get_config_ampere(DKQ, DV, ncols); +} + +static __host__ fattn_mma_config ggml_cuda_fattn_mma_get_config(const int DKQ, const int DV, const int ncols, const int cc) { + if (ampere_mma_available(cc)) { + return ggml_cuda_fattn_mma_get_config_ampere(DKQ, DV, ncols); } - - static constexpr __device__ int get_nbatch_K2_device(int /*ncols*/) { - return 40; + if (turing_mma_available(cc)) { + return ggml_cuda_fattn_mma_get_config_turing(DKQ, DV, ncols); } + GGML_ASSERT(volta_mma_available(cc)); + return ggml_cuda_fattn_mma_get_config_volta(DKQ, DV, ncols); +} - static int get_nbatch_V2_host(const int /*cc*/, const int /*ncols*/) { - return 40; - } - - static constexpr __device__ int get_nbatch_V2_device(int /*ncols*/) { - return 40; - } - - static int get_nbatch_combine_host(const int /*cc*/, const int /*ncols*/) { - return 40; - } - - static constexpr __device__ int get_nbatch_combine_device(int /*ncols*/) { - return 40; - } -}; - -template <> -struct fattn_mma_f16_config< 96, 96> { - static constexpr int nbatch_fa = 64; - static constexpr int nwarps_max = 4; - static constexpr bool Q_in_reg = true; - static constexpr int nstages_target = 2; - - static int get_nbatch_K2_host(const int /*cc*/, const int /*ncols*/) { - return 48; - } - - static constexpr __device__ int get_nbatch_K2_device(int /*ncols*/) { - return 48; - } - - static int get_nbatch_V2_host(const int /*cc*/, const int /*ncols*/) { - return 48; - } - - static constexpr __device__ int get_nbatch_V2_device(int /*ncols*/) { - return 48; - } - - static int get_nbatch_combine_host(const int /*cc*/, const int /*ncols*/) { - return 48; - } - - static constexpr __device__ int get_nbatch_combine_device(int /*ncols*/) { - return 48; - } -}; - -template <> -struct fattn_mma_f16_config<112, 112> { - static constexpr int nbatch_fa = 64; - static constexpr int nwarps_max = 4; - static constexpr bool Q_in_reg = true; - static constexpr int nstages_target = 2; - - static int get_nbatch_K2_host(const int /*cc*/, const int /*ncols*/) { - return 56; - } - - static constexpr __device__ int get_nbatch_K2_device(int /*ncols*/) { - return 56; - } - - static int get_nbatch_V2_host(const int /*cc*/, const int /*ncols*/) { - return 56; - } - - static constexpr __device__ int get_nbatch_V2_device(int /*ncols*/) { - return 56; - } - - static int get_nbatch_combine_host(const int /*cc*/, const int /*ncols*/) { - return 56; - } - - static constexpr __device__ int get_nbatch_combine_device(int /*ncols*/) { - return 56; - } -}; - -template <> -struct fattn_mma_f16_config<128, 128> { - static constexpr int nbatch_fa = 64; - static constexpr int nwarps_max = 4; - static constexpr bool Q_in_reg = true; - static constexpr int nstages_target = 2; - - static int get_nbatch_K2_host(const int /*cc*/, const int /*ncols*/) { - return 64; - } - - static constexpr __device__ int get_nbatch_K2_device(int /*ncols*/) { - return 64; - } - - static int get_nbatch_V2_host(const int /*cc*/, const int /*ncols*/) { - return 64; - } - - static constexpr __device__ int get_nbatch_V2_device(int /*ncols*/) { - return 64; - } - - static int get_nbatch_combine_host(const int /*cc*/, const int /*ncols*/) { - return 64; - } - - static constexpr __device__ int get_nbatch_combine_device(int /*ncols*/) { - return 64; - } -}; - -template <> -struct fattn_mma_f16_config<256, 256> { - static constexpr int nbatch_fa = 32; - static constexpr int nwarps_max = 4; - static constexpr bool Q_in_reg = true; - static constexpr int nstages_target = 2; - - static int get_nbatch_K2_host(const int /*cc*/, const int /*ncols*/) { - return 128; - } - - static constexpr __device__ int get_nbatch_K2_device(int /*ncols*/) { - return 128; - } - - static int get_nbatch_V2_host(const int /*cc*/, const int /*ncols*/) { - return 128; - } - - static constexpr __device__ int get_nbatch_V2_device(int /*ncols*/) { - return 128; - } - - static int get_nbatch_combine_host(const int cc, const int ncols) { - if (ggml_cuda_highest_compiled_arch(cc) == GGML_CUDA_CC_TURING) { - return ncols <= 16 ? 128 : 64; - } - return 64; - } - - static constexpr __device__ int get_nbatch_combine_device(int ncols) { -#if __CUDA_ARCH__ == GGML_CUDA_CC_TURING - return ncols <= 16 ? 128 : 64; +static constexpr __device__ fattn_mma_config ggml_cuda_fattn_mma_get_config(const int DKQ, const int DV, const int ncols) { +#if defined(AMPERE_MMA_AVAILABLE) + return ggml_cuda_fattn_mma_get_config_ampere(DKQ, DV, ncols); +#elif defined(TURING_MMA_AVAILABLE) + return ggml_cuda_fattn_mma_get_config_turing(DKQ, DV, ncols); +#elif defined(VOLTA_MMA_AVAILABLE) + return ggml_cuda_fattn_mma_get_config_volta(DKQ, DV, ncols); #else - GGML_UNUSED(ncols); - return 128; -#endif // __CUDA_ARCH__ == GGML_CUDA_CC_TURING - } -}; + GGML_UNUSED_VARS(DKQ, DV, ncols); + return fattn_mma_config(32, 1, 0, 0, 0, 0, 0, false); +#endif // defined(AMPERE_MMA_AVAILABLE) +} -template <> -struct fattn_mma_f16_config<576, 512> { - static constexpr int nbatch_fa = 32; - static constexpr int nwarps_max = 8; - static constexpr bool Q_in_reg = false; - static constexpr int nstages_target = 1; +static __host__ int ggml_cuda_fattn_mma_get_nthreads(const int DKQ, const int DV, const int ncols, const int cc) { + return ggml_cuda_fattn_mma_get_config(DKQ, DV, ncols, cc).nthreads; +} - static int get_nbatch_K2_host(const int cc, const int ncols) { - if (ggml_cuda_highest_compiled_arch(cc) == GGML_CUDA_CC_TURING) { - return ncols <= 16 ? 96 : 160; - } - return ncols <= 16 ? 288 : 160; - } +static constexpr __device__ int ggml_cuda_fattn_mma_get_nthreads(const int DKQ, const int DV, const int ncols) { + return ggml_cuda_fattn_mma_get_config(DKQ, DV, ncols).nthreads; +} - static constexpr __device__ int get_nbatch_K2_device(int ncols) { -#if __CUDA_ARCH__ == GGML_CUDA_CC_TURING - return ncols <= 16 ? 96 : 160; -#else - return ncols <= 16 ? 288 : 160; -#endif // __CUDA_ARCH__ == GGML_CUDA_CC_TURING - } +static __host__ int ggml_cuda_fattn_mma_get_occupancy(const int DKQ, const int DV, const int ncols, const int cc) { + return ggml_cuda_fattn_mma_get_config(DKQ, DV, ncols, cc).occupancy; +} - static int get_nbatch_V2_host(const int cc, const int ncols) { - if (ggml_cuda_highest_compiled_arch(cc) == GGML_CUDA_CC_TURING) { - return ncols <= 16 ? 64 : 128; - } - return ncols <= 16 ? 256 : 128; - } +static constexpr __device__ int ggml_cuda_fattn_mma_get_occupancy(const int DKQ, const int DV, const int ncols) { + return ggml_cuda_fattn_mma_get_config(DKQ, DV, ncols).occupancy; +} - static constexpr __device__ int get_nbatch_V2_device(int ncols) { -#if __CUDA_ARCH__ == GGML_CUDA_CC_TURING - return ncols <= 16 ? 64 : 128; -#else - return ncols <= 16 ? 256 : 128; -#endif // __CUDA_ARCH__ == GGML_CUDA_CC_TURING - } +static __host__ int ggml_cuda_fattn_mma_get_nbatch_fa(const int DKQ, const int DV, const int ncols, const int cc) { + return ggml_cuda_fattn_mma_get_config(DKQ, DV, ncols, cc).nbatch_fa; +} - static int get_nbatch_combine_host(const int /*cc*/, const int /*ncols*/) { - return 128; - } +static constexpr __device__ int ggml_cuda_fattn_mma_get_nbatch_fa(const int DKQ, const int DV, const int ncols) { + return ggml_cuda_fattn_mma_get_config(DKQ, DV, ncols).nbatch_fa; +} - static constexpr __device__ int get_nbatch_combine_device(int /*ncols*/) { - return 128; - } -}; +static __host__ int ggml_cuda_fattn_mma_get_nbatch_K2(const int DKQ, const int DV, const int ncols, const int cc) { + return ggml_cuda_fattn_mma_get_config(DKQ, DV, ncols, cc).nbatch_K2; +} + +static constexpr __device__ int ggml_cuda_fattn_mma_get_nbatch_K2(const int DKQ, const int DV, const int ncols) { + return ggml_cuda_fattn_mma_get_config(DKQ, DV, ncols).nbatch_K2; +} + +static __host__ int ggml_cuda_fattn_mma_get_nbatch_V2(const int DKQ, const int DV, const int ncols, const int cc) { + return ggml_cuda_fattn_mma_get_config(DKQ, DV, ncols, cc).nbatch_V2; +} + +static constexpr __device__ int ggml_cuda_fattn_mma_get_nbatch_V2(const int DKQ, const int DV, const int ncols) { + return ggml_cuda_fattn_mma_get_config(DKQ, DV, ncols).nbatch_V2; +} + +static __host__ int ggml_cuda_fattn_mma_get_nbatch_combine(const int DKQ, const int DV, const int ncols, const int cc) { + return ggml_cuda_fattn_mma_get_config(DKQ, DV, ncols, cc).nbatch_combine; +} + +static constexpr __device__ int ggml_cuda_fattn_mma_get_nbatch_combine(const int DKQ, const int DV, const int ncols) { + return ggml_cuda_fattn_mma_get_config(DKQ, DV, ncols).nbatch_combine; +} + +static __host__ int ggml_cuda_fattn_mma_get_nstages_target(const int DKQ, const int DV, const int ncols, const int cc) { + return ggml_cuda_fattn_mma_get_config(DKQ, DV, ncols, cc).nstages_target; +} + +static constexpr __device__ int ggml_cuda_fattn_mma_get_nstages_target(const int DKQ, const int DV, const int ncols) { + return ggml_cuda_fattn_mma_get_config(DKQ, DV, ncols).nstages_target; +} + +static __host__ bool ggml_cuda_fattn_mma_get_Q_in_reg(const int DKQ, const int DV, const int ncols, const int cc) { + return ggml_cuda_fattn_mma_get_config(DKQ, DV, ncols, cc).Q_in_reg; +} + +static constexpr __device__ bool ggml_cuda_fattn_mma_get_Q_in_reg(const int DKQ, const int DV, const int ncols) { + return ggml_cuda_fattn_mma_get_config(DKQ, DV, ncols).Q_in_reg; +} // ------------------------------------------------------------------------------------------------------------------ -template -static __device__ __forceinline__ void flash_attn_ext_f16_load_tile( - const half2 * const __restrict__ KV, half2 * const __restrict__ tile_KV, const int D2, const int stride_KV) { +static __host__ int ggml_cuda_fattn_mma_get_nstages(const int DKQ, const int DV, const int ncols1, const int ncols2, const int cc) { + return cp_async_available(cc) && ncols2 >= 2 ? ggml_cuda_fattn_mma_get_nstages_target(DKQ, DV, ncols1*ncols2, cc) : 0; +} +static constexpr __device__ int ggml_cuda_fattn_mma_get_nstages(const int DKQ, const int DV, const int ncols1, const int ncols2) { +#ifdef CP_ASYNC_AVAILABLE + return ncols2 >= 2 ? ggml_cuda_fattn_mma_get_nstages_target(DKQ, DV, ncols1*ncols2) : 0; +#else + GGML_UNUSED_VARS(DKQ, DV, ncols1, ncols2); + return 0; +#endif // CP_ASYNC_AVAILABLE +} + +// ------------------------------------------------------------------------------------------------------------------ + +template +static __device__ __forceinline__ void flash_attn_ext_f16_load_tile( + const half2 * const __restrict__ KV, half2 * const __restrict__ tile_KV, const int D2, const int stride_KV, const int i_sup) { // K/V data is loaded with decreasing granularity for D for better memory bandwidth. // The minimum granularity with cp.async is 16 bytes, with synchronous data loading it's 4 bytes. - - if (use_cp_async) { + if constexpr (use_cp_async) { + static_assert(!oob_check, "OOB check not compatible with cp_async"); constexpr int preload = 64; constexpr int h2_per_chunk = 16/sizeof(half2); const int chunks_per_row = D2 / h2_per_chunk; @@ -315,9 +242,15 @@ static __device__ __forceinline__ void flash_attn_ext_f16_load_tile( } } }; - ggml_cuda_unroll<5>{}(load); + // 1: max 32*16=512 bytes, 256 half + // 2: max 16*16=256 bytes, 128 half + // 3: max 8*16=128 bytes, 64 half + // 4: max 4*16= 64 bytes, 32 half + // 5: max 2*16= 32 bytes, 16 half + // 6: max 1*16= 16 bytes, 8 half + ggml_cuda_unroll<6>{}(load); } else { - static_assert(nbatch_fa % (4*nwarps) == 0, "out of bounds"); + // TODO use ggml_cuda_memcpy_1 auto load = [&] __device__ (const int n) { const int stride_k = WARP_SIZE >> n; const int k0_start = stride_k == WARP_SIZE ? 0 : D2 - D2 % (2*stride_k); @@ -340,20 +273,25 @@ static __device__ __forceinline__ void flash_attn_ext_f16_load_tile( for (int k0 = k0_start; k0 < k0_stop; k0 += stride_k) { const int k = k0 + (stride_k == WARP_SIZE ? threadIdx.x : threadIdx.x % stride_k); - tile_KV[i*stride_tile + k] = KV[i*stride_KV + k]; + tile_KV[i*stride_tile + k] = !oob_check || i < i_sup ? KV[i*stride_KV + k] : make_half2(0.0f, 0.0f); } } }; - ggml_cuda_unroll<3>{}(load); + // 1: max 32* 4=128 bytes, 64 half + // 2: max 16* 4= 64 bytes, 32 half + // 3: max 8* 4= 32 bytes, 16 half + // 4: max 4* 4= 16 bytes, 8 half + ggml_cuda_unroll<4>{}(load); } } -template +template static __device__ __forceinline__ void flash_attn_ext_f16_load_mask( - const half2 * const __restrict__ mask_h2, half2 * const __restrict__ tile_mask, const int stride_mask) { - static_assert(nbatch_fa == 2*WARP_SIZE || WARP_SIZE % nbatch_fa == 0, "bad KQ_per_iter"); - - if (use_cp_async) { + const half * const __restrict__ mask_h, half * const __restrict__ tile_mask, + const int stride_mask, const int i_sup, const int j0, const uint3 ne01) { + if constexpr (use_cp_async) { + static_assert(nbatch_fa <= 8*WARP_SIZE && nbatch_fa % 8 == 0, "bad nbatch_fa"); + static_assert(!oob_check, "OOB check incompatible with cp_async"); constexpr int preload = nbatch_fa >= 32 ? nbatch_fa * sizeof(half) : 64; constexpr int cols_per_warp = 8*WARP_SIZE/nbatch_fa; constexpr int stride_j = nwarps * cols_per_warp; @@ -361,50 +299,85 @@ static __device__ __forceinline__ void flash_attn_ext_f16_load_mask( const unsigned int tile_mask_32 = ggml_cuda_cvta_generic_to_shared(tile_mask); #pragma unroll - for (int j0 = 0; j0 < ncols1; j0 += stride_j) { - const int j = j0 + threadIdx.y*cols_per_warp + - (nbatch_fa == 2*WARP_SIZE ? threadIdx.x / (WARP_SIZE/4) : threadIdx.x / (WARP_SIZE/cols_per_warp)); + for (int j1 = 0; j1 < ncols1; j1 += stride_j) { + const int j_sram = j1 + threadIdx.y*cols_per_warp + threadIdx.x / (WARP_SIZE/cols_per_warp); + const int j_vram = fastmodulo(j0 + j_sram, ne01); - if (j0 + stride_j > ncols1 && j >= ncols1) { + if (j1 + stride_j > ncols1 && j_sram >= ncols1) { break; } - const int i = 4 * (threadIdx.x % (nbatch_fa/8)); + const int i = 8 * (threadIdx.x % (nbatch_fa/8)); - cp_async_cg_16(tile_mask_32 + j*(nbatch_fa*sizeof(half) + 16) + i*sizeof(half2), mask_h2 + j*stride_mask + i); + cp_async_cg_16(tile_mask_32 + j_sram*(nbatch_fa*sizeof(half) + 16) + i*sizeof(half), mask_h + j_vram*stride_mask + i); } - return; - } - - constexpr int cols_per_warp = 2*WARP_SIZE/nbatch_fa; - constexpr int stride_j = nwarps * cols_per_warp; + } else if constexpr (oob_check) { #pragma unroll - for (int j0 = 0; j0 < ncols1; j0 += stride_j) { - const int j = j0 + threadIdx.y*cols_per_warp + (nbatch_fa == 2*WARP_SIZE ? 0 : threadIdx.x / (WARP_SIZE/cols_per_warp)); + for (int j1 = 0; j1 < ncols1; j1 += nwarps) { + const int j_sram = j1 + threadIdx.y; + const int j_vram = fastmodulo(j0 + j_sram, ne01); - if (j0 + stride_j > ncols1 && j >= ncols1) { - break; + if (j1 + nwarps > ncols1 && j_sram >= ncols1) { + break; + } + +#pragma unroll + for (int i0 = 0; i0 < nbatch_fa; i0 += WARP_SIZE) { + const int i = i0 + threadIdx.x; + + tile_mask[j_sram*(nbatch_fa + 8) + i] = i < i_sup ? mask_h[j_vram*stride_mask + i] : half(0.0f); + } } + } else if constexpr (nbatch_fa < 2*WARP_SIZE) { + constexpr int cols_per_warp = 2*WARP_SIZE/nbatch_fa; + constexpr int stride_j = nwarps * cols_per_warp; +#pragma unroll + for (int j1 = 0; j1 < ncols1; j1 += stride_j) { + const int j_sram = j1 + threadIdx.y*cols_per_warp + threadIdx.x / (WARP_SIZE/cols_per_warp); + const int j_vram = fastmodulo(j0 + j_sram, ne01); - const int i = nbatch_fa == 2*WARP_SIZE ? threadIdx.x : threadIdx.x % (WARP_SIZE/cols_per_warp); + if (j1 + stride_j > ncols1 && j_sram >= ncols1) { + break; + } - tile_mask[j*(nbatch_fa/2 + 4) + i] = mask_h2[j*stride_mask + i]; + const int i = threadIdx.x % (WARP_SIZE/cols_per_warp); + + ggml_cuda_memcpy_1(tile_mask + j_sram*(nbatch_fa + 8) + 2*i, mask_h + j_vram*stride_mask + 2*i); + } + } else { +#pragma unroll + for (int j1 = 0; j1 < ncols1; j1 += nwarps) { + const int j_sram = j1 + threadIdx.y; + const int j_vram = fastmodulo(j0 + j_sram, ne01); + + if (j1 + nwarps > ncols1 && j_sram >= ncols1) { + break; + } + +#pragma unroll + for (int i0 = 0; i0 < nbatch_fa; i0 += 2*WARP_SIZE) { + const int i = i0 + 2*threadIdx.x; + + ggml_cuda_memcpy_1(tile_mask + j_sram*(nbatch_fa + 8) + i, mask_h + j_vram*stride_mask + i); + } + } } } -template +template static __device__ __forceinline__ void flash_attn_ext_f16_iter( const float2 * const __restrict__ Q_f2, const half2 * const __restrict__ K_h2, const half2 * const __restrict__ V_h2, - const half2 * const __restrict__ mask_h2, + const half * const __restrict__ mask_h, float2 * const __restrict__ dstk, float2 * const __restrict__ dstk_fixup, const float scale, const float slope, const float logit_softcap, - const int ne01, + const uint3 ne01, const int ne02, const int stride_K, const int stride_V, @@ -412,27 +385,24 @@ static __device__ __forceinline__ void flash_attn_ext_f16_iter( half2 * const __restrict__ tile_Q, half2 * const __restrict__ tile_K, half2 * const __restrict__ tile_V, - half2 * const __restrict__ tile_mask, - const tile_B * const __restrict__ Q_B, - tile_C_VKQ * const __restrict__ VKQ_C, + half * const __restrict__ tile_mask, + T_B_KQ * const __restrict__ Q_B, + T_C_VKQ * const __restrict__ VKQ_C, float * const __restrict__ KQ_max, float * const __restrict__ KQ_rowsum, - const int kb0) { -#ifdef TURING_MMA_AVAILABLE - typedef fattn_mma_f16_config c; - -#ifdef CP_ASYNC_AVAILABLE - constexpr int nstages = c::nstages_target; -#else - constexpr int nstages = 0; -#endif // CP_ASYNC_AVAILABLE - - constexpr int cols_per_warp = ntiles * tile_B::I; - constexpr int cols_per_thread = ntiles == 1 ? 2 : ntiles; - constexpr int np = nwarps * (cols_per_warp/ncols2) / ncols1; // Number of parallel CUDA warps per Q column. - constexpr int ncols = ncols1 * ncols2; - constexpr int nbatch_K2 = c::get_nbatch_K2_device(ncols); - constexpr int nbatch_V2 = c::get_nbatch_V2_device(ncols); + const int jt, + const int kb0, + const int k_VKQ_sup) { +#if defined(VOLTA_MMA_AVAILABLE) || defined(TURING_MMA_AVAILABLE) + constexpr int ncols = ncols1 * ncols2; + constexpr int cols_per_warp = T_B_KQ::I; + constexpr int cols_per_thread = 2; // This is specifically KQ columns, Volta only has a single VKQ column. + constexpr int np = nwarps * (cols_per_warp/ncols2) / ncols1; // Number of parallel CUDA warps per Q column. + constexpr int nbatch_fa = ggml_cuda_fattn_mma_get_nbatch_fa(DKQ, DV, ncols); + constexpr int nbatch_K2 = ggml_cuda_fattn_mma_get_nbatch_K2(DKQ, DV, ncols); + constexpr int nbatch_V2 = ggml_cuda_fattn_mma_get_nbatch_V2(DKQ, DV, ncols); + constexpr bool Q_in_reg = ggml_cuda_fattn_mma_get_Q_in_reg (DKQ, DV, ncols); + constexpr int nstages = ggml_cuda_fattn_mma_get_nstages (DKQ, DV, ncols1, ncols2); constexpr int stride_tile_Q = DKQ/2 + 4; constexpr int stride_tile_K = nbatch_K2 + 4; @@ -440,26 +410,27 @@ static __device__ __forceinline__ void flash_attn_ext_f16_iter( static_assert(!mla || nbatch_K2 >= nbatch_V2, "bad nbatch_K2, nbatch_V2 for MLA"); constexpr int stride_tile_V = mla ? stride_tile_K : nbatch_V2 + 4; - const int k_VKQ_0 = kb0 * c::nbatch_fa; - tile_C_KQ KQ_C[c::nbatch_fa/(np*tile_C_KQ::I) * ntiles]; - - // Use wide variants of tiles if ntiles >= 2. - tile_B_16 * Q_B_16 = (tile_B_16 *) Q_B; - tile_C_VKQ_16 * VKQ_C_16 = (tile_C_VKQ_16 *) VKQ_C; - tile_C_KQ_16 * KQ_C_16 = (tile_C_KQ_16 *) KQ_C; + const int k_VKQ_0 = kb0 * nbatch_fa; +#if defined(TURING_MMA_AVAILABLE) + T_C_KQ KQ_C[nbatch_fa/(np*(cols_per_warp == 8 ? T_C_KQ::I : T_C_KQ::J))]; +#else // Volta + T_C_KQ KQ_C[nbatch_fa/(np*T_C_KQ::J)]; +#endif // defined(TURING_MMA_AVAILABLE) if constexpr (nstages > 1) { + static_assert(!oob_check, "OOB check incompatible with multi-stage pipeline"); static_assert(!mla, "multi-stage loading not implemented for MLA"); static_assert(nbatch_K2 == DKQ/2, "batching not implemented for multi stage loading"); constexpr bool use_cp_async = true; cp_async_wait_all(); __syncthreads(); - flash_attn_ext_f16_load_tile - (V_h2 + int64_t(k_VKQ_0)*stride_V, tile_V, nbatch_V2, stride_V); + flash_attn_ext_f16_load_tile + (V_h2 + int64_t(k_VKQ_0)*stride_V, tile_V, nbatch_V2, stride_V, k_VKQ_sup); } else { constexpr bool use_cp_async = nstages == 1; - if (ncols2 > 1 || mask_h2) { - flash_attn_ext_f16_load_mask(mask_h2 + k_VKQ_0/2, tile_mask, stride_mask); + if (ncols2 > 1 || mask_h) { + flash_attn_ext_f16_load_mask + (mask_h + k_VKQ_0, tile_mask, stride_mask, k_VKQ_sup, jt*ncols1, ne01); } } @@ -468,10 +439,10 @@ static __device__ __forceinline__ void flash_attn_ext_f16_iter( const int k0_stop = k0_start + nbatch_K2 < DKQ/2 ? k0_start + nbatch_K2 : DKQ/2; const int k0_diff = k0_stop - k0_start; - if (nstages <= 1) { + if constexpr (nstages <= 1) { constexpr bool use_cp_async = nstages == 1; - flash_attn_ext_f16_load_tile - (K_h2 + int64_t(k_VKQ_0)*stride_K + k0_start, tile_K, k0_diff, stride_K); + flash_attn_ext_f16_load_tile + (K_h2 + int64_t(k_VKQ_0)*stride_K + k0_start, tile_K, k0_diff, stride_K, k_VKQ_sup); if (use_cp_async) { cp_async_wait_all(); } @@ -479,55 +450,53 @@ static __device__ __forceinline__ void flash_attn_ext_f16_iter( } // Calculate tile of KQ: - if constexpr (c::Q_in_reg) { + if constexpr (Q_in_reg) { #pragma unroll - for (int i_KQ_00 = 0; i_KQ_00 < c::nbatch_fa; i_KQ_00 += np*tile_A::I) { - const int i_KQ_0 = i_KQ_00 + (threadIdx.y % np)*tile_A::I; + for (int i_KQ_00 = 0; i_KQ_00 < nbatch_fa; i_KQ_00 += np*T_A_KQ::I) { + const int i_KQ_0 = i_KQ_00 + (threadIdx.y % np)*T_A_KQ::I; #pragma unroll - for (int k_KQ_0 = k0_start; k_KQ_0 < k0_stop; k_KQ_0 += tile_A::J) { - tile_A K_A; + for (int k_KQ_0 = k0_start; k_KQ_0 < k0_stop; k_KQ_0 += T_A_KQ::J) { + T_A_KQ K_A; load_ldmatrix(K_A, tile_K + i_KQ_0*stride_tile_K + (k_KQ_0 - k0_start), stride_tile_K); - if (ntiles == 1) { - mma(KQ_C[i_KQ_00/(np*tile_A::I)], K_A, Q_B[k_KQ_0/tile_A::J]); + if constexpr (cols_per_warp == 8) { + mma(KQ_C[i_KQ_00/(np*T_A_KQ::I)], K_A, Q_B[k_KQ_0/T_A_KQ::J]); } else { -#pragma unroll - for (int t = 0; t < ntiles/2; ++t) { - // Wide version of KQ_C is column-major => swap A and B. - mma(KQ_C_16[i_KQ_00/(np*tile_A::I) * ntiles/2 + t], Q_B_16[k_KQ_0/tile_A::J * ntiles/2 + t], K_A); - } + // Wide version of KQ_C is column-major => swap A and B. + mma(KQ_C[i_KQ_00/(np*T_A_KQ::I)], Q_B[k_KQ_0/T_A_KQ::J], K_A); } } } } else { - static_assert(ntiles == 2, "ntiles != 2 not implemented"); + static_assert(cols_per_warp != 8, "cols_per_warp == 8 not implemented"); #pragma unroll - for (int k_KQ_0 = k0_start; k_KQ_0 < k0_stop; k_KQ_0 += tile_A::J) { - load_ldmatrix(Q_B_16[0], tile_Q + (threadIdx.y / np)*(tile_B_16::I*stride_tile_Q) + k_KQ_0, stride_tile_Q); + for (int k_KQ_0 = k0_start; k_KQ_0 < k0_stop; k_KQ_0 += T_A_KQ::J) { + load_ldmatrix(Q_B[0], tile_Q + (threadIdx.y / np)*(T_B_KQ::I*stride_tile_Q) + k_KQ_0, stride_tile_Q); #pragma unroll - for (int i_KQ_00 = 0; i_KQ_00 < c::nbatch_fa; i_KQ_00 += np*tile_A::I) { - const int i_KQ_0 = i_KQ_00 + (threadIdx.y % np)*tile_A::I; + for (int i_KQ_00 = 0; i_KQ_00 < nbatch_fa; i_KQ_00 += np*T_A_KQ::I) { + const int i_KQ_0 = i_KQ_00 + (threadIdx.y % np)*T_A_KQ::I; - tile_A K_A; + T_A_KQ K_A; load_ldmatrix(K_A, tile_K + i_KQ_0*stride_tile_K + (k_KQ_0 - k0_start), stride_tile_K); // Wide version of KQ_C is column-major => swap A and B. - mma(KQ_C_16[i_KQ_00/(np*tile_A::I)], Q_B_16[0], K_A); + mma(KQ_C[i_KQ_00/(np*T_A_KQ::I)], Q_B[0], K_A); } } } - if (nstages <= 1) { + if constexpr (nstages <= 1) { __syncthreads(); // Only needed if tile_K == tile_V. } } if (use_logit_softcap) { - static_assert(c::nbatch_fa % (np*tile_C_KQ::I) == 0, "bad loop size"); + constexpr int stride = cols_per_warp == 8 ? np*T_C_KQ::I : np*T_C_KQ::J; + static_assert(nbatch_fa % stride == 0, "bad loop size"); #pragma unroll - for (int i = 0; i < c::nbatch_fa/(np*tile_C_KQ::I) * ntiles; ++i) { + for (int i = 0; i < nbatch_fa/stride; ++i) { #pragma unroll - for (int l = 0; l < tile_C_KQ::ne; ++l) { + for (int l = 0; l < T_C_KQ::ne; ++l) { KQ_C[i].x[l] = logit_softcap*tanhf(KQ_C[i].x[l]); } } @@ -540,34 +509,35 @@ static __device__ __forceinline__ void flash_attn_ext_f16_iter( } float KQ_rowsum_add[cols_per_thread] = {0.0f}; - if (ntiles == 1) { - if (ncols2 > 1 || mask_h2) { + if constexpr (cols_per_warp == 8) { + if (ncols2 > 1 || mask_h) { #pragma unroll - for (int i00 = 0; i00 < c::nbatch_fa; i00 += np*tile_C_KQ::I) { - const int i0 = i00 + (threadIdx.y % np)*tile_C_KQ::I; + for (int i00 = 0; i00 < nbatch_fa; i00 += np*T_C_KQ::I) { + const int i0 = i00 + (threadIdx.y % np)*T_C_KQ::I; #pragma unroll - for (int l = 0; l < tile_C_KQ::ne; ++l) { - const int i = i0 + tile_C_KQ::get_i(l); - const int j = ((threadIdx.y / np)*tile_C_KQ::J + tile_C_KQ::get_j(l)) / ncols2; + for (int l = 0; l < T_C_KQ::ne; ++l) { + const int i = i0 + T_C_KQ::get_i(l); + const int j = ((threadIdx.y / np)*T_C_KQ::J + T_C_KQ::get_j(l)) / ncols2; - KQ_C[i00/(np*tile_C_KQ::I)].x[l] += slope * - __half2float(((const half *) tile_mask)[j*(c::nbatch_fa + 8) + i]); + KQ_C[i00/(np*T_C_KQ::I)].x[l] += slope * __half2float(tile_mask[j*(nbatch_fa + 8) + i]); } } } // Calculate softmax for each KQ column using the current max. value. // The divisor is stored in KQ_rowsum and will be applied at the end. - static_assert(c::nbatch_fa % (np*tile_C_KQ::I) == 0, "bad loop size"); + static_assert(nbatch_fa % (np*T_C_KQ::I) == 0, "bad loop size"); #pragma unroll - for (int k = 0; k < c::nbatch_fa/(np*tile_C_KQ::I); ++k) { + for (int k0 = 0; k0 < nbatch_fa; k0 += np*T_C_KQ::I) { #pragma unroll - for (int l = 0; l < tile_C_KQ::ne; ++l) { - KQ_max_new[l % 2] = fmaxf(KQ_max_new[l % 2], KQ_C[k].x[l]); + for (int l = 0; l < T_C_KQ::ne; ++l) { + if (!oob_check || k0 + T_C_KQ::get_i(l) < k_VKQ_sup) { + KQ_max_new[l % 2] = fmaxf(KQ_max_new[l % 2], KQ_C[k0/(np*T_C_KQ::I)].x[l] + FATTN_KQ_MAX_OFFSET); + } } } - // Values per KQ column are spread across 8 threads, does not need full warp reduce: + // Values per KQ column are spread across 8 threads: #pragma unroll for (int col = 0; col < cols_per_thread; ++col) { #pragma unroll @@ -576,73 +546,78 @@ static __device__ __forceinline__ void flash_attn_ext_f16_iter( } } - static_assert(c::nbatch_fa % (np*tile_C_KQ::I) == 0, "bad loop size"); + static_assert(nbatch_fa % (np*T_C_KQ::I) == 0, "bad loop size"); #pragma unroll - for (int k = 0; k < c::nbatch_fa/(np*tile_C_KQ::I); ++k) { + for (int k0 = 0; k0 < nbatch_fa; k0 += np*T_C_KQ::I) { #pragma unroll - for (int l = 0; l < tile_C_KQ::ne; ++l) { - KQ_C[k].x[l] = expf(KQ_C[k].x[l] - KQ_max_new[l % 2]); - - KQ_rowsum_add[l % 2] += KQ_C[k].x[l]; + for (int l = 0; l < T_C_KQ::ne; ++l) { + if (!oob_check || k0 + (threadIdx.y % np)*T_C_KQ::I + T_C_KQ::get_i(l) < k_VKQ_sup) { + KQ_C[k0/(np*T_C_KQ::I)].x[l] = expf(KQ_C[k0/(np*T_C_KQ::I)].x[l] - KQ_max_new[l % 2]); + KQ_rowsum_add[l % 2] += KQ_C[k0/(np*T_C_KQ::I)].x[l]; + } else { + KQ_C[k0/(np*T_C_KQ::I)].x[l] = 0.0f; + } } } - } else { // ntiles > 1 - if (ncols2 > 1 || mask_h2) { + } else { // not Turing mma or T_B_KQ::I > 8 + if (ncols2 > 1 || mask_h) { #pragma unroll - for (int i00 = 0; i00 < c::nbatch_fa; i00 += np*tile_C_KQ_16::J) { - const int i0 = i00 + (threadIdx.y % np)*tile_C_KQ_16::J; + for (int i00 = 0; i00 < nbatch_fa; i00 += np*T_C_KQ::J) { + const int i0 = i00 + (threadIdx.y % np)*T_C_KQ::J; #pragma unroll - for (int t = 0; t < ntiles/2; ++t) { -#pragma unroll - for (int l0 = 0; l0 < tile_C_KQ_16::ne; l0 += 2) { - const int i = (i0 + tile_C_KQ_16::get_j(l0)) / 2; - const int j = ((threadIdx.y / np)*cols_per_warp + t*tile_C_KQ_16::I + tile_C_KQ_16::get_i(l0)) / ncols2; + for (int l0 = 0; l0 < T_C_KQ::ne; l0 += 2) { + const int i = (i0 + T_C_KQ::get_j(l0)) / 2; + const int j = ((threadIdx.y / np)*cols_per_warp + T_C_KQ::get_i(l0)) / ncols2; - const float2 tmp = __half22float2(tile_mask[j*(c::nbatch_fa/2 + 4) + i]); - const int KQ_index = i00/(np*tile_C_KQ_16::J) * ntiles/2 + t; - KQ_C_16[KQ_index].x[l0 + 0] += slope*tmp.x; - KQ_C_16[KQ_index].x[l0 + 1] += slope*tmp.y; - } + const float2 tmp = __half22float2(((const half2 *)tile_mask)[j*(nbatch_fa/2 + 4) + i]); + KQ_C[i00/(np*T_C_KQ::J)].x[l0 + 0] += slope*tmp.x; + KQ_C[i00/(np*T_C_KQ::J)].x[l0 + 1] += slope*tmp.y; } } } // Calculate softmax for each KQ column using the current max. value. // The divisor is stored in KQ_rowsum and will be applied at the end. - static_assert(c::nbatch_fa % (np*tile_C_KQ::I) == 0, "bad loop size"); + static_assert(nbatch_fa % (np*T_C_KQ::J) == 0, "bad loop size"); #pragma unroll - for (int k = 0; k < c::nbatch_fa/(np*tile_C_KQ_16::J); ++k) { + for (int k0 = 0; k0 < nbatch_fa; k0 += np*T_C_KQ::J) { #pragma unroll - for (int t = 0; t < ntiles/2; ++t) { -#pragma unroll - for (int l = 0; l < tile_C_KQ_16::ne; ++l) { - const int KQ_index = 2*t + (l/2) % 2; - KQ_max_new[KQ_index] = fmaxf(KQ_max_new[KQ_index], KQ_C_16[k*ntiles/2 + t].x[l]); + for (int l = 0; l < T_C_KQ::ne; ++l) { + if (!oob_check || k0 + T_C_KQ::get_j(l) < k_VKQ_sup) { + // Turing + Volta: + KQ_max_new[(l/2) % 2] = fmaxf(KQ_max_new[(l/2) % 2], KQ_C[(k0/(np*T_C_KQ::J))].x[l] + FATTN_KQ_MAX_OFFSET); } } } - // Values per KQ column are spread across 4 threads, does not need full warp reduce: #pragma unroll for (int col = 0; col < cols_per_thread; ++col) { +#if defined(TURING_MMA_AVAILABLE) + // Values per KQ column are spread across 4 threads: + constexpr int offset_first = 2; + constexpr int offset_last = 1; +#else + // Values per KQ column are spread across 2 threads: + constexpr int offset_first = 2; + constexpr int offset_last = 2; +#endif // defined(TURING_MMA_AVAILABLE) #pragma unroll - for (int offset = 2; offset >= 1; offset >>= 1) { + for (int offset = offset_first; offset >= offset_last; offset >>= 1) { KQ_max_new[col] = fmaxf(KQ_max_new[col], __shfl_xor_sync(0xFFFFFFFF, KQ_max_new[col], offset, WARP_SIZE)); } } - static_assert(c::nbatch_fa % (np*tile_C_KQ_16::J) == 0, "bad loop size"); + static_assert(nbatch_fa % (np*T_C_KQ::J) == 0, "bad loop size"); #pragma unroll - for (int k = 0; k < c::nbatch_fa/(np*tile_C_KQ_16::J); ++k) { + for (int k0 = 0; k0 < nbatch_fa; k0 += np*T_C_KQ::J) { #pragma unroll - for (int t = 0; t < ntiles/2; ++t) { -#pragma unroll - for (int l = 0; l < tile_C_KQ_16::ne; ++l) { - const int KQ_index = 2*t + (l/2) % 2; - - KQ_C_16[k*ntiles/2 + t].x[l] = expf(KQ_C_16[k*ntiles/2 + t].x[l] - KQ_max_new[KQ_index]); - - KQ_rowsum_add[KQ_index] += KQ_C_16[k*ntiles/2 + t].x[l]; + for (int l = 0; l < T_C_KQ::ne; ++l) { + // Turing + Volta: + if (!oob_check || k0 + (threadIdx.y % np)*T_C_KQ::J + T_C_KQ::get_j(l) < k_VKQ_sup) { + KQ_C[(k0/(np*T_C_KQ::J))].x[l] = expf(KQ_C[(k0/(np*T_C_KQ::J))].x[l] - KQ_max_new[(l/2) % 2]); + KQ_rowsum_add[(l/2) % 2] += KQ_C[(k0/(np*T_C_KQ::J))].x[l]; + } else { + KQ_C[(k0/(np*T_C_KQ::J))].x[l] = 0.0f; } } } @@ -662,12 +637,13 @@ static __device__ __forceinline__ void flash_attn_ext_f16_iter( KQ_rowsum[col] = KQ_max_scale[col]*KQ_rowsum[col] + KQ_rowsum_add[col]; } - if (ntiles == 1) { +#if defined(TURING_MMA_AVAILABLE) + if constexpr (cols_per_warp == 8) { const half2 KQ_max_scale_h2 = make_half2(KQ_max_scale[0], KQ_max_scale[1]); #pragma unroll - for (int i = 0; i < DV/tile_C_VKQ::I; ++i) { + for (int i = 0; i < DV/T_C_VKQ::I; ++i) { #pragma unroll - for (int l = 0; l < tile_C_VKQ::ne; ++l) { + for (int l = 0; l < T_C_VKQ::ne; ++l) { VKQ_C[i].x[l] *= KQ_max_scale_h2; } } @@ -676,46 +652,53 @@ static __device__ __forceinline__ void flash_attn_ext_f16_iter( for (int col = 0; col < cols_per_thread; ++col) { const half2 KQ_max_scale_h2 = make_half2(KQ_max_scale[col], KQ_max_scale[col]); #pragma unroll - for (int i = 0; i < DV/tile_C_VKQ_16::J; ++i) { + for (int i = 0; i < (DV/2)/T_C_VKQ::J; ++i) { #pragma unroll - for (int l0 = 0; l0 < tile_C_VKQ_16::ne; l0 += 2) { - VKQ_C_16[i*ntiles/2 + col/2].x[l0 + col % 2] *= KQ_max_scale_h2; + for (int l0 = 0; l0 < T_C_VKQ::ne; l0 += 2) { + VKQ_C[i].x[l0 + col] *= KQ_max_scale_h2; } } } } +#else // Volta + const half2 KQ_max_scale_h2 = make_half2( + KQ_max_scale[(threadIdx.x / 2) % 2], KQ_max_scale[(threadIdx.x / 2) % 2]); +#pragma unroll + for (int i = 0; i < (DV/2)/T_C_VKQ::J; ++i) { +#pragma unroll + for (int l = 0; l < T_C_VKQ::ne; ++l) { + VKQ_C[i].x[l] *= KQ_max_scale_h2; + } + } +#endif // defined(TURING_MMA_AVAILABLE) } // Convert KQ C tiles into B tiles for VKQ calculation: - tile_B B[c::nbatch_fa/(np*2*tile_B::J) * ntiles]; - tile_B_16 * B_16 = (tile_B_16 *) B; - static_assert(c::nbatch_fa % (np*2*tile_B::J) == 0, "bad loop size"); - if (ntiles == 1) { + T_B_VKQ B[nbatch_fa/(np*2*T_B_VKQ::J)]; + static_assert(nbatch_fa % (np*2*T_B_VKQ::J) == 0, "bad loop size"); + if constexpr (cols_per_warp == 8) { #pragma unroll - for (int k = 0; k < c::nbatch_fa/(np*2*tile_B::J); ++k) { + for (int k = 0; k < nbatch_fa/(np*2*T_B_VKQ::J); ++k) { B[k] = get_transposed(get_half2(KQ_C[k])); } } else { - for (int k = 0; k < c::nbatch_fa/(np*2*tile_B_16::J); ++k) { -#pragma unroll - for (int t = 0; t < ntiles/2; ++t) { - B_16[k*ntiles/2 + t] = get_half2(KQ_C_16[k*ntiles/2 + t]); - } + for (int k = 0; k < nbatch_fa/(np*2*T_B_VKQ::J); ++k) { + B[k] = get_half2(KQ_C[k]); } } - if (nstages > 1) { + if constexpr (nstages > 1) { // Preload K tile for next iteration: constexpr bool use_cp_async = true; cp_async_wait_all(); __syncthreads(); if (!last_iter) { - if (ncols2 > 1 || mask_h2) { - flash_attn_ext_f16_load_mask - (mask_h2 + (k_VKQ_0 + c::nbatch_fa)/2, tile_mask, stride_mask); + if (ncols2 > 1 || mask_h) { + flash_attn_ext_f16_load_mask + (mask_h + k_VKQ_0 + nbatch_fa, tile_mask, stride_mask, k_VKQ_sup, jt*ncols1, ne01); } - flash_attn_ext_f16_load_tile - (K_h2 + int64_t(k_VKQ_0 + c::nbatch_fa)*stride_K, tile_K, nbatch_K2, stride_K); + flash_attn_ext_f16_load_tile + (K_h2 + int64_t(k_VKQ_0 + nbatch_fa)*stride_K, tile_K, nbatch_K2, stride_K, k_VKQ_sup); } } @@ -724,72 +707,119 @@ static __device__ __forceinline__ void flash_attn_ext_f16_iter( // Therefore, iterate over V in reverse and re-use the data if possible. static_assert(!mla || nstages <= 1, "combination of MLA and multi-stage loading not implemented"); constexpr int reusable_cutoff = mla ? (DKQ - 1) - (DKQ - 1) % (2*nbatch_K2) - (DKQ - DV) : DV; + + // Calculate VKQ tile, need to use logical rather than physical elements for i0 due to transposition of V: #pragma unroll for (int i0_stop = DV; i0_stop > 0; i0_stop -= 2*nbatch_V2) { const int i0_start = i0_stop - 2*nbatch_V2 > 0 ? i0_stop - 2*nbatch_V2 : 0; const int i0_diff = i0_stop - i0_start; - if (nstages <= 1 && i0_start < reusable_cutoff) { - constexpr bool use_cp_async = nstages == 1; - flash_attn_ext_f16_load_tile - (V_h2 + int64_t(k_VKQ_0)*stride_V + i0_start/2, tile_V, i0_diff/2, stride_V); - if (use_cp_async) { - cp_async_wait_all(); + if constexpr (nstages <= 1) { + if (i0_start < reusable_cutoff) { + constexpr bool use_cp_async = nstages == 1; + flash_attn_ext_f16_load_tile + (V_h2 + int64_t(k_VKQ_0)*stride_V + i0_start/2, tile_V, i0_diff/2, stride_V, k_VKQ_sup); + if (use_cp_async) { + cp_async_wait_all(); + } + __syncthreads(); } - __syncthreads(); } const half2 * tile_V_i = i0_start < reusable_cutoff ? tile_V : tile_V + (i0_start - reusable_cutoff)/2; - // Calculate VKQ tile: +#if defined(TURING_MMA_AVAILABLE) + constexpr int i0_stride = cols_per_warp == 8 ? T_C_VKQ::I : 2*T_C_VKQ::J; #pragma unroll - for (int i_VKQ_0 = i0_start; i_VKQ_0 < i0_stop; i_VKQ_0 += tile_C_VKQ::I) { - static_assert((c::nbatch_fa/2) % (np*tile_A::J) == 0, "bad loop size"); + for (int i_VKQ_0 = i0_start; i_VKQ_0 < i0_stop; i_VKQ_0 += i0_stride) { + static_assert((nbatch_fa/2) % (np*T_A_VKQ::J) == 0, "bad loop size"); #pragma unroll - for (int k00 = 0; k00 < c::nbatch_fa/2; k00 += np*tile_A::J) { - const int k0 = k00 + (threadIdx.y % np)*tile_A::J; + for (int k00 = 0; k00 < nbatch_fa/2; k00 += np*T_A_VKQ::J) { + const int k0 = k00 + (threadIdx.y % np)*T_A_VKQ::J; - tile_A A; + T_A_VKQ A; // Transposed in SRAM but not in registers, gets transposed on load. load_ldmatrix_trans(A, tile_V_i + 2*k0*stride_tile_V + (i_VKQ_0 - i0_start)/2, stride_tile_V); - if (ntiles == 1) { - mma(VKQ_C[i_VKQ_0/tile_C_VKQ::I], A, B[k00/(np*tile_A::J)]); + if constexpr (T_B_KQ::I == 8) { + mma(VKQ_C[i_VKQ_0/i0_stride], A, B[k00/(np*T_A_VKQ::J)]); } else { -#pragma unroll - for (int t = 0; t < ntiles/2; ++t) { - // Wide version of VKQ_C is column-major => swap A and B. - mma(VKQ_C_16[i_VKQ_0/tile_C_VKQ::I * ntiles/2 + t], B_16[k00/(np*tile_A::J) * ntiles/2 + t], A); - } + // Wide version of VKQ_C is column-major => swap A and B. + mma(VKQ_C[i_VKQ_0/i0_stride], B[k00/(np*T_A_VKQ::J)], A); } } } +#else // Volta + constexpr int i0_stride = 2*T_C_VKQ::J; +#pragma unroll + for (int i_VKQ_0 = i0_start; i_VKQ_0 < i0_stop; i_VKQ_0 += i0_stride) { + static_assert(nbatch_fa % (np*T_A_VKQ::I) == 0, "bad loop size"); + static_assert(2*T_B_VKQ::J == T_A_VKQ::I, "bad tile sizes"); +#pragma unroll + for (int k00 = 0; k00 < nbatch_fa; k00 += np*T_A_VKQ::I) { + const int k0 = k00 + (threadIdx.y % np)*T_A_VKQ::I; - if (nstages <= 1) { + T_A_VKQ A; // Transposed in both SRAM and registers, load normally. + load_ldmatrix(A, tile_V_i + k0*stride_tile_V + (i_VKQ_0 - i0_start)/2, stride_tile_V); + mma(VKQ_C[i_VKQ_0/i0_stride], B[k00/(np*T_A_VKQ::I)], A); + } + } +#endif // defined(TURING_MMA_AVAILABLE) + + if constexpr (nstages <= 1) { __syncthreads(); // Only needed if tile_K == tile_V. } } #else - GGML_UNUSED_VARS(Q_f2, K_h2, V_h2, mask_h2, dstk, dstk_fixup, + GGML_UNUSED_VARS(Q_f2, K_h2, V_h2, mask_h, dstk, dstk_fixup, scale, slope, logit_softcap, ne01, ne02, stride_K, stride_V, stride_mask, tile_Q, tile_K, tile_V, tile_mask, Q_B, VKQ_C, KQ_max, KQ_rowsum, kb0); NO_DEVICE_CODE; -#endif // TURING_MMA_AVAILABLE +#endif // defined(VOLTA_MMA_AVAILABLE) || defined(TURING_MMA_AVAILABLE) } -template +#if defined(TURING_MMA_AVAILABLE) +template struct mma_tile_sizes { + using T_A_KQ = tile<16, 8, half2>; // row-major + using T_B_KQ = tile<16, 8, half2>; // column-major + using T_C_KQ = tile<16, 16, float>; // column-major + using T_A_VKQ = tile<16, 8, half2>; // row-major + using T_B_VKQ = tile<16, 8, half2>; // column-major + using T_C_VKQ = tile<16, 8, half2>; // column-major +}; +template<> struct mma_tile_sizes<8> { + using T_A_KQ = tile<16, 8, half2>; // row-major + using T_B_KQ = tile< 8, 8, half2>; // column-major + using T_C_KQ = tile<16, 8, float>; // row-major + using T_A_VKQ = tile<16, 8, half2>; // row-major + using T_B_VKQ = tile< 8, 8, half2>; // column-major + using T_C_VKQ = tile<16, 4, half2>; // row-major +}; +#else // Volta +template struct mma_tile_sizes { + using T_A_KQ = tile< 8, 4, half2, DATA_LAYOUT_I_MAJOR_MIRRORED>; // row-major + using T_B_KQ = tile<32, 4, half2, DATA_LAYOUT_I_MAJOR>; // column-major + using T_C_KQ = tile<32, 8, float, DATA_LAYOUT_I_MAJOR>; // column-major + using T_A_VKQ = tile< 8, 4, half2, DATA_LAYOUT_J_MAJOR_MIRRORED>; // column-major + using T_B_VKQ = tile<32, 4, half2, DATA_LAYOUT_I_MAJOR>; // column-major + using T_C_VKQ = tile<32, 4, half2, DATA_LAYOUT_I_MAJOR>; // column-major +}; +#endif // defined(TURING_MMA_AVAILABLE) + +template static __device__ __forceinline__ void flash_attn_ext_f16_process_tile( const float2 * const __restrict__ Q_f2, const half2 * const __restrict__ K_h2, const half2 * const __restrict__ V_h2, - const half2 * const __restrict__ mask_h2, + const half * const __restrict__ mask_h, const float * const __restrict__ sinks_f, float2 * const __restrict__ dstk, float2 * const __restrict__ dstk_fixup, const float scale, const float slope, const float logit_softcap, - const int ne01, + const uint3 ne01, const int ne02, + const int ne11, const int stride_Q1, const int stride_Q2, const int stride_K, @@ -798,23 +828,31 @@ static __device__ __forceinline__ void flash_attn_ext_f16_process_tile( const int jt, const int kb0_start, const int kb0_stop) { -#ifdef TURING_MMA_AVAILABLE +#if defined(VOLTA_MMA_AVAILABLE) || defined(TURING_MMA_AVAILABLE) //In this kernel Q, K, V are matrices while i, j, k are matrix indices. - typedef fattn_mma_f16_config c; + constexpr int ncols = ncols1 * ncols2; + using T_A_KQ = typename mma_tile_sizes::T_A_KQ; + using T_B_KQ = typename mma_tile_sizes::T_B_KQ; + using T_C_KQ = typename mma_tile_sizes::T_C_KQ; + using T_A_VKQ = typename mma_tile_sizes::T_A_VKQ; + using T_B_VKQ = typename mma_tile_sizes::T_B_VKQ; + using T_C_VKQ = typename mma_tile_sizes::T_C_VKQ; -#ifdef CP_ASYNC_AVAILABLE - constexpr int nstages = c::nstages_target; -#else - constexpr int nstages = 0; -#endif // CP_ASYNC_AVAILABLE + constexpr int cols_per_warp = T_B_KQ::I; + constexpr int cols_per_thread = 2; // This is specifically KQ columns, Volta only has a single VKQ column. + constexpr int np = nwarps * (cols_per_warp/ncols2) / ncols1; // Number of parallel CUDA warps per Q column. + constexpr int nbatch_fa = ggml_cuda_fattn_mma_get_nbatch_fa (DKQ, DV, ncols); + constexpr int nbatch_K2 = ggml_cuda_fattn_mma_get_nbatch_K2 (DKQ, DV, ncols); + constexpr int nbatch_V2 = ggml_cuda_fattn_mma_get_nbatch_V2 (DKQ, DV, ncols); + constexpr int nbatch_combine = ggml_cuda_fattn_mma_get_nbatch_combine(DKQ, DV, ncols); + constexpr bool Q_in_reg = ggml_cuda_fattn_mma_get_Q_in_reg (DKQ, DV, ncols); + constexpr int nstages = ggml_cuda_fattn_mma_get_nstages (DKQ, DV, ncols1, ncols2); - constexpr int ncols = ncols1 * ncols2; - constexpr int cols_per_warp = ntiles * tile_B::I; - constexpr int cols_per_thread = ntiles == 1 ? 2 : ntiles; - constexpr int np = nwarps * (cols_per_warp/ncols2) / ncols1; // Number of parallel CUDA warps per Q column. - constexpr int nbatch_K2 = c::get_nbatch_K2_device(ncols); - constexpr int nbatch_V2 = c::get_nbatch_V2_device(ncols); + if (cols_per_warp > ncols) { + NO_DEVICE_CODE; + return; + } static_assert(nwarps * (cols_per_warp/ncols2) % ncols1 == 0, "bad nwarps"); @@ -826,15 +864,16 @@ static __device__ __forceinline__ void flash_attn_ext_f16_process_tile( constexpr int stride_tile_KV_max = stride_tile_K > stride_tile_V ? stride_tile_K : stride_tile_V; extern __shared__ half2 tile_Q[]; - half2 * tile_K = c::Q_in_reg ? tile_Q : tile_Q + ncols * stride_tile_Q; - half2 * tile_V = nstages > 1 ? tile_K + c::nbatch_fa * stride_tile_K : tile_K; - half2 * tile_mask = nstages > 1 ? tile_V + c::nbatch_fa * stride_tile_V : tile_V + c::nbatch_fa * stride_tile_KV_max; + half2 * tile_K = Q_in_reg ? tile_Q : tile_Q + ncols * stride_tile_Q; + half2 * tile_V = nstages > 1 ? tile_K + nbatch_fa * stride_tile_K : tile_K; + half * tile_mask = (half *) (nstages > 1 ? tile_V + nbatch_fa * stride_tile_V : tile_V + nbatch_fa * stride_tile_KV_max); - tile_B Q_B[(c::Q_in_reg ? DKQ/(2*tile_B::J) : 1) * ntiles]; - tile_C_VKQ VKQ_C[DV/tile_C_VKQ::I * ntiles]; - - tile_B_16 * Q_B_16 = (tile_B_16 *) Q_B; - tile_C_VKQ_16 * VKQ_C_16 = (tile_C_VKQ_16 *) VKQ_C; + T_B_KQ Q_B[(Q_in_reg ? DKQ/(2*T_B_KQ::J) : 1)]; +#if defined(TURING_MMA_AVAILABLE) + T_C_VKQ VKQ_C[cols_per_warp == 8 ? DV/T_C_VKQ::I : DV/(2*T_C_VKQ::J)]; +#else // Volta + T_C_VKQ VKQ_C[ DV/(2*T_C_VKQ::J)]; +#endif // defined(TURING_MMA_AVAILABLE) float KQ_rowsum[cols_per_thread] = {0.0f}; float KQ_max[cols_per_thread]; @@ -868,7 +907,7 @@ static __device__ __forceinline__ void flash_attn_ext_f16_process_tile( const int j = jc / ncols2; const int c = jc % ncols2; - if (jt*ncols1 + j < ne01) { + if (jt*ncols1 + j < int(ne01.z)) { #pragma unroll for (int k0 = k0_start; k0 < k0_stop; k0 += stride_k) { const int k = k0 + (stride_k == WARP_SIZE ? threadIdx.x : threadIdx.x % stride_k); @@ -889,63 +928,96 @@ static __device__ __forceinline__ void flash_attn_ext_f16_process_tile( __syncthreads(); - if (c::Q_in_reg) { + if (Q_in_reg) { const int j0 = (threadIdx.y / np) * cols_per_warp; #pragma unroll - for (int k0 = 0; k0 < DKQ/2; k0 += tile_B::J) { - if (ntiles == 1) { - load_ldmatrix(Q_B[k0/tile_B::J], tile_Q + j0*stride_tile_Q + k0, stride_tile_Q); - } else { -#pragma unroll - for (int t = 0; t < ntiles/2; ++t) { - load_ldmatrix(Q_B_16[k0/tile_B_16::J * ntiles/2 + t], - tile_Q + (j0 + t*tile_B_16::I)*stride_tile_Q + k0, stride_tile_Q); - } - } + for (int k0 = 0; k0 < DKQ/2; k0 += T_B_KQ::J) { + load_ldmatrix(Q_B[k0/T_B_KQ::J], tile_Q + j0*stride_tile_Q + k0, stride_tile_Q); } } __syncthreads(); + int kb0 = kb0_start; + // Preload mask and K data for first iteration when using cp_async with multiple stages: if constexpr (nstages > 1) { static_assert(nbatch_K2 == DKQ/2, "batching not implemented for multi-stage pipeline"); constexpr bool use_cp_async = true; - if (ncols2 > 1 || mask_h2) { - flash_attn_ext_f16_load_mask - (mask_h2 + kb0_start*c::nbatch_fa/2, tile_mask, stride_mask); + constexpr bool oob_check = false; + constexpr int k_VKQ_sup = nbatch_fa; + if (ncols2 > 1 || mask_h) { + flash_attn_ext_f16_load_mask + (mask_h + kb0*nbatch_fa, tile_mask, stride_mask, k_VKQ_sup, jt*ncols1, ne01); } - flash_attn_ext_f16_load_tile - (K_h2 + int64_t(kb0_start)*c::nbatch_fa*stride_K, tile_K, nbatch_K2, stride_K); + flash_attn_ext_f16_load_tile + (K_h2 + int64_t(kb0)*nbatch_fa*stride_K, tile_K, nbatch_K2, stride_K, k_VKQ_sup); } - // Iterate over ne11 == previous tokens: - int kb0 = kb0_start; for (; kb0 < kb0_stop-1; ++kb0) { constexpr bool last_iter = false; - flash_attn_ext_f16_iter - (Q_f2, K_h2, V_h2, mask_h2, dstk, dstk_fixup, scale, slope, logit_softcap, - ne01, ne02, stride_K, stride_V, stride_mask, tile_Q, tile_K, tile_V, tile_mask, Q_B, VKQ_C, KQ_max, KQ_rowsum, kb0); + constexpr bool oob_check = false; + constexpr int k_VKQ_sup = nbatch_fa; + flash_attn_ext_f16_iter + + (Q_f2, K_h2, V_h2, mask_h, dstk, dstk_fixup, scale, slope, logit_softcap, + ne01, ne02, stride_K, stride_V, stride_mask, tile_Q, tile_K, tile_V, tile_mask, Q_B, VKQ_C, + KQ_max, KQ_rowsum, jt, kb0, k_VKQ_sup); } - { // kb0_start is always < kb0_stop so the last iter can be executed unconditionally. + // kb0_start is always < kb0_stop so the last iter can be executed unconditionally. + if constexpr (ncols2 == 1) { + if (ne11 % nbatch_fa == 0) { + constexpr bool last_iter = true; + constexpr bool oob_check = false; + constexpr int k_VKQ_sup = nbatch_fa; + flash_attn_ext_f16_iter + + (Q_f2, K_h2, V_h2, mask_h, dstk, dstk_fixup, scale, slope, logit_softcap, + ne01, ne02, stride_K, stride_V, stride_mask, tile_Q, tile_K, tile_V, tile_mask, Q_B, VKQ_C, + KQ_max, KQ_rowsum, jt, kb0, k_VKQ_sup); + } else { + constexpr bool last_iter = true; + constexpr bool oob_check = true; + const int k_VKQ_sup = ne11 - kb0*nbatch_fa; + flash_attn_ext_f16_iter + + (Q_f2, K_h2, V_h2, mask_h, dstk, dstk_fixup, scale, slope, logit_softcap, + ne01, ne02, stride_K, stride_V, stride_mask, tile_Q, tile_K, tile_V, tile_mask, Q_B, VKQ_C, + KQ_max, KQ_rowsum, jt, kb0, k_VKQ_sup); + } + } else { constexpr bool last_iter = true; - flash_attn_ext_f16_iter - (Q_f2, K_h2, V_h2, mask_h2, dstk, dstk_fixup, scale, slope, logit_softcap, - ne01, ne02, stride_K, stride_V, stride_mask, tile_Q, tile_K, tile_V, tile_mask, Q_B, VKQ_C, KQ_max, KQ_rowsum, kb0); + constexpr bool oob_check = false; + constexpr int k_VKQ_sup = nbatch_fa; + flash_attn_ext_f16_iter + + (Q_f2, K_h2, V_h2, mask_h, dstk, dstk_fixup, scale, slope, logit_softcap, + ne01, ne02, stride_K, stride_V, stride_mask, tile_Q, tile_K, tile_V, tile_mask, Q_B, VKQ_C, + KQ_max, KQ_rowsum, jt, kb0, k_VKQ_sup); } // With multi-stage loading there is no __syncthreads at the end of the iter, // there can be a race condition on shared memory access for combining/writing back results. - if (nstages > 1 && nwarps*cols_per_warp > c::nbatch_fa) { + if constexpr (nstages > 1 && nwarps*cols_per_warp > nbatch_fa) { __syncthreads(); } // Finally, sum up partial KQ rowsums. - // The partial sums are spread across 8/4 threads each, does not need full reduce. { - constexpr int offset_first = ntiles == 1 ? 16 : 2; - constexpr int offset_last = ntiles == 1 ? 4 : 1; +#if defined(TURING_MMA_AVAILABLE) + // The partial sums are spread across 8/4 threads. + constexpr int offset_first = cols_per_warp == 8 ? 16 : 2; + constexpr int offset_last = cols_per_warp == 8 ? 4 : 1; +#else // Volta + // The partial sums are spread across 2 threads. + constexpr int offset_first = 2; + constexpr int offset_last = 2; +#endif // defined(TURING_MMA_AVAILABLE) #pragma unroll for (int col = 0; col < cols_per_thread; ++col) { #pragma unroll @@ -962,8 +1034,7 @@ static __device__ __forceinline__ void flash_attn_ext_f16_process_tile( float KQ_max_scale[cols_per_thread]; #pragma unroll for (int col = 0; col < cols_per_thread; ++col) { - static_assert(ntiles == 1 || ntiles == 2, "ntiles > 2 not implemented"); - const int jc = ntiles == 1 ? 2*tile_C_VKQ::get_j(col/2) + col % 2 : tile_C_VKQ_16::get_i(col); + const int jc = cols_per_warp == 8 ? T_C_KQ::get_j(col) : T_C_KQ::get_i(2*col); const float sink = sinks_f[jc % ncols2]; const float KQ_max_new = fmaxf(KQ_max[col], sink); @@ -977,12 +1048,13 @@ static __device__ __forceinline__ void flash_attn_ext_f16_process_tile( KQ_rowsum[col] = KQ_max_scale[col]*KQ_rowsum[col] + KQ_max_add; } - if (ntiles == 1) { +#if defined(TURING_MMA_AVAILABLE) + if constexpr (cols_per_warp == 8) { const half2 KQ_max_scale_h2 = make_half2(KQ_max_scale[0], KQ_max_scale[1]); #pragma unroll - for (int i = 0; i < DV/tile_C_VKQ::I; ++i) { + for (int i = 0; i < DV/T_C_VKQ::I; ++i) { #pragma unroll - for (int l = 0; l < tile_C_VKQ::ne; ++l) { + for (int l = 0; l < T_C_VKQ::ne; ++l) { VKQ_C[i].x[l] *= KQ_max_scale_h2; } } @@ -991,30 +1063,40 @@ static __device__ __forceinline__ void flash_attn_ext_f16_process_tile( for (int col = 0; col < cols_per_thread; ++col) { const half2 KQ_max_scale_h2 = make_half2(KQ_max_scale[col], KQ_max_scale[col]); #pragma unroll - for (int i = 0; i < DV/tile_C_VKQ_16::J; ++i) { + for (int i = 0; i < (DV/2)/T_C_VKQ::J; ++i) { #pragma unroll - for (int l0 = 0; l0 < tile_C_VKQ_16::ne; l0 += 2) { - VKQ_C_16[i*ntiles/2 + col/2].x[l0 + col % 2] *= KQ_max_scale_h2; + for (int l0 = 0; l0 < T_C_VKQ::ne; l0 += 2) { + VKQ_C[i].x[l0 + col] *= KQ_max_scale_h2; } } } } +#else // Volta + const int col = (threadIdx.x / 2) % 2; + const half2 KQ_max_scale_h2 = make_half2(KQ_max_scale[col], KQ_max_scale[col]); +#pragma unroll + for (int i = 0; i < (DV/2)/T_C_VKQ::J; ++i) { +#pragma unroll + for (int l = 0; l < T_C_VKQ::ne; ++l) { + VKQ_C[i].x[l] *= KQ_max_scale_h2; + } + } +#endif // defined(TURING_MMA_AVAILABLE) } // Combine VKQ accumulator values if np > 1. // It's also faster to do small writes to shared memory, then large write to VRAM than to do small writes to VRAM. // So also write VKQ accumulators to shared memory in column-major format if np == 1. - constexpr int nbatch_combine = c::get_nbatch_combine_device(ncols); - constexpr int tile_stride = nbatch_combine + 4; + constexpr int tile_stride = nbatch_combine + 4; static_assert((DV/2) % nbatch_combine == 0, "bad nbatch_combine"); - if constexpr (ntiles == 1) { - const int jc_cwmo = (threadIdx.x % (2*tile_C_VKQ::J)) / tile_C_VKQ::J; // jc combine write meta offset - const int jc_cwm = threadIdx.y*(2*tile_C_VKQ::J) + 2*tile_C_VKQ::get_j(-1) + jc_cwmo; // jc combine write meta + if constexpr (cols_per_warp == 8) { + const int jc_cwmo = (threadIdx.x % (2*T_C_VKQ::J)) / T_C_VKQ::J; // jc combine write meta offset + const int jc_cwm = threadIdx.y*(2*T_C_VKQ::J) + 2*T_C_VKQ::get_j(-1) + jc_cwmo; // jc combine write meta const float2 KQ_cmr = make_float2(KQ_max[jc_cwmo], KQ_rowsum[jc_cwmo]); // KQ combine max rowsum - if (((!needs_fixup && !is_fixup) || np > 1) && threadIdx.x < 2*tile_C_VKQ::J) { + if (((!needs_fixup && !is_fixup) || np > 1) && threadIdx.x < 2*T_C_VKQ::J) { // Use the 16 bytes of padding in each row to store the meta data: KQ max, KQ rowsum, KQ max scale. ((float2 *) tile_Q)[jc_cwm*(tile_stride/2) + nbatch_combine/2] = KQ_cmr; } @@ -1023,24 +1105,30 @@ static __device__ __forceinline__ void flash_attn_ext_f16_process_tile( if (np == 1) { // No combination is needed, the meta data can be directly written from registers to VRAM. - if (needs_fixup && threadIdx.x < tile_B::I) { + if (needs_fixup && threadIdx.x < T_B_KQ::I) { float2 * dstk_fixup_meta = dstk_fixup + blockIdx.x*ncols; dstk_fixup_meta[jc_cwm] = KQ_cmr; } - if (is_fixup && threadIdx.x < tile_B::I) { + if (is_fixup && threadIdx.x < T_B_KQ::I) { float2 * dstk_fixup_meta = dstk_fixup + (gridDim.x + blockIdx.x)*ncols; dstk_fixup_meta[jc_cwm] = KQ_cmr; } } } else { - static_assert(ntiles == 2 || ntiles == 4, "bad ntiles"); - const int jc_cwm = threadIdx.y*cols_per_warp // jc combine write meta - + (ntiles == 4 ? ((threadIdx.x % 4) / 2) * tile_C_VKQ_16::I : 0) - + tile_C_VKQ_16::get_i(threadIdx.x % 4); - const float2 KQ_cmr = make_float2(KQ_max[threadIdx.x % cols_per_thread], KQ_rowsum[threadIdx.x % cols_per_thread]); // KQ combine max rowsum + // jc_cwm = jc combine write meta + // KQ_cmr = KQ combine max rowsum + // Use the 16 bytes of padding in each Q column to store the meta data: KQ max, KQ rowsum, KQ max scale. +#if defined(TURING_MMA_AVAILABLE) + const int jc_cwm = threadIdx.y*cols_per_warp + T_C_VKQ::get_i(threadIdx.x % 4); + const float2 KQ_cmr = make_float2(KQ_max[threadIdx.x % cols_per_thread], KQ_rowsum[threadIdx.x % cols_per_thread]); + const bool thread_should_write = threadIdx.x % 4 < cols_per_thread; +#else // Volta + const int jc_cwm = threadIdx.y*cols_per_warp + T_C_KQ::get_i(threadIdx.x & 2); + const float2 KQ_cmr = make_float2(KQ_max[(threadIdx.x & 2) / 2], KQ_rowsum[(threadIdx.x & 2) / 2]); + const bool thread_should_write = T_C_KQ::J == 8 || T_C_KQ::get_j(threadIdx.x & 2) < 8; +#endif // defined(TURING_MMA_AVAILABLE) - if (((!needs_fixup && !is_fixup) || np > 1) && (ntiles == 4 || threadIdx.x % 4 < cols_per_thread)) { - // Use the 16 bytes of padding in each row to store the meta data: KQ max, KQ rowsum, KQ max scale. + if (((!needs_fixup && !is_fixup) || np > 1) && thread_should_write) { ((float2 *) tile_Q)[jc_cwm*(tile_stride/2) + nbatch_combine/2] = KQ_cmr; } @@ -1048,18 +1136,17 @@ static __device__ __forceinline__ void flash_attn_ext_f16_process_tile( if (np == 1) { // No combination is needed, the meta data can be directly written from registers to VRAM. - if (needs_fixup && (ntiles == 4 || threadIdx.x % 4 < ntiles)) { + if (needs_fixup && thread_should_write) { float2 * dstk_fixup_meta = dstk_fixup + blockIdx.x*ncols; dstk_fixup_meta[jc_cwm] = KQ_cmr; } - if (is_fixup && (ntiles == 4 || threadIdx.x % 4 < ntiles)) { + if (is_fixup && thread_should_write) { float2 * dstk_fixup_meta = dstk_fixup + (gridDim.x + blockIdx.x)*ncols; dstk_fixup_meta[jc_cwm] = KQ_cmr; } } } - static_assert(np == 1 || ntiles == 1 || ntiles == 2, "bad ntiles"); if (np > 1 && threadIdx.y % np == 0) { // Combine the meta data for parallel warps via shared memory. // Warps with threadIdx.y % np != 0 must NOT return early. @@ -1135,32 +1222,29 @@ static __device__ __forceinline__ void flash_attn_ext_f16_process_tile( #pragma unroll for (int k00 = 0; k00 < DV/2; k00 += nbatch_combine) { - if (ntiles == 1) { - const int jc_cwd = threadIdx.y*tile_B::I + tile_B::get_i(-1); // jc combine write data + if constexpr (cols_per_warp == 8) { + const int jc_cwd = threadIdx.y*T_B_KQ::I + T_B_KQ::get_i(-1); // jc combine write data #pragma unroll - for (int k0 = 0; k0 < nbatch_combine; k0 += tile_B::J) { - const tile_B B = get_transposed(VKQ_C[(k00 + k0)/tile_B::J]); // Conversion of C to B matrix puts it in column-major format. + for (int k1 = 0; k1 < nbatch_combine; k1 += T_B_KQ::J) { + const T_B_KQ B = get_transposed(VKQ_C[(k00 + k1)/T_B_KQ::J]); // Conversion of C to B matrix puts it in column-major format. #pragma unroll - for (int l = 0; l < tile_B::ne; ++l) { - const int k = k0 + tile_B::get_j(l); + for (int l = 0; l < T_B_KQ::ne; ++l) { + const int k = k1 + T_B_KQ::get_j(l); tile_Q[jc_cwd*tile_stride + k] = B.x[l]; } } } else { + const int j0 = threadIdx.y*cols_per_warp; #pragma unroll - for (int t = 0; t < ntiles/2; ++t) { - const int j0 = threadIdx.y*cols_per_warp + t*tile_C_VKQ_16::I; + for (int k1 = 0; k1 < nbatch_combine; k1 += T_C_VKQ::J) { #pragma unroll - for (int k0 = 0; k0 < nbatch_combine; k0 += tile_C_VKQ_16::J) { -#pragma unroll - for (int l = 0; l < tile_C_VKQ_16::ne; ++l) { - const int j = j0 + tile_C_VKQ_16::get_i(l); - const int k = k0 + tile_C_VKQ_16::get_j(l); + for (int l = 0; l < T_C_VKQ::ne; ++l) { + const int j = j0 + T_C_VKQ::get_i(l); + const int k = k1 + T_C_VKQ::get_j(l); - tile_Q[j*tile_stride + k] = VKQ_C_16[(k00 + k0)/tile_C_VKQ_16::J * ntiles/2 + t].x[l]; - } + tile_Q[j*tile_stride + k] = VKQ_C[(k00 + k1)/T_C_VKQ::J].x[l]; } } } @@ -1195,7 +1279,7 @@ static __device__ __forceinline__ void flash_attn_ext_f16_process_tile( const int j_dst = jc_dst / ncols2; const int c_dst = jc_dst % ncols2; - if (!is_fixup && jt*ncols1 + j_dst >= ne01) { + if (!is_fixup && jt*ncols1 + j_dst >= int(ne01.z)) { continue; } @@ -1233,16 +1317,16 @@ static __device__ __forceinline__ void flash_attn_ext_f16_process_tile( } } #else - GGML_UNUSED_VARS(Q_f2, K_h2, V_h2, mask_h2, sinks_f, dstk, dstk_fixup, + GGML_UNUSED_VARS(Q_f2, K_h2, V_h2, mask_h, sinks_f, dstk, dstk_fixup, scale, slope, logit_softcap, ne01, ne02, stride_Q1, stride_Q2, stride_K, stride_V, stride_mask, jt, kb0_start, kb0_stop); NO_DEVICE_CODE; -#endif // TURING_MMA_AVAILABLE +#endif // defined(VOLTA_MMA_AVAILABLE) || defined(TURING_MMA_AVAILABLE) } -template -__launch_bounds__(nwarps*WARP_SIZE, 1) +template +__launch_bounds__(ggml_cuda_fattn_mma_get_nthreads(DKQ, DV, ncols1*ncols2), ggml_cuda_fattn_mma_get_occupancy(DKQ, DV, ncols1*ncols2)) static __global__ void flash_attn_ext_f16( const char * __restrict__ Q, const char * __restrict__ K, @@ -1258,14 +1342,14 @@ static __global__ void flash_attn_ext_f16( const float m1, const uint32_t n_head_log2, const float logit_softcap, - const int32_t ne00, const int32_t ne01, const int32_t ne02, const int32_t ne03, + const int32_t ne00, const uint3 ne01, const int32_t ne02, const int32_t ne03, const int32_t nb01, const int32_t nb02, const int32_t nb03, const int32_t ne10, const int32_t ne11, const int32_t ne12, const int32_t ne13, const int32_t nb11, const int32_t nb12, const int64_t nb13, const int32_t nb21, const int32_t nb22, const int64_t nb23, const int32_t ne31, const int32_t ne32, const int32_t ne33, const int32_t nb31, const int32_t nb32, const int64_t nb33) { -#if defined(FLASH_ATTN_AVAILABLE) && defined(TURING_MMA_AVAILABLE) +#if defined(FLASH_ATTN_AVAILABLE) && (defined(VOLTA_MMA_AVAILABLE) || defined(TURING_MMA_AVAILABLE)) // Skip unused kernel variants for faster compilation: if (use_logit_softcap && !(DKQ == 128 || DKQ == 256)) { @@ -1281,23 +1365,22 @@ static __global__ void flash_attn_ext_f16( static_assert(!mla || DKQ >= DV, "MLA needs DKQ >= DV"); - typedef fattn_mma_f16_config c; - - static_assert(FATTN_KQ_STRIDE % fattn_mma_f16_config::nbatch_fa == 0, "bad nbatch_fa"); + constexpr int ncols = ncols1 * ncols2; + constexpr int nbatch_fa = ggml_cuda_fattn_mma_get_nbatch_fa(DKQ, DV, ncols); + constexpr int nthreads = ggml_cuda_fattn_mma_get_nthreads(DKQ, DV, ncols); + constexpr int nwarps = nthreads / WARP_SIZE; const int gqa_ratio = ne02 / ne12; // With grouped query attention there are > 1 Q matrices per K, V matrix. const int stride_Q1 = nb01 / sizeof(float2); const int stride_Q2 = nb02 / sizeof(float2); const int stride_K = nb11 / sizeof(half2); - const int stride_mask = nb31 / sizeof(half2); + const int stride_mask = nb31 / sizeof(half); const int stride_V = mla ? stride_K : nb21 / sizeof(half2); - const int iter_k = ne11 / FATTN_KQ_STRIDE; - const int iter_j = (ne01 + (ncols1 - 1)) / ncols1; - - constexpr int kb_niter = FATTN_KQ_STRIDE / c::nbatch_fa; // Number of kernel iterations per assigned KQ slice. + const int iter_k = (ne11 + (nbatch_fa - 1)) / nbatch_fa; + const int iter_j = (ne01.z + (ncols1 - 1)) / ncols1; // kbc == k block continuous, current index in continuous ijk space. int kbc = (blockIdx.x + 0)*(iter_k*iter_j*(ne02/ncols2)*ne03) / gridDim.x; @@ -1318,35 +1401,31 @@ static __global__ void flash_attn_ext_f16( const int head0 = zt * ncols2; - const float2 * Q_f2 = (const float2 *) (Q + nb03*sequence + nb02* head0); - const half2 * K_h2 = (const half2 *) (K + nb13*sequence + nb12*(head0 / gqa_ratio)); - const half2 * mask_h2 = ncols2 == 1 && !mask ? nullptr : - (const half2 *) (mask + nb33*(sequence % ne33) + nb31*jt*ncols1); - float2 * dstk = ((float2 *) dst) + (sequence*ne01*ne02 + head0) * (DV/2); + const float2 * Q_f2 = (const float2 *) (Q + nb03*sequence + nb02* head0); + const half2 * K_h2 = (const half2 *) (K + nb13*sequence + nb12*(head0 / gqa_ratio)); + const half * mask_h = ncols2 == 1 && !mask ? nullptr : + (const half *) (mask + nb33*(sequence % ne33)); + float2 * dstk = ((float2 *) dst) + (sequence*ne01.z*ne02 + head0) * (DV/2); const half2 * V_h2 = mla ? K_h2 + (DKQ/2 - DV/2) : (const half2 *) (V + nb23*sequence + nb22*(head0 / gqa_ratio)); const float * sinks_f = sinks ? (const float *) sinks + head0 : nullptr; const float slope = ncols2 == 1 ? get_alibi_slope(max_bias, head0, n_head_log2, m0, m1) : 1.0f; - const int kb0_start_kernel = kb0_start * kb_niter; - int kb0_stop_kernel = kb0_stop * kb_niter; - if (KV_max) { - kb0_stop_kernel = min(kb0_stop_kernel, KV_max[sequence*iter_j + jt] / c::nbatch_fa); + kb0_stop = min(kb0_stop, KV_max[sequence*iter_j + jt] / nbatch_fa); } - constexpr bool is_fixup = false; // All but (potentially) the last iterations write their data to dst rather than the fixup buffer. if (kb0_start == 0) { constexpr bool needs_fixup = false; // CUDA block is working on an entire tile. - flash_attn_ext_f16_process_tile - (Q_f2, K_h2, V_h2, mask_h2, sinks_f, dstk, dst_meta, scale, slope, logit_softcap, - ne01, ne02, stride_Q1, stride_Q2, stride_K, stride_V, stride_mask, jt, kb0_start_kernel, kb0_stop_kernel); + flash_attn_ext_f16_process_tile + (Q_f2, K_h2, V_h2, mask_h, sinks_f, dstk, dst_meta, scale, slope, logit_softcap, + ne01, ne02, ne11, stride_Q1, stride_Q2, stride_K, stride_V, stride_mask, jt, kb0_start, kb0_stop); } else { - constexpr bool needs_fixup = true; // CUDA block is working on the beginning of a tile. - flash_attn_ext_f16_process_tile - (Q_f2, K_h2, V_h2, mask_h2, sinks_f, dstk, dst_meta, scale, slope, logit_softcap, - ne01, ne02, stride_Q1, stride_Q2, stride_K, stride_V, stride_mask, jt, kb0_start_kernel, kb0_stop_kernel); + constexpr bool needs_fixup = true; // CUDA block is missing the beginning of a tile. + flash_attn_ext_f16_process_tile + (Q_f2, K_h2, V_h2, mask_h, sinks_f, dstk, dst_meta, scale, slope, logit_softcap, + ne01, ne02, ne11, stride_Q1, stride_Q2, stride_K, stride_V, stride_mask, jt, kb0_start, kb0_stop); } kbc += iter_k; @@ -1366,29 +1445,26 @@ static __global__ void flash_attn_ext_f16( const int head0 = zt * ncols2; - const float2 * Q_f2 = (const float2 *) (Q + nb03*sequence + nb02* head0); - const half2 * K_h2 = (const half2 *) (K + nb13*sequence + nb12*(head0 / gqa_ratio)); - const half2 * mask_h2 = ncols2 == 1 && !mask ? nullptr : - (const half2 *) (mask + nb33*(sequence % ne33) + nb31*jt*ncols1); - float2 * dstk = ((float2 *) dst) + (sequence*ne01*ne02 + head0) * (DV/2); + const float2 * Q_f2 = (const float2 *) (Q + nb03*sequence + nb02* head0); + const half2 * K_h2 = (const half2 *) (K + nb13*sequence + nb12*(head0 / gqa_ratio)); + const half * mask_h = ncols2 == 1 && !mask ? nullptr : + (const half *) (mask + nb33*(sequence % ne33)); + float2 * dstk = ((float2 *) dst) + (sequence*ne01.z*ne02 + head0) * (DV/2); const half2 * V_h2 = mla ? K_h2 + (DKQ/2 - DV/2) : (const half2 *) (V + nb23*sequence + nb22*(head0 / gqa_ratio)); const float * sinks_f = sinks ? (const float *) sinks + head0 : nullptr; const float slope = ncols2 == 1 ? get_alibi_slope(max_bias, head0, n_head_log2, m0, m1) : 1.0f; - const int kb0_start_kernel = kb0_start * kb_niter; - int kb0_stop_kernel = kb0_stop * kb_niter; - if (KV_max) { - kb0_stop_kernel = min(kb0_stop_kernel, KV_max[sequence*iter_j + jt] / c::nbatch_fa); + kb0_stop = min(kb0_stop, KV_max[sequence*iter_j + jt] / nbatch_fa); } constexpr bool is_fixup = true; // Last index writes its data to fixup buffer to avoid data races with other blocks. constexpr bool needs_fixup = false; - flash_attn_ext_f16_process_tile - (Q_f2, K_h2, V_h2, mask_h2, sinks_f, dstk, dst_meta, scale, slope, logit_softcap, - ne01, ne02, stride_Q1, stride_Q2, stride_K, stride_V, stride_mask, jt, kb0_start_kernel, kb0_stop_kernel); + flash_attn_ext_f16_process_tile + (Q_f2, K_h2, V_h2, mask_h, sinks_f, dstk, dst_meta, scale, slope, logit_softcap, + ne01, ne02, ne11, stride_Q1, stride_Q2, stride_K, stride_V, stride_mask, jt, kb0_start, kb0_stop); #else GGML_UNUSED_VARS(Q, K, V, mask, sinks, KV_max, dst, dst_meta, scale, max_bias, m0, m1, n_head_log2, logit_softcap, @@ -1400,7 +1476,7 @@ static __global__ void flash_attn_ext_f16( ne31, ne32, ne33, nb31, nb32, nb33); NO_DEVICE_CODE; -#endif // defined(FLASH_ATTN_AVAILABLE) && defined(TURING_MMA_AVAILABLE) +#endif // defined(FLASH_ATTN_AVAILABLE) && (defined(VOLTA_MMA_AVAILABLE) || defined(TURING_MMA_AVAILABLE)) } template @@ -1409,36 +1485,30 @@ void ggml_cuda_flash_attn_ext_mma_f16_case(ggml_backend_cuda_context & ctx, ggml const int id = ggml_cuda_get_device(); const int cc = ggml_cuda_info().devices[id].cc; - typedef fattn_mma_f16_config c; + constexpr int ncols = ncols1 * ncols2; - const int nstages = cp_async_available(cc) ? c::nstages_target : 0; + const int nthreads = ggml_cuda_fattn_mma_get_nthreads (DKQ, DV, ncols, cc); + const int nbatch_fa = ggml_cuda_fattn_mma_get_nbatch_fa (DKQ, DV, ncols, cc); + const int nbatch_K2 = ggml_cuda_fattn_mma_get_nbatch_K2 (DKQ, DV, ncols, cc); + const int nbatch_V2 = ggml_cuda_fattn_mma_get_nbatch_V2 (DKQ, DV, ncols, cc); + const int nbatch_combine = ggml_cuda_fattn_mma_get_nbatch_combine(DKQ, DV, ncols, cc); + const bool Q_in_reg = ggml_cuda_fattn_mma_get_Q_in_reg (DKQ, DV, ncols, cc); + const int nstages = ggml_cuda_fattn_mma_get_nstages (DKQ, DV, ncols1, ncols2, cc); - constexpr int ncols = ncols1 * ncols2; - constexpr int ntiles = ncols <= 8 ? 1 : 2; // Number of tiles per warp. - constexpr int cols_per_warp = ntiles * tile_B::I; - constexpr int nwarps_max_x = ncols / cols_per_warp; - constexpr int nwarps_max_y = c::nbatch_fa / tile_A::I; - constexpr int nwarps = nwarps_max_x*nwarps_max_y <= c::nwarps_max ? nwarps_max_x*nwarps_max_y : c::nwarps_max; + const int cols_per_warp = std::min(ncols, turing_mma_available(cc) ? 16 : 32); + const int nwarps = nthreads / WARP_SIZE; constexpr bool mla = DKQ == 576; - const int nbatch_K2 = c::get_nbatch_K2_host (cc, ncols); - const int nbatch_V2 = c::get_nbatch_K2_host (cc, ncols); - const int nbatch_combine = c::get_nbatch_combine_host(cc, ncols); - - static_assert(DKQ % tile_B::J == 0, "bad DKQ"); - static_assert(DV % tile_A::J == 0, "bad DV"); - static_assert(ncols % cols_per_warp == 0, "bad ncols"); - - const size_t nbytes_shared_KV_1stage = c::nbatch_fa * std::max(nbatch_K2 + 4, nbatch_V2 + 4) * sizeof(half2); - const size_t nbytes_shared_KV_2stage = c::nbatch_fa * (nbatch_K2 + 4 + nbatch_V2 + 4) * sizeof(half2); + const size_t nbytes_shared_KV_1stage = nbatch_fa * std::max(nbatch_K2 + 4, nbatch_V2 + 4) * sizeof(half2); + const size_t nbytes_shared_KV_2stage = nbatch_fa * (nbatch_K2 + 4 + nbatch_V2 + 4) * sizeof(half2); const size_t nbytes_shared_Q = ncols * (DKQ/2 + 4) * sizeof(half2); - const size_t nbytes_shared_mask = ncols1 * (c::nbatch_fa/2 + 4) * sizeof(half2); + const size_t nbytes_shared_mask = ncols1 * (nbatch_fa/2 + 4) * sizeof(half2); const size_t nbytes_shared_combine = nwarps*cols_per_warp * (nbatch_combine + 4) * sizeof(half2); const size_t nbytes_shared_KV = nstages <= 1 ? nbytes_shared_KV_1stage : nbytes_shared_KV_2stage; - const size_t nbytes_shared_total = std::max(nbytes_shared_combine, c::Q_in_reg ? + const size_t nbytes_shared_total = std::max(nbytes_shared_combine, Q_in_reg ? std::max(nbytes_shared_Q, nbytes_shared_KV + nbytes_shared_mask) : nbytes_shared_Q + nbytes_shared_KV + nbytes_shared_mask); @@ -1448,7 +1518,7 @@ void ggml_cuda_flash_attn_ext_mma_f16_case(ggml_backend_cuda_context & ctx, ggml fattn_kernel_t fattn_kernel; if (logit_softcap == 0.0f) { constexpr bool use_logit_softcap = false; - fattn_kernel = flash_attn_ext_f16; + fattn_kernel = flash_attn_ext_f16; #if !defined(GGML_USE_HIP) && !defined(GGML_USE_MUSA) static bool shared_memory_limit_raised[GGML_CUDA_MAX_DEVICES] = {false}; @@ -1459,7 +1529,7 @@ void ggml_cuda_flash_attn_ext_mma_f16_case(ggml_backend_cuda_context & ctx, ggml #endif // !defined(GGML_USE_HIP) && !defined(GGML_USE_MUSA) } else { constexpr bool use_logit_softcap = true; - fattn_kernel = flash_attn_ext_f16; + fattn_kernel = flash_attn_ext_f16; #if !defined(GGML_USE_HIP) && !defined(GGML_USE_MUSA) static bool shared_memory_limit_raised[GGML_CUDA_MAX_DEVICES] = {false}; @@ -1471,7 +1541,7 @@ void ggml_cuda_flash_attn_ext_mma_f16_case(ggml_backend_cuda_context & ctx, ggml } launch_fattn - (ctx, dst, fattn_kernel, nwarps, nbytes_shared_total, FATTN_KQ_STRIDE, true, true, true); + (ctx, dst, fattn_kernel, nwarps, nbytes_shared_total, nbatch_fa, true, true, true); } diff --git a/ggml/src/ggml-cuda/fattn-tile.cuh b/ggml/src/ggml-cuda/fattn-tile.cuh index 3e58d64ff9..8afc1daaeb 100644 --- a/ggml/src/ggml-cuda/fattn-tile.cuh +++ b/ggml/src/ggml-cuda/fattn-tile.cuh @@ -501,6 +501,7 @@ static __device__ __forceinline__ void flash_attn_tile_iter( const half2 * const __restrict__ K_h2, const half2 * const __restrict__ V_h2, const half * const __restrict__ mask, + const uint3 ne01, const float logit_softcap, const float slope, T_KQ * const KQ, @@ -512,7 +513,8 @@ static __device__ __forceinline__ void flash_attn_tile_iter( float * const KQ_sum, T_acc * const VKQ, const int k_VKQ_0, - const int k_VKQ_max) { + const int k_VKQ_max, + const int col_Q_0) { constexpr int cpy_nb = ggml_cuda_get_max_cpy_bytes(); constexpr int cpy_ne = cpy_nb / 4; @@ -556,7 +558,7 @@ static __device__ __forceinline__ void flash_attn_tile_iter( // Apply logit softcap + mask, update KQ_max: #pragma unroll for (int jc0 = 0; jc0 < cpw; ++jc0) { - const int j = (jc0 + (threadIdx.y / np)*cpw)/ncols2; + const int j = fastmodulo(col_Q_0 + (jc0 + (threadIdx.y / np)*cpw)/ncols2, ne01); #pragma unroll for (int i_KQ_0 = 0; i_KQ_0 < nbatch_fa; i_KQ_0 += np*warp_size) { @@ -570,7 +572,7 @@ static __device__ __forceinline__ void flash_attn_tile_iter( KQ_acc[(i_KQ_0/(np*warp_size))*cpw + jc0] += (ncols2 > 1 || mask) ? slope*__half2float(mask[j*stride_mask + k_VKQ_0 + i_KQ]) : 0.0f; - KQ_max_new[jc0] = fmaxf(KQ_max_new[jc0], KQ_acc[(i_KQ_0/(np*warp_size))*cpw + jc0]); + KQ_max_new[jc0] = fmaxf(KQ_max_new[jc0], KQ_acc[(i_KQ_0/(np*warp_size))*cpw + jc0] + FATTN_KQ_MAX_OFFSET); } } @@ -736,7 +738,7 @@ static __global__ void flash_attn_tile( const float m1, const uint32_t n_head_log2, const float logit_softcap, - const int32_t ne00, const int32_t ne01, const int32_t ne02, const int32_t ne03, + const int32_t ne00, const uint3 ne01, const int32_t ne02, const int32_t ne03, const int32_t nb01, const int32_t nb02, const int32_t nb03, const int32_t ne10, const int32_t ne11, const int32_t ne12, const int32_t ne13, const int32_t nb11, const int32_t nb12, const int64_t nb13, @@ -781,11 +783,11 @@ static __global__ void flash_attn_tile( const int sequence = blockIdx.z / (ne02/ncols2); const int head0 = blockIdx.z*ncols2 - sequence*ne02; // == blockIdx.z % (ne02/ncols2) const int gqa_ratio = ne02 / ne12; // With grouped query attention there are > 1 Q matrices per K, V matrix. - const float * Q_f = (const float *) (Q + nb03*sequence + nb02* head0 + nb01*col_Q_0); + const float * Q_f = (const float *) (Q + nb03*sequence + nb02* head0); const half2 * K_h2 = (const half2 *) (K + nb13*sequence + nb12*(head0 / gqa_ratio)); const half2 * V_h2 = (const half2 *) (V + nb23*sequence + nb22*(head0 / gqa_ratio)); // K and V have same shape - const half * maskh = mask ? (const half *) (mask + nb33*(sequence % ne33) + nb31*col_Q_0) : nullptr; + const half * maskh = mask ? (const half *) (mask + nb33*(sequence % ne33)) : nullptr; const int stride_K2 = nb11 / sizeof(half2); const int stride_V2 = nb21 / sizeof(half2); @@ -842,11 +844,9 @@ static __global__ void flash_attn_tile( for (int i0 = 0; i0 < DKQp; i0 += np*warp_size*cpy_ne_D) { if (i0 + np*warp_size*cpy_ne_D <= DKQ || i0 + (threadIdx.y % np)*(warp_size*cpy_ne_D) + threadIdx.x*cpy_ne_D < DKQ) { float tmp_f[cpy_ne_D] = {0.0f}; - if (ncols1 == 1 || col_Q_0 + j < ne01) { - ggml_cuda_memcpy_1 - (tmp_f, &Q_f[c*(nb02/sizeof(float)) + j*(nb01/sizeof(float)) - + i0 + (threadIdx.y % np)*(warp_size*cpy_ne_D) + threadIdx.x*cpy_ne_D]); - } + ggml_cuda_memcpy_1 + (tmp_f, &Q_f[c*(nb02/sizeof(float)) + fastmodulo(col_Q_0 + j, ne01)*(nb01/sizeof(float)) + + i0 + (threadIdx.y % np)*(warp_size*cpy_ne_D) + threadIdx.x*cpy_ne_D]); #pragma unroll for (int i1 = 0; i1 < cpy_ne_D; ++i1) { @@ -881,23 +881,23 @@ static __global__ void flash_attn_tile( while (k_VKQ_0 < k_VKQ_max - nbatch_fa) { constexpr bool oob_check = false; flash_attn_tile_iter - (Q_tmp, K_h2, V_h2, maskh, logit_softcap, slope, KQ, KV_tmp, - stride_K2, stride_V2, stride_mask, KQ_max, KQ_sum, VKQ, k_VKQ_0, k_VKQ_max); + (Q_tmp, K_h2, V_h2, maskh, ne01, logit_softcap, slope, KQ, KV_tmp, + stride_K2, stride_V2, stride_mask, KQ_max, KQ_sum, VKQ, k_VKQ_0, k_VKQ_max, col_Q_0); k_VKQ_0 += gridDim.y*nbatch_fa; } if (k_VKQ_0 < k_VKQ_max) { constexpr bool oob_check = true; flash_attn_tile_iter - (Q_tmp, K_h2, V_h2, maskh, logit_softcap, slope, KQ, KV_tmp, - stride_K2, stride_V2, stride_mask, KQ_max, KQ_sum, VKQ, k_VKQ_0, k_VKQ_max); + (Q_tmp, K_h2, V_h2, maskh, ne01, logit_softcap, slope, KQ, KV_tmp, + stride_K2, stride_V2, stride_mask, KQ_max, KQ_sum, VKQ, k_VKQ_0, k_VKQ_max, col_Q_0); } } else { // Branch without out-of-bounds checks. for (int k_VKQ_0 = blockIdx.y*nbatch_fa; k_VKQ_0 < k_VKQ_max; k_VKQ_0 += gridDim.y*nbatch_fa) { constexpr bool oob_check = false; flash_attn_tile_iter - (Q_tmp, K_h2, V_h2, maskh, logit_softcap, slope, KQ, KV_tmp, - stride_K2, stride_V2, stride_mask, KQ_max, KQ_sum, VKQ, k_VKQ_0, k_VKQ_max); + (Q_tmp, K_h2, V_h2, maskh, ne01, logit_softcap, slope, KQ, KV_tmp, + stride_K2, stride_V2, stride_mask, KQ_max, KQ_sum, VKQ, k_VKQ_0, k_VKQ_max, col_Q_0); } } @@ -1010,13 +1010,13 @@ static __global__ void flash_attn_tile( const int j = jc / ncols2; const int c = jc % ncols2; - if (ncols1 > 1 && col_Q_0 + j >= ne01) { + if (ncols1 > 1 && col_Q_0 + j >= int(ne01.z)) { return; } const float scale = gridDim.y == 1 ? 1.0f/KQ_sum[jc0] : 1.0f; - const int j_dst_unrolled = ((sequence*ne01 + col_Q_0 + j)*ne02 + head0 + c)*gridDim.y + blockIdx.y; + const int j_dst_unrolled = ((sequence*int(ne01.z) + col_Q_0 + j)*ne02 + head0 + c)*gridDim.y + blockIdx.y; #ifdef FAST_FP16_AVAILABLE constexpr int cpy_ne_D = cpy_ne/2 < (DVp/2)/warp_size ? cpy_ne/2 : (DVp/2)/warp_size; diff --git a/ggml/src/ggml-cuda/fattn-vec.cuh b/ggml/src/ggml-cuda/fattn-vec.cuh index 67aa67ecb9..4d167b95a0 100644 --- a/ggml/src/ggml-cuda/fattn-vec.cuh +++ b/ggml/src/ggml-cuda/fattn-vec.cuh @@ -33,7 +33,7 @@ static __global__ void flash_attn_ext_vec( const float m1, const uint32_t n_head_log2, const float logit_softcap, - const int32_t ne00, const int32_t ne01, const int32_t ne02, const int32_t ne03, + const int32_t ne00, const uint3 ne01, const int32_t ne02, const int32_t ne03, const int32_t nb01, const int32_t nb02, const int32_t nb03, const int32_t ne10, const int32_t ne11, const int32_t ne12, const int32_t ne13, const int32_t nb11, const int32_t nb12, const int64_t nb13, @@ -150,7 +150,7 @@ static __global__ void flash_attn_ext_vec( float2 * tmp_q_ds = (float2 *) (tmp_q_i32 + D/sizeof(int)); // Set memory to zero if out of bounds: - if (ncols > 1 && ic0 + j >= ne01) { + if (ncols > 1 && ic0 + j >= int(ne01.z)) { #pragma unroll for (int i0 = 0; i0 < int(D/sizeof(int)); i0 += WARP_SIZE) { const int i = i0 + threadIdx.x; @@ -201,7 +201,7 @@ static __global__ void flash_attn_ext_vec( const int i = i0 + (nthreads_KQ == WARP_SIZE ? threadIdx.x : threadIdx.x % nthreads_KQ)*cpy_ne; float2 tmp[cpy_ne] = {{0.0f, 0.0f}}; - if (ncols == 1 || ic0 + j < ne01) { + if (ncols == 1 || ic0 + j < int(ne01.z)) { ggml_cuda_memcpy_1(tmp, &Q_j[i]); ggml_cuda_memcpy_1(tmp + cpy_ne/2, &Q_j[i + cpy_ne/2]); } @@ -222,7 +222,7 @@ static __global__ void flash_attn_ext_vec( #pragma unroll for (int i0 = 0; i0 < D/2; i0 += nthreads_KQ*cpy_ne) { const int i = i0 + (nthreads_KQ == WARP_SIZE ? threadIdx.x : threadIdx.x % nthreads_KQ)*cpy_ne; - if (ncols == 1 || ic0 + j < ne01) { + if (ncols == 1 || ic0 + j < int(ne01.z)) { ggml_cuda_memcpy_1(&Q_reg[j][i0/nthreads_KQ], &Q_j[i]); ggml_cuda_memcpy_1(&Q_reg[j][i0/nthreads_KQ + cpy_ne/2], &Q_j[i + cpy_ne/2]); } @@ -266,11 +266,11 @@ static __global__ void flash_attn_ext_vec( sum = logit_softcap*tanhf(sum); } - if (mask) { + if (mask && (ncols == 1 || ic0 + j < int(ne01.z))) { sum += slope*__half2float(maskh[j*ne11 + i_KQ]); } - KQ_max_new[j] = fmaxf(KQ_max_new[j], sum); + KQ_max_new[j] = fmaxf(KQ_max_new[j], sum + FATTN_KQ_MAX_OFFSET); if ((nthreads_KQ == WARP_SIZE ? threadIdx.x : threadIdx.x % nthreads_KQ) == uint32_t(i_KQ_0)) { KQ_reg[j] = sum; @@ -412,7 +412,7 @@ static __global__ void flash_attn_ext_vec( #pragma unroll for (int j_VKQ = 0; j_VKQ < ncols; ++j_VKQ) { - if (ncols > 1 && ic0 + j_VKQ >= ne01) { + if (ncols > 1 && ic0 + j_VKQ >= int(ne01.z)) { break; } @@ -479,7 +479,7 @@ static __global__ void flash_attn_ext_vec( if (gridDim.y == 1) { dst_val /= KQ_sum[j_VKQ]; } - dst[(((sequence*ne01 + ic0 + j_VKQ)*ne02 + head)*gridDim.y + blockIdx.y)*D + i0 + tid] = dst_val; + dst[(((sequence*int(ne01.z) + ic0 + j_VKQ)*ne02 + head)*gridDim.y + blockIdx.y)*D + i0 + tid] = dst_val; } } @@ -489,8 +489,8 @@ static __global__ void flash_attn_ext_vec( } - if (gridDim.y != 1 && tid < ncols && (ncols == 1 || ic0 + tid < ne01)) { - dst_meta[((sequence*ne01 + ic0 + tid)*ne02 + head)*gridDim.y + blockIdx.y] = make_float2(KQ_max[tid], KQ_sum[tid]); + if (gridDim.y != 1 && tid < ncols && (ncols == 1 || ic0 + tid < int(ne01.z))) { + dst_meta[((sequence*int(ne01.z) + ic0 + tid)*ne02 + head)*gridDim.y + blockIdx.y] = make_float2(KQ_max[tid], KQ_sum[tid]); } #else GGML_UNUSED_VARS(Q, K, V, mask, sinks, KV_max, dst, dst_meta, scale, diff --git a/ggml/src/ggml-cuda/fattn-wmma-f16.cu b/ggml/src/ggml-cuda/fattn-wmma-f16.cu index 6c90d6d52b..8694fd06c7 100644 --- a/ggml/src/ggml-cuda/fattn-wmma-f16.cu +++ b/ggml/src/ggml-cuda/fattn-wmma-f16.cu @@ -38,14 +38,14 @@ static __global__ void flash_attn_ext_f16( const float m1, const uint32_t n_head_log2, const float logit_softcap, - const int32_t ne00, const int32_t ne01, const int32_t ne02, const int32_t ne03, + const int32_t ne00, const uint3 ne01, const int32_t ne02, const int32_t ne03, const int32_t nb01, const int32_t nb02, const int32_t nb03, const int32_t ne10, const int32_t ne11, const int32_t ne12, const int32_t ne13, const int32_t nb11, const int32_t nb12, const int64_t nb13, const int32_t nb21, const int32_t nb22, const int64_t nb23, const int32_t ne31, const int32_t ne32, const int32_t ne33, const int32_t nb31, const int32_t nb32, const int64_t nb33) { -#if defined(FLASH_ATTN_AVAILABLE) && (__CUDA_ARCH__ == GGML_CUDA_CC_VOLTA || (defined(GGML_HIP_ROCWMMA_FATTN) && defined(GGML_USE_WMMA_FATTN))) +#if defined(FLASH_ATTN_AVAILABLE) && (defined(GGML_HIP_ROCWMMA_FATTN) && defined(GGML_USE_WMMA_FATTN)) // Skip unused kernel variants for faster compilation: if (use_logit_softcap && !(D == 128 || D == 256)) { NO_DEVICE_CODE; @@ -149,7 +149,7 @@ static __global__ void flash_attn_ext_f16( if (i0 + warp_size > D && i >= D) { break; } - KQ[j*D_padded + i] = ic0 + j < ne01 ? Q_f[j*stride_Q + i] * scale : 0.0f; + KQ[j*D_padded + i] = ic0 + j < int(ne01.z) ? Q_f[j*stride_Q + i] * scale : 0.0f; } } @@ -218,8 +218,9 @@ static __global__ void flash_attn_ext_f16( for (int k0 = 0; k0 < FATTN_KQ_STRIDE; k0 += warp_size) { const int k = k0 + threadIdx.x; - KQ_f_tmp[k0/warp_size] += mask ? __half2float(slopeh*maskh[j*(nb31/sizeof(half)) + k_VKQ_0 + k]) : 0.0f; - KQ_max_new = max(KQ_max_new, KQ_f_tmp[k0/warp_size]); + KQ_f_tmp[k0/warp_size] += mask && ic0 + j < int(ne01.z) ? + __half2float(slopeh*maskh[j*(nb31/sizeof(half)) + k_VKQ_0 + k]) : 0.0f; + KQ_max_new = max(KQ_max_new, KQ_f_tmp[k0/warp_size] + FATTN_KQ_MAX_OFFSET); } KQ_max_new = warp_reduce_max(KQ_max_new); @@ -270,7 +271,7 @@ static __global__ void flash_attn_ext_f16( for (int k0 = 0; k0 < FATTN_KQ_STRIDE/2; k0 += warp_size) { const int k = k0 + threadIdx.x; - KQ2_tmp[k0/warp_size] += mask ? slope2*mask2[(j*ne11 + k_VKQ_0)/2 + k] : make_half2(0.0f, 0.0f); + KQ2_tmp[k0/warp_size] += mask && ic0 + j < int(ne01.z) ? slope2*mask2[(j*ne11 + k_VKQ_0)/2 + k] : make_half2(0.0f, 0.0f); KQ_max_new = ggml_cuda_hmax2(KQ_max_new, KQ2_tmp[k0/warp_size]); } KQ_max_new = __half2half2(warp_reduce_max(ggml_cuda_hmax(__low2half(KQ_max_new), __high2half(KQ_max_new)))); @@ -431,7 +432,7 @@ static __global__ void flash_attn_ext_f16( #pragma unroll for (int j0 = 0; j0 < ncols; j0 += nwarps) { const int j_VKQ = j0 + threadIdx.y; - if (ic0 + j_VKQ >= ne01) { + if (ic0 + j_VKQ >= int(ne01.z)) { return; } @@ -442,7 +443,7 @@ static __global__ void flash_attn_ext_f16( KQ_rowsum_j = __low2float(KQ_rowsum_h2[j0/nwarps]) + __high2float(KQ_rowsum_h2[j0/nwarps]); } - const int j_dst_unrolled = ((sequence*ne01 + ic0 + j_VKQ)*ne02 + head)*gridDim.y + blockIdx.y; + const int j_dst_unrolled = ((sequence*int(ne01.z) + ic0 + j_VKQ)*ne02 + head)*gridDim.y + blockIdx.y; #pragma unroll for (int i0 = 0; i0 < D; i0 += warp_size) { @@ -481,7 +482,7 @@ static __global__ void flash_attn_ext_f16( ne31, ne32, ne33, nb31, nb32, nb33); NO_DEVICE_CODE; -#endif // defined(FLASH_ATTN_AVAILABLE) && (__CUDA_ARCH__ == GGML_CUDA_CC_VOLTA || (defined(GGML_HIP_ROCWMMA_FATTN) && defined(GGML_USE_WMMA_FATTN))) +#endif // defined(FLASH_ATTN_AVAILABLE) && (defined(GGML_HIP_ROCWMMA_FATTN) && defined(GGML_USE_WMMA_FATTN)) } constexpr int get_max_power_of_2(int x) { diff --git a/ggml/src/ggml-cuda/fattn-wmma-f16.cuh b/ggml/src/ggml-cuda/fattn-wmma-f16.cuh index 7235f1b77a..cd3bfd4051 100644 --- a/ggml/src/ggml-cuda/fattn-wmma-f16.cuh +++ b/ggml/src/ggml-cuda/fattn-wmma-f16.cuh @@ -2,9 +2,9 @@ #include "common.cuh" -#if (!defined(GGML_USE_HIP) && __CUDA_ARCH__ >= GGML_CUDA_CC_VOLTA) || defined(GGML_USE_MUSA) +#if defined(GGML_USE_MUSA) #define GGML_USE_WMMA_FATTN -#endif // (!defined(GGML_USE_HIP) && __CUDA_ARCH__ >= GGML_CUDA_CC_VOLTA) || defined(GGML_USE_MUSA) +#endif // defined(GGML_USE_MUSA) #if defined(GGML_HIP_ROCWMMA_FATTN) #if defined(CDNA) && (ROCWMMA_VERSION_MAJOR < 2 || ROCWMMA_VERSION_MINOR > 0 || ROCWMMA_VERSION_PATCH > 0) diff --git a/ggml/src/ggml-cuda/fattn.cu b/ggml/src/ggml-cuda/fattn.cu index 82405991ce..dec01ff8ad 100644 --- a/ggml/src/ggml-cuda/fattn.cu +++ b/ggml/src/ggml-cuda/fattn.cu @@ -12,13 +12,13 @@ static void ggml_cuda_flash_attn_ext_mma_f16_switch_ncols1(ggml_backend_cuda_con const ggml_tensor * Q = dst->src[0]; if constexpr (ncols2 <= 8) { - if (Q->ne[1] <= 8/ncols2) { + if (turing_mma_available(cc) && Q->ne[1] <= 8/ncols2) { ggml_cuda_flash_attn_ext_mma_f16_case(ctx, dst); return; } } - if (Q->ne[1] <= 16/ncols2) { + if (turing_mma_available(cc) && Q->ne[1] <= 16/ncols2) { ggml_cuda_flash_attn_ext_mma_f16_case(ctx, dst); return; } @@ -41,7 +41,7 @@ static void ggml_cuda_flash_attn_ext_mma_f16_switch_ncols2(ggml_backend_cuda_con float max_bias = 0.0f; memcpy(&max_bias, (const float *) KQV->op_params + 1, sizeof(float)); - const bool use_gqa_opt = mask && max_bias == 0.0f; + const bool use_gqa_opt = mask && max_bias == 0.0f && K->ne[1] % FATTN_KQ_STRIDE == 0; GGML_ASSERT(Q->ne[2] % K->ne[2] == 0); const int gqa_ratio = Q->ne[2] / K->ne[2]; @@ -275,8 +275,8 @@ static best_fattn_kernel ggml_cuda_get_best_fattn_kernel(const int device, const // For small batch sizes the vector kernel may be preferable over the kernels optimized for large batch sizes: const bool can_use_vector_kernel = Q->ne[0] <= 256 && Q->ne[0] % 64 == 0 && K->ne[1] % FATTN_KQ_STRIDE == 0; - // If Turing tensor cores available, use them: - if (turing_mma_available(cc) && K->ne[1] % FATTN_KQ_STRIDE == 0 && Q->ne[0] != 40 && Q->ne[0] != 72) { + // If Turing tensor cores are available, use them: + if (turing_mma_available(cc) && Q->ne[0] != 40 && Q->ne[0] != 72) { if (can_use_vector_kernel) { if (!ggml_is_quantized(K->type) && !ggml_is_quantized(V->type)) { if (cc >= GGML_CUDA_CC_ADA_LOVELACE && Q->ne[1] == 1 && Q->ne[3] == 1 && !(gqa_ratio > 4 && K->ne[1] >= 8192)) { @@ -297,7 +297,21 @@ static best_fattn_kernel ggml_cuda_get_best_fattn_kernel(const int device, const return BEST_FATTN_KERNEL_VEC; } } + return BEST_FATTN_KERNEL_MMA_F16; + } + if (volta_mma_available(cc) && Q->ne[0] != 40 && Q->ne[0] != 72) { + int gqa_ratio_eff = 1; + const int ncols2_max = Q->ne[0] == 576 ? 16 : 8; + while (gqa_ratio % (2*gqa_ratio_eff) == 0 && gqa_ratio_eff < ncols2_max) { + gqa_ratio_eff *= 2; + } + if (can_use_vector_kernel && Q->ne[1] * gqa_ratio_eff <= 2) { + return BEST_FATTN_KERNEL_VEC; + } + if (Q->ne[1] * gqa_ratio_eff <= 16) { + return BEST_FATTN_KERNEL_TILE; // On Volta tensor cores are only faster for sufficiently large matrices. + } return BEST_FATTN_KERNEL_MMA_F16; } diff --git a/ggml/src/ggml-cuda/fill.cu b/ggml/src/ggml-cuda/fill.cu new file mode 100644 index 0000000000..eb8ccb7802 --- /dev/null +++ b/ggml/src/ggml-cuda/fill.cu @@ -0,0 +1,37 @@ +#include "fill.cuh" +#include "convert.cuh" + +#define CUDA_FILL_BLOCK_SIZE 256 + +template +static __global__ void fill_kernel(T * __restrict__ dst, const int64_t k, const T value) { + const int64_t i = (int64_t)blockDim.x * blockIdx.x + threadIdx.x; + if (i >= k) { + return; + } + dst[i] = value; +} + +void ggml_cuda_op_fill(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { + void * dst_d = dst->data; + cudaStream_t stream = ctx.stream(); + + GGML_ASSERT(ggml_is_contiguous(dst)); + + float value; + memcpy(&value, dst->op_params, sizeof(float)); + + const int64_t k = ggml_nelements(dst); + const int64_t num_blocks = (k + CUDA_FILL_BLOCK_SIZE - 1) / CUDA_FILL_BLOCK_SIZE; + + switch (dst->type) { + case GGML_TYPE_F32: + fill_kernel<<>>((float *)dst_d, k, value); + break; + case GGML_TYPE_F16: + fill_kernel<<>>((half *)dst_d, k, ggml_cuda_cast(value)); + break; + default: + GGML_ABORT("unsupported type"); + } +} diff --git a/ggml/src/ggml-cuda/fill.cuh b/ggml/src/ggml-cuda/fill.cuh new file mode 100644 index 0000000000..8443c83620 --- /dev/null +++ b/ggml/src/ggml-cuda/fill.cuh @@ -0,0 +1,3 @@ +#include "common.cuh" + +void ggml_cuda_op_fill(ggml_backend_cuda_context & ctx, ggml_tensor * dst); diff --git a/ggml/src/ggml-cuda/ggml-cuda.cu b/ggml/src/ggml-cuda/ggml-cuda.cu index eb2e273110..d0463388c5 100644 --- a/ggml/src/ggml-cuda/ggml-cuda.cu +++ b/ggml/src/ggml-cuda/ggml-cuda.cu @@ -54,6 +54,9 @@ #include "ggml-cuda/set-rows.cuh" #include "ggml-cuda/pad_reflect_1d.cuh" #include "ggml-cuda/solve_tri.cuh" +#include "ggml-cuda/tri.cuh" +#include "ggml-cuda/cumsum.cuh" +#include "ggml-cuda/fill.cuh" #include "ggml.h" #include @@ -2701,6 +2704,12 @@ static bool ggml_cuda_compute_forward(ggml_backend_cuda_context & ctx, struct gg case GGML_OP_CROSS_ENTROPY_LOSS: ggml_cuda_cross_entropy_loss(ctx, dst); break; + case GGML_OP_CUMSUM: + ggml_cuda_op_cumsum(ctx, dst); + break; + case GGML_OP_TRI: + ggml_cuda_op_tri(ctx, dst); + break; case GGML_OP_RWKV_WKV6: ggml_cuda_op_rwkv_wkv6(ctx, dst); break; @@ -2722,6 +2731,9 @@ static bool ggml_cuda_compute_forward(ggml_backend_cuda_context & ctx, struct gg case GGML_OP_SOLVE_TRI: ggml_cuda_op_solve_tri(ctx, dst); break; + case GGML_OP_FILL: + ggml_cuda_op_fill(ctx, dst); + break; default: return false; } @@ -3238,9 +3250,56 @@ static void evaluate_and_capture_cuda_graph(ggml_backend_cuda_context * cuda_ctx } } if (should_launch_concurrent_events) { - //Restore the original graph to enable fusion within the streams - cgraph->nodes = const_cast(stream_ctx.original_nodes.data()); - cgraph->n_nodes = (int) stream_ctx.original_nodes.size(); + // Restore original node order within each concurrent region to enable fusion within streams + + std::unordered_map node_to_idx; + node_to_idx.reserve(cgraph->n_nodes); + for (int i = 0; i < cgraph->n_nodes; ++i) { + node_to_idx[cgraph->nodes[i]] = i; + } + + for (auto & [fork_node, event] : stream_ctx.concurrent_events) { + // Find positions of all nodes from this event in the current graph + std::vector positions; + positions.reserve(event.original_order.size()); + + bool all_found = true; + for (const ggml_tensor * orig_node : event.original_order) { + auto it = node_to_idx.find(orig_node); + if (it != node_to_idx.end()) { + positions.push_back(it->second); + } else { + all_found = false; + break; + } + } + + if (!all_found || positions.size() != event.original_order.size()) { + continue; + } + + // Sort positions to get contiguous range + std::vector sorted_positions = positions; + std::sort(sorted_positions.begin(), sorted_positions.end()); + + bool is_contiguous = true; + for (size_t i = 1; i < sorted_positions.size(); ++i) { + if (sorted_positions[i] != sorted_positions[i-1] + 1) { + is_contiguous = false; + break; + } + } + + if (!is_contiguous) { + continue; + } + + // Restore original order at the sorted positions + int start_pos = sorted_positions[0]; + for (size_t i = 0; i < event.original_order.size(); ++i) { + cgraph->nodes[start_pos + i] = const_cast(event.original_order[i]); + } + } } for (int i = 0; i < cgraph->n_nodes; i++) { @@ -3805,14 +3864,6 @@ static void ggml_backend_cuda_graph_optimize(ggml_backend_t backend, ggml_cgraph // store {fork_idx, join_idx} std::vector> concurrent_node_ranges; - // save the original nodes - std::vector original_nodes; - original_nodes.reserve(cgraph->n_nodes); - for (int i = 0; i < cgraph->n_nodes; ++i) { - original_nodes.push_back(cgraph->nodes[i]); - } - cuda_ctx->stream_context().original_nodes = std::move(original_nodes); - for (const auto & [root_node, count] : fan_out) { if (count >= min_fan_out && count <= max_fan_out) { const int root_node_idx = node_indices[root_node]; @@ -3917,6 +3968,13 @@ static void ggml_backend_cuda_graph_optimize(ggml_backend_t backend, ggml_cgraph continue; } + // Save the original order of nodes in this region before interleaving + // This is used later to restore grouping for fusion within streams + concurrent_event.original_order.reserve(total_branch_nodes); + for (int i = fork_node_idx + 1; i < join_node_idx; ++i) { + concurrent_event.original_order.push_back(cgraph->nodes[i]); + } + std::unordered_map & concurrent_events = cuda_ctx->stream_context().concurrent_events; GGML_ASSERT(concurrent_events.find(root_node) == concurrent_events.end()); concurrent_events.emplace(root_node, std::move(concurrent_event)); @@ -4563,6 +4621,9 @@ static bool ggml_backend_cuda_device_supports_op(ggml_backend_dev_t dev, const g case GGML_OP_CROSS_ENTROPY_LOSS_BACK: case GGML_OP_OPT_STEP_ADAMW: case GGML_OP_OPT_STEP_SGD: + case GGML_OP_FILL: + case GGML_OP_CUMSUM: + case GGML_OP_TRI: return true; case GGML_OP_SOLVE_TRI: return op->src[0]->ne[0] <= 64 && op->src[1]->ne[0] <= 32; diff --git a/ggml/src/ggml-cuda/mma.cuh b/ggml/src/ggml-cuda/mma.cuh index 0ed42e87d3..0b13293da9 100644 --- a/ggml/src/ggml-cuda/mma.cuh +++ b/ggml/src/ggml-cuda/mma.cuh @@ -68,10 +68,31 @@ static __device__ __forceinline__ half2 ggml_cuda_movmatrix(const half2 x) { namespace ggml_cuda_mma { + // Some architectures like Volta or CDNA3 perform multiple matrix multiplications per warp in parallel, + // effectively the warp is being split into subgroups of threads that each perform a single mma instruction. + // In those cases the data can be split in different ways across the warp. + enum data_layout { + // By default the data uses the I direction as its major dimension and the J direction as its minor dimension. + // For the A/C matrices this means I major == row major, J major == column major. + // For the B matrix this means I major == column major, J major == row major. + // MIRRORED == Each data value is held exactly once per thread subgroup. + DATA_LAYOUT_I_MAJOR = 0, // Always used for Turing, Ampere, Ada Lovelace, consumer Blackwell. + DATA_LAYOUT_I_MAJOR_MIRRORED = 10, + DATA_LAYOUT_J_MAJOR_MIRRORED = 20, + }; + // Implemented mma combinations are: + // - (I_MAJOR, I_MAJOR) -> I_MAJOR + // - (I_MAJOR, I_MAJOR_MIRRORED) -> I_MAJOR + // - (I_MAJOR, J_MAJOR_MIRRORED) -> I_MAJOR + + template + struct tile {}; + template - struct tile { - static constexpr int I = I_; - static constexpr int J = J_; + struct tile { + static constexpr int I = I_; + static constexpr int J = J_; + static constexpr data_layout dl = DATA_LAYOUT_I_MAJOR; #if defined(AMD_MFMA_AVAILABLE) static constexpr int ne = I * J / 64; @@ -131,9 +152,9 @@ namespace ggml_cuda_mma { static __device__ __forceinline__ int get_i(const int l) { if constexpr (I == 32 && J == 8) { #ifdef GGML_CUDA_MMA_NO_VOLTA_PERM - return (((threadIdx.x % 16) / 4) * 8) | ((threadIdx.x / 16) * 4) | (l & 2) | (threadIdx.x % 2); + return (((threadIdx.x % 16) / 4) * 8) + ((threadIdx.x / 16) * 4) + (l & 2) + (threadIdx.x % 2); #else - return (l & 2) | (threadIdx.x & ~2); + return (l & 2) + (threadIdx.x & ~2); #endif // GGML_CUDA_MMA_NO_VOLTA_PERM } else { NO_DEVICE_CODE; @@ -143,7 +164,7 @@ namespace ggml_cuda_mma { static __device__ __forceinline__ int get_j(const int l) { if constexpr (I == 32 && J == 8) { - return (threadIdx.x & 2) | (l & (4 + 1)); + return (threadIdx.x & 2) + (l & (4 + 1)); } else { NO_DEVICE_CODE; return -1; @@ -152,6 +173,9 @@ namespace ggml_cuda_mma { #elif defined(AMD_WMMA_AVAILABLE) #if defined(RDNA4) static constexpr int ne = I * J / 32; +#elif defined(RDNA3) + static constexpr int ne = (I == 16 && J == 16) ? I * J / 32 : I * J / 16; +#endif // defined(RDNA4) T x[ne] = {0}; static constexpr __device__ bool supported() { @@ -161,7 +185,11 @@ namespace ggml_cuda_mma { static __device__ __forceinline__ int get_i(const int l) { if constexpr (I == 16 && J == 16) { +#if defined(RDNA4) return 8 * (threadIdx.x / 16) + l; +#elif defined(RDNA3) + return 2 * l + (threadIdx.x / 16); +#endif // defined(RDNA4) } else { NO_DEVICE_CODE; return -1; @@ -176,7 +204,6 @@ namespace ggml_cuda_mma { return -1; } } -#endif #else static constexpr int ne = I * J / 32; T x[ne] = {0}; @@ -196,9 +223,9 @@ namespace ggml_cuda_mma { } else if constexpr (I == 8 && J == 8) { return threadIdx.x / 4; } else if constexpr (I == 16 && J == 8) { - return ((l / 2) * 8) | (threadIdx.x / 4); + return ((l / 2) * 8) + (threadIdx.x / 4); } else if constexpr (I == 16 && J == 16) { - return (((l / 2) % 2) * 8) | (threadIdx.x / 4); + return (((l / 2) % 2) * 8) + (threadIdx.x / 4); } else if constexpr (I == 32 && J == 8) { return tile<16, 8, T>::get_i(l); // Memory layout simply repeated with same pattern in i direction. } else { @@ -211,11 +238,11 @@ namespace ggml_cuda_mma { if constexpr (I == 8 && J == 4) { return threadIdx.x % 4; } else if constexpr (I == 8 && J == 8) { - return (l * 4) | (threadIdx.x % 4); + return (l * 4) + (threadIdx.x % 4); } else if constexpr (I == 16 && J == 8) { - return ((threadIdx.x % 4) * 2) | (l % 2); + return ((threadIdx.x % 4) * 2) + (l % 2); } else if constexpr (I == 16 && J == 16) { - return ((l / 4) * 8) | ((threadIdx.x % 4) * 2) | (l % 2); + return ((l / 4) * 8) + ((threadIdx.x % 4) * 2) + (l % 2); } else if constexpr (I == 32 && J == 8) { return tile<16, 8, T>::get_j(l); // Memory layout simply repeated with same pattern in i direction. } else { @@ -227,26 +254,24 @@ namespace ggml_cuda_mma { }; template - struct tile { - static constexpr int I = I_; - static constexpr int J = J_; + struct tile { + static constexpr int I = I_; + static constexpr int J = J_; + static constexpr data_layout dl = DATA_LAYOUT_I_MAJOR; #if __CUDA_ARCH__ == GGML_CUDA_CC_VOLTA - static constexpr int ne = I == 8 && J == 8 ? I * J / (WARP_SIZE/4) : I * J / WARP_SIZE; + static constexpr int ne = I * J / WARP_SIZE; half2 x[ne] = {{0.0f, 0.0f}}; static constexpr __device__ bool supported() { - if (I == 8 && J == 8) return true; - if (I == 32 && J == 8) return true; + if (I == 32 && J == 4) return true; return false; } static __device__ __forceinline__ int get_i(const int l) { - if constexpr (I == 8 && J == 8) { - return ((threadIdx.x / 16) * 4) | (threadIdx.x % 4); - } else if constexpr (I == 32 && J == 8) { + if constexpr (I == 32 && J == 4) { #ifdef GGML_CUDA_MMA_NO_VOLTA_PERM - return (((threadIdx.x % 16) / 4) * 8) | ((threadIdx.x / 16) * 4) | (threadIdx.x % 4); + return (((threadIdx.x % 16) / 4) * 8) + ((threadIdx.x / 16) * 4) + (threadIdx.x % 4); #else return threadIdx.x; #endif // GGML_CUDA_MMA_NO_VOLTA_PERM @@ -257,7 +282,7 @@ namespace ggml_cuda_mma { } static __device__ __forceinline__ int get_j(const int l) { - if constexpr ((I == 8 || I == 32) && J == 8) { + if constexpr (I == 32 && J == 4) { return l; } else { NO_DEVICE_CODE; @@ -265,6 +290,7 @@ namespace ggml_cuda_mma { } } #elif defined(AMD_WMMA_AVAILABLE) + static constexpr int ne = I * J / 32; half2 x[ne] = {{0.0f, 0.0f}}; @@ -307,11 +333,11 @@ namespace ggml_cuda_mma { if constexpr (I == 8 && J == 8) { return threadIdx.x / 4; } else if constexpr (I == 16 && J == 4) { - return (l * 8) | (threadIdx.x / 4); + return (l * 8) + (threadIdx.x / 4); } else if constexpr (I == 16 && J == 8) { - return ((l % 2) * 8) | (threadIdx.x / 4); + return ((l % 2) * 8) + (threadIdx.x / 4); } else if constexpr (I == 32 && J == 8) { - return ((l / 4) * 16) | ((l % 2) * 8) | (threadIdx.x / 4); + return ((l / 4) * 16) + ((l % 2) * 8) + (threadIdx.x / 4); } else { NO_DEVICE_CODE; return -1; @@ -320,13 +346,13 @@ namespace ggml_cuda_mma { static __device__ __forceinline__ int get_j(const int l) { if constexpr (I == 8 && J == 8) { - return (l * 4) | (threadIdx.x % 4); + return (l * 4) + (threadIdx.x % 4); } else if constexpr (I == 16 && J == 4) { return threadIdx.x % 4; } else if constexpr (I == 16 && J == 8) { - return ((l / 2) * 4) | (threadIdx.x % 4); + return ((l / 2) * 4) + (threadIdx.x % 4); } else if constexpr (I == 32 && J == 8) { - return ((l & 2) * 2) | (threadIdx.x % 4); + return ((l & 2) * 2) + (threadIdx.x % 4); } else { NO_DEVICE_CODE; return -1; @@ -336,14 +362,15 @@ namespace ggml_cuda_mma { }; template - struct tile { - static constexpr int I = I_; - static constexpr int J = J_; + struct tile { + static constexpr int I = I_; + static constexpr int J = J_; + static constexpr data_layout dl = DATA_LAYOUT_I_MAJOR; + static constexpr int ne = I * J / WARP_SIZE; -#if defined(AMD_WMMA_AVAILABLE) - static constexpr int ne = I * J / 32; nv_bfloat162 x[ne] = {{0.0f, 0.0f}}; +#if defined(AMD_WMMA_AVAILABLE) static constexpr __device__ bool supported() { if (I == 16 && J == 8) return true; return false; @@ -367,9 +394,6 @@ namespace ggml_cuda_mma { } } #else - static constexpr int ne = I * J / WARP_SIZE; - nv_bfloat162 x[ne] = {{0.0f, 0.0f}}; - static constexpr __device__ bool supported() { if (I == 8 && J == 8) return true; if (I == 16 && J == 4) return true; @@ -381,9 +405,9 @@ namespace ggml_cuda_mma { if constexpr (I == 8 && J == 8) { return threadIdx.x / 4; } else if constexpr (I == 16 && J == 4) { - return (l * 8) | (threadIdx.x / 4); + return (l * 8) + (threadIdx.x / 4); } else if constexpr (I == 16 && J == 8) { - return ((l % 2) * 8) | (threadIdx.x / 4); + return ((l % 2) * 8) + (threadIdx.x / 4); } else { NO_DEVICE_CODE; return -1; @@ -392,11 +416,11 @@ namespace ggml_cuda_mma { static __device__ __forceinline__ int get_j(const int l) { if constexpr (I == 8 && J == 8) { - return (l * 4) | (threadIdx.x % 4); + return (l * 4) + (threadIdx.x % 4); } else if constexpr (I == 16 && J == 4) { return threadIdx.x % 4; } else if constexpr (I == 16 && J == 8) { - return ((l / 2) * 4) | (threadIdx.x % 4); + return ((l / 2) * 4) + (threadIdx.x % 4); } else { NO_DEVICE_CODE; return -1; @@ -405,6 +429,73 @@ namespace ggml_cuda_mma { #endif // defined(AMD_WMMA_AVAILABLE) }; + template + struct tile { + static constexpr int I = I_; + static constexpr int J = J_; + static constexpr data_layout dl = DATA_LAYOUT_I_MAJOR_MIRRORED; + static constexpr int ne = I * J / (WARP_SIZE/4); + + half2 x[ne] = {{0.0f, 0.0f}}; + + static constexpr __device__ bool supported() { + if (I == 8 && J == 4) return true; + return false; + } + + static __device__ __forceinline__ int get_i(const int /*l*/) { + if constexpr (I == 8 && J == 4) { + return ((threadIdx.x / 16) * 4) + (threadIdx.x % 4); + } else { + NO_DEVICE_CODE; + return -1; + } + } + + static __device__ __forceinline__ int get_j(const int l) { + if constexpr (I == 8 && J == 4) { + return l; + } else { + NO_DEVICE_CODE; + return -1; + } + } + }; + + template + struct tile { + static constexpr int I = I_; + static constexpr int J = J_; + static constexpr data_layout dl = DATA_LAYOUT_J_MAJOR_MIRRORED; + static constexpr int ne = I * J / (WARP_SIZE/4); + + half2 x[ne] = {{0.0f, 0.0f}}; + + static constexpr __device__ bool supported() { + if (I == 8 && J == 4) return true; + return false; + } + + static __device__ __forceinline__ int get_i(const int l) { + if constexpr (I == 8 && J == 4) { + return ((l / 2) * 4) + (threadIdx.x % 4); + } else { + NO_DEVICE_CODE; + return -1; + } + } + + static __device__ __forceinline__ int get_j(const int l) { + if constexpr (I == 8 && J == 4) { + return ((threadIdx.x / 16) * 2) + (l % 2); + } else { + NO_DEVICE_CODE; + return -1; + } + } + }; + +#if defined(TURING_MMA_AVAILABLE) template static __device__ __forceinline__ tile get_half2(const tile & tile_float) { tile ret; @@ -422,9 +513,26 @@ namespace ggml_cuda_mma { return ret; } +#else // Volta + template + static __device__ __forceinline__ tile get_half2(const tile & tile_float) { + tile ret; +#pragma unroll + for (int l0 = 0; l0 < tile_float.ne; l0 += 4) { + ret.x[l0/2 + 0] = make_half2(tile_float.x[l0 + 0], tile_float.x[l0 + 1]); + ret.x[l0/2 + 1] = make_half2(tile_float.x[l0 + 2], tile_float.x[l0 + 3]); - template - static __device__ __forceinline__ void load_generic(tile & t, const T * __restrict__ xs0, const int stride) { + // On Volta FP16 and FP32 tiles have a different memory layout, + // for the conversion threads with an offset of 2 need to exchange half their values: + ret.x[l0/2 + (((threadIdx.x % 4) / 2) ^ 1)] = __shfl_xor_sync( + 0xFFFFFFFF, ret.x[l0/2 + (((threadIdx.x % 4) / 2) ^ 1)], 2, WARP_SIZE); + } + return ret; + } +#endif // defined(TURING_MMA_AVAILABLE) + + template + static __device__ __forceinline__ void load_generic(tile & t, const T * __restrict__ xs0, const int stride) { #if defined(AMD_MFMA_AVAILABLE) if constexpr (I == 64 && J == 2) { // Special tile size to load <16, 4> as <16, 8> #pragma unroll @@ -443,18 +551,34 @@ namespace ggml_cuda_mma { } else if constexpr (std::is_same_v) { if constexpr (I == 16 && J == 4) { int64_t * xi = (int64_t *) t.x; +#if defined(RDNA4) const int64_t * xs = (int64_t *) ((const int *) xs0 + (threadIdx.x % t.I) * stride + 2 * (threadIdx.x / t.I)); xi[0] = xs[0]; - - }else if constexpr (I == 16 && J == 8) { +#elif defined(RDNA3) + static_assert(tile::ne >= 4, "fragment too small"); + const int64_t * xs = (int64_t *) ((const int *) xs0 + (threadIdx.x % t.I) * stride); + xi[0] = xs[0]; + xi[1] = xs[1]; +#endif // defined(RDNA4) + } else if constexpr (I == 16 && J == 8) { int64_t * xi = (int64_t *) t.x; +#if defined(RDNA4) const int64_t * xs = (int64_t *) ((const int *) xs0 + (threadIdx.x % t.I) * stride + 4 * (threadIdx.x / t.I)); xi[0] = xs[0]; const int64_t * xs1 = (int64_t *) ((const int *) xs0 + (threadIdx.x % t.I) * stride + 4 * (threadIdx.x / t.I) + 2); xi[1] = xs1[0]; - - }else{ +#elif defined(RDNA3) + static_assert(tile::ne >= 8, "fragment too small"); + const int64_t * xs = (int64_t *) ((const int *) xs0 + (threadIdx.x % t.I) * stride); + // contiguous four 64-bit chunks per lane for the wider RDNA3 fragment + xi[0] = xs[0]; + xi[1] = xs[1]; + const int64_t * xs1 = xs + 2; + xi[2] = xs1[0]; + xi[3] = xs1[1]; +#endif // defined(RDNA4) + } else { NO_DEVICE_CODE; } } else { @@ -511,18 +635,6 @@ namespace ggml_cuda_mma { : "=r"(xi[0]), "=r"(xi[1]), "=r"(xi[2]), "=r"(xi[3]) : "l"(xs)); #else -#if __CUDA_ARCH__ == GGML_CUDA_CC_VOLTA - GGML_UNUSED_VARS(t, xs0, stride); - NO_DEVICE_CODE; -#else - load_generic(t, xs0, stride); -#endif // __CUDA_ARCH__ == GGML_CUDA_CC_VOLTA -#endif // TURING_MMA_AVAILABLE - } - - template - static __device__ __forceinline__ void load_ldmatrix( - tile<32, 8, T> & t, const T * __restrict__ xs0, const int stride) { #if __CUDA_ARCH__ == GGML_CUDA_CC_VOLTA #if 1 // TODO: more generic handling @@ -533,9 +645,31 @@ namespace ggml_cuda_mma { load_generic(t, xs0, stride); #endif // 1 #else - tile<16, 8, T> * t16 = (tile<16, 8, T> *) &t; - load_ldmatrix(t16[0], xs0 + 0*stride, stride); - load_ldmatrix(t16[1], xs0 + 16*stride, stride); + load_generic(t, xs0, stride); +#endif // __CUDA_ARCH__ == GGML_CUDA_CC_VOLTA +#endif // TURING_MMA_AVAILABLE + } + + static __device__ __forceinline__ void load_ldmatrix( + tile<8, 4, half2, DATA_LAYOUT_I_MAJOR_MIRRORED> & t, const half2 * __restrict__ xs0, const int stride) { + ggml_cuda_memcpy_1<4*sizeof(half2)>(t.x, xs0 + t.get_i(0)*stride); + } + + static __device__ __forceinline__ void load_ldmatrix( + tile<8, 4, half2, DATA_LAYOUT_J_MAJOR_MIRRORED> & t, const half2 * __restrict__ xs0, const int stride) { +#pragma unroll + for (int l0 = 0; l0 < t.ne; l0 += 2) { + ggml_cuda_memcpy_1<2*sizeof(half2)>(t.x + l0, xs0 + t.get_i(l0)*stride + t.get_j(l0)); + } + } + + static __device__ __forceinline__ void load_ldmatrix( + tile<32, 4, half2> & t, const half2 * __restrict__ xs0, const int stride) { +#if __CUDA_ARCH__ == GGML_CUDA_CC_VOLTA + ggml_cuda_memcpy_1<4*sizeof(half2)>(t.x, xs0 + t.get_i(0)*stride); +#else + GGML_UNUSED_VARS(t, xs0, stride); + NO_DEVICE_CODE; #endif // __CUDA_ARCH__ == GGML_CUDA_CC_VOLTA } @@ -747,12 +881,14 @@ namespace ggml_cuda_mma { : "r"(Axi[2]), "r"(Axi[3]), "r"(Bxi[3])); #endif // __CUDA_ARCH__ >= GGML_CUDA_CC_AMPERE #elif defined(AMD_WMMA_AVAILABLE) +#if defined(RDNA4) using halfx8_t = __attribute__((ext_vector_type(8))) _Float16; using floatx8_t = __attribute__((ext_vector_type(8))) float; floatx8_t& acc_frag = reinterpret_cast(D.x[0]); const halfx8_t& a_frag = reinterpret_cast(A.x[0]); const halfx8_t& b_frag = reinterpret_cast(B.x[0]); acc_frag = __builtin_amdgcn_wmma_f32_16x16x16_f16_w32_gfx12(a_frag, b_frag, acc_frag); +#endif // RDNA4 #else GGML_UNUSED_VARS(D, A, B); NO_DEVICE_CODE; @@ -762,12 +898,14 @@ namespace ggml_cuda_mma { static __device__ __forceinline__ void mma( tile<16, 16, float> & D, const tile<16, 8, nv_bfloat162> & A, const tile<16, 8, nv_bfloat162> & B) { #if defined(AMD_WMMA_AVAILABLE) +#if defined(RDNA4) using bf16x8_t = __attribute__((ext_vector_type(8))) __bf16; using floatx8_t = __attribute__((ext_vector_type(8))) float; floatx8_t& acc_frag = reinterpret_cast(D.x[0]); const bf16x8_t& a_frag = reinterpret_cast(A.x[0]); const bf16x8_t& b_frag = reinterpret_cast(B.x[0]); acc_frag = __builtin_amdgcn_wmma_f32_16x16x16_bf16_w32_gfx12(a_frag, b_frag, acc_frag); +#endif // RDNA4 #else GGML_UNUSED_VARS(D, A, B); NO_DEVICE_CODE; @@ -796,14 +934,14 @@ namespace ggml_cuda_mma { #endif // defined(CDNA3) #elif defined(AMD_WMMA_AVAILABLE) - using int32x2_t = __attribute__((__vector_size__(2 * sizeof(int)))) int; - int32x2_t * a_vec = (int32x2_t *) A.x; - int32x2_t * b_vec = (int32x2_t *) B.x; using int32x8_t = __attribute__((__vector_size__(8 * sizeof(int)))) int; int32x8_t * acc = (int32x8_t *) D.x; #if defined(RDNA4) + using int32x2_t = __attribute__((__vector_size__(2 * sizeof(int)))) int; + int32x2_t * a_vec = (int32x2_t *) A.x; + int32x2_t * b_vec = (int32x2_t *) B.x; acc[0] = __builtin_amdgcn_wmma_i32_16x16x16_iu8_w32_gfx12( true, @@ -822,7 +960,30 @@ namespace ggml_cuda_mma { acc[0], true ); -#endif // defined(RDNA4) + +#elif defined(RDNA3) + using int32x4_t = __attribute__((__vector_size__(4 * sizeof(int)))) int; + int32x4_t * a_vec = (int32x4_t *) A.x; + int32x4_t * b_vec = (int32x4_t *) B.x; + + acc[0] = __builtin_amdgcn_wmma_i32_16x16x16_iu8_w32( + true, + a_vec[0], + true, + b_vec[0], + acc[0], + true + ); + + acc[0] = __builtin_amdgcn_wmma_i32_16x16x16_iu8_w32( + true, + a_vec[1], + true, + b_vec[1], + acc[0], + true + ); +#endif // RDNA4 #else GGML_UNUSED_VARS(D, A, B); @@ -860,14 +1021,14 @@ namespace ggml_cuda_mma { template static __device__ __forceinline__ void mma( tile<32, J, T1> & D, const tile<32, K, T2> & A, const tile & B) { - tile<16, J, T1> * D16 = (tile<16, J, T1> *) &D; - tile<16, K, T2> * A16 = (tile<16, K, T2> *) &A; + tile <16, J, T1> * D16 = reinterpret_cast< tile<16, J, T1> *>(&D); + const tile<16, K, T2> * A16 = reinterpret_cast *>(&A); mma(D16[0], A16[0], B); mma(D16[1], A16[1], B); } static __device__ __forceinline__ void mma( - tile<32, 8, float> & D, const tile<32, 8, half2> & A, const tile<8, 8, half2> & B) { + tile<32, 8, float> & D, const tile<32, 4, half2> & A, const tile<8, 4, half2, DATA_LAYOUT_I_MAJOR_MIRRORED> & B) { #if __CUDA_ARCH__ == GGML_CUDA_CC_VOLTA const int * Axi = (const int *) A.x; const int * Bxi = (const int *) B.x; @@ -880,46 +1041,69 @@ namespace ggml_cuda_mma { "{%0, %1, %2, %3, %4, %5, %6, %7}, {%8, %9}, {%10, %11}, {%0, %1, %2, %3, %4, %5, %6, %7};" : "+r"(Dxi[0]), "+r"(Dxi[1]), "+r"(Dxi[2]), "+r"(Dxi[3]), "+r"(Dxi[4]), "+r"(Dxi[5]), "+r"(Dxi[6]), "+r"(Dxi[7]) : "r"(Axi[2]), "r"(Axi[3]), "r"(Bxi[2]), "r"(Bxi[3])); - asm("mma.sync.aligned.m8n8k4.row.col.f32.f16.f16.f32 " - "{%0, %1, %2, %3, %4, %5, %6, %7}, {%8, %9}, {%10, %11}, {%0, %1, %2, %3, %4, %5, %6, %7};" - : "+r"(Dxi[0]), "+r"(Dxi[1]), "+r"(Dxi[2]), "+r"(Dxi[3]), "+r"(Dxi[4]), "+r"(Dxi[5]), "+r"(Dxi[6]), "+r"(Dxi[7]) - : "r"(Axi[4]), "r"(Axi[5]), "r"(Bxi[4]), "r"(Bxi[5])); - asm("mma.sync.aligned.m8n8k4.row.col.f32.f16.f16.f32 " - "{%0, %1, %2, %3, %4, %5, %6, %7}, {%8, %9}, {%10, %11}, {%0, %1, %2, %3, %4, %5, %6, %7};" - : "+r"(Dxi[0]), "+r"(Dxi[1]), "+r"(Dxi[2]), "+r"(Dxi[3]), "+r"(Dxi[4]), "+r"(Dxi[5]), "+r"(Dxi[6]), "+r"(Dxi[7]) - : "r"(Axi[6]), "r"(Axi[7]), "r"(Bxi[6]), "r"(Bxi[7])); #else - tile <16, 8, float> * D16 = reinterpret_cast *>(&D); - const tile<16, 8, half2> * A16 = reinterpret_cast *>(&A); - mma(D16[0], A16[0], B); - mma(D16[1], A16[1], B); -#endif // __CUDA_ARCH__ >= GGML_CUDA_CC_AMPERE + GGML_UNUSED_VARS(D, A, B); + NO_DEVICE_CODE; +#endif // __CUDA_ARCH__ >= GGML_CUDA_CC_VOLTA + } + + static __device__ __forceinline__ void mma( + tile<32, 4, half2> & D, const tile<32, 4, half2> & A, const tile<8, 4, half2, DATA_LAYOUT_J_MAJOR_MIRRORED> & B) { +#if __CUDA_ARCH__ == GGML_CUDA_CC_VOLTA + const int * Axi = (const int *) A.x; + const int * Bxi = (const int *) B.x; + int * Dxi = (int *) D.x; + asm("mma.sync.aligned.m8n8k4.row.row.f16.f16.f16.f16 " + "{%0, %1, %2, %3}, {%4, %5}, {%6, %7}, {%0, %1, %2, %3};" + : "+r"(Dxi[0]), "+r"(Dxi[1]), "+r"(Dxi[2]), "+r"(Dxi[3]) + : "r"(Axi[0]), "r"(Axi[1]), "r"(Bxi[0]), "r"(Bxi[1])); + asm("mma.sync.aligned.m8n8k4.row.row.f16.f16.f16.f16 " + "{%0, %1, %2, %3}, {%4, %5}, {%6, %7}, {%0, %1, %2, %3};" + : "+r"(Dxi[0]), "+r"(Dxi[1]), "+r"(Dxi[2]), "+r"(Dxi[3]) + : "r"(Axi[2]), "r"(Axi[3]), "r"(Bxi[2]), "r"(Bxi[3])); +#else + GGML_UNUSED_VARS(D, A, B); + NO_DEVICE_CODE; +#endif // __CUDA_ARCH__ >= GGML_CUDA_CC_VOLTA } static __device__ __forceinline__ void mma( tile<16, 16, int> & D, const tile<16, 4, int> & A, const tile<16, 4, int> & B) { #if defined(AMD_WMMA_AVAILABLE) - using int32x2_t = __attribute__((__vector_size__(2 * sizeof(int)))) int; - int32x2_t * a_vec = (int32x2_t *) A.x; - int32x2_t * b_vec = (int32x2_t *) B.x; + using int32x8_t = __attribute__((__vector_size__(8 * sizeof(int)))) int; + int32x8_t * acc = (int32x8_t *) D.x; +#if defined(RDNA4) + using int32x2_t = __attribute__((__vector_size__(2 * sizeof(int)))) int; + int32x2_t * a_vec = (int32x2_t *) A.x; + int32x2_t * b_vec = (int32x2_t *) B.x; - using int32x8_t = __attribute__((__vector_size__(8 * sizeof(int)))) int; - int32x8_t * acc = (int32x8_t *) D.x; + acc[0] = __builtin_amdgcn_wmma_i32_16x16x16_iu8_w32_gfx12( + true, + a_vec[0], + true, + b_vec[0], + acc[0], + false + ); +#elif defined(RDNA3) + using int32x4_t = __attribute__((__vector_size__(4 * sizeof(int)))) int; + int32x4_t * a_vec = (int32x4_t *) A.x; + int32x4_t * b_vec = (int32x4_t *) B.x; - acc[0] = __builtin_amdgcn_wmma_i32_16x16x16_iu8_w32_gfx12( - true, - a_vec[0], - true, - b_vec[0], - acc[0], - false - ); + acc[0] = __builtin_amdgcn_wmma_i32_16x16x16_iu8_w32( + true, + a_vec[0], + true, + b_vec[0], + acc[0], + false + ); +#endif // RDNA4 #else GGML_UNUSED(D); GGML_UNUSED(A); GGML_UNUSED(B); NO_DEVICE_CODE; -#endif +#endif // AMD_WMMA_AVAILABLE } } - diff --git a/ggml/src/ggml-cuda/mmf.cu b/ggml/src/ggml-cuda/mmf.cu index be2ad1c6b6..7cf33f0ddf 100644 --- a/ggml/src/ggml-cuda/mmf.cu +++ b/ggml/src/ggml-cuda/mmf.cu @@ -160,9 +160,9 @@ bool ggml_cuda_should_use_mmf(enum ggml_type type, int cc, int warp_size, const case GGML_TYPE_F32: return ampere_mma_available(cc); case GGML_TYPE_F16: - return volta_mma_available(cc) || turing_mma_available(cc) || amd_wmma_available(cc); + return volta_mma_available(cc) || turing_mma_available(cc) || (amd_wmma_available(cc) && GGML_CUDA_CC_IS_RDNA4(cc)); case GGML_TYPE_BF16: - return ampere_mma_available(cc) || amd_wmma_available(cc); + return ampere_mma_available(cc) || (amd_wmma_available(cc) && GGML_CUDA_CC_IS_RDNA4(cc)); default: return false; } diff --git a/ggml/src/ggml-cuda/mmf.cuh b/ggml/src/ggml-cuda/mmf.cuh index c2a0a2e42f..e1c695c5c0 100644 --- a/ggml/src/ggml-cuda/mmf.cuh +++ b/ggml/src/ggml-cuda/mmf.cuh @@ -37,23 +37,19 @@ static __global__ void mul_mat_f( typedef tile<16, 8, T> tile_A; typedef tile tile_B; typedef tile<16, tile_C_J, float> tile_C; - - constexpr bool a_supported = tile_A::supported(); - constexpr bool b_supported = tile_B::supported(); - constexpr bool c_supported = tile_C::supported(); - constexpr bool supported = a_supported && b_supported && c_supported; #else - constexpr bool I_16_supported = tile<16, 8, T>::supported() && tile<16, 8, float>::supported(); - constexpr bool I_32_supported = tile<32, 8, T>::supported() && tile<32, 8, float>::supported(); - constexpr bool supported = I_16_supported || I_32_supported; - - constexpr int I_preferred = I_16_supported ? 16 : 32; // For Turing MMA both work but 16 is ~1% faster. - - typedef tile tile_A; - typedef tile<8, 8, T> tile_B; - typedef tile tile_C; +#ifdef VOLTA_MMA_AVAILABLE + if constexpr (!std::is_same_v) {NO_DEVICE_CODE;} else { + typedef tile<32, 4, T, DATA_LAYOUT_I_MAJOR> tile_A; + typedef tile< 8, 4, T, DATA_LAYOUT_I_MAJOR_MIRRORED> tile_B; + typedef tile<32, 8, float, DATA_LAYOUT_I_MAJOR> tile_C; +#else + typedef tile<16, 8, T> tile_A; + typedef tile<8, 8, T> tile_B; + typedef tile<16, 8, float> tile_C; +#endif // VOLTA_MMA_AVAILABLE #endif // defined(AMD_WMMA_AVAILABLE) - if constexpr (!supported) { + if constexpr (!tile_A::supported() || !tile_B::supported() || !tile_C::supported()) { NO_DEVICE_CODE; return; } @@ -248,6 +244,9 @@ static __global__ void mul_mat_f( } } } +#ifdef VOLTA_MMA_AVAILABLE + } +#endif //VOLTA_MMA_AVAILABLE #else GGML_UNUSED_VARS(x, y, ids, dst, ncols, ncols_dst_total, nchannels_dst, stride_row, stride_col_y, stride_col_dst, @@ -278,27 +277,24 @@ static __global__ void mul_mat_f_ids( typedef tile<16, 8, T> tile_A; typedef tile tile_B; typedef tile<16, tile_C_J, float> tile_C; - - constexpr bool a_supported = tile_A::supported(); - constexpr bool b_supported = tile_B::supported(); - constexpr bool c_supported = tile_C::supported(); - constexpr bool supported = a_supported && b_supported && c_supported; #else - constexpr bool I_16_supported = tile<16, 8, T>::supported() && tile<16, 8, float>::supported(); - constexpr bool I_32_supported = tile<32, 8, T>::supported() && tile<32, 8, float>::supported(); - constexpr bool supported = I_16_supported || I_32_supported; - - constexpr int I_preferred = I_16_supported ? 16 : 32; // For Turing MMA both work but 16 is ~1% faster. - - typedef tile tile_A; - typedef tile<8, 8, T> tile_B; - typedef tile tile_C; +#ifdef VOLTA_MMA_AVAILABLE + if constexpr (!std::is_same_v) {NO_DEVICE_CODE;} else { + typedef tile<32, 4, T, DATA_LAYOUT_I_MAJOR> tile_A; + typedef tile< 8, 4, T, DATA_LAYOUT_I_MAJOR_MIRRORED> tile_B; + typedef tile<32, 8, float, DATA_LAYOUT_I_MAJOR> tile_C; +#else + typedef tile<16, 8, T> tile_A; + typedef tile<8, 8, T> tile_B; + typedef tile<16, 8, float> tile_C; +#endif // VOLTA_MMA_AVAILABLE #endif // defined(AMD_WMMA_AVAILABLE) - if constexpr (!supported) { + if constexpr (!tile_A::supported() || !tile_B::supported() || !tile_C::supported()) { NO_DEVICE_CODE; return; } + constexpr int warp_size = ggml_cuda_get_physical_warp_size(); constexpr int tile_k_padded = warp_size + 4; constexpr int ntA = rows_per_block / tile_A::I; @@ -517,6 +513,9 @@ static __global__ void mul_mat_f_ids( } } } +#ifdef VOLTA_MMA_AVAILABLE + } +#endif // VOLTA_MMA_AVAILABLE #else GGML_UNUSED_VARS(x, y, ids_src_compact, ids_dst_compact, expert_bounds, dst, ncols, ncols_dst_total, nchannels_dst, stride_row, stride_col_y, stride_col_dst, diff --git a/ggml/src/ggml-cuda/mmq.cu b/ggml/src/ggml-cuda/mmq.cu index 03ceba874d..f7a2cbca90 100644 --- a/ggml/src/ggml-cuda/mmq.cu +++ b/ggml/src/ggml-cuda/mmq.cu @@ -307,10 +307,9 @@ bool ggml_cuda_should_use_mmq(enum ggml_type type, int cc, int64_t ne11) { } if (amd_wmma_available(cc)) { - if (GGML_CUDA_CC_IS_RDNA4(cc)) { - return true; - } + return true; } - return (!GGML_CUDA_CC_IS_RDNA3(cc) && !GGML_CUDA_CC_IS_CDNA(cc)) || ne11 < MMQ_DP4A_MAX_BATCH_SIZE; + return (!GGML_CUDA_CC_IS_CDNA(cc)) || ne11 < MMQ_DP4A_MAX_BATCH_SIZE; + } diff --git a/ggml/src/ggml-cuda/mmq.cuh b/ggml/src/ggml-cuda/mmq.cuh index 82468b384e..1298f99fff 100644 --- a/ggml/src/ggml-cuda/mmq.cuh +++ b/ggml/src/ggml-cuda/mmq.cuh @@ -1542,8 +1542,10 @@ static __device__ __forceinline__ void vec_dot_q2_K_q8_1_mma( tile_C Cm; if (k01 >= MMQ_TILE_NE_K * 3/4) { tile_A A1; - A1.x[0] = 0x01010101; - A1.x[1] = 0x01010101; +#pragma unroll + for (int l = 0; l < tile_A::ne; ++l) { + A1.x[l] = 0x01010101; + } mma(Cm, A1, B); } diff --git a/ggml/src/ggml-cuda/pad.cu b/ggml/src/ggml-cuda/pad.cu index 29aef33c1a..660c192e48 100644 --- a/ggml/src/ggml-cuda/pad.cu +++ b/ggml/src/ggml-cuda/pad.cu @@ -1,9 +1,17 @@ #include "pad.cuh" +#include + +__device__ __forceinline__ int64_t wrap_around(int64_t coord, int64_t size) { + // + size ensures negatives are handled properly + return (coord + size) % size; +} + static __global__ void pad_f32(const float * src, float * dst, const int lp0, const int rp0, const int lp1, const int rp1, const int lp2, const int rp2, const int lp3, const int rp3, - const int ne0, const int ne1, const int ne2, const int ne3) { + const int ne0, const int ne1, const int ne2, const int ne3, + const bool circular) { // blockIdx.z: i3*ne2+i2 // blockIdx.y: i1 // blockIDx.x: i0 / CUDA_PAD_BLOCK_SIZE @@ -12,61 +20,84 @@ static __global__ void pad_f32(const float * src, float * dst, int i1 = blockIdx.y; int i2 = blockIdx.z % ne2; int i3 = blockIdx.z / ne2; + if (i0 >= ne0 || i1 >= ne1 || i2 >= ne2 || i3 >= ne3) { return; } - // operation - const int64_t dst_idx = i3*(ne0*ne1*ne2) + i2*(ne0*ne1) + i1*ne0 + i0; - if ((i0 >= lp0 && i0 < ne0 - rp0) && - (i1 >= lp1 && i1 < ne1 - rp1) && - (i2 >= lp2 && i2 < ne2 - rp2) && - (i3 >= lp3 && i3 < ne3 - rp3)) { - const int64_t i00 = i0 - lp0; - const int64_t i01 = i1 - lp1; - const int64_t i02 = i2 - lp2; - const int64_t i03 = i3 - lp3; - const int64_t ne02 = ne2 - lp2 - rp2; - const int64_t ne01 = ne1 - lp1 - rp1; - const int64_t ne00 = ne0 - lp0 - rp0; + const int64_t dst_idx = i3 * (ne0 * ne1 * ne2) + i2 * (ne0 * ne1) + i1 * ne0 + i0; - const int64_t src_idx = i03*(ne00*ne01*ne02) + i02*(ne00*ne01) + i01*ne00 + i00; + if (!circular) { + if ((i0 >= lp0 && i0 < ne0 - rp0) && (i1 >= lp1 && i1 < ne1 - rp1) && (i2 >= lp2 && i2 < ne2 - rp2) && + (i3 >= lp3 && i3 < ne3 - rp3)) { + const int64_t i00 = i0 - lp0; + const int64_t i01 = i1 - lp1; + const int64_t i02 = i2 - lp2; + const int64_t i03 = i3 - lp3; + const int64_t ne02 = ne2 - lp2 - rp2; + const int64_t ne01 = ne1 - lp1 - rp1; + const int64_t ne00 = ne0 - lp0 - rp0; + + const int64_t src_idx = i03 * (ne00 * ne01 * ne02) + i02 * (ne00 * ne01) + i01 * ne00 + i00; + + dst[dst_idx] = src[src_idx]; + } else { + dst[dst_idx] = 0.0f; + } + } + // circular means on a torus, so x and y wrap around + else { + const int64_t ne00 = ne0 - lp0 - rp0; + const int64_t ne01 = ne1 - lp1 - rp1; + const int64_t ne02 = ne2 - lp2 - rp2; + const int64_t ne03 = ne3 - lp3 - rp3; + + const int64_t i00 = wrap_around(i0 - lp0, ne00); + const int64_t i01 = wrap_around(i1 - lp1, ne01); + const int64_t i02 = wrap_around(i2 - lp2, ne02); + const int64_t i03 = wrap_around(i3 - lp3, ne03); + + const int64_t src_idx = i03 * (ne00 * ne01 * ne02) + i02 * (ne00 * ne01) + i01 * ne00 + i00; dst[dst_idx] = src[src_idx]; - } else { - dst[dst_idx] = 0.0f; } } + static void pad_f32_cuda(const float * src, float * dst, const int lp0, const int rp0, const int lp1, const int rp1, const int lp2, const int rp2, const int lp3, const int rp3, - const int ne0, const int ne1, const int ne2, const int ne3, cudaStream_t stream) { - int num_blocks = (ne0 + CUDA_PAD_BLOCK_SIZE - 1) / CUDA_PAD_BLOCK_SIZE; - dim3 gridDim(num_blocks, ne1, ne2*ne3); - pad_f32<<>>(src, dst, lp0, rp0, lp1, rp1, lp2, rp2, lp3, rp3, ne0, ne1, ne2, ne3); + const int ne0, const int ne1, const int ne2, const int ne3, + const bool circular, cudaStream_t stream) { + int num_blocks = (ne0 + CUDA_PAD_BLOCK_SIZE - 1) / CUDA_PAD_BLOCK_SIZE; + dim3 gridDim(num_blocks, ne1, ne2 * ne3); + pad_f32<<>>(src, dst, + lp0, rp0, lp1, rp1, lp2, rp2, lp3, rp3, + ne0, ne1, ne2, ne3, circular); } void ggml_cuda_op_pad(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { - const ggml_tensor * src0 = dst->src[0]; - const float * src0_d = (const float *)src0->data; - float * dst_d = (float *)dst->data; - cudaStream_t stream = ctx.stream(); + const ggml_tensor * src0 = dst->src[0]; + const float * src0_d = (const float *) src0->data; + float * dst_d = (float *) dst->data; + cudaStream_t stream = ctx.stream(); GGML_ASSERT(src0->type == GGML_TYPE_F32); GGML_ASSERT(dst->type == GGML_TYPE_F32); GGML_ASSERT(ggml_is_contiguous(src0)); - const int32_t lp0 = ((const int32_t*)(dst->op_params))[0]; - const int32_t rp0 = ((const int32_t*)(dst->op_params))[1]; - const int32_t lp1 = ((const int32_t*)(dst->op_params))[2]; - const int32_t rp1 = ((const int32_t*)(dst->op_params))[3]; - const int32_t lp2 = ((const int32_t*)(dst->op_params))[4]; - const int32_t rp2 = ((const int32_t*)(dst->op_params))[5]; - const int32_t lp3 = ((const int32_t*)(dst->op_params))[6]; - const int32_t rp3 = ((const int32_t*)(dst->op_params))[7]; + const int32_t lp0 = ((const int32_t *) (dst->op_params))[0]; + const int32_t rp0 = ((const int32_t *) (dst->op_params))[1]; + const int32_t lp1 = ((const int32_t *) (dst->op_params))[2]; + const int32_t rp1 = ((const int32_t *) (dst->op_params))[3]; + const int32_t lp2 = ((const int32_t *) (dst->op_params))[4]; + const int32_t rp2 = ((const int32_t *) (dst->op_params))[5]; + const int32_t lp3 = ((const int32_t *) (dst->op_params))[6]; + const int32_t rp3 = ((const int32_t *) (dst->op_params))[7]; + const int32_t circular = ((const int32_t *) (dst->op_params))[8]; pad_f32_cuda(src0_d, dst_d, lp0, rp0, lp1, rp1, lp2, rp2, lp3, rp3, - dst->ne[0], dst->ne[1], dst->ne[2], dst->ne[3], stream); + dst->ne[0], dst->ne[1], dst->ne[2], dst->ne[3], + (bool) circular, stream); } diff --git a/ggml/src/ggml-cuda/solve_tri.cu b/ggml/src/ggml-cuda/solve_tri.cu index 2e2b39720f..e161d4dc43 100644 --- a/ggml/src/ggml-cuda/solve_tri.cu +++ b/ggml/src/ggml-cuda/solve_tri.cu @@ -3,7 +3,6 @@ #include "solve_tri.cuh" #define MAX_N_FAST 64 -#define MAX_K_FAST 32 // ====================== // Fast Kernel (n <= 64, k <= 32) - Warp-based parallel reduction @@ -48,65 +47,58 @@ static __global__ void solve_tri_f32_fast(const float * __restrict__ A, float * X_batch = (float *) (X + i02 * nb2 + i03 * nb3); __shared__ float sA[MAX_N_FAST * MAX_N_FAST]; - __shared__ float sXt[MAX_N_FAST * (MAX_K_FAST + 1)]; const int offset = threadIdx.x + threadIdx.y * blockDim.x; #pragma unroll for (int i = 0; i < n * n; i += k * WARP_SIZE) { - int i0 = i + offset; + const int i0 = i + offset; if (i0 < n * n) { sA[i0] = A_batch[i0]; } } - const int rows_per_warp = (n + WARP_SIZE - 1) / WARP_SIZE; - -#pragma unroll - for (int i = 0; i < rows_per_warp; i++) { - const int i0 = lane + i * WARP_SIZE; - if (i0 < n) { - sXt[col_idx * n + i0] = B_batch[i0 * k + col_idx]; - } - } - __syncthreads(); + float x_low = (lane < n) ? B_batch[lane * k + col_idx] : 0.0f; + float x_high = (WARP_SIZE + lane < n) ? B_batch[(WARP_SIZE + lane) * k + col_idx] : 0.0f; + + const int half = WARP_SIZE; + const int nrows_low = (n < half) ? n : half; + #pragma unroll - for (int row = 0; row < n; ++row) { + for (int row = 0; row < nrows_low; ++row) { float sum = 0.0f; - - { - int j = lane; - if (j < row) { - sum += sA[row * n + j] * sXt[col_idx * n + j]; - } + if (lane < row) { + sum += sA[row * n + lane] * x_low; } - if (row >= WARP_SIZE) { - int j = WARP_SIZE + lane; - if (j < row) { - sum += sA[row * n + j] * sXt[col_idx * n + j]; - } - } - sum = warp_reduce_sum(sum); - if (lane == 0) { - const float b_val = sXt[col_idx * n + row]; - const float a_diag = sA[row * n + row]; - // no safeguards for division by zero because that indicates corrupt - // data anyway - sXt[col_idx * n + row] = (b_val - sum) / a_diag; + if (lane == row) { + x_low = (x_low - sum) / sA[row * n + row]; } } - __syncthreads(); +#pragma unroll + for (int row = half; row < n; ++row) { + float sum = sA[row * n + lane] * x_low; + const int j = half + lane; + if (j < row) { + sum += sA[row * n + j] * x_high; + } + sum = warp_reduce_sum(sum); + + if (lane == row - half) { + x_high = (x_high - sum) / sA[row * n + row]; + } + } #pragma unroll - for (int i = 0; i < rows_per_warp; i++) { - const int i0 = lane + i * WARP_SIZE; - if (i0 < n) { - X_batch[i0 * k + col_idx] = sXt[col_idx * n + i0]; + for (int rr = 0; rr < 2; ++rr) { + const int row = rr * WARP_SIZE + lane; + if (row < n) { + const float val = (row < half) ? x_low : x_high; + X_batch[row * k + col_idx] = val; } } } diff --git a/ggml/src/ggml-cuda/tri.cu b/ggml/src/ggml-cuda/tri.cu new file mode 100644 index 0000000000..44156b63e7 --- /dev/null +++ b/ggml/src/ggml-cuda/tri.cu @@ -0,0 +1,136 @@ +#include "common.cuh" +#include "convert.cuh" +#include "tri.cuh" +#include "ggml.h" + +template +static __global__ void tri_kernel( + const T * src, T * dst, + const int64_t ne00, const int64_t ne01, const int64_t ne02, const int64_t ne03, + const int64_t nb00, const int64_t nb01, const int64_t nb02, const int64_t nb03, + const int64_t nb0, const int64_t nb1, const int64_t nb2, const int64_t nb3) { + const int64_t i3 = blockIdx.z; + const int64_t i2 = blockIdx.y; + const int64_t i1 = blockIdx.x; + const int64_t split_point = i1 + add_to_split; + + GGML_UNUSED_VARS(nb00, nb0); + + if (i3 >= ne03 || i2 >= ne02 || i1 >= ne01) { + return; + } + + const T * src_row = src + i1*nb01 + i2*nb02 + i3*nb03; + T * dst_row = dst + i1*nb1 + i2*nb2 + i3*nb3; + + if constexpr (prefix_keep) { + for (int64_t i0 = threadIdx.x; i0 < split_point; i0 += blockDim.x) { + dst_row[i0] = src_row[i0]; + } + for (int64_t i0 = threadIdx.x + split_point; i0 < ne00; i0 += blockDim.x) { + dst_row[i0] = ggml_cuda_cast(0.0f); + } + } else { + for (int64_t i0 = threadIdx.x; i0 < split_point; i0 += blockDim.x) { + dst_row[i0] = ggml_cuda_cast(0.0f); + } + for (int64_t i0 = threadIdx.x + split_point; i0 < ne00; i0 += blockDim.x) { + dst_row[i0] = src_row[i0]; + } + } +} + +template +static void tri_cuda( + const T * src, T * dst, + const int64_t ne00, const int64_t ne01, const int64_t ne02, const int64_t ne03, + const int64_t nb00, const int64_t nb01, const int64_t nb02, const int64_t nb03, + const int64_t nb0, const int64_t nb1, const int64_t nb2, const int64_t nb3, + const ggml_tri_type ttype, + cudaStream_t stream) { + + dim3 block_dims(CUDA_TRI_BLOCK_SIZE, 1, 1); + dim3 grid_dims(ne01, ne02, ne03); + const size_t type_size = sizeof(T); + + const int add_to_split = (ttype == GGML_TRI_TYPE_LOWER_DIAG || ttype == GGML_TRI_TYPE_UPPER) ? 1 : 0; + const bool prefix_keep = (ttype == GGML_TRI_TYPE_LOWER || ttype == GGML_TRI_TYPE_LOWER_DIAG); + + if (prefix_keep) { + if (add_to_split == 0) { + tri_kernel<<>>( + src, dst, + ne00, ne01, ne02, ne03, + nb00 / type_size, nb01 / type_size, nb02 / type_size, nb03 / type_size, + nb0 / type_size, nb1 / type_size, nb2 / type_size, nb3 / type_size + ); + } else { // only 0 and 1 supported + tri_kernel<<>>( + src, dst, + ne00, ne01, ne02, ne03, + nb00 / type_size, nb01 / type_size, nb02 / type_size, nb03 / type_size, + nb0 / type_size, nb1 / type_size, nb2 / type_size, nb3 / type_size + ); + } + } else { + if (add_to_split == 0) { + tri_kernel<<>>( + src, dst, + ne00, ne01, ne02, ne03, + nb00 / type_size, nb01 / type_size, nb02 / type_size, nb03 / type_size, + nb0 / type_size, nb1 / type_size, nb2 / type_size, nb3 / type_size + ); + } else { + tri_kernel<<>>( + src, dst, + ne00, ne01, ne02, ne03, + nb00 / type_size, nb01 / type_size, nb02 / type_size, nb03 / type_size, + nb0 / type_size, nb1 / type_size, nb2 / type_size, nb3 / type_size + ); + } + } +} + +void ggml_cuda_op_tri(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { + const ggml_tensor * src0 = dst->src[0]; + cudaStream_t stream = ctx.stream(); + + const ggml_tri_type ttype = static_cast(ggml_get_op_params_i32(dst, 0)); + + GGML_ASSERT(src0->type == dst->type); + + switch(src0->type) { + case GGML_TYPE_F32: + { + tri_cuda( + (const float *)src0->data, (float *)dst->data, + src0->ne[0], src0->ne[1], src0->ne[2], src0->ne[3], + src0->nb[0], src0->nb[1], src0->nb[2], src0->nb[3], + dst->nb[0], dst->nb[1], dst->nb[2], dst->nb[3], + ttype, stream + ); + } break; + case GGML_TYPE_F16: + { + tri_cuda( + (const half *)src0->data, (half *)dst->data, + src0->ne[0], src0->ne[1], src0->ne[2], src0->ne[3], + src0->nb[0], src0->nb[1], src0->nb[2], src0->nb[3], + dst->nb[0], dst->nb[1], dst->nb[2], dst->nb[3], + ttype, stream + ); + } break; + case GGML_TYPE_BF16: + { + tri_cuda( + (const nv_bfloat16 *)src0->data, (nv_bfloat16 *)dst->data, + src0->ne[0], src0->ne[1], src0->ne[2], src0->ne[3], + src0->nb[0], src0->nb[1], src0->nb[2], src0->nb[3], + dst->nb[0], dst->nb[1], dst->nb[2], dst->nb[3], + ttype, stream + ); + } break; + default: + GGML_ABORT("fatal error"); + } +} diff --git a/ggml/src/ggml-cuda/tri.cuh b/ggml/src/ggml-cuda/tri.cuh new file mode 100644 index 0000000000..a4cc66750d --- /dev/null +++ b/ggml/src/ggml-cuda/tri.cuh @@ -0,0 +1,5 @@ +#include "common.cuh" + +#define CUDA_TRI_BLOCK_SIZE 256 + +void ggml_cuda_op_tri(ggml_backend_cuda_context & ctx, ggml_tensor * dst); diff --git a/ggml/src/ggml-metal/ggml-metal-context.m b/ggml/src/ggml-metal/ggml-metal-context.m index e66646284d..42a35736ee 100644 --- a/ggml/src/ggml-metal/ggml-metal-context.m +++ b/ggml/src/ggml-metal/ggml-metal-context.m @@ -24,9 +24,6 @@ struct ggml_metal_command_buffer { }; struct ggml_metal { - id device; - id queue; // currently a pointer to the device queue, but might become separate queue [TAG_QUEUE_PER_BACKEND] - ggml_metal_device_t dev; ggml_metal_library_t lib; @@ -91,15 +88,15 @@ ggml_metal_t ggml_metal_init(ggml_metal_device_t dev) { // init context ggml_metal_t res = calloc(1, sizeof(struct ggml_metal)); - res->device = ggml_metal_device_get_obj(dev); + id device = ggml_metal_device_get_obj(dev); - GGML_LOG_INFO("%s: picking default device: %s\n", __func__, [[res->device name] UTF8String]); + GGML_LOG_INFO("%s: picking default device: %s\n", __func__, [[device name] UTF8String]); // TODO: would it be better to have one queue for the backend and one queue for the device? // the graph encoders and async ops would use the backend queue while the sync ops would use the device queue? //res->queue = [device newCommandQueue]; [TAG_QUEUE_PER_BACKEND] - res->queue = ggml_metal_device_get_queue(dev); - if (res->queue == nil) { + id queue = ggml_metal_device_get_queue(dev); + if (queue == nil) { GGML_LOG_ERROR("%s: error: failed to create command queue\n", __func__); return NULL; } @@ -274,7 +271,8 @@ static struct ggml_metal_buffer_id ggml_metal_get_buffer_id(const struct ggml_te void ggml_metal_set_tensor_async(ggml_metal_t ctx, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size) { @autoreleasepool { // wrap the source data into a Metal buffer - id buf_src = [ctx->device newBufferWithBytes:data + id device = ggml_metal_device_get_obj(ctx->dev); + id buf_src = [device newBufferWithBytes:data length:size options:MTLResourceStorageModeShared]; @@ -289,7 +287,8 @@ void ggml_metal_set_tensor_async(ggml_metal_t ctx, struct ggml_tensor * tensor, // queue the copy operation into the queue of the Metal context // this will be queued at the end, after any currently ongoing GPU operations - id cmd_buf = [ctx->queue commandBuffer]; + id queue = ggml_metal_device_get_queue(ctx->dev); + id cmd_buf = [queue commandBuffer]; id encoder = [cmd_buf blitCommandEncoder]; [encoder copyFromBuffer:buf_src @@ -315,7 +314,8 @@ void ggml_metal_set_tensor_async(ggml_metal_t ctx, struct ggml_tensor * tensor, void ggml_metal_get_tensor_async(ggml_metal_t ctx, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size) { @autoreleasepool { - id buf_dst = [ctx->device newBufferWithBytesNoCopy:data + id device = ggml_metal_device_get_obj(ctx->dev); + id buf_dst = [device newBufferWithBytesNoCopy:data length:size options:MTLResourceStorageModeShared deallocator:nil]; @@ -331,7 +331,8 @@ void ggml_metal_get_tensor_async(ggml_metal_t ctx, const struct ggml_tensor * te // queue the copy operation into the queue of the Metal context // this will be queued at the end, after any currently ongoing GPU operations - id cmd_buf = [ctx->queue commandBuffer]; + id queue = ggml_metal_device_get_queue(ctx->dev); + id cmd_buf = [queue commandBuffer]; id encoder = [cmd_buf blitCommandEncoder]; [encoder copyFromBuffer:bid_src.metal @@ -362,6 +363,9 @@ enum ggml_status ggml_metal_graph_compute(ggml_metal_t ctx, struct ggml_cgraph * // number of threads in addition to the main thread const int n_cb = ctx->n_cb; + // keep the memory wired + ggml_metal_device_rsets_keep_alive(ctx->dev); + // submit the ggml compute graph to the GPU by creating command buffers and encoding the ops in them // the first n_nodes_0 are encoded and submitted for processing directly by the calling thread // while these nodes are processing, we start n_cb threads to enqueue the rest of the nodes @@ -389,7 +393,8 @@ enum ggml_status ggml_metal_graph_compute(ggml_metal_t ctx, struct ggml_cgraph * if (!ctx->capture_started) { // create capture scope - ctx->capture_scope = [[MTLCaptureManager sharedCaptureManager] newCaptureScopeWithDevice:ctx->device]; + id device = ggml_metal_device_get_obj(ctx->dev); + ctx->capture_scope = [[MTLCaptureManager sharedCaptureManager] newCaptureScopeWithDevice:device]; MTLCaptureDescriptor * descriptor = [MTLCaptureDescriptor new]; descriptor.captureObject = ctx->capture_scope; @@ -406,10 +411,13 @@ enum ggml_status ggml_metal_graph_compute(ggml_metal_t ctx, struct ggml_cgraph * } } + // short-hand + id queue = ggml_metal_device_get_queue(ctx->dev); + // the main thread commits the first few commands immediately // cmd_buf[n_cb] { - id cmd_buf = [ctx->queue commandBufferWithUnretainedReferences]; + id cmd_buf = [queue commandBufferWithUnretainedReferences]; [cmd_buf retain]; if (ctx->cmd_bufs[n_cb].obj) { @@ -428,7 +436,7 @@ enum ggml_status ggml_metal_graph_compute(ggml_metal_t ctx, struct ggml_cgraph * // prepare the rest of the command buffers asynchronously (optional) // cmd_buf[0.. n_cb) for (int cb_idx = 0; cb_idx < n_cb; ++cb_idx) { - id cmd_buf = [ctx->queue commandBufferWithUnretainedReferences]; + id cmd_buf = [queue commandBufferWithUnretainedReferences]; [cmd_buf retain]; if (ctx->cmd_bufs[cb_idx].obj) { @@ -589,9 +597,11 @@ void ggml_metal_set_abort_callback(ggml_metal_t ctx, ggml_abort_callback abort_c } bool ggml_metal_supports_family(ggml_metal_t ctx, int family) { - GGML_ASSERT(ctx->device != nil); + GGML_ASSERT(ctx->dev != nil); - return [ctx->device supportsFamily:(MTLGPUFamilyApple1 + family - 1)]; + id device = ggml_metal_device_get_obj(ctx->dev); + + return [device supportsFamily:(MTLGPUFamilyApple1 + family - 1)]; } void ggml_metal_capture_next_compute(ggml_metal_t ctx) { diff --git a/ggml/src/ggml-metal/ggml-metal-device.cpp b/ggml/src/ggml-metal/ggml-metal-device.cpp index 329500a03e..ba3c342751 100644 --- a/ggml/src/ggml-metal/ggml-metal-device.cpp +++ b/ggml/src/ggml-metal/ggml-metal-device.cpp @@ -50,14 +50,14 @@ void ggml_metal_pipelines_add(ggml_metal_pipelines_t ppls, const char * name, gg } ggml_metal_pipeline_t ggml_metal_pipelines_get(ggml_metal_pipelines_t ppls, const char * name) { - if (ppls->data.find(name) == ppls->data.end()) { + if (ppls->data.find(name) == ppls->data.end()) { return nullptr; } return ppls->data[name]; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_base(ggml_metal_library_t lib, ggml_op op) { +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_base(ggml_metal_library_t lib, ggml_op op) { char base[256]; char name[256]; @@ -71,34 +71,30 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_base(ggml_metal_library_t snprintf(base, 256, "kernel_%s", op_str); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_cpy(ggml_metal_library_t lib, ggml_type tsrc, ggml_type tdst) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_cpy(ggml_metal_library_t lib, ggml_type tsrc, ggml_type tdst) { char base[256]; char name[256]; snprintf(base, 256, "kernel_cpy_%s_%s", ggml_type_name(tsrc), ggml_type_name(tdst)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_pool_2d(ggml_metal_library_t lib, const ggml_tensor * op, ggml_op_pool op_pool) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_pool_2d(ggml_metal_library_t lib, const ggml_tensor * op, ggml_op_pool op_pool) { GGML_ASSERT(ggml_is_contiguous(op->src[0])); GGML_ASSERT(op->src[0]->type == GGML_TYPE_F32 && op->src[0]->type == op->type); @@ -115,68 +111,60 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_pool_2d(ggml_metal_library snprintf(base, 256, "kernel_pool_2d_%s_%s", pool_str, ggml_type_name(op->src[0]->type)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_get_rows(ggml_metal_library_t lib, ggml_type tsrc) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_get_rows(ggml_metal_library_t lib, ggml_type tsrc) { char base[256]; char name[256]; snprintf(base, 256, "kernel_get_rows_%s", ggml_type_name(tsrc)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_set_rows(ggml_metal_library_t lib, ggml_type tidx, ggml_type tdst) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_set_rows(ggml_metal_library_t lib, ggml_type tidx, ggml_type tdst) { char base[256]; char name[256]; snprintf(base, 256, "kernel_set_rows_%s_%s", ggml_type_name(tdst), ggml_type_name(tidx)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_repeat(ggml_metal_library_t lib, ggml_type tsrc) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_repeat(ggml_metal_library_t lib, ggml_type tsrc) { char base[256]; char name[256]; snprintf(base, 256, "kernel_repeat_%s", ggml_type_name(tsrc)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_unary(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_unary(ggml_metal_library_t lib, const ggml_tensor * op) { GGML_ASSERT(ggml_is_contiguous(op->src[0])); char base[256]; @@ -187,6 +175,7 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_unary(ggml_metal_library_t const char * op_str = "undefined"; switch (op->op) { case GGML_OP_SCALE: op_str = "scale"; break; + case GGML_OP_FILL: op_str = "fill"; break; case GGML_OP_CLAMP: op_str = "clamp"; break; case GGML_OP_SQR: op_str = "sqr"; break; case GGML_OP_SQRT: op_str = "sqrt"; break; @@ -211,6 +200,8 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_unary(ggml_metal_library_t case GGML_UNARY_OP_HARDSWISH: op_str = "hardswish"; break; case GGML_UNARY_OP_HARDSIGMOID: op_str = "hardsigmoid"; break; case GGML_UNARY_OP_EXP: op_str = "exp"; break; + case GGML_UNARY_OP_SOFTPLUS: op_str = "softplus"; break; + case GGML_UNARY_OP_EXPM1: op_str = "expm1"; break; default: GGML_ABORT("fatal error"); } break; default: GGML_ABORT("fatal error"); @@ -224,17 +215,15 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_unary(ggml_metal_library_t snprintf(base, 256, "kernel_%s_%s%s", op_str, ggml_type_name(op->src[0]->type), suffix); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_glu(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_glu(ggml_metal_library_t lib, const ggml_tensor * op) { GGML_ASSERT(ggml_is_contiguous_1(op->src[0])); char base[256]; @@ -258,17 +247,15 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_glu(ggml_metal_library_t l snprintf(base, 256, "kernel_%s_%s", op_str, ggml_type_name(op->src[0]->type)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_sum(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_sum(ggml_metal_library_t lib, const ggml_tensor * op) { assert(op->op == GGML_OP_SUM); char base[256]; @@ -277,17 +264,15 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_sum(ggml_metal_library_t l snprintf(base, 256, "kernel_op_sum_%s", ggml_type_name(op->src[0]->type)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_sum_rows(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_sum_rows(ggml_metal_library_t lib, const ggml_tensor * op) { GGML_ASSERT(op->src[0]->nb[0] == ggml_type_size(op->src[0]->type)); char base[256]; @@ -306,19 +291,17 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_sum_rows(ggml_metal_librar snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - - ggml_metal_pipeline_set_smem(res, 32*sizeof(float)); + res.smem = 32*sizeof(float); return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_cumsum_blk(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_cumsum_blk(ggml_metal_library_t lib, const ggml_tensor * op) { GGML_ASSERT(op->op == GGML_OP_CUMSUM); char base[256]; @@ -327,17 +310,15 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_cumsum_blk(ggml_metal_libr snprintf(base, 256, "kernel_cumsum_blk_%s", ggml_type_name(op->src[0]->type)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_cumsum_add(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_cumsum_add(ggml_metal_library_t lib, const ggml_tensor * op) { GGML_ASSERT(op->op == GGML_OP_CUMSUM); char base[256]; @@ -346,17 +327,37 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_cumsum_add(ggml_metal_libr snprintf(base, 256, "kernel_cumsum_add_%s", ggml_type_name(op->src[0]->type)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_soft_max(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_tri(ggml_metal_library_t lib, const ggml_tensor * op) { + GGML_ASSERT(op->op == GGML_OP_TRI); + GGML_ASSERT(op->src[0]->nb[0] == ggml_type_size(op->src[0]->type)); + + char base[256]; + char name[256]; + + const char * op_str = "tri"; + const int ttype = op->op_params[0]; + + snprintf(base, 256, "kernel_%s_%s_%d", op_str, ggml_type_name(op->src[0]->type), ttype); + + snprintf(name, 256, "%s", base); + + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + } + + return res; +} + +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_soft_max(ggml_metal_library_t lib, const ggml_tensor * op) { GGML_ASSERT(!op->src[1] || op->src[1]->type == GGML_TYPE_F16 || op->src[1]->type == GGML_TYPE_F32); char base[256]; @@ -373,19 +374,17 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_soft_max(ggml_metal_librar snprintf(base, 256, "kernel_soft_max_%s%s", ggml_type_name(tsrc1), suffix); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - - ggml_metal_pipeline_set_smem(res, 32*sizeof(float)); + res.smem = 32*sizeof(float); return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_ssm_conv(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_ssm_conv(ggml_metal_library_t lib, const ggml_tensor * op) { GGML_ASSERT(op->src[0]->type == GGML_TYPE_F32); GGML_ASSERT(op->src[1]->type == GGML_TYPE_F32); @@ -404,17 +403,15 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_ssm_conv(ggml_metal_librar snprintf(base, 256, "kernel_ssm_conv_%s_%s%s", ggml_type_name(op->src[0]->type), ggml_type_name(op->src[1]->type), suffix); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_ssm_scan(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_ssm_scan(ggml_metal_library_t lib, const ggml_tensor * op) { GGML_TENSOR_LOCALS( int32_t, ne0, op->src[0], ne); char base[256]; @@ -425,19 +422,17 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_ssm_scan(ggml_metal_librar snprintf(base, 256, "kernel_ssm_scan_%s", ggml_type_name(op->src[0]->type)); snprintf(name, 256, "%s_nsg=%d", base, nsg); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - - ggml_metal_pipeline_set_smem(res, 32*sizeof(float)*nsg); + res.smem = 32*sizeof(float)*nsg; return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_rwkv(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_rwkv(ggml_metal_library_t lib, const ggml_tensor * op) { char base[256]; char name[256]; @@ -467,41 +462,37 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_rwkv(ggml_metal_library_t snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mv_ext(ggml_metal_library_t lib, ggml_type tsrc0, ggml_type tsrc1, int nsg, int nxpsg, int r1ptg) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_mul_mv_ext(ggml_metal_library_t lib, ggml_type tsrc0, ggml_type tsrc1, int nsg, int nxpsg, int r1ptg) { char base[256]; char name[256]; snprintf(base, 256, "kernel_mul_mv_ext_%s_%s_r1_%d", ggml_type_name(tsrc0), ggml_type_name(tsrc1), r1ptg); snprintf(name, 256, "%s_nsg=%d_nxpsg=%d", base, nsg, nxpsg); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + ggml_metal_cv_t cv = ggml_metal_cv_init(); + + ggml_metal_cv_set_int16(cv, nsg, FC_MUL_MV + 0); + ggml_metal_cv_set_int16(cv, nxpsg, FC_MUL_MV + 1); + + res = ggml_metal_library_compile_pipeline(lib, base, name, cv); + + ggml_metal_cv_free(cv); } - ggml_metal_cv_t cv = ggml_metal_cv_init(); - - ggml_metal_cv_set_int16(cv, nsg, FC_MUL_MV + 0); - ggml_metal_cv_set_int16(cv, nxpsg, FC_MUL_MV + 1); - - res = ggml_metal_library_compile_pipeline(lib, base, name, cv); - - ggml_metal_cv_free(cv); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mm(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_mul_mm(ggml_metal_library_t lib, const ggml_tensor * op) { char base[256]; char name[256]; @@ -514,27 +505,25 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mm(ggml_metal_library_ snprintf(base, 256, "kernel_mul_mm_%s_%s", ggml_type_name(tsrc0), ggml_type_name(tsrc1)); snprintf(name, 256, "%s_bci=%d_bco=%d", base, bc_inp, bc_out); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + ggml_metal_cv_t cv = ggml_metal_cv_init(); + + ggml_metal_cv_set_bool(cv, bc_inp, FC_MUL_MM + 0); + ggml_metal_cv_set_bool(cv, bc_out, FC_MUL_MM + 1); + + res = ggml_metal_library_compile_pipeline(lib, base, name, cv); + + ggml_metal_cv_free(cv); } - ggml_metal_cv_t cv = ggml_metal_cv_init(); - - ggml_metal_cv_set_bool(cv, bc_inp, FC_MUL_MM + 0); - ggml_metal_cv_set_bool(cv, bc_out, FC_MUL_MM + 1); - - res = ggml_metal_library_compile_pipeline(lib, base, name, cv); - - ggml_metal_cv_free(cv); - // when the output size is not multiple of 64x32, we need extra smem to prevent out-of-bounds writes - ggml_metal_pipeline_set_smem(res, bc_out ? 8192 : 4096 + 2048); + res.smem = bc_out ? 8192 : 4096 + 2048; return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mv(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_mul_mv(ggml_metal_library_t lib, const ggml_tensor * op) { GGML_TENSOR_LOCALS( int32_t, ne0, op->src[0], ne); GGML_TENSOR_LOCALS( int32_t, ne1, op->src[1], ne); @@ -689,49 +678,43 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mv(ggml_metal_library_ snprintf(base, 256, "kernel_mul_mv_%s_%s%s", ggml_type_name(tsrc0), ggml_type_name(tsrc1), suffix); snprintf(name, 256, "%s_nsg=%d", base, nsg); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + ggml_metal_cv_t cv = ggml_metal_cv_init(); + + ggml_metal_cv_set_int16(cv, nsg, FC_MUL_MV + 0); + + res = ggml_metal_library_compile_pipeline(lib, base, name, cv); + + ggml_metal_cv_free(cv); } - ggml_metal_cv_t cv = ggml_metal_cv_init(); - - ggml_metal_cv_set_int16(cv, nsg, FC_MUL_MV + 0); - - res = ggml_metal_library_compile_pipeline(lib, base, name, cv); - - ggml_metal_cv_free(cv); - - ggml_metal_pipeline_set_nr0 (res, nr0); - ggml_metal_pipeline_set_nr1 (res, nr1); - ggml_metal_pipeline_set_nsg (res, nsg); - ggml_metal_pipeline_set_smem(res, smem); + res.nr0 = nr0; + res.nr1 = nr1; + res.nsg = nsg; + res.smem = smem; return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mm_id_map0(ggml_metal_library_t lib, int ne02, int ne20) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_mul_mm_id_map0(ggml_metal_library_t lib, int ne02, int ne20) { char base[256]; char name[256]; snprintf(base, 256, "kernel_mul_mm_id_map0_ne20_%d", ne20); snprintf(name, 256, "%s_ne02=%d", base, ne02); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - - const size_t smem = (size_t) ne02*ne20*sizeof(uint16_t); - - ggml_metal_pipeline_set_smem(res, smem); + res.smem = (size_t) ne02*ne20*sizeof(uint16_t); return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mm_id(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_mul_mm_id(ggml_metal_library_t lib, const ggml_tensor * op) { char base[256]; char name[256]; @@ -743,25 +726,23 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mm_id(ggml_metal_libra snprintf(base, 256, "kernel_mul_mm_id_%s_%s", ggml_type_name(tsrc0), ggml_type_name(tsrc1)); snprintf(name, 256, "%s_bci=%d", base, bc_inp); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + ggml_metal_cv_t cv = ggml_metal_cv_init(); + + ggml_metal_cv_set_bool(cv, bc_inp, FC_MUL_MM + 0); + + res = ggml_metal_library_compile_pipeline(lib, base, name, cv); + + ggml_metal_cv_free(cv); } - ggml_metal_cv_t cv = ggml_metal_cv_init(); - - ggml_metal_cv_set_bool(cv, bc_inp, FC_MUL_MM + 0); - - res = ggml_metal_library_compile_pipeline(lib, base, name, cv); - - ggml_metal_cv_free(cv); - - ggml_metal_pipeline_set_smem(res, 8192); + res.smem = 8192; return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mv_id(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_mul_mv_id(ggml_metal_library_t lib, const ggml_tensor * op) { GGML_TENSOR_LOCALS( int32_t, ne0, op->src[0], ne); GGML_TENSOR_LOCALS( int32_t, ne1, op->src[1], ne); @@ -909,28 +890,26 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mv_id(ggml_metal_libra snprintf(base, 256, "kernel_mul_mv_id_%s_%s%s", ggml_type_name(tsrc0), ggml_type_name(tsrc1), suffix); snprintf(name, 256, "%s_nsg=%d", base, nsg); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + ggml_metal_cv_t cv = ggml_metal_cv_init(); + + ggml_metal_cv_set_int16(cv, nsg, FC_MUL_MV + 0); + + res = ggml_metal_library_compile_pipeline(lib, base, name, cv); + + ggml_metal_cv_free(cv); } - ggml_metal_cv_t cv = ggml_metal_cv_init(); - - ggml_metal_cv_set_int16(cv, nsg, FC_MUL_MV + 0); - - res = ggml_metal_library_compile_pipeline(lib, base, name, cv); - - ggml_metal_cv_free(cv); - - ggml_metal_pipeline_set_nr0 (res, nr0); - ggml_metal_pipeline_set_nr1 (res, nr1); - ggml_metal_pipeline_set_nsg (res, nsg); - ggml_metal_pipeline_set_smem(res, smem); + res.nr0 = nr0; + res.nr1 = nr1; + res.nsg = nsg; + res.smem = smem; return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_argmax(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_argmax(ggml_metal_library_t lib, const ggml_tensor * op) { GGML_ASSERT(op->src[0]->type == GGML_TYPE_F32); GGML_ASSERT(ggml_is_contiguous_1(op->src[0])); GGML_ASSERT(op->src[0]->nb[0] == ggml_type_size(op->src[0]->type)); @@ -941,19 +920,17 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_argmax(ggml_metal_library_ snprintf(base, 256, "kernel_argmax_%s", ggml_type_name(op->src[0]->type)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - - ggml_metal_pipeline_set_smem(res, 32*(sizeof(float) + sizeof(int32_t))); + res.smem = 32*(sizeof(float) + sizeof(int32_t)); return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_argsort(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_argsort(ggml_metal_library_t lib, const ggml_tensor * op) { assert(op->op == GGML_OP_ARGSORT); char base[256]; @@ -971,17 +948,15 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_argsort(ggml_metal_library snprintf(base, 256, "kernel_argsort_%s_%s_%s", ggml_type_name(op->src[0]->type), ggml_type_name(op->type), order_str); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_argsort_merge(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_argsort_merge(ggml_metal_library_t lib, const ggml_tensor * op) { assert(op->op == GGML_OP_ARGSORT); char base[256]; @@ -999,18 +974,16 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_argsort_merge(ggml_metal_l snprintf(base, 256, "kernel_argsort_merge_%s_%s_%s", ggml_type_name(op->src[0]->type), ggml_type_name(op->type), order_str); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } // note: reuse the argsort kernel for top_k -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_top_k(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_top_k(ggml_metal_library_t lib, const ggml_tensor * op) { assert(op->op == GGML_OP_TOP_K); char base[256]; @@ -1029,17 +1002,15 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_top_k(ggml_metal_library_t snprintf(base, 256, "kernel_argsort_%s_%s_%s", ggml_type_name(op->src[0]->type), ggml_type_name(op->type), order_str); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_top_k_merge(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_top_k_merge(ggml_metal_library_t lib, const ggml_tensor * op) { assert(op->op == GGML_OP_TOP_K); char base[256]; @@ -1057,17 +1028,15 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_top_k_merge(ggml_metal_lib snprintf(base, 256, "kernel_argsort_merge_%s_%s_%s", ggml_type_name(op->src[0]->type), ggml_type_name(op->type), order_str); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext_pad( +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext_pad( ggml_metal_library_t lib, const struct ggml_tensor * op, bool has_mask, @@ -1086,33 +1055,31 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext_pad( has_mask, ncpsg); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + ggml_metal_cv_t cv = ggml_metal_cv_init(); + + ggml_metal_cv_set_bool(cv, has_mask, FC_FLASH_ATTN_EXT_PAD + 0); + //ggml_metal_cv_set_bool(cv, has_sinks, FC_FLASH_ATTN_EXT_PAD + 1); + //ggml_metal_cv_set_bool(cv, has_bias, FC_FLASH_ATTN_EXT_PAD + 2); + //ggml_metal_cv_set_bool(cv, has_scap, FC_FLASH_ATTN_EXT_PAD + 3); + + //ggml_metal_cv_set_int32(cv, ns10, FC_FLASH_ATTN_EXT_PAD + 20); + //ggml_metal_cv_set_int32(cv, ns20, FC_FLASH_ATTN_EXT_PAD + 21); + //ggml_metal_cv_set_int32(cv, nsg, FC_FLASH_ATTN_EXT_PAD + 22); + //ggml_metal_cv_set_int32(cv, nwg, FC_FLASH_ATTN_EXT_PAD + 23); + //ggml_metal_cv_set_int32(cv, nqptg, FC_FLASH_ATTN_EXT_PAD + 24); + ggml_metal_cv_set_int32(cv, ncpsg, FC_FLASH_ATTN_EXT_PAD + 25); + + res = ggml_metal_library_compile_pipeline(lib, base, name, cv); + + ggml_metal_cv_free(cv); } - ggml_metal_cv_t cv = ggml_metal_cv_init(); - - ggml_metal_cv_set_bool(cv, has_mask, FC_FLASH_ATTN_EXT_PAD + 0); - //ggml_metal_cv_set_bool(cv, has_sinks, FC_FLASH_ATTN_EXT_PAD + 1); - //ggml_metal_cv_set_bool(cv, has_bias, FC_FLASH_ATTN_EXT_PAD + 2); - //ggml_metal_cv_set_bool(cv, has_scap, FC_FLASH_ATTN_EXT_PAD + 3); - - //ggml_metal_cv_set_int32(cv, ns10, FC_FLASH_ATTN_EXT_PAD + 20); - //ggml_metal_cv_set_int32(cv, ns20, FC_FLASH_ATTN_EXT_PAD + 21); - //ggml_metal_cv_set_int32(cv, nsg, FC_FLASH_ATTN_EXT_PAD + 22); - //ggml_metal_cv_set_int32(cv, nwg, FC_FLASH_ATTN_EXT_PAD + 23); - //ggml_metal_cv_set_int32(cv, nqptg, FC_FLASH_ATTN_EXT_PAD + 24); - ggml_metal_cv_set_int32(cv, ncpsg, FC_FLASH_ATTN_EXT_PAD + 25); - - res = ggml_metal_library_compile_pipeline(lib, base, name, cv); - - ggml_metal_cv_free(cv); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext_blk( +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext_blk( ggml_metal_library_t lib, const struct ggml_tensor * op, int32_t nqptg, @@ -1131,33 +1098,31 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext_blk( nqptg, ncpsg); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + ggml_metal_cv_t cv = ggml_metal_cv_init(); + + //ggml_metal_cv_set_bool(cv, has_mask, FC_FLASH_ATTN_EXT_BLK + 0); + //ggml_metal_cv_set_bool(cv, has_sinks, FC_FLASH_ATTN_EXT_BLK + 1); + //ggml_metal_cv_set_bool(cv, has_bias, FC_FLASH_ATTN_EXT_BLK + 2); + //ggml_metal_cv_set_bool(cv, has_scap, FC_FLASH_ATTN_EXT_BLK + 3); + + //ggml_metal_cv_set_int32(cv, ns10, FC_FLASH_ATTN_EXT_BLK + 20); + //ggml_metal_cv_set_int32(cv, ns20, FC_FLASH_ATTN_EXT_BLK + 21); + //ggml_metal_cv_set_int32(cv, nsg, FC_FLASH_ATTN_EXT_BLK + 22); + //ggml_metal_cv_set_int32(cv, nwg, FC_FLASH_ATTN_EXT_BLK + 23); + ggml_metal_cv_set_int32(cv, nqptg, FC_FLASH_ATTN_EXT_BLK + 24); + ggml_metal_cv_set_int32(cv, ncpsg, FC_FLASH_ATTN_EXT_BLK + 25); + + res = ggml_metal_library_compile_pipeline(lib, base, name, cv); + + ggml_metal_cv_free(cv); } - ggml_metal_cv_t cv = ggml_metal_cv_init(); - - //ggml_metal_cv_set_bool(cv, has_mask, FC_FLASH_ATTN_EXT_BLK + 0); - //ggml_metal_cv_set_bool(cv, has_sinks, FC_FLASH_ATTN_EXT_BLK + 1); - //ggml_metal_cv_set_bool(cv, has_bias, FC_FLASH_ATTN_EXT_BLK + 2); - //ggml_metal_cv_set_bool(cv, has_scap, FC_FLASH_ATTN_EXT_BLK + 3); - - //ggml_metal_cv_set_int32(cv, ns10, FC_FLASH_ATTN_EXT_BLK + 20); - //ggml_metal_cv_set_int32(cv, ns20, FC_FLASH_ATTN_EXT_BLK + 21); - //ggml_metal_cv_set_int32(cv, nsg, FC_FLASH_ATTN_EXT_BLK + 22); - //ggml_metal_cv_set_int32(cv, nwg, FC_FLASH_ATTN_EXT_BLK + 23); - ggml_metal_cv_set_int32(cv, nqptg, FC_FLASH_ATTN_EXT_BLK + 24); - ggml_metal_cv_set_int32(cv, ncpsg, FC_FLASH_ATTN_EXT_BLK + 25); - - res = ggml_metal_library_compile_pipeline(lib, base, name, cv); - - ggml_metal_cv_free(cv); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext( +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext( ggml_metal_library_t lib, const ggml_tensor * op, bool has_mask, @@ -1198,33 +1163,31 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext( ns20, nsg); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + ggml_metal_cv_t cv = ggml_metal_cv_init(); + + ggml_metal_cv_set_bool(cv, has_mask, FC_FLASH_ATTN_EXT + 0); + ggml_metal_cv_set_bool(cv, has_sinks, FC_FLASH_ATTN_EXT + 1); + ggml_metal_cv_set_bool(cv, has_bias, FC_FLASH_ATTN_EXT + 2); + ggml_metal_cv_set_bool(cv, has_scap, FC_FLASH_ATTN_EXT + 3); + ggml_metal_cv_set_bool(cv, has_kvpad, FC_FLASH_ATTN_EXT + 4); + + ggml_metal_cv_set_bool(cv, bc_mask, FC_FLASH_ATTN_EXT + 10); + + ggml_metal_cv_set_int32(cv, ns10, FC_FLASH_ATTN_EXT + 20); + ggml_metal_cv_set_int32(cv, ns20, FC_FLASH_ATTN_EXT + 21); + ggml_metal_cv_set_int32(cv, nsg, FC_FLASH_ATTN_EXT + 22); + + res = ggml_metal_library_compile_pipeline(lib, base, name, cv); + + ggml_metal_cv_free(cv); } - ggml_metal_cv_t cv = ggml_metal_cv_init(); - - ggml_metal_cv_set_bool(cv, has_mask, FC_FLASH_ATTN_EXT + 0); - ggml_metal_cv_set_bool(cv, has_sinks, FC_FLASH_ATTN_EXT + 1); - ggml_metal_cv_set_bool(cv, has_bias, FC_FLASH_ATTN_EXT + 2); - ggml_metal_cv_set_bool(cv, has_scap, FC_FLASH_ATTN_EXT + 3); - ggml_metal_cv_set_bool(cv, has_kvpad, FC_FLASH_ATTN_EXT + 4); - - ggml_metal_cv_set_bool(cv, bc_mask, FC_FLASH_ATTN_EXT + 10); - - ggml_metal_cv_set_int32(cv, ns10, FC_FLASH_ATTN_EXT + 20); - ggml_metal_cv_set_int32(cv, ns20, FC_FLASH_ATTN_EXT + 21); - ggml_metal_cv_set_int32(cv, nsg, FC_FLASH_ATTN_EXT + 22); - - res = ggml_metal_library_compile_pipeline(lib, base, name, cv); - - ggml_metal_cv_free(cv); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext_vec( +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext_vec( ggml_metal_library_t lib, const ggml_tensor * op, bool has_mask, @@ -1262,32 +1225,30 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext_vec( ns20, nsg, nwg); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + ggml_metal_cv_t cv = ggml_metal_cv_init(); + + ggml_metal_cv_set_bool(cv, has_mask, FC_FLASH_ATTN_EXT_VEC + 0); + ggml_metal_cv_set_bool(cv, has_sinks, FC_FLASH_ATTN_EXT_VEC + 1); + ggml_metal_cv_set_bool(cv, has_bias, FC_FLASH_ATTN_EXT_VEC + 2); + ggml_metal_cv_set_bool(cv, has_scap, FC_FLASH_ATTN_EXT_VEC + 3); + ggml_metal_cv_set_bool(cv, has_kvpad, FC_FLASH_ATTN_EXT_VEC + 4); + + ggml_metal_cv_set_int32(cv, ns10, FC_FLASH_ATTN_EXT_VEC + 20); + ggml_metal_cv_set_int32(cv, ns20, FC_FLASH_ATTN_EXT_VEC + 21); + ggml_metal_cv_set_int32(cv, nsg, FC_FLASH_ATTN_EXT_VEC + 22); + ggml_metal_cv_set_int32(cv, nwg, FC_FLASH_ATTN_EXT_VEC + 23); + + res = ggml_metal_library_compile_pipeline(lib, base, name, cv); + + ggml_metal_cv_free(cv); } - ggml_metal_cv_t cv = ggml_metal_cv_init(); - - ggml_metal_cv_set_bool(cv, has_mask, FC_FLASH_ATTN_EXT_VEC + 0); - ggml_metal_cv_set_bool(cv, has_sinks, FC_FLASH_ATTN_EXT_VEC + 1); - ggml_metal_cv_set_bool(cv, has_bias, FC_FLASH_ATTN_EXT_VEC + 2); - ggml_metal_cv_set_bool(cv, has_scap, FC_FLASH_ATTN_EXT_VEC + 3); - ggml_metal_cv_set_bool(cv, has_kvpad, FC_FLASH_ATTN_EXT_VEC + 4); - - ggml_metal_cv_set_int32(cv, ns10, FC_FLASH_ATTN_EXT_VEC + 20); - ggml_metal_cv_set_int32(cv, ns20, FC_FLASH_ATTN_EXT_VEC + 21); - ggml_metal_cv_set_int32(cv, nsg, FC_FLASH_ATTN_EXT_VEC + 22); - ggml_metal_cv_set_int32(cv, nwg, FC_FLASH_ATTN_EXT_VEC + 23); - - res = ggml_metal_library_compile_pipeline(lib, base, name, cv); - - ggml_metal_cv_free(cv); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext_vec_reduce( +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext_vec_reduce( ggml_metal_library_t lib, const ggml_tensor * op, int32_t dv, @@ -1300,26 +1261,24 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext_vec_reduce( snprintf(base, 256, "kernel_flash_attn_ext_vec_reduce"); snprintf(name, 256, "%s_dv=%d_nwg=%d", base, dv, nwg); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + ggml_metal_cv_t cv = ggml_metal_cv_init(); + + ggml_metal_cv_set_int32(cv, dv, FC_FLASH_ATTN_EXT_VEC_REDUCE + 0); + ggml_metal_cv_set_int32(cv, nwg, FC_FLASH_ATTN_EXT_VEC_REDUCE + 1); + + res = ggml_metal_library_compile_pipeline(lib, base, name, cv); + + ggml_metal_cv_free(cv); } - ggml_metal_cv_t cv = ggml_metal_cv_init(); - - ggml_metal_cv_set_int32(cv, dv, FC_FLASH_ATTN_EXT_VEC_REDUCE + 0); - ggml_metal_cv_set_int32(cv, nwg, FC_FLASH_ATTN_EXT_VEC_REDUCE + 1); - - res = ggml_metal_library_compile_pipeline(lib, base, name, cv); - - ggml_metal_cv_free(cv); - return res; GGML_UNUSED(op); } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_bin( +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_bin( ggml_metal_library_t lib, ggml_op op, int32_t n_fuse, @@ -1344,17 +1303,15 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_bin( snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_l2_norm(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_l2_norm(ggml_metal_library_t lib, const ggml_tensor * op) { assert(op->op == GGML_OP_L2_NORM); GGML_ASSERT(op->src[0]->ne[0] % 4 == 0); @@ -1366,19 +1323,17 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_l2_norm(ggml_metal_library snprintf(base, 256, "kernel_l2_norm_f32"); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - - ggml_metal_pipeline_set_smem(res, 32*sizeof(float)); + res.smem = 32*sizeof(float); return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_group_norm(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_group_norm(ggml_metal_library_t lib, const ggml_tensor * op) { assert(op->op == GGML_OP_GROUP_NORM); GGML_ASSERT(ggml_is_contiguous(op->src[0])); @@ -1389,19 +1344,17 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_group_norm(ggml_metal_libr snprintf(base, 256, "kernel_group_norm_f32"); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - - ggml_metal_pipeline_set_smem(res, 32*sizeof(float)); + res.smem = 32*sizeof(float); return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_norm(ggml_metal_library_t lib, const ggml_tensor * op, int n_fuse) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_norm(ggml_metal_library_t lib, const ggml_tensor * op, int n_fuse) { assert(op->op == GGML_OP_NORM || op->op == GGML_OP_RMS_NORM); GGML_ASSERT(ggml_is_contiguous_rows(op->src[0])); @@ -1434,19 +1387,17 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_norm(ggml_metal_library_t snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - - ggml_metal_pipeline_set_smem(res, 32*sizeof(float)); + res.smem = 32*sizeof(float); return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_rope(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_rope(ggml_metal_library_t lib, const ggml_tensor * op) { assert(op->op == GGML_OP_ROPE); char base[256]; @@ -1473,23 +1424,21 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_rope(ggml_metal_library_t snprintf(name, 256, "%s_imrope=%d", base, is_imrope ? 1 : 0); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + ggml_metal_cv_t cv = ggml_metal_cv_init(); + + ggml_metal_cv_set_bool(cv, is_imrope, FC_ROPE + 0); + + res = ggml_metal_library_compile_pipeline(lib, base, name, cv); + + ggml_metal_cv_free(cv); } - ggml_metal_cv_t cv = ggml_metal_cv_init(); - - ggml_metal_cv_set_bool(cv, is_imrope, FC_ROPE + 0); - - res = ggml_metal_library_compile_pipeline(lib, base, name, cv); - - ggml_metal_cv_free(cv); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_im2col(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_im2col(ggml_metal_library_t lib, const ggml_tensor * op) { assert(op->op == GGML_OP_IM2COL); GGML_ASSERT(ggml_is_contiguous(op->src[1])); @@ -1502,17 +1451,15 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_im2col(ggml_metal_library_ snprintf(base, 256, "kernel_im2col_%s", ggml_type_name(op->type)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_conv_transpose_1d(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_conv_transpose_1d(ggml_metal_library_t lib, const ggml_tensor * op) { assert(op->op == GGML_OP_CONV_TRANSPOSE_1D); GGML_ASSERT(ggml_is_contiguous(op->src[0])); @@ -1527,17 +1474,15 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_conv_transpose_1d(ggml_met snprintf(base, 256, "kernel_conv_transpose_1d_%s_%s", ggml_type_name(op->src[0]->type), ggml_type_name(op->src[1]->type)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_conv_transpose_2d(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_conv_transpose_2d(ggml_metal_library_t lib, const ggml_tensor * op) { assert(op->op == GGML_OP_CONV_TRANSPOSE_2D); GGML_ASSERT(ggml_is_contiguous(op->src[0])); @@ -1552,17 +1497,15 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_conv_transpose_2d(ggml_met snprintf(base, 256, "kernel_conv_transpose_2d_%s_%s", ggml_type_name(op->src[0]->type), ggml_type_name(op->src[1]->type)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_conv_2d(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_conv_2d(ggml_metal_library_t lib, const ggml_tensor * op) { assert(op->op == GGML_OP_CONV_2D); GGML_ASSERT(ggml_is_contiguous(op->src[0])); @@ -1576,17 +1519,15 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_conv_2d(ggml_metal_library snprintf(base, 256, "kernel_conv_2d_%s_%s", ggml_type_name(op->src[0]->type), ggml_type_name(op->src[1]->type)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_upscale(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_upscale(ggml_metal_library_t lib, const ggml_tensor * op) { assert(op->op == GGML_OP_UPSCALE); char base[256]; @@ -1595,17 +1536,15 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_upscale(ggml_metal_library snprintf(base, 256, "kernel_upscale_%s", ggml_type_name(op->src[0]->type)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_pad(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_pad(ggml_metal_library_t lib, const ggml_tensor * op) { assert(op->op == GGML_OP_PAD); char base[256]; @@ -1614,8 +1553,8 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_pad(ggml_metal_library_t l snprintf(base, 256, "kernel_pad_%s", ggml_type_name(op->src[0]->type)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (res.pipeline) { return res; } @@ -1624,7 +1563,7 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_pad(ggml_metal_library_t l return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_pad_reflect_1d(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_pad_reflect_1d(ggml_metal_library_t lib, const ggml_tensor * op) { assert(op->op == GGML_OP_PAD_REFLECT_1D); char base[256]; @@ -1633,17 +1572,15 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_pad_reflect_1d(ggml_metal_ snprintf(base, 256, "kernel_pad_reflect_1d_%s", ggml_type_name(op->src[0]->type)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_arange(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_arange(ggml_metal_library_t lib, const ggml_tensor * op) { assert(op->op == GGML_OP_ARANGE); char base[256]; @@ -1652,17 +1589,15 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_arange(ggml_metal_library_ snprintf(base, 256, "kernel_arange_%s", ggml_type_name(op->type)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_timestep_embedding(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_timestep_embedding(ggml_metal_library_t lib, const ggml_tensor * op) { assert(op->op == GGML_OP_TIMESTEP_EMBEDDING); char base[256]; @@ -1671,17 +1606,15 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_timestep_embedding(ggml_me snprintf(base, 256, "kernel_timestep_embedding_%s", ggml_type_name(op->src[0]->type)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_opt_step_adamw(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_opt_step_adamw(ggml_metal_library_t lib, const ggml_tensor * op) { assert(op->op == GGML_OP_OPT_STEP_ADAMW); char base[256]; @@ -1690,17 +1623,15 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_opt_step_adamw(ggml_metal_ snprintf(base, 256, "kernel_opt_step_adamw_%s", ggml_type_name(op->src[0]->type)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_opt_step_sgd(ggml_metal_library_t lib, const ggml_tensor * op) { +ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_opt_step_sgd(ggml_metal_library_t lib, const ggml_tensor * op) { assert(op->op == GGML_OP_OPT_STEP_SGD); char base[256]; @@ -1709,12 +1640,10 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_opt_step_sgd(ggml_metal_li snprintf(base, 256, "kernel_opt_step_sgd_%s", ggml_type_name(op->src[0]->type)); snprintf(name, 256, "%s", base); - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - return res; + ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name); + if (!res.pipeline) { + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); - return res; } diff --git a/ggml/src/ggml-metal/ggml-metal-device.h b/ggml/src/ggml-metal/ggml-metal-device.h index 3976e622b9..77f2e98cfe 100644 --- a/ggml/src/ggml-metal/ggml-metal-device.h +++ b/ggml/src/ggml-metal/ggml-metal-device.h @@ -35,20 +35,6 @@ typedef struct ggml_metal_pipeline * ggml_metal_pipeline_t; ggml_metal_pipeline_t ggml_metal_pipeline_init(void); void ggml_metal_pipeline_free(ggml_metal_pipeline_t pipeline); -void ggml_metal_pipeline_set_nsg(ggml_metal_pipeline_t pipeline, int nsg); -int ggml_metal_pipeline_get_nsg(ggml_metal_pipeline_t pipeline); - -void ggml_metal_pipeline_set_nr0(ggml_metal_pipeline_t pipeline, int nr0); -int ggml_metal_pipeline_get_nr0(ggml_metal_pipeline_t pipeline); - -void ggml_metal_pipeline_set_nr1(ggml_metal_pipeline_t pipeline, int nr1); -int ggml_metal_pipeline_get_nr1(ggml_metal_pipeline_t pipeline); - -void ggml_metal_pipeline_set_smem(ggml_metal_pipeline_t pipeline, size_t smem); -size_t ggml_metal_pipeline_get_smem(ggml_metal_pipeline_t pipeline); - -int ggml_metal_pipeline_max_theads_per_threadgroup(ggml_metal_pipeline_t pipeline); - // a collection of pipelines typedef struct ggml_metal_pipelines * ggml_metal_pipelines_t; @@ -58,6 +44,19 @@ void ggml_metal_pipelines_free(ggml_metal_pipelines_t ppls); void ggml_metal_pipelines_add(ggml_metal_pipelines_t ppls, const char * name, ggml_metal_pipeline_t pipeline); ggml_metal_pipeline_t ggml_metal_pipelines_get(ggml_metal_pipelines_t ppls, const char * name); +struct ggml_metal_pipeline_with_params { + ggml_metal_pipeline_t pipeline; + + int nsg; + + int nr0; + int nr1; + + size_t smem; +}; + +int ggml_metal_pipeline_max_theads_per_threadgroup(struct ggml_metal_pipeline_with_params pipeline); + // // MTLCommandBuffer wrapper // @@ -76,7 +75,7 @@ void ggml_metal_encoder_free(ggml_metal_encoder_t encoder); void ggml_metal_encoder_debug_group_push(ggml_metal_encoder_t encoder, const char * name); void ggml_metal_encoder_debug_group_pop (ggml_metal_encoder_t encoder); -void ggml_metal_encoder_set_pipeline(ggml_metal_encoder_t encoder, ggml_metal_pipeline_t pipeline); +void ggml_metal_encoder_set_pipeline(ggml_metal_encoder_t encoder, struct ggml_metal_pipeline_with_params pipeline); void ggml_metal_encoder_set_bytes (ggml_metal_encoder_t encoder, void * data, size_t size, int idx); void ggml_metal_encoder_set_buffer(ggml_metal_encoder_t encoder, struct ggml_metal_buffer_id buffer, int idx); @@ -100,66 +99,67 @@ ggml_metal_library_t ggml_metal_library_init_from_source(ggml_metal_device_t dev void ggml_metal_library_free(ggml_metal_library_t lib); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline (ggml_metal_library_t lib, const char * name); -ggml_metal_pipeline_t ggml_metal_library_compile_pipeline(ggml_metal_library_t lib, const char * base, const char * name, ggml_metal_cv_t cv); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline (ggml_metal_library_t lib, const char * name); +struct ggml_metal_pipeline_with_params ggml_metal_library_compile_pipeline(ggml_metal_library_t lib, const char * base, const char * name, ggml_metal_cv_t cv); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_base (ggml_metal_library_t lib, enum ggml_op op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_cpy (ggml_metal_library_t lib, enum ggml_type tsrc, enum ggml_type tdst); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_pool_2d (ggml_metal_library_t lib, const struct ggml_tensor * op, enum ggml_op_pool op_pool); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_get_rows (ggml_metal_library_t lib, enum ggml_type tsrc); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_set_rows (ggml_metal_library_t lib, enum ggml_type tidx, enum ggml_type tdst); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_repeat (ggml_metal_library_t lib, enum ggml_type tsrc); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_unary (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_glu (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_sum (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_sum_rows (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_cumsum_blk (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_cumsum_add (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_soft_max (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_ssm_conv (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_ssm_scan (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_rwkv (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mv_ext (ggml_metal_library_t lib, enum ggml_type tsrc0, enum ggml_type tsrc1, int nsg, int nxpsg, int r1ptg); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mm (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mv (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mm_id_map0 (ggml_metal_library_t lib, int ne02, int ne20); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mm_id (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mv_id (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_argmax (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_argsort (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_argsort_merge (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_top_k (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_top_k_merge (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_bin (ggml_metal_library_t lib, enum ggml_op op, int32_t n_fuse, bool row); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_l2_norm (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_group_norm (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_norm (ggml_metal_library_t lib, const struct ggml_tensor * op, int32_t n_fuse); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_rope (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_im2col (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_conv_transpose_1d (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_conv_transpose_2d (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_conv_2d (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_upscale (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_pad (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_pad_reflect_1d (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_arange (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_timestep_embedding(ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_opt_step_adamw (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_opt_step_sgd (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_base (ggml_metal_library_t lib, enum ggml_op op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_cpy (ggml_metal_library_t lib, enum ggml_type tsrc, enum ggml_type tdst); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_pool_2d (ggml_metal_library_t lib, const struct ggml_tensor * op, enum ggml_op_pool op_pool); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_get_rows (ggml_metal_library_t lib, enum ggml_type tsrc); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_set_rows (ggml_metal_library_t lib, enum ggml_type tidx, enum ggml_type tdst); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_repeat (ggml_metal_library_t lib, enum ggml_type tsrc); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_unary (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_glu (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_sum (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_sum_rows (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_cumsum_blk (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_cumsum_add (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_tri (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_soft_max (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_ssm_conv (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_ssm_scan (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_rwkv (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_mul_mv_ext (ggml_metal_library_t lib, enum ggml_type tsrc0, enum ggml_type tsrc1, int nsg, int nxpsg, int r1ptg); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_mul_mm (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_mul_mv (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_mul_mm_id_map0 (ggml_metal_library_t lib, int ne02, int ne20); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_mul_mm_id (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_mul_mv_id (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_argmax (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_argsort (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_argsort_merge (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_top_k (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_top_k_merge (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_bin (ggml_metal_library_t lib, enum ggml_op op, int32_t n_fuse, bool row); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_l2_norm (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_group_norm (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_norm (ggml_metal_library_t lib, const struct ggml_tensor * op, int32_t n_fuse); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_rope (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_im2col (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_conv_transpose_1d (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_conv_transpose_2d (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_conv_2d (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_upscale (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_pad (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_pad_reflect_1d (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_arange (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_timestep_embedding(ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_opt_step_adamw (ggml_metal_library_t lib, const struct ggml_tensor * op); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_opt_step_sgd (ggml_metal_library_t lib, const struct ggml_tensor * op); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext_pad( +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext_pad( ggml_metal_library_t lib, const struct ggml_tensor * op, bool has_mask, int32_t ncpsg); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext_blk( +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext_blk( ggml_metal_library_t lib, const struct ggml_tensor * op, int32_t nqptg, int32_t ncpsg); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext( +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext( ggml_metal_library_t lib, const struct ggml_tensor * op, bool has_mask, @@ -169,7 +169,7 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext( bool has_kvpad, int32_t nsg); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext_vec( +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext_vec( ggml_metal_library_t lib, const struct ggml_tensor * op, bool has_mask, @@ -180,12 +180,22 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext_vec( int32_t nsg, int32_t nwg); -ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext_vec_reduce( +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext_vec_reduce( ggml_metal_library_t lib, const struct ggml_tensor * op, int32_t dv, int32_t nwg); +// MTLResidencySet wrapper + +typedef void * ggml_metal_rset_t; + +// a collection of residency sets (non-owning) +typedef struct ggml_metal_rsets * ggml_metal_rsets_t; + +ggml_metal_rsets_t ggml_metal_rsets_init(void); +void ggml_metal_rsets_free(ggml_metal_rsets_t rsets); + // // device // @@ -219,6 +229,11 @@ void * ggml_metal_device_get_queue(ggml_metal_device_t dev); // id @@ -75,14 +74,6 @@ void ggml_metal_cv_set_bool(ggml_metal_cv_t cv, bool value, int32_t idx) { struct ggml_metal_pipeline { id obj; - - // suggested dispatch sizes - int nsg; - - int nr0; - int nr1; - - size_t smem; }; ggml_metal_pipeline_t ggml_metal_pipeline_init(void) { @@ -90,10 +81,6 @@ ggml_metal_pipeline_t ggml_metal_pipeline_init(void) { *res = (struct ggml_metal_pipeline) { /*.obj =*/ nil, - /*.nsg =*/ 0, - /*.nr0 =*/ 0, - /*.nr1 =*/ 0, - /*.smem =*/ 0, }; return res; @@ -105,40 +92,8 @@ void ggml_metal_pipeline_free(ggml_metal_pipeline_t pipeline) { free(pipeline); } -void ggml_metal_pipeline_set_nsg(ggml_metal_pipeline_t pipeline, int nsg) { - pipeline->nsg = nsg; -} - -int ggml_metal_pipeline_get_nsg(ggml_metal_pipeline_t pipeline) { - return pipeline->nsg; -} - -void ggml_metal_pipeline_set_nr0(ggml_metal_pipeline_t pipeline, int nr0) { - pipeline->nr0 = nr0; -} - -int ggml_metal_pipeline_get_nr0(ggml_metal_pipeline_t pipeline) { - return pipeline->nr0; -} - -void ggml_metal_pipeline_set_nr1(ggml_metal_pipeline_t pipeline, int nr1) { - pipeline->nr1 = nr1; -} - -int ggml_metal_pipeline_get_nr1(ggml_metal_pipeline_t pipeline) { - return pipeline->nr1; -} - -void ggml_metal_pipeline_set_smem(ggml_metal_pipeline_t pipeline, size_t smem) { - pipeline->smem = smem; -} - -size_t ggml_metal_pipeline_get_smem(ggml_metal_pipeline_t pipeline) { - return pipeline->smem; -} - -int ggml_metal_pipeline_max_theads_per_threadgroup(ggml_metal_pipeline_t pipeline) { - return pipeline->obj.maxTotalThreadsPerThreadgroup; +int ggml_metal_pipeline_max_theads_per_threadgroup(struct ggml_metal_pipeline_with_params pipeline) { + return pipeline.pipeline->obj.maxTotalThreadsPerThreadgroup; } struct ggml_metal_library { @@ -146,6 +101,8 @@ struct ggml_metal_library { id device; ggml_metal_pipelines_t pipelines; // cache of compiled pipelines + + NSLock * lock; }; ggml_metal_library_t ggml_metal_library_init(ggml_metal_device_t dev) { @@ -296,9 +253,10 @@ ggml_metal_library_t ggml_metal_library_init(ggml_metal_device_t dev) { ggml_metal_library_t res = calloc(1, sizeof(struct ggml_metal_library)); - res->obj = library; - res->device = device; + res->obj = library; + res->device = device; res->pipelines = ggml_metal_pipelines_init(); + res->lock = [NSLock new]; return res; } @@ -365,6 +323,7 @@ ggml_metal_library_t ggml_metal_library_init_from_source(ggml_metal_device_t dev res->obj = library; res->device = device; res->pipelines = ggml_metal_pipelines_init(); + res->lock = [NSLock new]; return res; } @@ -380,26 +339,47 @@ void ggml_metal_library_free(ggml_metal_library_t lib) { ggml_metal_pipelines_free(lib->pipelines); + [lib->lock release]; + free(lib); } -ggml_metal_pipeline_t ggml_metal_library_get_pipeline(ggml_metal_library_t lib, const char * name) { - return ggml_metal_pipelines_get(lib->pipelines, name); +struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline(ggml_metal_library_t lib, const char * name) { + [lib->lock lock]; + + struct ggml_metal_pipeline_with_params res = { + /*.pipeline =*/ nil, + /*.nr0 =*/ 0, + /*.nr1 =*/ 0, + /*.nsg =*/ 0, + /*.smem =*/ 0, + }; + + res.pipeline = ggml_metal_pipelines_get(lib->pipelines, name); + + [lib->lock unlock]; + + return res; } -ggml_metal_pipeline_t ggml_metal_library_compile_pipeline(ggml_metal_library_t lib, const char * base, const char * name, ggml_metal_cv_t cv) { - // note: the pipelines are cached in the library per device, so they are shared across all metal contexts - ggml_critical_section_start(); +struct ggml_metal_pipeline_with_params ggml_metal_library_compile_pipeline(ggml_metal_library_t lib, const char * base, const char * name, ggml_metal_cv_t cv) { + struct ggml_metal_pipeline_with_params res = { + /*.pipeline =*/ nil, + /*.nr0 =*/ 0, + /*.nr1 =*/ 0, + /*.nsg =*/ 0, + /*.smem =*/ 0, + }; - ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); - if (res) { - ggml_critical_section_end(); + [lib->lock lock]; + + res.pipeline = ggml_metal_pipelines_get(lib->pipelines, name); + if (res.pipeline) { + [lib->lock unlock]; return res; } - res = ggml_metal_pipeline_init(); - @autoreleasepool { NSError * error = nil; @@ -414,36 +394,53 @@ ggml_metal_pipeline_t ggml_metal_library_compile_pipeline(ggml_metal_library_t l mtl_function = [lib->obj newFunctionWithName:base_func constantValues:cv->obj error:&error]; } if (!mtl_function) { - ggml_critical_section_end(); + [lib->lock unlock]; GGML_LOG_ERROR("%s: failed to compile pipeline: base = '%s', name = '%s'\n", __func__, base, name); if (error) { GGML_LOG_ERROR("%s: %s\n", __func__, [[error description] UTF8String]); } - return nil; + return res; } - res->obj = [lib->device newComputePipelineStateWithFunction:mtl_function error:&error]; + id obj = [lib->device newComputePipelineStateWithFunction:mtl_function error:&error]; [mtl_function release]; - GGML_LOG_DEBUG("%s: loaded %-40s %16p | th_max = %4d | th_width = %4d\n", __func__, name, (void *) res->obj, - (int) res->obj.maxTotalThreadsPerThreadgroup, - (int) res->obj.threadExecutionWidth); + if (!obj) { + [lib->lock unlock]; - if (res->obj.maxTotalThreadsPerThreadgroup == 0 || res->obj.threadExecutionWidth == 0) { - ggml_critical_section_end(); + GGML_LOG_ERROR("%s: failed to create pipeline state: base = '%s', name = '%s'\n", __func__, base, name); + if (error) { + GGML_LOG_ERROR("%s: %s\n", __func__, [[error description] UTF8String]); + } + + return res; + } + + GGML_LOG_DEBUG("%s: loaded %-40s %16p | th_max = %4d | th_width = %4d\n", __func__, name, + (void *) obj, + (int) obj.maxTotalThreadsPerThreadgroup, + (int) obj.threadExecutionWidth); + + if (obj.maxTotalThreadsPerThreadgroup == 0 || obj.threadExecutionWidth == 0) { + [obj release]; + + [lib->lock unlock]; GGML_LOG_ERROR("%s: incompatible pipeline %s\n", __func__, name); - return nil; + return res; } - ggml_metal_pipelines_add(lib->pipelines, name, res); + res.pipeline = ggml_metal_pipeline_init(); + res.pipeline->obj = obj; + + ggml_metal_pipelines_add(lib->pipelines, name, res.pipeline); } - ggml_critical_section_end(); + [lib->lock unlock]; return res; } @@ -485,8 +482,8 @@ void ggml_metal_encoder_debug_group_pop (ggml_metal_encoder_t encoder) { [encoder->obj popDebugGroup]; } -void ggml_metal_encoder_set_pipeline(ggml_metal_encoder_t encoder, ggml_metal_pipeline_t pipeline) { - [encoder->obj setComputePipelineState:pipeline->obj]; +void ggml_metal_encoder_set_pipeline(ggml_metal_encoder_t encoder, struct ggml_metal_pipeline_with_params pipeline) { + [encoder->obj setComputePipelineState:pipeline.pipeline->obj]; } void ggml_metal_encoder_set_bytes(ggml_metal_encoder_t encoder, void * data, size_t size, int idx) { @@ -521,11 +518,106 @@ struct ggml_metal_device { // ref: https://github.com/ggml-org/llama.cpp/pull/15906 id mtl_queue; + ggml_metal_rsets_t rsets; + ggml_metal_library_t library; struct ggml_metal_device_props props; }; +// +// MTLResidenceSet wrapper +// + +struct ggml_metal_rsets { + NSLock * lock; + + NSMutableArray * data; + + // number of seconds since the last graph computation + // keep the residency sets wired for that amount of time to avoid being collected by the OS + int keep_alive_s; + + // background heartbeat thread to keep the residency sets alive + atomic_bool d_stop; + atomic_int d_loop; + + dispatch_group_t d_group; +}; + +ggml_metal_rsets_t ggml_metal_rsets_init(void) { + ggml_metal_rsets_t res = calloc(1, sizeof(struct ggml_metal_rsets)); + + res->lock = [[NSLock alloc] init]; + res->data = [[NSMutableArray alloc] init]; + + // by default keep the memory wired for 3 minutes + res->keep_alive_s = 3*60; + + const char * GGML_METAL_RESIDENCY_KEEP_ALIVE_S = getenv("GGML_METAL_RESIDENCY_KEEP_ALIVE_S"); + if (GGML_METAL_RESIDENCY_KEEP_ALIVE_S) { + res->keep_alive_s = atoi(GGML_METAL_RESIDENCY_KEEP_ALIVE_S); + } + + if (res->keep_alive_s <= 0) { + res->keep_alive_s = 3*60; + } + + GGML_LOG_INFO("%s: creating a residency set collection (keep_alive = %d s)\n", __func__, res->keep_alive_s); + + atomic_store_explicit(&res->d_stop, false, memory_order_relaxed); + atomic_store_explicit(&res->d_loop, 2*res->keep_alive_s, memory_order_relaxed); + + res->d_group = dispatch_group_create(); + + // start a background thread that periodically requests residency for all the currently active sets in the collection + // the requests stop after a certain amount of time (keep_alive_s) of inactivity + dispatch_queue_t d_queue = dispatch_get_global_queue(QOS_CLASS_DEFAULT, 0); + dispatch_group_async(res->d_group, d_queue, ^{ +#if defined(GGML_METAL_HAS_RESIDENCY_SETS) + if (@available(macOS 15.0, iOS 18.0, tvOS 18.0, visionOS 2.0, *)) { + while (!atomic_load_explicit(&res->d_stop, memory_order_relaxed)) { + if (atomic_load_explicit(&res->d_loop, memory_order_relaxed) > 0) { + [res->lock lock]; + + for (int i = 0; i < (int) res->data.count; ++i) { + [res->data[i] requestResidency]; + } + + atomic_fetch_sub_explicit(&res->d_loop, 1, memory_order_relaxed); + + [res->lock unlock]; + } + + // half a second + usleep(500 * 1000); + } + } +#endif + }); + + return res; +} + +void ggml_metal_rsets_free(ggml_metal_rsets_t rsets) { + if (rsets == NULL) { + return; + } + + // note: if you hit this assert, most likely you haven't deallocated all Metal resources before exiting + GGML_ASSERT([rsets->data count] == 0); + + atomic_store_explicit(&rsets->d_stop, true, memory_order_relaxed); + + dispatch_group_wait(rsets->d_group, DISPATCH_TIME_FOREVER); + dispatch_release(rsets->d_group); + + [rsets->data release]; + [rsets->lock release]; + + free(rsets); +} + ggml_metal_device_t ggml_metal_device_init(void) { ggml_metal_device_t dev = calloc(1, sizeof(struct ggml_metal_device)); @@ -611,8 +703,8 @@ ggml_metal_device_t ggml_metal_device_init(void) { GGML_LOG_WARN("%s: - the tensor API is not supported in this environment - disabling\n", __func__); dev->props.has_tensor = false; } else { - ggml_metal_pipeline_t ppl = ggml_metal_library_compile_pipeline(lib, "dummy_kernel", "dummy_kernel", nil); - if (!ppl) { + struct ggml_metal_pipeline_with_params ppl = ggml_metal_library_compile_pipeline(lib, "dummy_kernel", "dummy_kernel", nil); + if (!ppl.pipeline) { GGML_LOG_WARN("%s: - the tensor API is not supported in this environment - disabling\n", __func__); dev->props.has_tensor = false; } @@ -661,8 +753,8 @@ ggml_metal_device_t ggml_metal_device_init(void) { GGML_LOG_WARN("%s: - the tensor API does not support bfloat - disabling bfloat support\n", __func__); dev->props.has_bfloat = false; } else { - ggml_metal_pipeline_t ppl = ggml_metal_library_compile_pipeline(lib, "dummy_kernel", "dummy_kernel", nil); - if (!ppl) { + struct ggml_metal_pipeline_with_params ppl = ggml_metal_library_compile_pipeline(lib, "dummy_kernel", "dummy_kernel", nil); + if (!ppl.pipeline) { GGML_LOG_WARN("%s: - the tensor API does not support bfloat - disabling bfloat support\n", __func__); dev->props.has_bfloat = false; } @@ -694,7 +786,11 @@ ggml_metal_device_t ggml_metal_device_init(void) { GGML_LOG_ERROR("%s: error: failed to create library\n", __func__); } - // -------------------------------------------------- + if (dev->props.use_residency_sets) { + dev->rsets = ggml_metal_rsets_init(); + } else { + dev->rsets = nil; + } // print MTL GPU family: GGML_LOG_INFO("%s: GPU name: %s\n", __func__, dev->props.name); @@ -747,6 +843,8 @@ ggml_metal_device_t ggml_metal_device_init(void) { void ggml_metal_device_free(ggml_metal_device_t dev) { assert(dev != NULL); + ggml_metal_rsets_free(dev->rsets); + ggml_metal_library_free(dev->library); dev->library = NULL; @@ -775,6 +873,42 @@ ggml_metal_library_t ggml_metal_device_get_library(ggml_metal_device_t dev) { return dev->library; } +void ggml_metal_device_rsets_add(ggml_metal_device_t dev, ggml_metal_rset_t rset) { + if (rset == nil) { + return; + } + + GGML_ASSERT(dev->rsets); + + [dev->rsets->lock lock]; + + [dev->rsets->data addObject:rset]; + + [dev->rsets->lock unlock]; +} + +void ggml_metal_device_rsets_rm(ggml_metal_device_t dev, ggml_metal_rset_t rset) { + if (rset == nil) { + return; + } + + GGML_ASSERT(dev->rsets); + + [dev->rsets->lock lock]; + + [dev->rsets->data removeObject:rset]; + + [dev->rsets->lock unlock]; +} + +void ggml_metal_device_rsets_keep_alive(ggml_metal_device_t dev) { + if (dev->rsets == NULL) { + return; + } + + atomic_store_explicit(&dev->rsets->d_loop, 2*dev->rsets->keep_alive_s, memory_order_relaxed); +} + void ggml_metal_device_get_memory(ggml_metal_device_t dev, size_t * free, size_t * total) { if (@available(macOS 10.12, iOS 16.0, *)) { *total = dev->mtl_device.recommendedMaxWorkingSetSize; @@ -820,6 +954,8 @@ bool ggml_metal_device_supports_op(ggml_metal_device_t dev, const struct ggml_te case GGML_UNARY_OP_HARDSWISH: case GGML_UNARY_OP_HARDSIGMOID: case GGML_UNARY_OP_EXP: + case GGML_UNARY_OP_SOFTPLUS: + case GGML_UNARY_OP_EXPM1: return ggml_is_contiguous(op->src[0]) && op->src[0]->type == GGML_TYPE_F32; default: return false; @@ -852,6 +988,7 @@ bool ggml_metal_device_supports_op(ggml_metal_device_t dev, const struct ggml_te case GGML_OP_ACC: case GGML_OP_REPEAT: case GGML_OP_SCALE: + case GGML_OP_FILL: case GGML_OP_CONV_TRANSPOSE_1D: return true; case GGML_OP_CONV_TRANSPOSE_2D: @@ -869,6 +1006,8 @@ bool ggml_metal_device_supports_op(ggml_metal_device_t dev, const struct ggml_te return ggml_is_contiguous(op->src[0]) && op->src[0]->type == GGML_TYPE_F32; case GGML_OP_SUM: return has_simdgroup_reduction && ggml_is_contiguous(op->src[0]); + case GGML_OP_TRI: + return ggml_is_contiguous_rows(op->src[0]); case GGML_OP_SUM_ROWS: case GGML_OP_CUMSUM: case GGML_OP_MEAN: @@ -898,6 +1037,11 @@ bool ggml_metal_device_supports_op(ggml_metal_device_t dev, const struct ggml_te case GGML_OP_POOL_2D: return op->src[0]->type == GGML_TYPE_F32; case GGML_OP_PAD: + // TODO: add circular padding support for metal, see https://github.com/ggml-org/llama.cpp/pull/16985 + if (ggml_get_op_params_i32(op, 8) != 0) { + return false; + } + return (ggml_get_op_params_i32(op, 0) == 0) && (ggml_get_op_params_i32(op, 2) == 0) && (ggml_get_op_params_i32(op, 4) == 0) && (ggml_get_op_params_i32(op, 6) == 0); case GGML_OP_PAD_REFLECT_1D: @@ -1063,9 +1207,8 @@ struct ggml_metal_buffer { // note: cannot use explicity "id" here because it is not available on certain OSes id rset; - // pointers to global device objects - id device; - id queue; + // pointers to global device + ggml_metal_device_t dev; }; static void ggml_metal_log_allocated_size(id device, size_t size_aligned) { @@ -1108,7 +1251,7 @@ static bool ggml_metal_buffer_rset_init(ggml_metal_buffer_t buf) { desc.initialCapacity = buf->n_buffers; NSError * error; - buf->rset = [buf->device newResidencySetWithDescriptor:desc error:&error]; + buf->rset = [buf->dev->mtl_device newResidencySetWithDescriptor:desc error:&error]; if (error) { GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]); [desc release]; @@ -1169,6 +1312,8 @@ static void * ggml_metal_host_malloc(size_t n) { ggml_metal_buffer_t ggml_metal_buffer_init(ggml_metal_device_t dev, size_t size, bool shared) { ggml_metal_buffer_t res = calloc(1, sizeof(struct ggml_metal_buffer)); + res->dev = dev; + const size_t size_page = sysconf(_SC_PAGESIZE); size_t size_aligned = size; @@ -1193,9 +1338,6 @@ ggml_metal_buffer_t ggml_metal_buffer_init(ggml_metal_device_t dev, size_t size, res->owned = true; - res->device = ggml_metal_device_get_obj(dev); - res->queue = ggml_metal_device_get_queue(dev); - res->n_buffers = 1; if (res->all_data != NULL) { @@ -1204,12 +1346,12 @@ ggml_metal_buffer_t ggml_metal_buffer_init(ggml_metal_device_t dev, size_t size, if (size_aligned > 0) { if (props_dev->use_shared_buffers && shared) { - res->buffers[0].metal = [res->device newBufferWithBytesNoCopy:res->all_data + res->buffers[0].metal = [res->dev->mtl_device newBufferWithBytesNoCopy:res->all_data length:size_aligned options:MTLResourceStorageModeShared deallocator:nil]; } else { - res->buffers[0].metal = [res->device newBufferWithLength:size_aligned options:MTLResourceStorageModePrivate]; + res->buffers[0].metal = [res->dev->mtl_device newBufferWithLength:size_aligned options:MTLResourceStorageModePrivate]; } } @@ -1230,6 +1372,8 @@ ggml_metal_buffer_t ggml_metal_buffer_init(ggml_metal_device_t dev, size_t size, return NULL; } + ggml_metal_device_rsets_add(dev, res->rset); + //ggml_metal_log_allocated_size(device, size_aligned); return res; @@ -1238,6 +1382,8 @@ ggml_metal_buffer_t ggml_metal_buffer_init(ggml_metal_device_t dev, size_t size, ggml_metal_buffer_t ggml_metal_buffer_map(ggml_metal_device_t dev, void * ptr, size_t size, size_t max_tensor_size) { ggml_metal_buffer_t res = calloc(1, sizeof(struct ggml_metal_buffer)); + res->dev = dev; + res->all_data = ptr; res->all_size = size; @@ -1260,9 +1406,6 @@ ggml_metal_buffer_t ggml_metal_buffer_map(ggml_metal_device_t dev, void * ptr, s size_aligned += (size_page - (size_aligned % size_page)); } - res->device = ggml_metal_device_get_obj(dev); - res->queue = ggml_metal_device_get_queue(dev); - const struct ggml_metal_device_props * props_dev = ggml_metal_device_get_props(dev); // the buffer fits into the max buffer size allowed by the device @@ -1272,7 +1415,7 @@ ggml_metal_buffer_t ggml_metal_buffer_map(ggml_metal_device_t dev, void * ptr, s res->buffers[res->n_buffers].metal = nil; if (size_aligned > 0) { - res->buffers[res->n_buffers].metal = [res->device newBufferWithBytesNoCopy:ptr length:size_aligned options:MTLResourceStorageModeShared deallocator:nil]; + res->buffers[res->n_buffers].metal = [res->dev->mtl_device newBufferWithBytesNoCopy:ptr length:size_aligned options:MTLResourceStorageModeShared deallocator:nil]; if (res->buffers[res->n_buffers].metal == nil) { GGML_LOG_ERROR("%s: error: failed to allocate buffer, size = %8.2f MiB\n", __func__, size_aligned / 1024.0 / 1024.0); @@ -1281,7 +1424,7 @@ ggml_metal_buffer_t ggml_metal_buffer_map(ggml_metal_device_t dev, void * ptr, s } } - ggml_metal_log_allocated_size(res->device, size_aligned); + ggml_metal_log_allocated_size(res->dev->mtl_device, size_aligned); ++res->n_buffers; } else { @@ -1299,7 +1442,7 @@ ggml_metal_buffer_t ggml_metal_buffer_map(ggml_metal_device_t dev, void * ptr, s res->buffers[res->n_buffers].metal = nil; if (size_step_aligned > 0) { - res->buffers[res->n_buffers].metal = [res->device newBufferWithBytesNoCopy:(void *) ((uint8_t *) ptr + i) length:size_step_aligned options:MTLResourceStorageModeShared deallocator:nil]; + res->buffers[res->n_buffers].metal = [res->dev->mtl_device newBufferWithBytesNoCopy:(void *) ((uint8_t *) ptr + i) length:size_step_aligned options:MTLResourceStorageModeShared deallocator:nil]; if (res->buffers[res->n_buffers].metal == nil) { GGML_LOG_ERROR("%s: error: failed to allocate buffer, size = %8.2f MiB\n", __func__, size_step_aligned / 1024.0 / 1024.0); @@ -1308,7 +1451,7 @@ ggml_metal_buffer_t ggml_metal_buffer_map(ggml_metal_device_t dev, void * ptr, s } } - ggml_metal_log_allocated_size(res->device, size_step_aligned); + ggml_metal_log_allocated_size(res->dev->mtl_device, size_step_aligned); if (i + size_step < size) { GGML_LOG_INFO("\n"); @@ -1326,10 +1469,14 @@ ggml_metal_buffer_t ggml_metal_buffer_map(ggml_metal_device_t dev, void * ptr, s return NULL; } + ggml_metal_device_rsets_add(dev, res->rset); + return res; } void ggml_metal_buffer_free(ggml_metal_buffer_t buf) { + ggml_metal_device_rsets_rm(buf->dev, buf->rset); + for (int i = 0; i < buf->n_buffers; i++) { [buf->buffers[i].metal release]; } @@ -1366,8 +1513,7 @@ void ggml_metal_buffer_memset_tensor(ggml_metal_buffer_t buf, struct ggml_tensor struct ggml_metal_buffer_id bid_dst = ggml_metal_buffer_get_id(buf, tensor); bid_dst.offs += offset; - id queue = buf->queue; - id cmd_buf = [queue commandBufferWithUnretainedReferences]; + id cmd_buf = [buf->dev->mtl_queue commandBufferWithUnretainedReferences]; { id encoder = [cmd_buf blitCommandEncoder]; @@ -1393,7 +1539,7 @@ void ggml_metal_buffer_set_tensor(ggml_metal_buffer_t buf, struct ggml_tensor * @autoreleasepool { // src void * data_ptr = (void *)(uintptr_t) data; // "const cast" the src data - id buf_src = [buf->device newBufferWithBytesNoCopy:data_ptr + id buf_src = [buf->dev->mtl_device newBufferWithBytesNoCopy:data_ptr length:size options:MTLResourceStorageModeShared deallocator:nil]; @@ -1408,8 +1554,7 @@ void ggml_metal_buffer_set_tensor(ggml_metal_buffer_t buf, struct ggml_tensor * // this is alternative to waitUntilCompleted, which should be faster, but don't seem to make much difference dispatch_semaphore_t completion_semaphore = dispatch_semaphore_create(0); - id queue = buf->queue; - id cmd_buf = [queue commandBufferWithUnretainedReferences]; + id cmd_buf = [buf->dev->mtl_queue commandBufferWithUnretainedReferences]; { id encoder = [cmd_buf blitCommandEncoder]; @@ -1451,15 +1596,14 @@ void ggml_metal_buffer_get_tensor(ggml_metal_buffer_t buf, const struct ggml_ten bid_src.offs += offset; // dst - id buf_dst = [buf->device newBufferWithBytesNoCopy:data + id buf_dst = [buf->dev->mtl_device newBufferWithBytesNoCopy:data length:size options:MTLResourceStorageModeShared deallocator:nil]; GGML_ASSERT(buf_dst); - id queue = buf->queue; - id cmd_buf = [queue commandBufferWithUnretainedReferences]; + id cmd_buf = [buf->dev->mtl_queue commandBufferWithUnretainedReferences]; { id encoder = [cmd_buf blitCommandEncoder]; @@ -1485,8 +1629,7 @@ void ggml_metal_buffer_clear(ggml_metal_buffer_t buf, uint8_t value) { } @autoreleasepool { - id queue = buf->queue; - id cmd_buf = [queue commandBufferWithUnretainedReferences]; + id cmd_buf = [buf->dev->mtl_queue commandBufferWithUnretainedReferences]; { id encoder = [cmd_buf blitCommandEncoder]; diff --git a/ggml/src/ggml-metal/ggml-metal-impl.h b/ggml/src/ggml-metal/ggml-metal-impl.h index 342dc4f8c3..30109f83e1 100644 --- a/ggml/src/ggml-metal/ggml-metal-impl.h +++ b/ggml/src/ggml-metal/ggml-metal-impl.h @@ -182,6 +182,10 @@ typedef struct { float bias; } ggml_metal_kargs_scale; +typedef struct { + float val; +} ggml_metal_kargs_fill; + typedef struct { float min; float max; @@ -831,6 +835,25 @@ typedef struct { float slope; } ggml_metal_kargs_leaky_relu; +typedef struct { + int32_t ne00; + int32_t ne01; + int32_t ne02; + int32_t ne03; + uint64_t nb00; + uint64_t nb01; + uint64_t nb02; + uint64_t nb03; + int32_t ne0; + int32_t ne1; + int32_t ne2; + int32_t ne3; + uint64_t nb0; + uint64_t nb1; + uint64_t nb2; + uint64_t nb3; +} ggml_metal_kargs_tri; + typedef struct { int32_t ne00; int32_t ne01; diff --git a/ggml/src/ggml-metal/ggml-metal-ops.cpp b/ggml/src/ggml-metal/ggml-metal-ops.cpp index 9871e976f2..9efd51abba 100644 --- a/ggml/src/ggml-metal/ggml-metal-ops.cpp +++ b/ggml/src/ggml-metal/ggml-metal-ops.cpp @@ -286,6 +286,10 @@ static int ggml_metal_op_encode_impl(ggml_metal_op_t ctx, int idx) { { n_fuse = ggml_metal_op_scale(ctx, idx); } break; + case GGML_OP_FILL: + { + n_fuse = ggml_metal_op_fill(ctx, idx); + } break; case GGML_OP_CLAMP: { n_fuse = ggml_metal_op_clamp(ctx, idx); @@ -414,6 +418,10 @@ static int ggml_metal_op_encode_impl(ggml_metal_op_t ctx, int idx) { { n_fuse = ggml_metal_op_leaky_relu(ctx, idx); } break; + case GGML_OP_TRI: + { + n_fuse = ggml_metal_op_tri(ctx, idx); + } break; case GGML_OP_FLASH_ATTN_EXT: { n_fuse = ggml_metal_op_flash_attn_ext(ctx, idx); @@ -524,7 +532,7 @@ int ggml_metal_op_concat(ggml_metal_op_t ctx, int idx) { /*.dim =*/ dim, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_base(lib, GGML_OP_CONCAT); + auto pipeline = ggml_metal_library_get_pipeline_base(lib, GGML_OP_CONCAT); ggml_metal_encoder_set_pipeline(enc, pipeline); ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); @@ -550,7 +558,7 @@ int ggml_metal_op_repeat(ggml_metal_op_t ctx, int idx) { GGML_TENSOR_LOCALS( int32_t, ne, op, ne); GGML_TENSOR_LOCALS(uint64_t, nb, op, nb); - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_repeat(lib, op->type); + auto pipeline = ggml_metal_library_get_pipeline_repeat(lib, op->type); ggml_metal_kargs_repeat args = { /*.ne00 =*/ ne00, @@ -616,7 +624,7 @@ int ggml_metal_op_acc(ggml_metal_op_t ctx, int idx) { // TODO: make a simpler cpy_bytes kernel //const id pipeline = ctx->pipelines[GGML_METAL_PIPELINE_TYPE_CPY_F32_F32].obj; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_cpy(lib, op->src[0]->type, op->type); + auto pipeline = ggml_metal_library_get_pipeline_cpy(lib, op->src[0]->type, op->type); ggml_metal_kargs_cpy args = { /*.nk0 =*/ ne00, @@ -679,7 +687,7 @@ int ggml_metal_op_acc(ggml_metal_op_t ctx, int idx) { /*.o1 =*/ { 0 }, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_bin(lib, GGML_OP_ADD, 1, false); + auto pipeline = ggml_metal_library_get_pipeline_bin(lib, GGML_OP_ADD, 1, false); ggml_metal_encoder_set_pipeline(enc, pipeline); ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); @@ -721,7 +729,42 @@ int ggml_metal_op_scale(ggml_metal_op_t ctx, int idx) { n /= 4; } - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_unary(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_unary(lib, op); + + ggml_metal_encoder_set_pipeline(enc, pipeline); + ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[0]), 1); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), 2); + + ggml_metal_encoder_dispatch_threadgroups(enc, n, 1, 1, 1, 1, 1); + + return 1; +} + +int ggml_metal_op_fill(ggml_metal_op_t ctx, int idx) { + ggml_tensor * op = ctx->node(idx); + + ggml_metal_library_t lib = ctx->lib; + ggml_metal_encoder_t enc = ctx->enc; + + GGML_TENSOR_LOCALS( int32_t, ne0, op->src[0], ne); + GGML_TENSOR_LOCALS(uint64_t, nb0, op->src[0], nb); + GGML_TENSOR_LOCALS( int32_t, ne, op, ne); + GGML_TENSOR_LOCALS(uint64_t, nb, op, nb); + + const float val = ggml_get_op_params_f32(op, 0); + + ggml_metal_kargs_fill args = { + /*.val =*/ val + }; + + int64_t n = ggml_nelements(op); + + if (n % 4 == 0) { + n /= 4; + } + + auto pipeline = ggml_metal_library_get_pipeline_unary(lib, op); ggml_metal_encoder_set_pipeline(enc, pipeline); ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); @@ -760,7 +803,7 @@ int ggml_metal_op_clamp(ggml_metal_op_t ctx, int idx) { n /= 4; } - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_unary(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_unary(lib, op); ggml_metal_encoder_set_pipeline(enc, pipeline); ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); @@ -789,7 +832,7 @@ int ggml_metal_op_unary(ggml_metal_op_t ctx, int idx) { n /= 4; } - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_unary(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_unary(lib, op); ggml_metal_encoder_set_pipeline(enc, pipeline); ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[0]), 0); @@ -817,7 +860,7 @@ int ggml_metal_op_glu(ggml_metal_op_t ctx, int idx) { GGML_ASSERT(ggml_are_same_shape(op->src[0], op->src[1])); } - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_glu(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_glu(lib, op); const int32_t swp = ggml_get_op_params_i32(op, 1); const float alpha = ggml_get_op_params_f32(op, 2); @@ -870,7 +913,7 @@ int ggml_metal_op_sum(ggml_metal_op_t ctx, int idx) { /*.np =*/ n, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_sum(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_sum(lib, op); int nth = 32; // SIMD width @@ -925,7 +968,7 @@ int ggml_metal_op_sum_rows(ggml_metal_op_t ctx, int idx) { /*.nb3 =*/ nb3, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_sum_rows(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_sum_rows(lib, op); int nth = 32; // SIMD width @@ -936,7 +979,7 @@ int ggml_metal_op_sum_rows(ggml_metal_op_t ctx, int idx) { nth = std::min(nth, ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)); nth = std::min(nth, ne00); - const size_t smem = ggml_metal_pipeline_get_smem(pipeline); + const size_t smem = pipeline.smem; ggml_metal_encoder_set_pipeline(enc, pipeline); ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); @@ -963,7 +1006,7 @@ int ggml_metal_op_cumsum(ggml_metal_op_t ctx, int idx) { GGML_TENSOR_LOCALS( int32_t, ne, op, ne); GGML_TENSOR_LOCALS(uint64_t, nb, op, nb); - ggml_metal_pipeline_t pipeline_blk = ggml_metal_library_get_pipeline_cumsum_blk(lib, op); + auto pipeline_blk = ggml_metal_library_get_pipeline_cumsum_blk(lib, op); int nth = 1; while (nth < ne00 && 2*nth <= ggml_metal_pipeline_max_theads_per_threadgroup(pipeline_blk)) { @@ -1060,7 +1103,7 @@ int ggml_metal_op_cumsum(ggml_metal_op_t ctx, int idx) { ggml_metal_op_concurrency_reset(ctx); { - ggml_metal_pipeline_t pipeline_add = ggml_metal_library_get_pipeline_cumsum_add(lib, op); + auto pipeline_add = ggml_metal_library_get_pipeline_cumsum_add(lib, op); ggml_metal_kargs_cumsum_add args = { /*.ne00 =*/ ne00, @@ -1106,7 +1149,7 @@ int ggml_metal_op_get_rows(ggml_metal_op_t ctx, int idx) { GGML_TENSOR_LOCALS( int32_t, ne, op, ne); GGML_TENSOR_LOCALS(uint64_t, nb, op, nb); - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_get_rows(lib, op->src[0]->type); + auto pipeline = ggml_metal_library_get_pipeline_get_rows(lib, op->src[0]->type); ggml_metal_kargs_get_rows args = { /*.ne00t =*/ ggml_is_quantized(op->src[0]->type) ? ne00/16 : ne00, @@ -1151,7 +1194,7 @@ int ggml_metal_op_set_rows(ggml_metal_op_t ctx, int idx) { GGML_TENSOR_LOCALS( int32_t, ne, op, ne); GGML_TENSOR_LOCALS(uint64_t, nb, op, nb); - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_set_rows(lib, op->src[1]->type, op->type); + auto pipeline = ggml_metal_library_get_pipeline_set_rows(lib, op->src[1]->type, op->type); const int32_t nk0 = ne0/ggml_blck_size(op->type); @@ -1252,7 +1295,7 @@ int ggml_metal_op_soft_max(ggml_metal_op_t ctx, int idx) { /*.n_head_log2 =*/ n_head_log2, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_soft_max(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_soft_max(lib, op); int nth = 32; // SIMD width @@ -1266,7 +1309,7 @@ int ggml_metal_op_soft_max(ggml_metal_op_t ctx, int idx) { } } - const size_t smem = ggml_metal_pipeline_get_smem(pipeline); + const size_t smem = pipeline.smem; ggml_metal_encoder_set_pipeline(enc, pipeline); ggml_metal_encoder_set_bytes(enc, &args, sizeof(args), 0); @@ -1322,7 +1365,7 @@ int ggml_metal_op_ssm_conv(ggml_metal_op_t ctx, int idx) { /*.nb2 =*/ nb2, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_ssm_conv(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_ssm_conv(lib, op); ggml_metal_encoder_set_pipeline(enc, pipeline); ggml_metal_encoder_set_bytes(enc, &args, sizeof(args), 0); @@ -1409,11 +1452,11 @@ int ggml_metal_op_ssm_scan(ggml_metal_op_t ctx, int idx) { /*.nb0 =*/ nb0, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_ssm_scan(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_ssm_scan(lib, op); GGML_ASSERT(d_state <= ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)); - const size_t sms = ggml_metal_pipeline_get_smem(pipeline); + const size_t smem = pipeline.smem; ggml_metal_encoder_set_pipeline(enc, pipeline); ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); @@ -1426,7 +1469,7 @@ int ggml_metal_op_ssm_scan(ggml_metal_op_t ctx, int idx) { ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[6]), 7); ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), 8); - ggml_metal_encoder_set_threadgroup_memory_size(enc, sms, 0); + ggml_metal_encoder_set_threadgroup_memory_size(enc, smem, 0); ggml_metal_encoder_dispatch_threadgroups(enc, d_inner, n_head, n_seqs, d_state, 1, 1); @@ -1449,7 +1492,7 @@ int ggml_metal_op_rwkv(ggml_metal_op_t ctx, int idx) { const int64_t C = op->ne[0]; const int64_t H = op->src[0]->ne[1]; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_rwkv(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_rwkv(lib, op); int ida = 0; @@ -1485,7 +1528,7 @@ int ggml_metal_op_cpy(ggml_metal_op_t ctx, int idx) { GGML_TENSOR_LOCALS( int32_t, ne, op, ne); GGML_TENSOR_LOCALS(uint64_t, nb, op, nb); - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_cpy(lib, op->src[0]->type, op->type); + auto pipeline = ggml_metal_library_get_pipeline_cpy(lib, op->src[0]->type, op->type); GGML_ASSERT(ne00 % ggml_blck_size(op->src[0]->type) == 0); @@ -1592,7 +1635,7 @@ int ggml_metal_op_pool_2d(ggml_metal_op_t ctx, int idx) { /* .np = */ np }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_pool_2d(lib, op, op_pool); + auto pipeline = ggml_metal_library_get_pipeline_pool_2d(lib, op, op_pool); const int nth = std::min(ggml_metal_pipeline_max_theads_per_threadgroup(pipeline), (int) np); const int ntg = (np + nth - 1) / nth; @@ -1701,7 +1744,7 @@ int ggml_metal_op_mul_mat(ggml_metal_op_t ctx, int idx) { GGML_ABORT("unsupported ne11"); }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_mul_mv_ext(lib, op->src[0]->type, op->src[1]->type, nsg, nxpsg, r1ptg); + auto pipeline = ggml_metal_library_get_pipeline_mul_mv_ext(lib, op->src[0]->type, op->src[1]->type, nsg, nxpsg, r1ptg); ggml_metal_kargs_mul_mv_ext args = { /*.ne00 =*/ ne00, @@ -1748,7 +1791,7 @@ int ggml_metal_op_mul_mat(ggml_metal_op_t ctx, int idx) { // default: break; //} - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_mul_mm(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_mul_mm(lib, op); ggml_metal_kargs_mul_mm args = { /*.ne00 =*/ ne00, @@ -1773,18 +1816,18 @@ int ggml_metal_op_mul_mat(ggml_metal_op_t ctx, int idx) { ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[1]), 2); ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), 3); - const size_t smem = ggml_metal_pipeline_get_smem(pipeline); + const size_t smem = pipeline.smem; ggml_metal_encoder_set_threadgroup_memory_size(enc, smem, 0); ggml_metal_encoder_dispatch_threadgroups(enc, ((ne11 + 31)/32), ((ne01 + 63)/64), ne12*ne13, 128, 1, 1); } else { - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_mul_mv(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_mul_mv(lib, op); - const int nr0 = ggml_metal_pipeline_get_nr0(pipeline); - const int nr1 = ggml_metal_pipeline_get_nr1(pipeline); - const int nsg = ggml_metal_pipeline_get_nsg(pipeline); + const int nr0 = pipeline.nr0; + const int nr1 = pipeline.nr1; + const int nsg = pipeline.nsg; - const size_t smem = ggml_metal_pipeline_get_smem(pipeline); + const size_t smem = pipeline.smem; ggml_metal_kargs_mul_mv args = { /*.ne00 =*/ ne00, @@ -1915,9 +1958,9 @@ int ggml_metal_op_mul_mat_id(ggml_metal_op_t ctx, int idx) { nb21, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_mul_mm_id_map0(lib, ne02, ne20); + auto pipeline = ggml_metal_library_get_pipeline_mul_mm_id_map0(lib, ne02, ne20); - const size_t smem = ggml_metal_pipeline_get_smem(pipeline); + const size_t smem = pipeline.smem; GGML_ASSERT(ne02 <= ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)); @@ -1938,7 +1981,7 @@ int ggml_metal_op_mul_mat_id(ggml_metal_op_t ctx, int idx) { ggml_metal_op_concurrency_reset(ctx); { - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_mul_mm_id(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_mul_mm_id(lib, op); ggml_metal_kargs_mul_mm_id args = { /*.ne00 =*/ ne00, @@ -1967,20 +2010,20 @@ int ggml_metal_op_mul_mat_id(ggml_metal_op_t ctx, int idx) { ggml_metal_encoder_set_buffer (enc, bid_ids, 4); ggml_metal_encoder_set_buffer (enc, bid_dst, 5); - const size_t smem = ggml_metal_pipeline_get_smem(pipeline); + const size_t smem = pipeline.smem; ggml_metal_encoder_set_threadgroup_memory_size(enc, smem, 0); ggml_metal_encoder_dispatch_threadgroups(enc, (ne21 + 31)/32, (ne01 + 63)/64, ne02, 128, 1, 1); } } else { - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_mul_mv_id(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_mul_mv_id(lib, op); - const int nr0 = ggml_metal_pipeline_get_nr0(pipeline); - const int nr1 = ggml_metal_pipeline_get_nr1(pipeline); - const int nsg = ggml_metal_pipeline_get_nsg(pipeline); + const int nr0 = pipeline.nr0; + const int nr1 = pipeline.nr1; + const int nsg = pipeline.nsg; - const size_t smem = ggml_metal_pipeline_get_smem(pipeline); + const size_t smem = pipeline.smem; ggml_metal_kargs_mul_mv_id args = { /*.nei0 =*/ ne20, @@ -2064,7 +2107,7 @@ int ggml_metal_op_add_id(ggml_metal_op_t ctx, int idx) { /*.nb21 =*/ nb21, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_base(lib, GGML_OP_ADD_ID); + auto pipeline = ggml_metal_library_get_pipeline_base(lib, GGML_OP_ADD_ID); ggml_metal_encoder_set_pipeline(enc, pipeline); ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); @@ -2308,7 +2351,7 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) { /*.nb33 =*/nb33, }; - ggml_metal_pipeline_t pipeline0 = ggml_metal_library_get_pipeline_flash_attn_ext_pad(lib, op, has_mask, ncpsg); + auto pipeline0 = ggml_metal_library_get_pipeline_flash_attn_ext_pad(lib, op, has_mask, ncpsg); ggml_metal_encoder_set_pipeline(enc, pipeline0); ggml_metal_encoder_set_bytes (enc, &args0, sizeof(args0), 0); @@ -2339,7 +2382,7 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) { /*.nb33 =*/ nb33, }; - ggml_metal_pipeline_t pipeline0 = ggml_metal_library_get_pipeline_flash_attn_ext_blk(lib, op, nqptg, ncpsg); + auto pipeline0 = ggml_metal_library_get_pipeline_flash_attn_ext_blk(lib, op, nqptg, ncpsg); ggml_metal_encoder_set_pipeline(enc, pipeline0); ggml_metal_encoder_set_bytes (enc, &args0, sizeof(args0), 0); @@ -2424,7 +2467,7 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) { /*.logit_softcap =*/ logit_softcap, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_flash_attn_ext(lib, op, has_mask, has_sinks, has_bias, has_scap, has_kvpad, nsg); + auto pipeline = ggml_metal_library_get_pipeline_flash_attn_ext(lib, op, has_mask, has_sinks, has_bias, has_scap, has_kvpad, nsg); ggml_metal_encoder_set_pipeline(enc, pipeline); ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); @@ -2476,7 +2519,7 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) { /*.nb33 =*/nb33, }; - ggml_metal_pipeline_t pipeline0 = ggml_metal_library_get_pipeline_flash_attn_ext_pad(lib, op, has_mask, ncpsg); + auto pipeline0 = ggml_metal_library_get_pipeline_flash_attn_ext_pad(lib, op, has_mask, ncpsg); ggml_metal_encoder_set_pipeline(enc, pipeline0); ggml_metal_encoder_set_bytes (enc, &args0, sizeof(args0), 0); @@ -2578,7 +2621,7 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) { /*.logit_softcap =*/ logit_softcap, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_flash_attn_ext_vec(lib, op, has_mask, has_sinks, has_bias, has_scap, has_kvpad, nsg, nwg); + auto pipeline = ggml_metal_library_get_pipeline_flash_attn_ext_vec(lib, op, has_mask, has_sinks, has_bias, has_scap, has_kvpad, nsg, nwg); GGML_ASSERT(nsg*32 <= ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)); @@ -2630,7 +2673,7 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) { nrows, }; - ggml_metal_pipeline_t pipeline0 = ggml_metal_library_get_pipeline_flash_attn_ext_vec_reduce(lib, op, ne20, nwg); + auto pipeline0 = ggml_metal_library_get_pipeline_flash_attn_ext_vec_reduce(lib, op, ne20, nwg); ggml_metal_encoder_set_pipeline(enc, pipeline0); ggml_metal_encoder_set_bytes (enc, &args0, sizeof(args0), 0); @@ -2762,7 +2805,7 @@ int ggml_metal_op_bin(ggml_metal_op_t ctx, int idx) { // the offsets of src1 and all fused buffers are relative to the start of the src1 buffer bid_src1.offs = 0; - ggml_metal_pipeline_t pipeline = nullptr; + struct ggml_metal_pipeline_with_params pipeline; if (ggml_nelements(op->src[1]) == ne10 && ggml_is_contiguous(op->src[1]) && ne00 % 4 == 0 && ne10 % 4 == 0) { GGML_ASSERT(ggml_is_contiguous(op->src[0])); @@ -2835,7 +2878,7 @@ int ggml_metal_op_l2_norm(ggml_metal_op_t ctx, int idx) { /*.eps =*/ eps, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_l2_norm(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_l2_norm(lib, op); while (nth < ne00/4 && nth < ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)) { nth *= 2; @@ -2844,7 +2887,7 @@ int ggml_metal_op_l2_norm(ggml_metal_op_t ctx, int idx) { nth = std::min(nth, ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)); nth = std::min(nth, ne00/4); - const size_t smem = ggml_metal_pipeline_get_smem(pipeline); + const size_t smem = pipeline.smem; const int64_t nrows = ggml_nrows(op->src[0]); @@ -2887,7 +2930,7 @@ int ggml_metal_op_group_norm(ggml_metal_op_t ctx, int idx) { /*.eps =*/ eps, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_group_norm(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_group_norm(lib, op); int nth = 32; // SIMD width //while (nth < ne00/4 && nth < ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)) { @@ -2897,7 +2940,7 @@ int ggml_metal_op_group_norm(ggml_metal_op_t ctx, int idx) { //nth = std::min(nth, ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)); //nth = std::min(nth, ne00/4); - const size_t smem = ggml_metal_pipeline_get_smem(pipeline); + const size_t smem = pipeline.smem; ggml_metal_encoder_set_pipeline(enc, pipeline); ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); @@ -3022,7 +3065,7 @@ int ggml_metal_op_norm(ggml_metal_op_t ctx, int idx) { } } - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_norm(lib, op, n_fuse); + auto pipeline = ggml_metal_library_get_pipeline_norm(lib, op, n_fuse); int nth = 32; // SIMD width @@ -3033,7 +3076,7 @@ int ggml_metal_op_norm(ggml_metal_op_t ctx, int idx) { nth = std::min(nth, ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)); nth = std::min(nth, args.ne00_t); - const size_t smem = ggml_metal_pipeline_get_smem(pipeline); + const size_t smem = pipeline.smem; ggml_metal_encoder_set_pipeline(enc, pipeline); ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); @@ -3127,7 +3170,7 @@ int ggml_metal_op_rope(ggml_metal_op_t ctx, int idx) { /* src2 =*/ op->src[2] != nullptr, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_rope(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_rope(lib, op); ggml_metal_encoder_set_pipeline(enc, pipeline); ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); @@ -3199,7 +3242,7 @@ int ggml_metal_op_im2col(ggml_metal_op_t ctx, int idx) { /*.KHW =*/ KH * KW, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_im2col(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_im2col(lib, op); GGML_ASSERT(KH*KW <= ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)); @@ -3270,7 +3313,7 @@ int ggml_metal_op_conv_2d(ggml_metal_op_t ctx, int idx) { /*.d1 =*/ d1, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_conv_2d(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_conv_2d(lib, op); int nth = ggml_metal_pipeline_max_theads_per_threadgroup(pipeline); nth = std::min(nth, 256); @@ -3325,7 +3368,7 @@ int ggml_metal_op_conv_transpose_1d(ggml_metal_op_t ctx, int idx) { /*.nb1 =*/ nb1, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_conv_transpose_1d(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_conv_transpose_1d(lib, op); ggml_metal_encoder_set_pipeline(enc, pipeline); ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); @@ -3377,7 +3420,7 @@ int ggml_metal_op_conv_transpose_2d(ggml_metal_op_t ctx, int idx) { /*.nb2 =*/ nb2, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_conv_transpose_2d(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_conv_transpose_2d(lib, op); ggml_metal_encoder_set_pipeline(enc, pipeline); ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); @@ -3433,7 +3476,7 @@ int ggml_metal_op_upscale(ggml_metal_op_t ctx, int idx) { /*.sf3 =*/ sf3 }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_upscale(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_upscale(lib, op); const int nth = std::min(ggml_metal_pipeline_max_theads_per_threadgroup(pipeline), ne0); @@ -3477,7 +3520,7 @@ int ggml_metal_op_pad(ggml_metal_op_t ctx, int idx) { /*.nb3 =*/ nb3 }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_pad(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_pad(lib, op); const int nth = std::min(1024, ne0); @@ -3523,7 +3566,7 @@ int ggml_metal_op_pad_reflect_1d(ggml_metal_op_t ctx, int idx) { /*.p1 =*/ ((const int32_t *)(op->op_params))[1] }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_pad_reflect_1d(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_pad_reflect_1d(lib, op); const int nth = std::min(1024, ne0); @@ -3560,7 +3603,7 @@ int ggml_metal_op_arange(ggml_metal_op_t ctx, int idx) { const int nth = std::min(1024, ne0); - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_arange(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_arange(lib, op); ggml_metal_encoder_set_pipeline(enc, pipeline); ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); @@ -3591,7 +3634,7 @@ int ggml_metal_op_timestep_embedding(ggml_metal_op_t ctx, int idx) { /*.max_period =*/ max_period, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_timestep_embedding(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_timestep_embedding(lib, op); const int nth = std::max(1, std::min(1024, dim/2)); @@ -3621,7 +3664,7 @@ int ggml_metal_op_argmax(ggml_metal_op_t ctx, int idx) { /*.nb01 = */ nb01, }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_argmax(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_argmax(lib, op); const int64_t nrows = ggml_nrows(op->src[0]); @@ -3630,7 +3673,7 @@ int ggml_metal_op_argmax(ggml_metal_op_t ctx, int idx) { nth *= 2; } - const size_t smem = ggml_metal_pipeline_get_smem(pipeline); + const size_t smem = pipeline.smem; ggml_metal_encoder_set_pipeline(enc, pipeline); ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); @@ -3657,7 +3700,7 @@ int ggml_metal_op_argsort(ggml_metal_op_t ctx, int idx) { GGML_TENSOR_LOCALS( int32_t, ne, op, ne); GGML_TENSOR_LOCALS(uint64_t, nb, op, nb); - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_argsort(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_argsort(lib, op); // bitonic sort requires the number of elements to be power of 2 int nth = 1; @@ -3706,7 +3749,7 @@ int ggml_metal_op_argsort(ggml_metal_op_t ctx, int idx) { ggml_metal_encoder_dispatch_threadgroups(enc, npr*ne01, ne02, ne03, nth, 1, 1); - ggml_metal_pipeline_t pipeline_merge = ggml_metal_library_get_pipeline_argsort_merge(lib, op); + auto pipeline_merge = ggml_metal_library_get_pipeline_argsort_merge(lib, op); int len = nth; @@ -3764,7 +3807,7 @@ int ggml_metal_op_top_k(ggml_metal_op_t ctx, int idx) { GGML_TENSOR_LOCALS( int32_t, ne, op, ne); GGML_TENSOR_LOCALS(uint64_t, nb, op, nb); - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_top_k(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_top_k(lib, op); // bitonic sort requires the number of elements to be power of 2 int nth = 1; @@ -3818,7 +3861,7 @@ int ggml_metal_op_top_k(ggml_metal_op_t ctx, int idx) { ggml_metal_encoder_dispatch_threadgroups(enc, npr*ne01, ne02, ne03, nth, 1, 1); - ggml_metal_pipeline_t pipeline_merge = ggml_metal_library_get_pipeline_top_k_merge(lib, op); + auto pipeline_merge = ggml_metal_library_get_pipeline_top_k_merge(lib, op); int len = args.top_k; @@ -3881,7 +3924,7 @@ int ggml_metal_op_leaky_relu(ggml_metal_op_t ctx, int idx) { /*.slope =*/ slope }; - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_unary(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_unary(lib, op); int64_t n = ggml_nelements(op); @@ -3899,6 +3942,57 @@ int ggml_metal_op_leaky_relu(ggml_metal_op_t ctx, int idx) { return 1; } +int ggml_metal_op_tri(ggml_metal_op_t ctx, int idx) { + ggml_tensor * op = ctx->node(idx); + + ggml_metal_library_t lib = ctx->lib; + ggml_metal_encoder_t enc = ctx->enc; + + GGML_TENSOR_LOCALS( int32_t, ne0, op->src[0], ne); + GGML_TENSOR_LOCALS(uint64_t, nb0, op->src[0], nb); + GGML_TENSOR_LOCALS( int32_t, ne, op, ne); + GGML_TENSOR_LOCALS(uint64_t, nb, op, nb); + + ggml_metal_kargs_tri args = { + /*.ne00 =*/ ne00, + /*.ne01 =*/ ne01, + /*.ne02 =*/ ne02, + /*.ne03 =*/ ne03, + /*.nb00 =*/ nb00, + /*.nb01 =*/ nb01, + /*.nb02 =*/ nb02, + /*.nb03 =*/ nb03, + /*.ne0 =*/ ne0, + /*.ne1 =*/ ne1, + /*.ne2 =*/ ne2, + /*.ne3 =*/ ne3, + /*.nb0 =*/ nb0, + /*.nb1 =*/ nb1, + /*.nb2 =*/ nb2, + /*.nb3 =*/ nb3, + }; + + auto pipeline = ggml_metal_library_get_pipeline_tri(lib, op); + + int nth = 32; // SIMD width + + while (nth < ne00 && nth < ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)) { + nth *= 2; + } + + nth = std::min(nth, ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)); + nth = std::min(nth, ne00); + + ggml_metal_encoder_set_pipeline(enc, pipeline); + ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[0]), 1); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), 2); + + ggml_metal_encoder_dispatch_threadgroups(enc, ne01, ne02, ne03, nth, 1, 1); + + return 1; +} + int ggml_metal_op_opt_step_adamw(ggml_metal_op_t ctx, int idx) { ggml_tensor * op = ctx->node(idx); @@ -3910,7 +4004,7 @@ int ggml_metal_op_opt_step_adamw(ggml_metal_op_t ctx, int idx) { GGML_TENSOR_LOCALS( int32_t, ne, op, ne); GGML_TENSOR_LOCALS(uint64_t, nb, op, nb); - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_opt_step_adamw(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_opt_step_adamw(lib, op); const int64_t np = ggml_nelements(op->src[0]); ggml_metal_kargs_opt_step_adamw args = { @@ -3946,7 +4040,7 @@ int ggml_metal_op_opt_step_sgd(ggml_metal_op_t ctx, int idx) { GGML_TENSOR_LOCALS( int32_t, ne, op, ne); GGML_TENSOR_LOCALS(uint64_t, nb, op, nb); - ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_opt_step_sgd(lib, op); + auto pipeline = ggml_metal_library_get_pipeline_opt_step_sgd(lib, op); const int64_t np = ggml_nelements(op->src[0]); ggml_metal_kargs_opt_step_sgd args = { diff --git a/ggml/src/ggml-metal/ggml-metal-ops.h b/ggml/src/ggml-metal/ggml-metal-ops.h index b5546146e1..902b544523 100644 --- a/ggml/src/ggml-metal/ggml-metal-ops.h +++ b/ggml/src/ggml-metal/ggml-metal-ops.h @@ -47,6 +47,7 @@ int ggml_metal_op_concat (ggml_metal_op_t ctx, int idx); int ggml_metal_op_repeat (ggml_metal_op_t ctx, int idx); int ggml_metal_op_acc (ggml_metal_op_t ctx, int idx); int ggml_metal_op_scale (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_fill (ggml_metal_op_t ctx, int idx); int ggml_metal_op_clamp (ggml_metal_op_t ctx, int idx); int ggml_metal_op_unary (ggml_metal_op_t ctx, int idx); int ggml_metal_op_glu (ggml_metal_op_t ctx, int idx); @@ -83,6 +84,7 @@ int ggml_metal_op_argmax (ggml_metal_op_t ctx, int idx); int ggml_metal_op_argsort (ggml_metal_op_t ctx, int idx); int ggml_metal_op_top_k (ggml_metal_op_t ctx, int idx); int ggml_metal_op_leaky_relu (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_tri (ggml_metal_op_t ctx, int idx); int ggml_metal_op_opt_step_adamw (ggml_metal_op_t ctx, int idx); int ggml_metal_op_opt_step_sgd (ggml_metal_op_t ctx, int idx); diff --git a/ggml/src/ggml-metal/ggml-metal.metal b/ggml/src/ggml-metal/ggml-metal.metal index 3ca8d9b322..4b78d5a2ba 100644 --- a/ggml/src/ggml-metal/ggml-metal.metal +++ b/ggml/src/ggml-metal/ggml-metal.metal @@ -1249,6 +1249,22 @@ kernel void kernel_scale_f32_4( dst[tpig] = src0[tpig] * args.scale + args.bias; } +kernel void kernel_fill_f32( + constant ggml_metal_kargs_fill & args, + device const float * src0, + device float * dst, + uint tpig[[thread_position_in_grid]]) { + dst[tpig] = args.val; +} + +kernel void kernel_fill_f32_4( + constant ggml_metal_kargs_fill & args, + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + dst[tpig] = args.val; +} + kernel void kernel_clamp_f32( constant ggml_metal_kargs_clamp & args, device const float * src0, @@ -1595,6 +1611,36 @@ kernel void kernel_exp_f32_4( dst[tpig] = exp(src0[tpig]); } +kernel void kernel_softplus_f32( + device const float * src0, + device float * dst, + uint tpig[[thread_position_in_grid]]) { + device const float & x = src0[tpig]; + dst[tpig] = select(log(1.0f + exp(x)), x, x > 20.0f); +} + +kernel void kernel_softplus_f32_4( + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + device const float4 & x = src0[tpig]; + dst[tpig] = select(log(1.0f + exp(x)), x, x > 20.0f); +} + +kernel void kernel_expm1_f32( + device const float * src0, + device float * dst, + uint tpig[[thread_position_in_grid]]) { + dst[tpig] = exp(src0[tpig]) - 1.0f; +} + +kernel void kernel_expm1_f32_4( + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + dst[tpig] = exp(src0[tpig]) - 1.0f; +} + kernel void kernel_reglu_f32( constant ggml_metal_kargs_glu & args, device const char * src0, @@ -1943,6 +1989,75 @@ typedef decltype(kernel_cumsum_add) kernel_cumsum_add_t; template [[host_name("kernel_cumsum_add_f32")]] kernel kernel_cumsum_add_t kernel_cumsum_add; + +template +bool _ggml_vec_tri_cmp(const int i, const int r); + +template<> +bool _ggml_vec_tri_cmp(const int i, const int r) { + return i < r; +} + +template<> +bool _ggml_vec_tri_cmp(const int i, const int r) { + return i <= r; +} + +template<> +bool _ggml_vec_tri_cmp(const int i, const int r) { + return i > r; +} + +template<> +bool _ggml_vec_tri_cmp(const int i, const int r) { + return i >= r; +} + +template +kernel void kernel_tri( + constant ggml_metal_kargs_tri & args, + device const char * src0, + device const char * dst, + uint3 tgpig[[threadgroup_position_in_grid]], + ushort3 tpitg[[thread_position_in_threadgroup]], + ushort3 ntg[[threads_per_threadgroup]]) { + const int i3 = tgpig.z; + const int i2 = tgpig.y; + const int i1 = tgpig.x; + + if (i3 >= args.ne03 || i2 >= args.ne02 || i1 >= args.ne01) { + return; + } + + device const T * src_row = (device const T *) ((device const char *) src0 + i1*args.nb01 + i2*args.nb02 + i3*args.nb03); + device T * dst_row = (device T *) ((device char *) dst + i1*args.nb1 + i2*args.nb2 + i3*args.nb3); + + // Each thread is a single element of the row if ne00 < max threads per + // threadgroup, so this will loop once for each index that this thread is + // responsible for + for (int64_t i0 = tpitg.x; i0 < args.ne00; i0 += ntg.x) { + // Use the comparison as a mask for branchless + dst_row[i0] = static_cast(_ggml_vec_tri_cmp(i0, i1)) * src_row[i0]; + } +} + +typedef decltype(kernel_tri) kernel_tri_t; + +template [[host_name("kernel_tri_f32_0")]] kernel kernel_tri_t kernel_tri; +template [[host_name("kernel_tri_f32_1")]] kernel kernel_tri_t kernel_tri; +template [[host_name("kernel_tri_f32_2")]] kernel kernel_tri_t kernel_tri; +template [[host_name("kernel_tri_f32_3")]] kernel kernel_tri_t kernel_tri; +template [[host_name("kernel_tri_f16_0")]] kernel kernel_tri_t kernel_tri; +template [[host_name("kernel_tri_f16_1")]] kernel kernel_tri_t kernel_tri; +template [[host_name("kernel_tri_f16_2")]] kernel kernel_tri_t kernel_tri; +template [[host_name("kernel_tri_f16_3")]] kernel kernel_tri_t kernel_tri; +#if defined(GGML_METAL_HAS_BF16) +template [[host_name("kernel_tri_bf16_0")]] kernel kernel_tri_t kernel_tri; +template [[host_name("kernel_tri_bf16_1")]] kernel kernel_tri_t kernel_tri; +template [[host_name("kernel_tri_bf16_2")]] kernel kernel_tri_t kernel_tri; +template [[host_name("kernel_tri_bf16_3")]] kernel kernel_tri_t kernel_tri; +#endif + template kernel void kernel_soft_max( constant ggml_metal_kargs_soft_max & args, diff --git a/ggml/src/ggml-opencl/ggml-opencl.cpp b/ggml/src/ggml-opencl/ggml-opencl.cpp index 277a30d30e..0d37587f60 100644 --- a/ggml/src/ggml-opencl/ggml-opencl.cpp +++ b/ggml/src/ggml-opencl/ggml-opencl.cpp @@ -3083,6 +3083,10 @@ static bool ggml_opencl_supports_op(ggml_backend_dev_t dev, const struct ggml_te case GGML_OP_REPEAT: return op->src[0]->type == GGML_TYPE_F32 && op->type == GGML_TYPE_F32; // Assuming F32 for now, can be expanded case GGML_OP_PAD: + // TODO: add circular padding support for opencl, see https://github.com/ggml-org/llama.cpp/pull/16985 + if (ggml_get_op_params_i32(op, 8) != 0) { + return false; + } return op->src[0]->type == GGML_TYPE_F32 && op->type == GGML_TYPE_F32; case GGML_OP_UPSCALE: { ggml_scale_mode mode = (ggml_scale_mode)(ggml_get_op_params_i32(op, 0) & 0xFF); diff --git a/ggml/src/ggml-rpc/ggml-rpc.cpp b/ggml/src/ggml-rpc/ggml-rpc.cpp index 48fd99a762..18a45d2d96 100644 --- a/ggml/src/ggml-rpc/ggml-rpc.cpp +++ b/ggml/src/ggml-rpc/ggml-rpc.cpp @@ -128,6 +128,7 @@ struct rpc_msg_device_count_rsp { struct rpc_msg_get_alloc_size_req { uint32_t device; rpc_tensor tensor; + rpc_tensor srcs[GGML_MAX_SRC]; }; struct rpc_msg_get_alloc_size_rsp { @@ -572,6 +573,11 @@ static void * ggml_backend_rpc_buffer_get_base(ggml_backend_buffer_t buffer) { static rpc_tensor serialize_tensor(const ggml_tensor * tensor) { rpc_tensor result; + if (!tensor) { + memset(&result, 0, sizeof(result)); + return result; + } + result.id = reinterpret_cast(tensor); result.type = tensor->type; if (tensor->buffer) { @@ -753,23 +759,41 @@ static size_t ggml_backend_rpc_get_max_size(ggml_backend_buffer_type_t buft) { } static size_t ggml_backend_rpc_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) { + // should we query the remote server for the actual size + bool rpc_get = false; + // See comments in init_tensor. - if (ggml_is_quantized(tensor->type) && (tensor->ne[0] % 512 != 0) && (tensor->view_src == nullptr)) { + rpc_get |= ggml_is_quantized(tensor->type) && (tensor->ne[0] % 512 != 0) && (tensor->view_src == nullptr); + + // ops that require additional memory for fleeting data on certain backends + // ref: https://github.com/ggml-org/llama.cpp/pull/15966 + rpc_get |= tensor->op == GGML_OP_FLASH_ATTN_EXT; + rpc_get |= tensor->op == GGML_OP_MUL_MAT_ID; + + if (rpc_get) { ggml_backend_rpc_buffer_type_context * buft_ctx = (ggml_backend_rpc_buffer_type_context *)buft->context; auto sock = get_socket(buft_ctx->endpoint); - rpc_msg_get_alloc_size_req request; - request.device = buft_ctx->device; - request.tensor = serialize_tensor(tensor); + rpc_msg_get_alloc_size_req request = { + /*.device =*/ buft_ctx->device, + /*.tensor =*/ serialize_tensor(tensor), + /*.srcs =*/ {}, + }; + // .get_alloc_size could be a function of the tensor's srcs, so we must serialize them as well + for (int i = 0; i < GGML_MAX_SRC; i++) { + request.srcs[i] = serialize_tensor(tensor->src[i]); + } + + // TODO: cache the alloc responses to avoid extra RPC calls? rpc_msg_get_alloc_size_rsp response; bool status = send_rpc_cmd(sock, RPC_CMD_GET_ALLOC_SIZE, &request, sizeof(request), &response, sizeof(response)); RPC_STATUS_ASSERT(status); return response.alloc_size; - } else { - return ggml_nbytes(tensor); } + + return ggml_nbytes(tensor); } static ggml_backend_buffer_type_i ggml_backend_rpc_buffer_type_interface = { @@ -1017,7 +1041,7 @@ bool rpc_server::get_alloc_size(const rpc_msg_get_alloc_size_req & request, rpc_ } ggml_backend_buffer_type_t buft; struct ggml_init_params params { - /*.mem_size =*/ ggml_tensor_overhead(), + /*.mem_size =*/ ggml_tensor_overhead()*(1 + GGML_MAX_SRC), /*.mem_buffer =*/ NULL, /*.no_alloc =*/ true, }; @@ -1025,12 +1049,18 @@ bool rpc_server::get_alloc_size(const rpc_msg_get_alloc_size_req & request, rpc_ ggml_context_ptr ctx_ptr { ggml_init(params) }; GGML_ASSERT(ctx_ptr != nullptr); ggml_context * ctx = ctx_ptr.get(); - ggml_tensor * tensor = deserialize_tensor(ctx, &request.tensor); + ggml_tensor * tensor = deserialize_tensor(ctx, &request.tensor); if (tensor == nullptr) { GGML_LOG_ERROR("Null tensor pointer passed to server get_alloc_size function.\n"); return false; } + for (int i = 0; i < GGML_MAX_SRC; i++) { + if (request.srcs[i].id != 0) { + tensor->src[i] = deserialize_tensor(ctx, &request.srcs[i]); + } + } + LOG_DBG("[%s] device: %d, buffer: %p, data: %p\n", __func__, dev_id, (void*)tensor->buffer, tensor->data); if (tensor->buffer == nullptr) { //No buffer allocated. @@ -1227,7 +1257,8 @@ bool rpc_server::get_cached_file(uint64_t hash, std::vector & data) { char hash_str[17]; snprintf(hash_str, sizeof(hash_str), "%016" PRIx64, hash); fs::path cache_file = fs::path(cache_dir) / hash_str; - if (!fs::exists(cache_file)) { + std::error_code ec; + if (!fs::exists(cache_file, ec)) { return false; } std::ifstream ifs(cache_file, std::ios::binary); diff --git a/ggml/src/ggml-sycl/convert.cpp b/ggml/src/ggml-sycl/convert.cpp index 96d2583b13..7c6ea8a57a 100644 --- a/ggml/src/ggml-sycl/convert.cpp +++ b/ggml/src/ggml-sycl/convert.cpp @@ -2,6 +2,13 @@ #include "dequantize.hpp" #include "presets.hpp" +#if defined(__INTEL_LLVM_COMPILER) + #if __has_include() + #include + #define GGML_SYCL_HAS_BF16 + #endif +#endif + template static void dequantize_block(const void * __restrict__ vx, dst_t * __restrict__ y, const int64_t k, const sycl::nd_item<3> &item_ct1) { @@ -566,6 +573,10 @@ to_fp16_sycl_t ggml_get_to_fp16_sycl(ggml_type type, ggml_tensor * dst) { return dequantize_row_iq4_nl_sycl; case GGML_TYPE_F32: return convert_unary_sycl; +#ifdef GGML_SYCL_HAS_BF16 + case GGML_TYPE_BF16: + return convert_unary_sycl; +#endif default: return nullptr; } @@ -627,6 +638,10 @@ to_fp32_sycl_t ggml_get_to_fp32_sycl(ggml_type type, ggml_tensor *dst) { return dequantize_row_iq4_nl_sycl; case GGML_TYPE_F16: return convert_unary_sycl; +#ifdef GGML_SYCL_HAS_BF16 + case GGML_TYPE_BF16: + return convert_unary_sycl; +#endif default: return nullptr; } @@ -636,6 +651,10 @@ to_fp16_nc_sycl_t get_to_fp16_nc_sycl(ggml_type type) { switch (type) { case GGML_TYPE_F32: return convert_unary_nc_sycl; +#ifdef GGML_SYCL_HAS_BF16 + case GGML_TYPE_BF16: + return convert_unary_nc_sycl; +#endif default: return nullptr; } diff --git a/ggml/src/ggml-sycl/ggml-sycl.cpp b/ggml/src/ggml-sycl/ggml-sycl.cpp index a264ade0b7..7449a91609 100644 --- a/ggml/src/ggml-sycl/ggml-sycl.cpp +++ b/ggml/src/ggml-sycl/ggml-sycl.cpp @@ -4613,6 +4613,10 @@ static bool ggml_backend_sycl_device_supports_op(ggml_backend_dev_t dev, const g case GGML_OP_ACC: return true; case GGML_OP_PAD: + // TODO: add circular padding support for syscl, see https://github.com/ggml-org/llama.cpp/pull/16985 + if (ggml_get_op_params_i32(op, 8) != 0) { + return false; + } return ggml_is_contiguous(op->src[0]); case GGML_OP_LEAKY_RELU: case GGML_OP_TIMESTEP_EMBEDDING: diff --git a/ggml/src/ggml-vulkan/ggml-vulkan.cpp b/ggml/src/ggml-vulkan/ggml-vulkan.cpp index 95966ce1d8..c6f5809ccd 100644 --- a/ggml/src/ggml-vulkan/ggml-vulkan.cpp +++ b/ggml/src/ggml-vulkan/ggml-vulkan.cpp @@ -353,10 +353,17 @@ enum vk_conv_shapes { CONV_SHAPE_COUNT, }; -uint32_t conv_shapes_wg_denoms[][3] = { - { 128, 128, 1 }, - { 64, 32, 1 }, - { 32, 256, 1 }, +struct vk_conv_block_size { + uint32_t K; + uint32_t NPQ; + uint32_t CRS; +}; + +vk_conv_block_size vk_conv_block_sizes[CONV_SHAPE_COUNT] = { + // K NPQ CRS + { 128, 128, 16 }, // CONV_SHAPE_128x128 + { 64, 32, 32 }, // CONV_SHAPE_64x32 + { 32, 256, 16 }, // CONV_SHAPE_32x256 }; enum dmmv_wg_sizes { @@ -519,6 +526,7 @@ struct vk_device_struct { bool fp16; bool bf16; bool pipeline_robustness; + bool memory_priority; vk::Device device; uint32_t vendor_id; vk::DriverId driver_id; @@ -769,11 +777,6 @@ struct vk_device_struct { std::unique_ptr memory_logger; #endif - // for GGML_VK_PERF_LOGGER - std::unique_ptr perf_logger; - vk::QueryPool query_pool; - int32_t num_queries; - ~vk_device_struct() { VK_LOG_DEBUG("destroy device " << name); @@ -1042,6 +1045,7 @@ struct vk_op_pad_push_constants { uint32_t ne00; uint32_t ne01; uint32_t ne02; uint32_t ne03; uint32_t nb00; uint32_t nb01; uint32_t nb02; uint32_t nb03; uint32_t ne10; uint32_t ne11; uint32_t ne12; uint32_t ne13; uint32_t nb10; uint32_t nb11; uint32_t nb12; uint32_t nb13; uint32_t misalign_offsets; + uint32_t circular; uint32_t lp0; uint32_t rp0; uint32_t lp1; uint32_t rp1; @@ -1084,6 +1088,7 @@ static vk_op_pad_push_constants vk_op_pad_push_constants_init(const ggml_tensor p.rp2 = dst->op_params[5]; p.lp3 = dst->op_params[6]; p.rp3 = dst->op_params[7]; + p.circular = dst->op_params[8]; return p; // fastdiv values and offsets are initialized later in ggml_vk_op } @@ -1227,6 +1232,7 @@ struct vk_op_topk_push_constants { uint32_t orig_ncols; uint32_t ncols_input; uint32_t ncols_output; + uint32_t k; uint32_t nrows; uint32_t first_pass; uint32_t last_pass; @@ -1342,20 +1348,11 @@ struct vk_op_conv2d_push_constants { uint32_t Cin; uint32_t N; - uint32_t KW; - uint32_t KH; uint32_t W; uint32_t H; uint32_t OW; uint32_t OH; - uint32_t s0; - uint32_t s1; - uint32_t p0; - uint32_t p1; - uint32_t d0; - uint32_t d1; - uint32_t nb01; uint32_t nb02; uint32_t nb03; @@ -1379,48 +1376,6 @@ template <> void init_pushconst_fastdiv(vk_op_conv2d_push_constants &p) { init_fastdiv_values(p.OW*p.OH, p.OWOHmp, p.OWOHL); } -struct vk_op_conv_transpose_2d_push_constants { - uint32_t Cout; - uint32_t Cin; - uint32_t N; - - uint32_t KW; - uint32_t KH; - uint32_t W; - uint32_t H; - uint32_t OW; - uint32_t OH; - - uint32_t s0; - uint32_t s1; - uint32_t p0; - uint32_t p1; - uint32_t d0; - uint32_t d1; - - uint32_t nb01; - uint32_t nb02; - uint32_t nb03; - - uint32_t nb11; - uint32_t nb12; - uint32_t nb13; - - uint32_t nb1; - uint32_t nb2; - uint32_t nb3; - - // init_fastdiv_values constants for dividing by OW, OW*OH - uint32_t OWmp; uint32_t OWL; - uint32_t OWOHmp; uint32_t OWOHL; -}; - -template <> void init_pushconst_fastdiv(vk_op_conv_transpose_2d_push_constants &p) { - // Compute magic values to divide by OW, OW*OH - init_fastdiv_values(p.OW, p.OWmp, p.OWL); - init_fastdiv_values(p.OW*p.OH, p.OWOHmp, p.OWOHL); -} - struct vk_op_conv2d_dw_push_constants { uint32_t ne; uint32_t batches; @@ -1563,12 +1518,21 @@ private: #define VK_LOG_MEMORY(msg) ((void) 0) #endif // GGML_VULKAN_MEMORY_DEBUG +static bool vk_perf_logger_enabled = false; +// number of calls between perf logger prints +static uint32_t vk_perf_logger_frequency = 1; + class vk_perf_logger { public: - void print_timings() { + void print_timings(bool force = false) { if (timings.empty()) { return; } + print_count++; + if ((print_count % vk_perf_logger_frequency) != 0 && !force) { + return; + } + print_count = 0; uint64_t total_all_op_times = 0; std::cerr << "----------------\nVulkan Timings:" << std::endl; for (const auto & t : timings) { @@ -1605,16 +1569,20 @@ class vk_perf_logger { flops.clear(); } - void log_timing(const ggml_tensor * node, uint64_t time) { + void log_timing(const ggml_tensor * node, const char *fusion_name, uint64_t time) { + std::string fusion_str; + if (fusion_name) { + fusion_str = fusion_name + std::string(" "); + } if (node->op == GGML_OP_UNARY) { - timings[ggml_unary_op_name(ggml_get_unary_op(node))].push_back(time); + timings[fusion_str + ggml_unary_op_name(ggml_get_unary_op(node))].push_back(time); return; } if (node->op == GGML_OP_MUL_MAT || node->op == GGML_OP_MUL_MAT_ID) { - const uint64_t m = node->src[0]->ne[1]; - const uint64_t n = (node->op == GGML_OP_MUL_MAT) ? node->ne[1] : node->ne[2]; + const uint64_t m = node->ne[0]; + const uint64_t n = node->ne[1]; const uint64_t k = node->src[1]->ne[0]; - const uint64_t batch = node->src[1]->ne[2] * node->src[1]->ne[3]; + const uint64_t batch = node->ne[2] * node->ne[3]; std::string name = ggml_op_name(node->op); if ((node->op == GGML_OP_MUL_MAT && n <= mul_mat_vec_max_cols) || (node->op == GGML_OP_MUL_MAT_ID && node->src[2]->ne[1] == 1)) { @@ -1623,9 +1591,13 @@ class vk_perf_logger { name += " "; name += ggml_type_name(node->src[0]->type); name += " m=" + std::to_string(m) + " n=" + std::to_string(n) + " k=" + std::to_string(k); + if (node->op == GGML_OP_MUL_MAT_ID) { + name += " n_expert=" + std::to_string(node->src[0]->ne[2]); + } if (batch > 1) { name += " batch=" + std::to_string(batch); } + name = fusion_str + name; timings[name].push_back(time); flops[name].push_back(m * n * (k + (k - 1)) * batch); return; @@ -1647,6 +1619,7 @@ class vk_perf_logger { uint64_t n_flops = size_M * size_N * (size_K + (size_K - 1)); name += " M=Cout=" + std::to_string(size_M) + ", K=Cin*KW*KH=" + std::to_string(size_K) + ", N=N*OW*OH=" + std::to_string(size_N); + name = fusion_str + name; flops[name].push_back(n_flops); timings[name].push_back(time); return; @@ -1654,6 +1627,7 @@ class vk_perf_logger { if (node->op == GGML_OP_RMS_NORM) { std::string name = ggml_op_name(node->op); name += "(" + std::to_string(node->ne[0]) + "," + std::to_string(node->ne[1]) + "," + std::to_string(node->ne[2]) + "," + std::to_string(node->ne[3]) + ")"; + name = fusion_str + name; timings[name].push_back(time); return; } @@ -1664,6 +1638,7 @@ class vk_perf_logger { const ggml_tensor * v = node->src[2]; const ggml_tensor * m = node->src[3]; std::stringstream name; + name << fusion_str; name << ggml_op_name(node->op) << " dst(" << dst->ne[0] << "," << dst->ne[1] << "," << dst->ne[2] << "," << dst->ne[3] << "), " << " q(" << q->ne[0] << "," << q->ne[1] << "," << q->ne[2] << "," << q->ne[3] << "), " << @@ -1673,11 +1648,21 @@ class vk_perf_logger { timings[name.str()].push_back(time); return; } - timings[ggml_op_name(node->op)].push_back(time); + if (node->op == GGML_OP_TOP_K) { + std::stringstream name; + name << fusion_str; + name << ggml_op_name(node->op) << + " K=" << node->ne[0] << + " (" << node->src[0]->ne[0] << "," << node->src[0]->ne[1] << "," << node->src[0]->ne[2] << "," << node->src[0]->ne[3] << ")"; + timings[name.str()].push_back(time); + return; + } + timings[fusion_str + ggml_op_name(node->op)].push_back(time); } private: std::map> timings; std::map> flops; + uint32_t print_count {}; }; struct ggml_backend_vk_context { @@ -1731,6 +1716,14 @@ struct ggml_backend_vk_context { // Bit 'i' means nodes[start_of_fusion + i] writes to memory. // If there's no fusion, bit 0 is still set. int fused_ops_write_mask {}; + + // for GGML_VK_PERF_LOGGER + std::unique_ptr perf_logger; + vk::QueryPool query_pool; + std::vector query_fusion_names; + std::vector query_nodes; + int32_t num_queries {}; + int32_t query_idx {}; }; static void * const vk_ptr_base = (void *)(uintptr_t) 0x1000; // NOLINT @@ -1856,8 +1849,6 @@ struct vk_instance_t { static bool vk_instance_initialized = false; static vk_instance_t vk_instance; -static bool vk_perf_logger_enabled = false; - #ifdef GGML_VULKAN_CHECK_RESULTS static size_t vk_skip_checks; static size_t vk_output_tensor; @@ -2360,7 +2351,13 @@ static vk_buffer ggml_vk_create_buffer(vk_device& device, size_t size, const std vk::PhysicalDeviceMemoryProperties mem_props = device->physical_device.getMemoryProperties(); - const vk::MemoryAllocateFlagsInfo mem_flags_info { mem_flags }; + const vk::MemoryPriorityAllocateInfoEXT mem_priority_info { 1.0f }; + + vk::MemoryAllocateFlagsInfo mem_flags_info { mem_flags }; + + if (device->memory_priority) { + mem_flags_info.setPNext(&mem_priority_info); + } for (auto it = req_flags_list.begin(); it != req_flags_list.end(); it++) { const auto & req_flags = *it; @@ -3565,7 +3562,7 @@ static void ggml_vk_load_shaders(vk_device& device) { SHADER_REDUCTION_MODE_SHMEM; for (uint32_t i = 0; i < mul_mat_vec_max_cols; ++i) { - ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[w][GGML_TYPE_F32 ][i], "mul_mat_vec_f32_f32_f32", arr_dmmv_f32_f32_f32_len[reduc], arr_dmmv_f32_f32_f32_data[reduc], "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {2, 1, 1}, {wg_size_subgroup, 2, i+1}, 1, false, use_subgroups, force_subgroup_size); + ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[w][GGML_TYPE_F32 ][i], "mul_mat_vec_f32_f32_f32", arr_dmmv_f32_f32_f32_len[reduc], arr_dmmv_f32_f32_f32_data[reduc], "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, {wg_size_subgroup, 1, i+1}, 1, false, use_subgroups, force_subgroup_size); ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[w][GGML_TYPE_F16 ][i], "mul_mat_vec_f16_f32_f32", arr_dmmv_f16_f32_f32_len[reduc], arr_dmmv_f16_f32_f32_data[reduc], "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {2, 1, 1}, {wg_size_subgroup, 2, i+1}, 1, false, use_subgroups, force_subgroup_size); ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[w][GGML_TYPE_BF16][i], "mul_mat_vec_bf16_f32_f32", arr_dmmv_bf16_f32_f32_len[reduc], arr_dmmv_bf16_f32_f32_data[reduc], "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {2, 1, 1}, {wg_size_subgroup, 2, i+1}, 1, false, use_subgroups, force_subgroup_size); ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[w][GGML_TYPE_Q4_0][i], "mul_mat_vec_q4_0_f32_f32", arr_dmmv_q4_0_f32_f32_len[reduc], arr_dmmv_q4_0_f32_f32_data[reduc], "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {2*rm_stdq, 1, 1}, {wg_size_subgroup, 2*rm_stdq, i+1}, 1, true, use_subgroups, force_subgroup_size); @@ -3589,7 +3586,7 @@ static void ggml_vk_load_shaders(vk_device& device) { ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[w][GGML_TYPE_IQ4_NL][i], "mul_mat_vec_iq4_nl_f32_f32", arr_dmmv_iq4_nl_f32_f32_len[reduc16], arr_dmmv_iq4_nl_f32_f32_data[reduc16], "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq, i+1}, 1, true, use_subgroups16, force_subgroup_size16); ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[w][GGML_TYPE_MXFP4][i], "mul_mat_vec_mxfp4_f32_f32", arr_dmmv_mxfp4_f32_f32_len[reduc16], arr_dmmv_mxfp4_f32_f32_data[reduc16], "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {wg_size_subgroup16, rm_iq, i+1}, 1, true, use_subgroups16, force_subgroup_size16); - ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[w][GGML_TYPE_F32 ][i], "mul_mat_vec_f32_f16_f32", arr_dmmv_f32_f16_f32_len[reduc], arr_dmmv_f32_f16_f32_data[reduc], "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {2, 1, 1}, {wg_size_subgroup, 2, i+1}, 1, false, use_subgroups, force_subgroup_size); + ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[w][GGML_TYPE_F32 ][i], "mul_mat_vec_f32_f16_f32", arr_dmmv_f32_f16_f32_len[reduc], arr_dmmv_f32_f16_f32_data[reduc], "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, {wg_size_subgroup, 1, i+1}, 1, false, use_subgroups, force_subgroup_size); ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[w][GGML_TYPE_F16 ][i], "mul_mat_vec_f16_f16_f32", arr_dmmv_f16_f16_f32_len[reduc], arr_dmmv_f16_f16_f32_data[reduc], "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {2, 1, 1}, {wg_size_subgroup, 2, i+1}, 1, false, use_subgroups, force_subgroup_size); ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[w][GGML_TYPE_BF16][i], "mul_mat_vec_bf16_f16_f32", arr_dmmv_bf16_f16_f32_len[reduc], arr_dmmv_bf16_f16_f32_data[reduc], "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {2, 1, 1}, {wg_size_subgroup, 2, i+1}, 1, false, use_subgroups, force_subgroup_size); ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[w][GGML_TYPE_Q4_0][i], "mul_mat_vec_q4_0_f16_f32", arr_dmmv_q4_0_f16_f32_len[reduc], arr_dmmv_q4_0_f16_f32_data[reduc], "main", mul_mat_vec_num_bindings, sizeof(vk_mat_vec_push_constants), {2*rm_stdq, 1, 1}, {wg_size_subgroup, 2*rm_stdq, i+1}, 1, true, use_subgroups, force_subgroup_size); @@ -3635,7 +3632,7 @@ static void ggml_vk_load_shaders(vk_device& device) { #endif // GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT } - ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[w][GGML_TYPE_F32 ], "mul_mat_vec_id_f32_f32", arr_dmmv_id_f32_f32_f32_len[reduc], arr_dmmv_id_f32_f32_f32_data[reduc], "main", mul_mat_vec_id_num_bindings, sizeof(vk_mat_vec_id_push_constants), {2, 1, 1}, {wg_size_subgroup, 2}, 1, false, use_subgroups, force_subgroup_size); + ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[w][GGML_TYPE_F32 ], "mul_mat_vec_id_f32_f32", arr_dmmv_id_f32_f32_f32_len[reduc], arr_dmmv_id_f32_f32_f32_data[reduc], "main", mul_mat_vec_id_num_bindings, sizeof(vk_mat_vec_id_push_constants), {1, 1, 1}, {wg_size_subgroup, 1}, 1, false, use_subgroups, force_subgroup_size); ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[w][GGML_TYPE_F16 ], "mul_mat_vec_id_f16_f32", arr_dmmv_id_f16_f32_f32_len[reduc], arr_dmmv_id_f16_f32_f32_data[reduc], "main", mul_mat_vec_id_num_bindings, sizeof(vk_mat_vec_id_push_constants), {2, 1, 1}, {wg_size_subgroup, 2}, 1, false, use_subgroups, force_subgroup_size); ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[w][GGML_TYPE_BF16], "mul_mat_vec_id_bf16_f32", arr_dmmv_id_bf16_f32_f32_len[reduc], arr_dmmv_id_bf16_f32_f32_data[reduc], "main", mul_mat_vec_id_num_bindings, sizeof(vk_mat_vec_id_push_constants), {2, 1, 1}, {wg_size_subgroup, 2}, 1, false, use_subgroups, force_subgroup_size); ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[w][GGML_TYPE_Q4_0], "mul_mat_vec_id_q4_0_f32", arr_dmmv_id_q4_0_f32_f32_len[reduc], arr_dmmv_id_q4_0_f32_f32_data[reduc], "main", mul_mat_vec_id_num_bindings, sizeof(vk_mat_vec_id_push_constants), {2*rm_stdq, 1, 1}, {wg_size_subgroup, 2*rm_stdq}, 1, true, use_subgroups, force_subgroup_size); @@ -4041,7 +4038,7 @@ static void ggml_vk_load_shaders(vk_device& device) { uint32_t nary_shmem = 2 * sizeof(int) * BLOCK_SIZE + sizeof(int) * device->subgroup_size + 2 * sizeof(int) + - (BLOCK_SIZE / device->subgroup_size) * sizeof(int); + 2 * (BLOCK_SIZE / device->subgroup_size) * sizeof(int); if (device->subgroup_arithmetic && device->subgroup_require_full_support && device->subgroup_shuffle && device->subgroup_ballot && nary_shmem <= device->properties.limits.maxComputeSharedMemorySize) { ggml_vk_create_pipeline2(device, device->pipeline_topk_f32[i], "topk_f32_"+std::to_string(i), topk_nary_search_f32_len, topk_nary_search_f32_data, "main", 2, sizeof(vk_op_topk_push_constants), {BLOCK_SIZE, 1, 1}, {BLOCK_SIZE, device->subgroup_size, device->subgroup_size_log2}, 1, true, true, device->subgroup_size); @@ -4061,10 +4058,16 @@ static void ggml_vk_load_shaders(vk_device& device) { for (auto &s : device->pipeline_solve_tri_f32) { const vk_solve_tri_pipeline_state &state = s.first; + + // Max number of rows to load at a time, limited by shared memory + const uint32_t batch_N = device->properties.limits.maxComputeSharedMemorySize / ((state.N + state.K) * sizeof(float)); + // Need at least K invocations, and prefer a minimum of 128 to spread out loading shared memory + const uint32_t block_size = std::max(128u, 1u << (uint32_t)ceilf(log2f(float(state.K)))); + ggml_vk_create_pipeline( device, s.second, "solve_tri_f32", solve_tri_f32_len, solve_tri_f32_data, "main", 3, - sizeof(vk_op_binary_push_constants), {1, 1, 1}, { 0, state.N, state.K }, 1, true); + sizeof(vk_op_binary_push_constants), {1, 1, 1}, { 0, state.N, state.K, batch_N, block_size }, 1, true); } #define IM2COL(bda) \ @@ -4110,12 +4113,10 @@ static void ggml_vk_load_shaders(vk_device& device) { // conv2d, conv_transpose_2d for (uint32_t s = 0; s < CONV_SHAPE_COUNT; ++s) { uint32_t conv2d_WG_SIZE = 256; - uint32_t conv2d_BS_K = 128; - uint32_t conv2d_BS_CRS = 16; uint32_t use_collectives = 0; // Enables subgroup ops for preventing the re-calculation of indices. - uint32_t conv2d_BS_NPQ = 128; - uint32_t conv2d_TS_K = 8; + uint32_t conv2d_TS_K = (s == CONV_SHAPE_64x32) ? 4 : 8; uint32_t conv2d_SHMEM_PAD = 4; + vk_conv_block_size conv2d_BS = vk_conv_block_sizes[s]; bool conv2d_UNROLL = true; #if defined(GGML_VULKAN_COOPMAT2_GLSLC_SUPPORT) @@ -4129,29 +4130,9 @@ static void ggml_vk_load_shaders(vk_device& device) { conv2d_UNROLL = false; } else if (device->vendor_id == VK_VENDOR_ID_AMD) { conv2d_SHMEM_PAD = device->architecture == vk_device_architecture::AMD_GCN ? 1 : 4; - } - - switch (s) { - default: - case CONV_SHAPE_128x128: - conv2d_BS_K = conv_shapes_wg_denoms[CONV_SHAPE_128x128][0]; - conv2d_BS_NPQ = conv_shapes_wg_denoms[CONV_SHAPE_128x128][1]; - conv2d_BS_CRS = 16; - if (device->vendor_id == VK_VENDOR_ID_AMD && device->architecture != vk_device_architecture::AMD_GCN) { + if (s == CONV_SHAPE_128x128 && device->architecture != vk_device_architecture::AMD_GCN) { conv2d_UNROLL = false; } - break; - case CONV_SHAPE_64x32: - conv2d_BS_K = conv_shapes_wg_denoms[CONV_SHAPE_64x32][0]; - conv2d_BS_NPQ = conv_shapes_wg_denoms[CONV_SHAPE_64x32][1]; - conv2d_BS_CRS = 32; - conv2d_TS_K = 4; - break; - case CONV_SHAPE_32x256: - conv2d_BS_K = conv_shapes_wg_denoms[CONV_SHAPE_32x256][0]; - conv2d_BS_NPQ = conv_shapes_wg_denoms[CONV_SHAPE_32x256][1]; - conv2d_BS_CRS = 16; - break; } // Use collectives on pre-Turing NVIDIA GPUs and GCN AMD cards, which had slower integer math. @@ -4165,22 +4146,22 @@ static void ggml_vk_load_shaders(vk_device& device) { allow_collectives_nv && allow_collectives_amd) { use_collectives = 1; - conv2d_BS_CRS = std::min( + conv2d_BS.CRS = std::min( device->subgroup_size, - conv2d_BS_CRS); // CRS block size should be capped at subgroup size for correctness when shuffle is used. + conv2d_BS.CRS); // CRS block size should be capped at subgroup size for correctness when shuffle is used. } uint32_t conv2d_shmem_req = - (conv2d_BS_K * (conv2d_BS_CRS + conv2d_SHMEM_PAD) + conv2d_BS_CRS * (conv2d_BS_NPQ + conv2d_SHMEM_PAD)) * sizeof(float); + (conv2d_BS.K * (conv2d_BS.CRS + conv2d_SHMEM_PAD) + conv2d_BS.CRS * (conv2d_BS.NPQ + conv2d_SHMEM_PAD)) * sizeof(float); if (device->properties.limits.maxComputeSharedMemorySize < conv2d_shmem_req) { - conv2d_BS_CRS = 8; + conv2d_BS.CRS = 8; if (use_collectives) { - conv2d_BS_CRS = std::min(device->subgroup_size, conv2d_BS_CRS); + conv2d_BS.CRS = std::min(device->subgroup_size, conv2d_BS.CRS); } } - std::array wg_denoms = { conv2d_BS_K, conv2d_BS_NPQ, 1 }; - std::vector spec_constants = { conv2d_WG_SIZE, conv2d_BS_K, conv2d_BS_CRS, conv2d_BS_NPQ, conv2d_TS_K, use_collectives, conv2d_SHMEM_PAD }; + std::array wg_denoms = { conv2d_BS.K, 1, 1 }; + std::vector spec_constants = { conv2d_WG_SIZE, conv2d_BS.K, conv2d_BS.CRS, conv2d_BS.NPQ, conv2d_TS_K, use_collectives, conv2d_SHMEM_PAD }; #define CREATE_CONV(name, type_suffix, spv_suffix) \ for (auto &c : device->pipeline_##name##type_suffix[s]) { \ @@ -4197,15 +4178,13 @@ static void ggml_vk_load_shaders(vk_device& device) { ggml_vk_create_pipeline( \ device, c.second, #name #type_suffix, \ name##type_suffix##spv_suffix##_len, name##type_suffix##spv_suffix##_data, "main", 3, \ - sizeof(vk_op_##name##_push_constants), wg_denoms, spec_constants_cpy, 1, true, use_collectives); \ + sizeof(vk_op_conv2d_push_constants), wg_denoms, spec_constants_cpy, 1, true, use_collectives); \ } #define CREATE_CONVS(spv_suffix) \ CREATE_CONV(conv2d, _f32, spv_suffix) \ CREATE_CONV(conv2d, _f16_f32, spv_suffix) \ - if (device->properties.limits.maxPushConstantsSize >= sizeof(vk_op_conv_transpose_2d_push_constants)) { \ - CREATE_CONV(conv_transpose_2d, _f32, spv_suffix) \ - CREATE_CONV(conv_transpose_2d, _f16_f32, spv_suffix) \ - } + CREATE_CONV(conv_transpose_2d, _f32, spv_suffix) \ + CREATE_CONV(conv_transpose_2d, _f16_f32, spv_suffix) #if defined(GGML_VULKAN_COOPMAT2_GLSLC_SUPPORT) if (device->coopmat2) { CREATE_CONVS(_cm2) @@ -4226,9 +4205,9 @@ static void ggml_vk_load_shaders(vk_device& device) { ggml_vk_create_pipeline(device, device->pipeline_conv2d_dw_cwhn_f16_f32, "conv2d_dw_cwhn_f16_f32", conv2d_dw_cwhn_f16_f32_len, conv2d_dw_cwhn_f16_f32_data, "main", 3, sizeof(vk_op_conv2d_dw_push_constants), {512, 1, 1}, {}, 1); for (uint32_t i = 0; i < num_topk_moe_pipelines; ++i) { - ggml_vk_create_pipeline2(device, device->pipeline_topk_moe[i][TOPK_MOE_EARLY_SOFTMAX], "topk_moe_f32_early_softmax_"+std::to_string(i), topk_moe_f32_len, topk_moe_f32_data, "main", 3, sizeof(vk_op_topk_moe_push_constants), {1, 1, 1}, {device->subgroup_size, 1u<pipeline_topk_moe[i][TOPK_MOE_EARLY_SOFTMAX_NORM], "topk_moe_f32_early_softmax_norm"+std::to_string(i), topk_moe_f32_len, topk_moe_f32_data, "main", 3, sizeof(vk_op_topk_moe_push_constants), {1, 1, 1}, {device->subgroup_size, 1u<pipeline_topk_moe[i][TOPK_MOE_LATE_SOFTMAX], "topk_moe_f32_late_softmax"+std::to_string(i), topk_moe_f32_len, topk_moe_f32_data, "main", 3, sizeof(vk_op_topk_moe_push_constants), {1, 1, 1}, {device->subgroup_size, 1u<pipeline_topk_moe[i][TOPK_MOE_EARLY_SOFTMAX], "topk_moe_f32_early_softmax_"+std::to_string(i), topk_moe_f32_len, topk_moe_f32_data, "main", 3, sizeof(vk_op_topk_moe_push_constants), {1, 1, 1}, {device->subgroup_size, 1u<subgroup_size); + ggml_vk_create_pipeline2(device, device->pipeline_topk_moe[i][TOPK_MOE_EARLY_SOFTMAX_NORM], "topk_moe_f32_early_softmax_norm"+std::to_string(i), topk_moe_f32_len, topk_moe_f32_data, "main", 3, sizeof(vk_op_topk_moe_push_constants), {1, 1, 1}, {device->subgroup_size, 1u<subgroup_size); + ggml_vk_create_pipeline2(device, device->pipeline_topk_moe[i][TOPK_MOE_LATE_SOFTMAX], "topk_moe_f32_late_softmax"+std::to_string(i), topk_moe_f32_len, topk_moe_f32_data, "main", 3, sizeof(vk_op_topk_moe_push_constants), {1, 1, 1}, {device->subgroup_size, 1u<subgroup_size); } for (auto &c : compiles) { @@ -4249,9 +4228,6 @@ static vk_device ggml_vk_get_device(size_t idx) { #ifdef GGML_VULKAN_MEMORY_DEBUG device->memory_logger = std::unique_ptr(new vk_memory_logger()); #endif - if (vk_perf_logger_enabled) { - device->perf_logger = std::unique_ptr(new vk_perf_logger()); - } size_t dev_num = vk_instance.device_indices[idx]; @@ -4331,6 +4307,9 @@ static vk_device ggml_vk_get_device(size_t idx) { #endif } else if (strcmp("VK_KHR_pipeline_executable_properties", properties.extensionName) == 0) { pipeline_executable_properties_support = true; + } else if (strcmp("VK_EXT_memory_priority", properties.extensionName) == 0 && + getenv("GGML_VK_ENABLE_MEMORY_PRIORITY")) { + device->memory_priority = true; } } @@ -4522,6 +4501,16 @@ static vk_device ggml_vk_get_device(size_t idx) { device_extensions.push_back("VK_EXT_pipeline_robustness"); } + VkPhysicalDeviceMemoryPriorityFeaturesEXT memory_priority_features; + memory_priority_features.pNext = nullptr; + memory_priority_features.sType = VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_MEMORY_PRIORITY_FEATURES_EXT; + memory_priority_features.memoryPriority = VK_FALSE; + if (device->memory_priority) { + last_struct->pNext = (VkBaseOutStructure *)&memory_priority_features; + last_struct = (VkBaseOutStructure *)&memory_priority_features; + device_extensions.push_back("VK_EXT_memory_priority"); + } + VkPhysicalDeviceSubgroupSizeControlFeaturesEXT subgroup_size_control_features; subgroup_size_control_features.pNext = nullptr; subgroup_size_control_features.sType = VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_SUBGROUP_SIZE_CONTROL_FEATURES_EXT; @@ -5101,7 +5090,7 @@ static void ggml_vk_print_gpu_info(size_t idx) { } } -static bool ggml_vk_instance_validation_ext_available(); +static bool ggml_vk_instance_layer_settings_available(); static bool ggml_vk_instance_portability_enumeration_ext_available(const std::vector& instance_extensions); static bool ggml_vk_instance_debug_utils_ext_available(const std::vector & instance_extensions); static bool ggml_vk_device_is_supported(const vk::PhysicalDevice & vkdev); @@ -5130,19 +5119,19 @@ static void ggml_vk_instance_init() { vk::ApplicationInfo app_info{ "ggml-vulkan", 1, nullptr, 0, api_version }; const std::vector instance_extensions = vk::enumerateInstanceExtensionProperties(); - const bool validation_ext = ggml_vk_instance_validation_ext_available(); + const bool layer_settings = ggml_vk_instance_layer_settings_available(); #ifdef __APPLE__ const bool portability_enumeration_ext = ggml_vk_instance_portability_enumeration_ext_available(instance_extensions); #endif const bool debug_utils_ext = ggml_vk_instance_debug_utils_ext_available(instance_extensions) && getenv("GGML_VK_DEBUG_MARKERS") != nullptr; std::vector layers; - if (validation_ext) { + if (layer_settings) { layers.push_back("VK_LAYER_KHRONOS_validation"); } std::vector extensions; - if (validation_ext) { - extensions.push_back("VK_EXT_validation_features"); + if (layer_settings) { + extensions.push_back("VK_EXT_layer_settings"); } #ifdef __APPLE__ if (portability_enumeration_ext) { @@ -5152,26 +5141,24 @@ static void ggml_vk_instance_init() { if (debug_utils_ext) { extensions.push_back("VK_EXT_debug_utils"); } - vk::InstanceCreateInfo instance_create_info(vk::InstanceCreateFlags{}, &app_info, layers, extensions); + VkBool32 enable_best_practice = layer_settings; + std::vector settings = { + { + "VK_LAYER_KHRONOS_validation", + "validate_best_practices", + vk::LayerSettingTypeEXT::eBool32, + 1, + &enable_best_practice + }, + }; + vk::LayerSettingsCreateInfoEXT layer_setting_info(settings); + vk::InstanceCreateInfo instance_create_info(vk::InstanceCreateFlags{}, &app_info, layers, extensions, &layer_setting_info); #ifdef __APPLE__ if (portability_enumeration_ext) { instance_create_info.flags |= vk::InstanceCreateFlagBits::eEnumeratePortabilityKHR; } #endif - std::vector features_enable; - vk::ValidationFeaturesEXT validation_features; - - if (validation_ext) { - features_enable = { vk::ValidationFeatureEnableEXT::eBestPractices }; - validation_features = { - features_enable, - {}, - }; - validation_features.setPNext(nullptr); - instance_create_info.setPNext(&validation_features); - GGML_LOG_DEBUG("ggml_vulkan: Validation layers enabled\n"); - } vk_instance.instance = vk::createInstance(instance_create_info); vk_instance_initialized = true; @@ -5186,6 +5173,11 @@ static void ggml_vk_instance_init() { } vk_perf_logger_enabled = getenv("GGML_VK_PERF_LOGGER") != nullptr; + const char* GGML_VK_PERF_LOGGER_FREQUENCY = getenv("GGML_VK_PERF_LOGGER_FREQUENCY"); + + if (GGML_VK_PERF_LOGGER_FREQUENCY != nullptr) { + vk_perf_logger_frequency = std::stoul(GGML_VK_PERF_LOGGER_FREQUENCY); + } // See https://github.com/KhronosGroup/Vulkan-Hpp?tab=readme-ov-file#extensions--per-device-function-pointers- VULKAN_HPP_DEFAULT_DISPATCHER.init(vk_instance.instance); @@ -5363,6 +5355,10 @@ static void ggml_vk_init(ggml_backend_vk_context * ctx, size_t idx) { ctx->compute_cmd_pool.init(ctx->device, &ctx->device->compute_queue); ctx->transfer_cmd_pool.init(ctx->device, &ctx->device->transfer_queue); + if (vk_perf_logger_enabled) { + ctx->perf_logger = std::unique_ptr(new vk_perf_logger()); + } + #ifdef GGML_VULKAN_CHECK_RESULTS const char* skip_checks = getenv("GGML_VULKAN_SKIP_CHECKS"); vk_skip_checks = (skip_checks == NULL ? 0 : atoi(skip_checks)); @@ -6919,6 +6915,10 @@ static bool ggml_vk_should_use_mmvq(const vk_device& device, uint32_t m, uint32_ // Quantization overhead is not worth it for small k switch (device->vendor_id) { case VK_VENDOR_ID_NVIDIA: + if (src0_type == GGML_TYPE_Q2_K) { + return true; + } + if (k <= 4096) { return false; } @@ -8251,59 +8251,23 @@ static void ggml_vk_flash_attn(ggml_backend_vk_context * ctx, vk_context& subctx } } -static std::array ggml_vk_get_conv_elements(const ggml_tensor *dst) { - const ggml_tensor *src0 = dst->src[0]; - const ggml_tensor *src1 = dst->src[1]; - - // src0 - kernel: [KW, KH, Cin, Cout] - // src1 - input: [W, H, Cin, N] - // dst - result: [OW, OH, Cout, N] - - // Copied from ggml.c: int64_t ggml_calc_conv_output_size(int64_t ins, int64_t ks, int s, int p, int d) - auto calc_conv_output_size = [](int64_t ins, int64_t ks, int s, int p, int d) -> int64_t { - return (ins + 2 * p - d * (ks - 1) - 1) / s + 1; +static vk_conv_shapes ggml_vk_conv_select_shape(ggml_backend_vk_context * ctx, uint32_t K, uint32_t NPQ) { + auto n_tiles = [&](vk_conv_shapes s) { + return CEIL_DIV(K, vk_conv_block_sizes[s].K) + * CEIL_DIV(NPQ, vk_conv_block_sizes[s].NPQ); }; - // parallelize in {OW/BS_K, OH/BS_NPQ, 1} - int64_t W = src1->ne[0]; - int64_t H = src1->ne[1]; - int64_t KW = src0->ne[0]; - int64_t KH = src0->ne[1]; - int64_t Cout = src0->ne[3]; - int64_t N = src1->ne[3]; - int64_t OH = calc_conv_output_size(H, KH, dst->op_params[1], dst->op_params[3], dst->op_params[5]); - int64_t OW = calc_conv_output_size(W, KW, dst->op_params[0], dst->op_params[2], dst->op_params[4]); - int64_t NPQ = N * OW * OH; - // Tile output matrix to (K/NB_K, NPQ/NB_NPQ, 1) workgroups - std::array elements = { static_cast(Cout), static_cast(NPQ), 1 }; - return elements; -} + // We can't query number of shader cores on Intel, use 32 as a placeholder + // so small convolutions will still choose a smaller tile. + const uint32_t shader_core_count = ctx->device->shader_core_count > 0 ? ctx->device->shader_core_count : 32; -static std::array ggml_vk_get_conv_transpose_2d_elements(const ggml_tensor *dst) { - const ggml_tensor *src0 = dst->src[0]; - const ggml_tensor *src1 = dst->src[1]; - - // src0 - kernel: [KW, KH, Cout, Cin] - // src1 - input: [W, H, Cin, N] - // dst - result: [OW, OH, Cout, N] - - auto calc_conv_output_size = [](int64_t ins, int64_t ks, int s, int p, int d) -> int64_t { - return (ins - 1) * s - 2 * p + (ks - 1) * d + 1; - }; - // parallelize in {OW/BS_K, OH/BS_NPQ, 1} - int64_t W = src1->ne[0]; - int64_t H = src1->ne[1]; - int64_t KW = src0->ne[0]; - int64_t KH = src0->ne[1]; - int64_t Cout = src0->ne[2]; - int64_t N = src1->ne[3]; - int64_t OH = calc_conv_output_size(H, KH, dst->op_params[0], 0, 1); - int64_t OW = calc_conv_output_size(W, KW, dst->op_params[0], 0, 1); - int64_t NPQ = N * OW * OH; - - // Tile output matrix to (K/NB_K, NPQ/NB_NPQ, 1) workgroups - std::array elements = { static_cast(Cout), static_cast(NPQ), 1 }; - return elements; + if (K > 64 && n_tiles(CONV_SHAPE_128x128) >= shader_core_count * 2) { + return CONV_SHAPE_128x128; + } else if (K <= 32 && n_tiles(CONV_SHAPE_32x256) >= shader_core_count * 2) { + return CONV_SHAPE_32x256; + } else { + return CONV_SHAPE_64x32; + } } static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, const ggml_tensor * dst, ggml_op op) { @@ -8766,39 +8730,20 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const return nullptr; case GGML_OP_CONV_2D: case GGML_OP_CONV_TRANSPOSE_2D: - if (src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32 && - ggml_is_contiguous(src0) && ggml_is_contiguous(src1) && ggml_is_contiguous(dst)) { - std::array elements{}; - if (op == GGML_OP_CONV_2D) elements = ggml_vk_get_conv_elements(dst); - else if (op == GGML_OP_CONV_TRANSPOSE_2D) elements = ggml_vk_get_conv_transpose_2d_elements(dst); - vk_conv_shapes shape; - - uint32_t tiles[CONV_SHAPE_COUNT]; - for (uint32_t i = 0; i < CONV_SHAPE_COUNT; ++i) { - tiles[i] = CEIL_DIV(elements[0], conv_shapes_wg_denoms[i][0]) * CEIL_DIV(elements[1], conv_shapes_wg_denoms[i][1]); - } - - // We can't query number of shader cores on Intel, use 32 as a placeholder - // so small convolutions will still choose a smaller tile. - const uint32_t shader_core_count = ctx->device->shader_core_count > 0 ? ctx->device->shader_core_count : 32; - - if (elements[0] > 64 && tiles[CONV_SHAPE_128x128] >= shader_core_count * 2) { - shape = CONV_SHAPE_128x128; - } else if (elements[0] <= 32 && tiles[CONV_SHAPE_32x256] >= shader_core_count * 2) { - shape = CONV_SHAPE_32x256; - } else { - shape = CONV_SHAPE_64x32; - } - - uint32_t KW = static_cast(src0->ne[0]); - uint32_t KH = static_cast(src0->ne[1]); - uint32_t s0 = static_cast(dst->op_params[0]); - uint32_t s1 = op == GGML_OP_CONV_2D ? static_cast(dst->op_params[1]) : static_cast(dst->op_params[0]); - uint32_t p0 = op == GGML_OP_CONV_2D ? static_cast(dst->op_params[2]) : 0; - uint32_t p1 = op == GGML_OP_CONV_2D ? static_cast(dst->op_params[3]) : 0; - uint32_t d0 = op == GGML_OP_CONV_2D ? static_cast(dst->op_params[4]) : 1; - uint32_t d1 = op == GGML_OP_CONV_2D ? static_cast(dst->op_params[5]) : 1; + if (src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) { + uint32_t K = dst->ne[2]; // Cout + uint32_t NPQ = dst->ne[3] * dst->ne[1] * dst->ne[0]; // N * OH * OW + vk_conv_shapes shape = ggml_vk_conv_select_shape(ctx, K, NPQ); + bool transpose = dst->op == GGML_OP_CONV_TRANSPOSE_2D; + uint32_t KW = (uint32_t)src0->ne[0]; + uint32_t KH = (uint32_t)src0->ne[1]; + uint32_t s0 = (uint32_t)(ggml_get_op_params_i32(dst, 0)); + uint32_t s1 = !transpose ? (uint32_t)ggml_get_op_params_i32(dst, 1) : s0; + uint32_t p0 = !transpose ? (uint32_t)ggml_get_op_params_i32(dst, 2) : 0; + uint32_t p1 = !transpose ? (uint32_t)ggml_get_op_params_i32(dst, 3) : 0; + uint32_t d0 = !transpose ? (uint32_t)ggml_get_op_params_i32(dst, 4) : 1; + uint32_t d1 = !transpose ? (uint32_t)ggml_get_op_params_i32(dst, 5) : 1; vk_conv2d_pipeline_state conv2d_pipeline_state(s0, s1, p0, p1, d0, d1, KW, KH); std::map *pipelines = nullptr; @@ -9117,13 +9062,21 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co elements = { N * OC * OH * OW, 1, 1}; } break; case GGML_OP_CONV_2D: - { - elements = ggml_vk_get_conv_elements(dst); - } break; case GGML_OP_CONV_TRANSPOSE_2D: - { - elements = ggml_vk_get_conv_transpose_2d_elements(dst); - } break; + if constexpr (std::is_same_v) { + const uint32_t NPQ = pc.N * pc.OH * pc.OW; + const vk_conv_shapes shape = ggml_vk_conv_select_shape(ctx, pc.Cout, NPQ); + const uint32_t NPQ_blocks = CEIL_DIV(NPQ, vk_conv_block_sizes[shape].NPQ); + + elements = { pc.Cout, NPQ_blocks, 1 }; + if (elements[1] > 512) { + elements[2] = CEIL_DIV(elements[1], 512); + elements[1] = 512; + } + } else { + GGML_ABORT("invalid push constant type for CONV_2D"); + } + break; case GGML_OP_ADD: case GGML_OP_SUB: case GGML_OP_DIV: @@ -10345,17 +10298,8 @@ static void ggml_vk_topk(ggml_backend_vk_context * ctx, vk_context& subctx, cons uint32_t nrows = ggml_nrows(src0); uint32_t k = dst->ne[0]; - vk_op_topk_push_constants pc { ncols, ncols, k, nrows, 0, 0 }; + vk_op_topk_push_constants pc { ncols, ncols, ncols, k, nrows, 0, 0 }; - // Reserve space for ivec2 per element, double buffered - const size_t dbl_buf_size = size_t{ncols} * nrows * 2 * sizeof(int); - const size_t x_sz = dbl_buf_size * 2; - uint32_t dbl_buf_index = 0; - - if (ctx->prealloc_size_x < x_sz) { - ctx->prealloc_size_x = x_sz; - ggml_vk_preallocate_buffers(ctx, subctx); - } if (ctx->prealloc_x_need_sync) { ggml_vk_sync_buffers(ctx, subctx); } @@ -10370,8 +10314,9 @@ static void ggml_vk_topk(ggml_backend_vk_context * ctx, vk_context& subctx, cons // largest elements. Repeat until we have the top K elements. // Need to do at least one iteration to write out the results. bool done_one_iter = false; + uint32_t dbl_buf_index = 0; + size_t dbl_buf_size; while (num_elements > k || !done_one_iter) { - done_one_iter = true; // Prefer going as small as num_topk_pipelines - 3 for perf reasons. // But if K is larger, then we need a larger workgroup @@ -10411,6 +10356,21 @@ static void ggml_vk_topk(ggml_backend_vk_context * ctx, vk_context& subctx, cons // Number of elements remaining after this pass uint32_t num_dst_elements = (num_elements / pipeline->wg_denoms[0]) * k + std::min(k, num_elements % pipeline->wg_denoms[0]); + pc2.ncols_output = num_dst_elements; + + if (!done_one_iter) { + // Reserve space for ivec2 per element, double buffered + // K per workgroup per row + dbl_buf_size = num_dst_elements * nrows * 2 * sizeof(int); + dbl_buf_size = ROUNDUP_POW2(dbl_buf_size, ctx->device->properties.limits.minStorageBufferOffsetAlignment); + const size_t x_sz = dbl_buf_size * 2; + + if (ctx->prealloc_size_x < x_sz) { + ctx->prealloc_size_x = x_sz; + ggml_vk_preallocate_buffers(ctx, subctx); + } + } + vk_subbuffer src_buf; vk_subbuffer dst_buf; @@ -10436,6 +10396,7 @@ static void ggml_vk_topk(ggml_backend_vk_context * ctx, vk_context& subctx, cons if (num_elements > k) { ggml_vk_sync_buffers(ctx, subctx); } + done_one_iter = true; } ctx->prealloc_x_need_sync = true; } @@ -10666,30 +10627,24 @@ static void ggml_vk_conv_2d(ggml_backend_vk_context * ctx, vk_context & subctx, GGML_ASSERT(dst->type == GGML_TYPE_F32); GGML_TENSOR_BINARY_OP_LOCALS - GGML_ASSERT(nb00 == sizeof(float) || nb00 == sizeof(ggml_fp16_t)); GGML_ASSERT(nb10 == sizeof(float)); GGML_ASSERT(nb0 == sizeof(float)); + bool transpose = dst->op == GGML_OP_CONV_TRANSPOSE_2D; + vk_op_conv2d_push_constants p{}; - p.Cout = static_cast(ne03); - p.Cin = static_cast(ne02); + p.Cout = static_cast(!transpose ? ne03 : ne02); + p.Cin = static_cast(!transpose ? ne02 : ne03); p.N = static_cast(ne13); + GGML_ASSERT(p.Cout == ne2); + GGML_ASSERT(p.Cin == ne12); - p.KW = static_cast(ne00); - p.KH = static_cast(ne01); p.W = static_cast(ne10); p.H = static_cast(ne11); p.OW = static_cast(ne0); p.OH = static_cast(ne1); - p.s0 = static_cast(dst->op_params[0]); - p.s1 = static_cast(dst->op_params[1]); - p.p0 = static_cast(dst->op_params[2]); - p.p1 = static_cast(dst->op_params[3]); - p.d0 = static_cast(dst->op_params[4]); - p.d1 = static_cast(dst->op_params[5]); - p.nb01 = static_cast(nb01 / nb00); p.nb02 = static_cast(nb02 / nb00); p.nb03 = static_cast(nb03 / nb00); @@ -10702,59 +10657,7 @@ static void ggml_vk_conv_2d(ggml_backend_vk_context * ctx, vk_context & subctx, p.nb2 = static_cast(nb2 / nb0); p.nb3 = static_cast(nb3 / nb0); - GGML_ASSERT(ne03 == ne2); - GGML_ASSERT(ne02 == ne12); - - ggml_vk_op_f32(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_CONV_2D, std::move(p)); -} - -static void ggml_vk_conv_transpose_2d(ggml_backend_vk_context * ctx, vk_context & subctx, const ggml_tensor * src0, - const ggml_tensor * src1, ggml_tensor * dst) { - GGML_ASSERT(src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16); - GGML_ASSERT(src1->type == GGML_TYPE_F32); - GGML_ASSERT(dst->type == GGML_TYPE_F32); - - GGML_TENSOR_BINARY_OP_LOCALS - - GGML_ASSERT(nb00 == sizeof(float) || nb00 == sizeof(ggml_fp16_t)); - GGML_ASSERT(nb10 == sizeof(float)); - GGML_ASSERT(nb0 == sizeof(float)); - - vk_op_conv_transpose_2d_push_constants p{}; - p.Cout = static_cast(ne02); - p.Cin = static_cast(ne03); - p.N = static_cast(ne13); - - p.KW = static_cast(ne00); - p.KH = static_cast(ne01); - p.W = static_cast(ne10); - p.H = static_cast(ne11); - p.OW = static_cast(ne0); - p.OH = static_cast(ne1); - - p.s0 = static_cast(dst->op_params[0]); - p.s1 = static_cast(dst->op_params[0]); - p.p0 = 0; - p.p1 = 0; - p.d0 = 1; - p.d1 = 1; - - p.nb01 = static_cast(nb01 / nb00); - p.nb02 = static_cast(nb02 / nb00); - p.nb03 = static_cast(nb03 / nb00); - - p.nb11 = static_cast(nb11 / nb10); - p.nb12 = static_cast(nb12 / nb10); - p.nb13 = static_cast(nb13 / nb10); - - p.nb1 = static_cast(nb1 / nb0); - p.nb2 = static_cast(nb2 / nb0); - p.nb3 = static_cast(nb3 / nb0); - - GGML_ASSERT(ne02 == ne2); - GGML_ASSERT(ne03 == ne12); - - ggml_vk_op_f32(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_CONV_TRANSPOSE_2D, std::move(p)); + ggml_vk_op_f32(ctx, subctx, src0, src1, nullptr, nullptr, dst, dst->op, std::move(p)); } static void ggml_vk_conv_2d_dw(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { @@ -12125,11 +12028,8 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_cgraph * cgr break; case GGML_OP_CONV_2D: - ggml_vk_conv_2d(ctx, compute_ctx, src0, src1, node); - - break; case GGML_OP_CONV_TRANSPOSE_2D: - ggml_vk_conv_transpose_2d(ctx, compute_ctx, src0, src1, node); + ggml_vk_conv_2d(ctx, compute_ctx, src0, src1, node); break; case GGML_OP_CONV_2D_DW: @@ -12334,6 +12234,9 @@ static void ggml_vk_cleanup(ggml_backend_vk_context * ctx) { ctx->compute_cmd_pool.destroy(ctx->device->device); ctx->transfer_cmd_pool.destroy(ctx->device->device); + if (vk_perf_logger_enabled) { + ctx->perf_logger->print_timings(true); + } } static int ggml_vk_get_device_count() { @@ -13132,24 +13035,29 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg vk_context compute_ctx; if (vk_perf_logger_enabled) { // allocate/resize the query pool - if (ctx->device->num_queries < cgraph->n_nodes + 1) { - if (ctx->device->query_pool) { - ctx->device->device.destroyQueryPool(ctx->device->query_pool); + if (ctx->num_queries < cgraph->n_nodes + 1) { + if (ctx->query_pool) { + ctx->device->device.destroyQueryPool(ctx->query_pool); } vk::QueryPoolCreateInfo query_create_info; query_create_info.queryType = vk::QueryType::eTimestamp; query_create_info.queryCount = cgraph->n_nodes + 100; - ctx->device->query_pool = ctx->device->device.createQueryPool(query_create_info); - ctx->device->num_queries = query_create_info.queryCount; + ctx->query_pool = ctx->device->device.createQueryPool(query_create_info); + ctx->num_queries = query_create_info.queryCount; + ctx->query_fusion_names.resize(ctx->num_queries); + ctx->query_nodes.resize(ctx->num_queries); } - ctx->device->device.resetQueryPool(ctx->device->query_pool, 0, cgraph->n_nodes+1); + ctx->device->device.resetQueryPool(ctx->query_pool, 0, cgraph->n_nodes+1); + std::fill(ctx->query_fusion_names.begin(), ctx->query_fusion_names.end(), nullptr); + std::fill(ctx->query_nodes.begin(), ctx->query_nodes.end(), nullptr); GGML_ASSERT(ctx->compute_ctx.expired()); compute_ctx = ggml_vk_create_context(ctx, ctx->compute_cmd_pool); ctx->compute_ctx = compute_ctx; ggml_vk_ctx_begin(ctx->device, compute_ctx); - compute_ctx->s->buffer.writeTimestamp(vk::PipelineStageFlagBits::eAllCommands, ctx->device->query_pool, 0); + ctx->query_idx = 0; + compute_ctx->s->buffer.writeTimestamp(vk::PipelineStageFlagBits::eAllCommands, ctx->query_pool, ctx->query_idx++); } ctx->prealloc_y_last_pipeline_used = nullptr; @@ -13190,52 +13098,66 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg total_mul_mat_bytes += bytes; } + const char *fusion_string {}; if (!ctx->device->disable_fusion) { uint32_t num_adds = ggml_vk_fuse_multi_add(ctx, cgraph, i); if (num_adds) { ctx->num_additional_fused_ops = num_adds - 1; + fusion_string = "MULTI_ADD"; } else if (ggml_vk_can_fuse(ctx, cgraph, i, { GGML_OP_MUL_MAT, GGML_OP_ADD, GGML_OP_ADD })) { ctx->num_additional_fused_ops = 2; + fusion_string = "MUL_MAT_ADD_ADD"; } else if (ggml_vk_can_fuse(ctx, cgraph, i, { GGML_OP_MUL_MAT, GGML_OP_ADD })) { ctx->num_additional_fused_ops = 1; + fusion_string = "MUL_MAT_ADD"; } else if (ggml_vk_can_fuse(ctx, cgraph, i, { GGML_OP_MUL_MAT_ID, GGML_OP_ADD_ID, GGML_OP_MUL })) { ctx->num_additional_fused_ops = 2; + fusion_string = "MUL_MAT_ID_ADD_ID_MUL"; } else if (ggml_vk_can_fuse(ctx, cgraph, i, { GGML_OP_MUL_MAT_ID, GGML_OP_ADD_ID })) { ctx->num_additional_fused_ops = 1; + fusion_string = "MUL_MAT_ID_ADD_ID"; } else if (ggml_vk_can_fuse(ctx, cgraph, i, { GGML_OP_MUL_MAT_ID, GGML_OP_MUL })) { ctx->num_additional_fused_ops = 1; + fusion_string = "MUL_MAT_ID_MUL"; } else if (ggml_can_fuse_subgraph(cgraph, i, { GGML_OP_RMS_NORM, GGML_OP_MUL, GGML_OP_ROPE, GGML_OP_VIEW, GGML_OP_SET_ROWS }, { i + 4 }) && ggml_check_edges(cgraph, i, rms_norm_mul_rope_view_set_rows_edges) && ggml_vk_can_fuse_rms_norm_mul_rope(ctx, cgraph, i) && ggml_vk_can_fuse_rope_set_rows(ctx, cgraph, i + 2)) { ctx->num_additional_fused_ops = 4; + fusion_string = "RMS_NORM_MUL_ROPE_VIEW_SET_ROWS"; } else if (ggml_vk_can_fuse(ctx, cgraph, i, { GGML_OP_RMS_NORM, GGML_OP_MUL, GGML_OP_ROPE })&& ggml_vk_can_fuse_rms_norm_mul_rope(ctx, cgraph, i)) { ctx->num_additional_fused_ops = 2; + fusion_string = "RMS_NORM_MUL_ROPE"; } else if (ggml_vk_can_fuse(ctx, cgraph, i, { GGML_OP_RMS_NORM, GGML_OP_MUL })) { ctx->num_additional_fused_ops = 1; + fusion_string = "RMS_NORM_MUL"; } else if (ggml_can_fuse_subgraph(cgraph, i, { GGML_OP_ROPE, GGML_OP_VIEW, GGML_OP_SET_ROWS }, { i + 2 }) && ggml_check_edges(cgraph, i, rope_view_set_rows_edges) && ggml_vk_can_fuse_rope_set_rows(ctx, cgraph, i)) { ctx->num_additional_fused_ops = 2; + fusion_string = "ROPE_VIEW_SET_ROWS"; } else if (ggml_can_fuse_subgraph(cgraph, i, topk_moe_early_softmax_norm, { i + 3, i + 9 }) && ggml_check_edges(cgraph, i, topk_moe_early_softmax_norm_edges) && ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, TOPK_MOE_EARLY_SOFTMAX_NORM)) { ctx->num_additional_fused_ops = topk_moe_early_softmax_norm.size() - 1; // view of argsort writes to memory ctx->fused_ops_write_mask |= 1 << 3; + fusion_string = "TOPK_MOE_EARLY_SOFTMAX_NORM"; } else if (ggml_can_fuse_subgraph(cgraph, i, topk_moe_early_softmax, { i + 3, i + 4 }) && ggml_check_edges(cgraph, i, topk_moe_early_softmax_edges) && ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, TOPK_MOE_EARLY_SOFTMAX)) { ctx->num_additional_fused_ops = topk_moe_early_softmax.size() - 1; // view of argsort writes to memory ctx->fused_ops_write_mask |= 1 << 3; + fusion_string = "TOPK_MOE_EARLY_SOFTMAX"; } else if (ggml_can_fuse_subgraph(cgraph, i, topk_moe_late_softmax, { i + 1, i + 5 }) && ggml_check_edges(cgraph, i, topk_moe_late_softmax_edges) && ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, TOPK_MOE_LATE_SOFTMAX)) { ctx->num_additional_fused_ops = topk_moe_late_softmax.size() - 1; // view of argsort writes to memory ctx->fused_ops_write_mask |= 1 << 1; + fusion_string = "TOPK_MOE_LATE_SOFTMAX"; } } ctx->fused_ops_write_mask |= 1 << ctx->num_additional_fused_ops; @@ -13249,7 +13171,7 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg bool enqueued = ggml_vk_build_graph(ctx, cgraph, i, cgraph->nodes[submit_node_idx], submit_node_idx, i + ctx->num_additional_fused_ops >= last_node, almost_ready, submit); - if (vk_perf_logger_enabled) { + if (vk_perf_logger_enabled && enqueued) { if (ctx->compute_ctx.expired()) { compute_ctx = ggml_vk_create_context(ctx, ctx->compute_cmd_pool); ctx->compute_ctx = compute_ctx; @@ -13257,10 +13179,9 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg } else { compute_ctx = ctx->compute_ctx.lock(); } - // If there are fused ops, just write out timestamps for all nodes to keep the accounting simple - for (int j = 0; j < ctx->num_additional_fused_ops + 1; ++j) { - compute_ctx->s->buffer.writeTimestamp(vk::PipelineStageFlagBits::eAllCommands, ctx->device->query_pool, i+j+1); - } + ctx->query_nodes[ctx->query_idx] = cgraph->nodes[i]; + ctx->query_fusion_names[ctx->query_idx] = fusion_string; + compute_ctx->s->buffer.writeTimestamp(vk::PipelineStageFlagBits::eAllCommands, ctx->query_pool, ctx->query_idx++); } if (enqueued) { @@ -13301,14 +13222,14 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg // Get the results and pass them to the logger std::vector timestamps(cgraph->n_nodes + 1); - VK_CHECK(ctx->device->device.getQueryPoolResults(ctx->device->query_pool, 0, cgraph->n_nodes + 1, (cgraph->n_nodes + 1)*sizeof(uint64_t), timestamps.data(), sizeof(uint64_t), vk::QueryResultFlagBits::e64 | vk::QueryResultFlagBits::eWait), "get timestamp results"); - for (int i = 0; i < cgraph->n_nodes; i++) { - if (!ggml_vk_is_empty(cgraph->nodes[i])) { - ctx->device->perf_logger->log_timing(cgraph->nodes[i], uint64_t((timestamps[i+1] - timestamps[i]) * ctx->device->properties.limits.timestampPeriod)); - } + VK_CHECK(ctx->device->device.getQueryPoolResults(ctx->query_pool, 0, ctx->query_idx, (cgraph->n_nodes + 1)*sizeof(uint64_t), timestamps.data(), sizeof(uint64_t), vk::QueryResultFlagBits::e64 | vk::QueryResultFlagBits::eWait), "get timestamp results"); + for (int i = 1; i < ctx->query_idx; i++) { + auto node = ctx->query_nodes[i]; + auto name = ctx->query_fusion_names[i]; + ctx->perf_logger->log_timing(node, name, uint64_t((timestamps[i] - timestamps[i-1]) * ctx->device->properties.limits.timestampPeriod)); } - ctx->device->perf_logger->print_timings(); + ctx->perf_logger->print_timings(); } if (!ctx->device->support_async) { @@ -14162,10 +14083,12 @@ static bool ggml_backend_vk_device_supports_op(ggml_backend_dev_t dev, const ggm const uint32_t N = op->src[0]->ne[0]; const uint32_t K = op->src[1]->ne[0]; // K dimension limited to workgroup size - if (K > 128) { + if (K > 1u << device->max_workgroup_size_log2) { return false; } - if (N * N * sizeof(float) + N * K * sizeof(float) > device->properties.limits.maxComputeSharedMemorySize) { + const uint32_t batch_N = device->properties.limits.maxComputeSharedMemorySize / ((N + K) * sizeof(float)); + + if (batch_N == 0) { return false; } return true; @@ -14238,13 +14161,6 @@ static bool ggml_backend_vk_device_supports_op(ggml_backend_dev_t dev, const ggm case GGML_OP_CONV_2D: case GGML_OP_CONV_TRANSPOSE_2D: { - // Op is disabled for Apple because it segfaults at pipeline create time on MoltenVK - ggml_backend_vk_device_context * ctx = (ggml_backend_vk_device_context *)dev->context; - const vk_device& device = ggml_vk_get_device(ctx->device); - if (op->op == GGML_OP_CONV_TRANSPOSE_2D && - device->properties.limits.maxPushConstantsSize < sizeof(vk_op_conv_transpose_2d_push_constants)) { - return false; - } // Channel-contiguous format is not supported yet. return ((op->src[0]->type == GGML_TYPE_F32 || op->src[0]->type == GGML_TYPE_F16) && op->src[1]->type == GGML_TYPE_F32 && @@ -14369,21 +14285,21 @@ ggml_backend_reg_t ggml_backend_vk_reg() { } // Extension availability -static bool ggml_vk_instance_validation_ext_available() { +static bool ggml_vk_instance_layer_settings_available() { #ifdef GGML_VULKAN_VALIDATE // Check if validation layer provides the extension const std::string layer_name = "VK_LAYER_KHRONOS_validation"; for (const auto& layer : vk::enumerateInstanceLayerProperties()) { if (layer_name == layer.layerName.data()) { for (const auto& ext : vk::enumerateInstanceExtensionProperties(layer_name)) { - if (strcmp("VK_EXT_validation_features", ext.extensionName.data()) == 0) { + if (strcmp("VK_EXT_layer_settings", ext.extensionName.data()) == 0) { return true; } } } } - std::cerr << "ggml_vulkan: WARNING: Validation layer or layer extension VK_EXT_validation_features not found." << std::endl; + std::cerr << "ggml_vulkan: WARNING: Validation layer or layer extension VK_EXT_layer_settings not found." << std::endl; #endif return false; } diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/conv2d_mm.comp b/ggml/src/ggml-vulkan/vulkan-shaders/conv2d_mm.comp index e9bdbf7db5..875c012cd3 100644 --- a/ggml/src/ggml-vulkan/vulkan-shaders/conv2d_mm.comp +++ b/ggml/src/ggml-vulkan/vulkan-shaders/conv2d_mm.comp @@ -32,22 +32,12 @@ layout(push_constant) uniform parameter { uint32_t Cin; uint32_t N; - // Tensor spatial sizes: kernel, input, output - uint32_t KW; - uint32_t KH; + // Tensor spatial sizes: input, output uint32_t W; uint32_t H; uint32_t OW; uint32_t OH; - // Parameters: stride, padding, dilation - 0=y, 1=x - uint32_t s0; - uint32_t s1; - uint32_t p0; - uint32_t p1; - uint32_t d0; - uint32_t d1; - // Strides in elements uint32_t nb01; uint32_t nb02; @@ -77,13 +67,14 @@ layout(constant_id = 3) const uint BS_NPQ = 128; layout(constant_id = 4) const uint TS_K = 8; layout(constant_id = 5) const uint use_collectives = 1; layout(constant_id = 6) const uint SHMEM_PAD = 4; - +// Stride, padding, dilation layout(constant_id = 7) const uint s0 = 1; layout(constant_id = 8) const uint s1 = 1; layout(constant_id = 9) const uint p0 = 0; layout(constant_id = 10) const uint p1 = 0; layout(constant_id = 11) const uint d0 = 1; layout(constant_id = 12) const uint d1 = 1; +// Kernel spatial sizes layout(constant_id = 13) const uint KW = 1; layout(constant_id = 14) const uint KH = 1; @@ -138,7 +129,7 @@ P,Q=OH,OW */ uint32_t B_idx_K = gl_WorkGroupID.x; -uint32_t B_idx_NPQ = gl_WorkGroupID.y; +uint32_t B_idx_NPQ = gl_WorkGroupID.y + gl_WorkGroupID.z * 512; uint32_t T_y = tid / NT_NPQ; uint32_t T_x = tid % NT_NPQ; @@ -178,6 +169,10 @@ ACC_TYPE perElemOpStore(const in uint32_t r, const in uint32_t c, const in ACC_T #endif void main() { + if (B_idx_NPQ * BS_NPQ >= NPQ) { + return; + } + #ifdef COOPMAT2 coopmat matC; matC = coopmat(0.0); diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_iq1_m.comp b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_iq1_m.comp index 4cb292380c..e5cc7ff862 100644 --- a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_iq1_m.comp +++ b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_iq1_m.comp @@ -7,35 +7,85 @@ layout(local_size_x_id = 0, local_size_y = 1, local_size_z = 1) in; FLOAT_TYPE temp[NUM_COLS][NUM_ROWS]; -void calc_superblock(const uint a_offset, const uint b_offset, const uint ib32, const uint i, const uint num_blocks_per_row, const uint first_row, const uint num_rows) { +void calc_superblock(const uint a_offset, const uint b_offset, const uint ib32, const uint i, + const uint num_blocks_per_row, const uint first_row, const uint num_rows) { + // Compute starting index in matrix B for this superblock const uint y_idx = i * QUANT_K + 32 * ib32; - uint ibi = a_offset / QUANT_K + first_row * num_blocks_per_row + i; + + // Precompute indices for quantization lookup tables + const uint qh_base = 2 * ib32; + const uint qs_base = 4 * ib32; + const uint sc_index = ib32 / 2; + const uint sc_shift = 6 * (ib32 & 1); + + // Loop over rows in the superblock [[unroll]] for (uint n = 0; n < num_rows; ++n) { + // Load per-block scales and shift for quantization const uint16_t[4] scales = data_a[ibi].scales; const u16vec4 s = u16vec4(scales[0], scales[1], scales[2], scales[3]) >> 12; const float d = float(unpackHalf2x16(s.x | (s.y << 4) | (s.z << 8) | (s.w << 12)).x); + const uint sc = data_a[ibi].scales[sc_index] >> sc_shift; - const uint sc = data_a[ibi].scales[ib32 / 2] >> (6 * (ib32 & 1)); + // Temporary caches for decoding + FLOAT_TYPE dl_cache[4]; + uint16_t gvf_cache[4]; + float delta_cache[4]; + + // Precompute the multiplier and lookup values for 4 sub-blocks [[unroll]] for (uint l = 0; l < 4; ++l) { - const uint qh = data_a[ibi].qh[2 * ib32 + l / 2] >> (4 * (l&1)); - const uint qs = data_a[ibi].qs[4 * ib32 + l]; - const float delta = ((qh & 8) != 0) ? -IQ1M_DELTA : IQ1M_DELTA; - const float dl = d * (2 * bitfieldExtract(sc, 3 * int(l / 2), 3) + 1); + dl_cache[l] = FLOAT_TYPE(d * (2 * bitfieldExtract(sc, 3 * int(l / 2), 3) + 1)); + const uint qh = data_a[ibi].qh[qh_base + l / 2] >> (4 * (l & 1)); + const uint qs = data_a[ibi].qs[qs_base + l]; + gvf_cache[l] = iq1s_grid[qs | ((qh & 7) << 8)]; + delta_cache[l] = ((qh & 8) != 0) ? -IQ1M_DELTA : IQ1M_DELTA; + } - const int16_t grid = int16_t(iq1s_grid[qs | ((qh & 7) << 8)]); + // Loop over columns of the output + [[unroll]] for (uint j = 0; j < NUM_COLS; ++j) { + // Compute base index for matrix B + const uint base_b_idx = (j * p.batch_stride_b + b_offset + y_idx) / 4; + vec4 b_vals[8]; - [[unroll]] for (uint j = 0; j < NUM_COLS; ++j) { - vec4 b0 = vec4(data_b_v4[(j*p.batch_stride_b + b_offset + y_idx) / 4 + 2*l + 0]); - vec4 b4 = vec4(data_b_v4[(j*p.batch_stride_b + b_offset + y_idx) / 4 + 2*l + 1]); - - FLOAT_TYPE sum = FLOAT_TYPE(0.0); - [[unroll]] for (int k = 0; k < 4; ++k) { - sum = fma(FLOAT_TYPE(b0[k]), bitfieldExtract(grid, 2 * k, 2) + delta, - fma(FLOAT_TYPE(b4[k]), bitfieldExtract(grid, 8 + 2 * k, 2) + delta, sum)); - } - temp[j][n] = fma(dl, sum, temp[j][n]); + // Load 8 vec4 values from matrix B + [[unroll]] for (int idx = 0; idx < 8; ++idx) { + b_vals[idx] = vec4(data_b_v4[base_b_idx + idx]); } + + FLOAT_TYPE col_sum = FLOAT_TYPE(0.0); + + // Loop over sub-blocks + [[unroll]] for (uint l = 0; l < 4; ++l) { + const uint16_t grid = gvf_cache[l]; + const float dl = dl_cache[l]; + + // Decode 8 2-bit fbits from gvf_cache + float f0 = float(bitfieldExtract(grid, 0, 2)); + float f1 = float(bitfieldExtract(grid, 2, 2)); + float f2 = float(bitfieldExtract(grid, 4, 2)); + float f3 = float(bitfieldExtract(grid, 6, 2)); + float f4 = float(bitfieldExtract(grid, 8, 2)); + float f5 = float(bitfieldExtract(grid, 10, 2)); + float f6 = float(bitfieldExtract(grid, 12, 2)); + float f7 = float(bitfieldExtract(grid, 14, 2)); + + // Pack into vec4 for vectorized FMA + const vec4 fbits_v0 = vec4(f0, f1, f2, f3); + const vec4 fbits_v1 = vec4(f4, f5, f6, f7); + const vec4 delta_v = vec4(delta_cache[l]); + + // Vectorized fused multiply-add + vec4 sum_v = fma(b_vals[2*l + 0], fbits_v0 + delta_v, vec4(0.0)); + sum_v = fma(b_vals[2*l + 1], fbits_v1 + delta_v, sum_v); + + // Horizontal add to get scalar sum + FLOAT_TYPE sum = sum_v.x + sum_v.y + sum_v.z + sum_v.w; + + // Accumulate to column sum + col_sum = fma(dl, sum, col_sum); + } + // Write result to temporary buffer + temp[j][n] += col_sum; } ibi += num_blocks_per_row; } diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/pad.comp b/ggml/src/ggml-vulkan/vulkan-shaders/pad.comp index f3c8176872..5abd2f6fc6 100644 --- a/ggml/src/ggml-vulkan/vulkan-shaders/pad.comp +++ b/ggml/src/ggml-vulkan/vulkan-shaders/pad.comp @@ -8,6 +8,7 @@ layout (push_constant) uniform parameter uint ne00; uint ne01; uint ne02; uint ne03; uint nb00; uint nb01; uint nb02; uint nb03; uint ne10; uint ne11; uint ne12; uint ne13; uint nb10; uint nb11; uint nb12; uint nb13; uint misalign_offsets; + uint circular; uint lp0; uint rp0; uint lp1; uint rp1; @@ -18,6 +19,10 @@ layout (push_constant) uniform parameter uint get_aoffset() { return p.misalign_offsets >> 16; } uint get_doffset() { return p.misalign_offsets & 0xFFFF; } +uint wrap_around(int coord, uint size) { + return (uint(coord + int(size))) % size; // add size to avoid issues with negative +} + layout (binding = 0) readonly buffer A {A_TYPE data_a[];}; layout (binding = 1) writeonly buffer D {D_TYPE data_d[];}; @@ -40,10 +45,20 @@ void main() { const uint src0_idx = (i3 - p.lp3)*p.nb03 + (i2 - p.lp2)*p.nb02 + (i1 - p.lp1)*p.nb01 + (i0 - p.lp0)*p.nb00; const uint dst_idx = i3*p.nb13 + i2*p.nb12 + i1*p.nb11 + i0*p.nb10; - const bool is_src0 = i0 >= p.lp0 && i0 < p.ne10 - p.rp0 && - i1 >= p.lp1 && i1 < p.ne11 - p.rp1 && - i2 >= p.lp2 && i2 < p.ne12 - p.rp2 && - i3 >= p.lp3 && i3 < p.ne13 - p.rp3; + if (p.circular != 0u) { + const uint ci0 = wrap_around(int(i0) - int(p.lp0), p.ne00); + const uint ci1 = wrap_around(int(i1) - int(p.lp1), p.ne01); + const uint ci2 = wrap_around(int(i2) - int(p.lp2), p.ne02); + const uint ci3 = wrap_around(int(i3) - int(p.lp3), p.ne03); + const uint circular_src_idx = ci3*p.nb03 + ci2*p.nb02 + ci1*p.nb01 + ci0*p.nb00; + data_d[get_doffset() + dst_idx] = D_TYPE(data_a[get_aoffset() + circular_src_idx]); + } else { + const bool is_src0 = i0 >= p.lp0 && i0 < p.ne10 - p.rp0 && + i1 >= p.lp1 && i1 < p.ne11 - p.rp1 && + i2 >= p.lp2 && i2 < p.ne12 - p.rp2 && + i3 >= p.lp3 && i3 < p.ne13 - p.rp3; + data_d[get_doffset() + dst_idx] = D_TYPE(is_src0 ? data_a[get_aoffset() + src0_idx] : 0.0f); + } + - data_d[get_doffset() + dst_idx] = D_TYPE(is_src0 ? data_a[get_aoffset() + src0_idx] : 0.0f); } diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/rms_norm.comp b/ggml/src/ggml-vulkan/vulkan-shaders/rms_norm.comp index 3a47949d5a..9d6d366542 100644 --- a/ggml/src/ggml-vulkan/vulkan-shaders/rms_norm.comp +++ b/ggml/src/ggml-vulkan/vulkan-shaders/rms_norm.comp @@ -131,8 +131,12 @@ void main() { rms_norm(num_blocks); } else if (num_blocks > 16) { rms_norm(32); - } else if (num_blocks > 8) { + } else if (num_blocks > 12) { rms_norm(16); + } else if (num_blocks > 10) { + rms_norm(12); + } else if (num_blocks > 8) { + rms_norm(10); } else if (num_blocks > 4) { rms_norm(8); } else if (num_blocks == 4) { diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/solve_tri.comp b/ggml/src/ggml-vulkan/vulkan-shaders/solve_tri.comp index 253a9e7efe..3b65145032 100644 --- a/ggml/src/ggml-vulkan/vulkan-shaders/solve_tri.comp +++ b/ggml/src/ggml-vulkan/vulkan-shaders/solve_tri.comp @@ -5,8 +5,9 @@ layout (constant_id = 1) const uint N = 64; layout (constant_id = 2) const uint K = 32; +layout (constant_id = 3) const uint BATCH_N = 32; -layout(local_size_x = 128, local_size_y = 1, local_size_z = 1) in; +layout(local_size_x_id = 4, local_size_y = 1, local_size_z = 1) in; uint a_base, b_base, x_base; @@ -22,8 +23,8 @@ void store_x(uint r, uint c, FLOAT_TYPE v) { data_d[x_base + r * p.nb21 + c * p.nb20] = D_TYPE(v); } -shared FLOAT_TYPE shA[N * N]; -shared FLOAT_TYPE shB[N * K]; +shared FLOAT_TYPE shA[BATCH_N * N]; +shared FLOAT_TYPE shB[BATCH_N * K]; void main() { const uint batch = gl_WorkGroupID.z * 262144 + gl_WorkGroupID.y * 512 + gl_WorkGroupID.x; @@ -39,34 +40,42 @@ void main() { b_base = get_boffset() + i2 * p.nb12 + i3 * p.nb13; x_base = get_doffset() + i2 * p.nb22 + i3 * p.nb23; - // Load the A matrix into shA - [[unroll]] for (uint i = 0; i < N * N; i += gl_WorkGroupSize.x) { - uint idx = i + tid; - if (((N * N) % gl_WorkGroupSize.x == 0) || idx < N * N) { - shA[idx] = get_a(idx / N, idx % N); - } - } - // Load the B matrix into shB - [[unroll]] for (uint i = 0; i < N * K; i += gl_WorkGroupSize.x) { - uint idx = i + tid; - if (((N * K) % gl_WorkGroupSize.x == 0) || idx < N * K) { - shB[idx] = get_b(idx / K, idx % K); - } - } - barrier(); - FLOAT_TYPE X[N]; - // Each thread solves one column - if (tid < K) { - [[unroll]] for (int r = 0; r < N; ++r) { - FLOAT_TYPE b = shB[r * K + tid]; - // Compute x[r,c] = (b[r,c] - sum(a[r,c]*x[c])) / a[r,r] - [[unroll]] for (int c = 0; c < r; ++c) { - b -= shA[r * N + c] * X[c]; + + // Loop over batches of rows + [[unroll]] for (uint row_base = 0; row_base < N; row_base += BATCH_N) { + const uint cur_N = min(BATCH_N, N - row_base); + + // Load the A matrix batch into shA + [[unroll]] for (uint i = 0; i < cur_N * N; i += gl_WorkGroupSize.x) { + uint idx = i + tid; + if (((cur_N * N) % gl_WorkGroupSize.x == 0) || idx < cur_N * N) { + shA[idx] = get_a(row_base + idx / N, idx % N); } - FLOAT_TYPE x = b / shA[r * N + r]; - X[r] = x; - store_x(r, tid, x); } + // Load the B matrix batch into shB + [[unroll]] for (uint i = 0; i < cur_N * K; i += gl_WorkGroupSize.x) { + uint idx = i + tid; + if (((cur_N * K) % gl_WorkGroupSize.x == 0) || idx < cur_N * K) { + shB[idx] = get_b(row_base + idx / K, idx % K); + } + } + barrier(); + + // Each thread solves one column + if (tid < K) { + [[unroll]] for (uint row_offset = 0; row_offset < cur_N; ++row_offset) { + uint r = row_base + row_offset; + FLOAT_TYPE b = shB[row_offset * K + tid]; + // Compute x[r,c] = (b[r,c] - sum(a[r,c]*x[c])) / a[r,r] + [[unroll]] for (int c = 0; c < r; ++c) { + b -= shA[row_offset * N + c] * X[c]; + } + FLOAT_TYPE x = b / shA[row_offset * N + r]; + X[r] = x; + store_x(r, tid, x); + } + } + barrier(); } } diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/topk_argsort.comp b/ggml/src/ggml-vulkan/vulkan-shaders/topk_argsort.comp index cd858b7d32..49d4ab8e7c 100644 --- a/ggml/src/ggml-vulkan/vulkan-shaders/topk_argsort.comp +++ b/ggml/src/ggml-vulkan/vulkan-shaders/topk_argsort.comp @@ -19,6 +19,7 @@ layout (push_constant) uniform parameter { uint orig_ncols; uint ncols_input; uint ncols_output; + uint k; uint nrows; uint first_pass; uint last_pass; @@ -36,7 +37,7 @@ void topk(bool needs_bounds_check, const uint row) { const uint row_offset = row * p.ncols_input; dst_row[col] = ivec2(gl_GlobalInvocationID.x, floatBitsToInt(data_a[row_offset + gl_GlobalInvocationID.x])); } else { - const uint row_offset = row * p.orig_ncols; + const uint row_offset = row * p.ncols_input; dst_row[col] = data_s[row_offset + gl_GlobalInvocationID.x]; } } else { @@ -44,7 +45,7 @@ void topk(bool needs_bounds_check, const uint row) { } barrier(); - if (p.ncols_output == 1) { + if (p.k == 1) { // Fast path for single output - just do a max reduction [[unroll]] for (int s = BLOCK_SIZE / 2; s >= 1; s /= 2) { if (col < s) { @@ -84,13 +85,17 @@ void topk(bool needs_bounds_check, const uint row) { } } - if (col < p.ncols_output && gl_GlobalInvocationID.x < p.orig_ncols) { + if (col < p.k) { if (p.last_pass != 0) { - const uint row_offset = row * p.ncols_output; - data_d[row_offset + col] = dst_row[col].x; + if (gl_GlobalInvocationID.x < p.ncols_input) { + const uint row_offset = row * p.k; + data_d[row_offset + col] = dst_row[col].x; + } } else { - const uint row_offset = row * p.orig_ncols + gl_WorkGroupID.x * p.ncols_output; - data_t[row_offset + col] = dst_row[col]; + if (gl_WorkGroupID.x * p.k + col < p.ncols_output) { + const uint row_offset = row * p.ncols_output + gl_WorkGroupID.x * p.k; + data_t[row_offset + col] = dst_row[col]; + } } } } diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/topk_moe.comp b/ggml/src/ggml-vulkan/vulkan-shaders/topk_moe.comp index bc1c278bf4..5cd0785d20 100644 --- a/ggml/src/ggml-vulkan/vulkan-shaders/topk_moe.comp +++ b/ggml/src/ggml-vulkan/vulkan-shaders/topk_moe.comp @@ -75,7 +75,7 @@ void softmax_warp_inplace(inout float vals[experts_per_thread], const uint limit } void main() { - const uint row = gl_WorkGroupID.x * gl_WorkGroupSize.y + gl_LocalInvocationID.y; + const uint row = gl_WorkGroupID.x * gl_WorkGroupSize.y + gl_SubgroupID; if (row >= n_rows) { return; } @@ -83,17 +83,18 @@ void main() { const uint logits_offset = n_experts * row; const uint weights_offset = n_expert_used * row; const uint ids_offset = n_experts * row; + const uint lane = gl_SubgroupInvocationID; float wt[experts_per_thread]; [[unroll]] for (uint i = 0; i < n_experts; i += WARP_SIZE) { - const uint expert = i + gl_LocalInvocationID.x; + const uint expert = i + lane; wt[i / WARP_SIZE] = (n_experts % WARP_SIZE == 0 || expert < n_experts) ? logits[logits_offset + expert] : -INFINITY; } if (!late_softmax) { - softmax_warp_inplace(wt, n_experts, gl_LocalInvocationID.x, false); + softmax_warp_inplace(wt, n_experts, lane, false); } // at this point, each thread holds a portion of softmax, @@ -111,11 +112,11 @@ void main() { for (int k = 0; k < n_expert_used; k++) { float max_val = wt[0]; - uint max_expert = gl_LocalInvocationID.x; + uint max_expert = lane; [[unroll]] for (int i = 1; i < experts_per_thread; i++) { - const uint expert = gl_LocalInvocationID.x + i * WARP_SIZE; + const uint expert = lane + i * WARP_SIZE; if ((n_experts % WARP_SIZE == 0 || expert < n_experts) && wt[i] > max_val) { max_val = wt[i]; max_expert = expert; @@ -132,11 +133,11 @@ void main() { } } - if ((k & (WARP_SIZE - 1)) == gl_LocalInvocationID.x) { + if ((k & (WARP_SIZE - 1)) == lane) { output_weights[k / WARP_SIZE] = max_val; } - if ((max_expert & (WARP_SIZE - 1)) == gl_LocalInvocationID.x) { + if ((max_expert & (WARP_SIZE - 1)) == lane) { wt[max_expert / WARP_SIZE] = -INFINITY; ids[ids_offset + k] = max_expert; @@ -158,12 +159,12 @@ void main() { } if (late_softmax) { - softmax_warp_inplace(output_weights, n_expert_used, gl_LocalInvocationID.x, true); + softmax_warp_inplace(output_weights, n_expert_used, lane, true); } [[unroll]] for (uint i = 0; i < experts_per_thread; ++i) { - uint idx = i * WARP_SIZE + gl_LocalInvocationID.x; + uint idx = i * WARP_SIZE + lane; if (idx < n_expert_used) { weights[weights_offset + idx] = output_weights[i]; } diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/topk_nary_search.comp b/ggml/src/ggml-vulkan/vulkan-shaders/topk_nary_search.comp index c902e60237..0b757f38e1 100644 --- a/ggml/src/ggml-vulkan/vulkan-shaders/topk_nary_search.comp +++ b/ggml/src/ggml-vulkan/vulkan-shaders/topk_nary_search.comp @@ -25,6 +25,7 @@ layout (push_constant) uniform parameter { uint orig_ncols; uint ncols_input; uint ncols_output; + uint k; uint nrows; uint first_pass; uint last_pass; @@ -37,6 +38,7 @@ shared int counts[SUBGROUP_SIZE]; shared int sh_min_idx; shared uint sh_total; shared uint offset_partials[BLOCK_SIZE / SUBGROUP_SIZE]; +shared uint eq_min_partials[BLOCK_SIZE / SUBGROUP_SIZE]; // Map float values to uint such that comparisons still work. // Positive values set the high bit, negative values are inverted. @@ -60,7 +62,7 @@ void topk(const uint row) { const uint row_offset = row * p.ncols_input; dst_row[tid] = ivec2(gl_GlobalInvocationID.x, floatBitsToInt(data_a[row_offset + gl_GlobalInvocationID.x])); } else { - const uint row_offset = row * p.orig_ncols; + const uint row_offset = row * p.ncols_input; dst_row[tid] = data_s[row_offset + gl_GlobalInvocationID.x]; } } else { @@ -68,7 +70,7 @@ void topk(const uint row) { } barrier(); - if (p.ncols_output == 1) { + if (p.k == 1) { // Fast path for single output - just do a max reduction [[unroll]] for (int s = BLOCK_SIZE / 2; s >= 1; s /= 2) { if (tid < s) { @@ -98,7 +100,7 @@ void topk(const uint row) { uint range_max = 0xFF800000; // How many are above the current range, and how many we need to find. uint total = 0; - uint limit = min(p.ncols_output, p.ncols_input - gl_WorkGroupID.x * BLOCK_SIZE); + uint limit = min(p.k, p.ncols_input - gl_WorkGroupID.x * BLOCK_SIZE); while (mask != 0) { barrier(); @@ -139,7 +141,7 @@ void topk(const uint row) { range_max = range_min + ((min_idx + 1) << shift); range_min = range_min + (min_idx << shift); - if (total == p.ncols_output) { + if (total == p.k) { break; } total -= counts[min_idx]; @@ -155,37 +157,82 @@ void topk(const uint row) { // We need to compact these values to the start of the dst_row array. // Have each subgroup count how many items it'll store, so other // subgroups can compute their base offset. - bool top = f2ui(intBitsToFloat(v.y)) >= range_min; - uvec4 b = subgroupBallot(top); - uint bit_count = subgroupBallotBitCount(b); - if ((tid % SUBGROUP_SIZE) == 0) { - offset_partials[tid / SUBGROUP_SIZE] = bit_count; - } - barrier(); - - uint out_idx = 0; - [[unroll]] for (int i = 0; i < BLOCK_SIZE / SUBGROUP_SIZE; ++i) { - if (i < tid / SUBGROUP_SIZE) { - out_idx += offset_partials[i]; + // Values strictly greater than range_min must be stored. For values equal + // to range_min, there can be ties and it's possible we'll need to store + // an arbitrary subset of them. + // If total == p.k, have a fast path where we don't need to handle ties. + if (total == p.k) { + bool top = f2ui(intBitsToFloat(v.y)) >= range_min; + uvec4 b = subgroupBallot(top); + uint bit_count = subgroupBallotBitCount(b); + if ((tid % SUBGROUP_SIZE) == 0) { + offset_partials[tid / SUBGROUP_SIZE] = bit_count; } - } + barrier(); - uint bit_count_ex = subgroupBallotExclusiveBitCount(b); - if (top) { - // TODO: Copy directly to the output? - dst_row[out_idx + bit_count_ex] = v; + uint out_idx = 0; + [[unroll]] for (int i = 0; i < BLOCK_SIZE / SUBGROUP_SIZE; ++i) { + if (i < tid / SUBGROUP_SIZE) { + out_idx += offset_partials[i]; + } + } + + uint bit_count_ex = subgroupBallotExclusiveBitCount(b); + if (top) { + // TODO: Copy directly to the output? + dst_row[out_idx + bit_count_ex] = v; + } + } else { + bool top = f2ui(intBitsToFloat(v.y)) > range_min; + bool eq_min = f2ui(intBitsToFloat(v.y)) == range_min; + uvec4 b_top = subgroupBallot(top); + uvec4 b_eq_min = subgroupBallot(eq_min); + uint bit_count_top = subgroupBallotBitCount(b_top); + uint bit_count_eq_min = subgroupBallotBitCount(b_eq_min); + if ((tid % SUBGROUP_SIZE) == 0) { + offset_partials[tid / SUBGROUP_SIZE] = bit_count_top; + eq_min_partials[tid / SUBGROUP_SIZE] = bit_count_eq_min; + } + barrier(); + + uint out_idx = 0; + uint eq_min_base = 0; + uint eq_min_idx = 0; + [[unroll]] for (int i = 0; i < BLOCK_SIZE / SUBGROUP_SIZE; ++i) { + if (i < tid / SUBGROUP_SIZE) { + out_idx += offset_partials[i]; + eq_min_idx += eq_min_partials[i]; + } + eq_min_base += offset_partials[i]; + } + // range_min values are stored at the end + eq_min_idx += eq_min_base; + + uint bit_count_ex_top = subgroupBallotExclusiveBitCount(b_top); + uint bit_count_ex_eq_min = subgroupBallotExclusiveBitCount(b_eq_min); + if (top) { + // TODO: Copy directly to the output? + dst_row[out_idx + bit_count_ex_top] = v; + } + if (eq_min && eq_min_idx + bit_count_ex_eq_min < p.k) { + dst_row[eq_min_idx + bit_count_ex_eq_min] = v; + } } barrier(); } - if (tid < p.ncols_output && gl_GlobalInvocationID.x < p.orig_ncols) { + if (tid < p.k) { if (p.last_pass != 0) { - const uint row_offset = row * p.ncols_output; - data_d[row_offset + tid] = dst_row[tid].x; + if (gl_GlobalInvocationID.x < p.ncols_input) { + const uint row_offset = row * p.k; + data_d[row_offset + tid] = dst_row[tid].x; + } } else { - const uint row_offset = row * p.orig_ncols + gl_WorkGroupID.x * p.ncols_output; - data_t[row_offset + tid] = dst_row[tid]; + if (gl_WorkGroupID.x * p.k + tid < p.ncols_output) { + const uint row_offset = row * p.ncols_output + gl_WorkGroupID.x * p.k; + data_t[row_offset + tid] = dst_row[tid]; + } } } } diff --git a/ggml/src/ggml-webgpu/CMakeLists.txt b/ggml/src/ggml-webgpu/CMakeLists.txt index c6a95d5151..3ccce58aa3 100644 --- a/ggml/src/ggml-webgpu/CMakeLists.txt +++ b/ggml/src/ggml-webgpu/CMakeLists.txt @@ -39,8 +39,23 @@ add_dependencies(ggml-webgpu generate_shaders) if(EMSCRIPTEN) set(EMDAWNWEBGPU_DIR "" CACHE PATH "Path to emdawnwebgpu_pkg") - target_compile_options(ggml-webgpu PRIVATE "--use-port=${EMDAWNWEBGPU_DIR}/emdawnwebgpu.port.py") - target_link_options(ggml-webgpu PRIVATE "--use-port=${EMDAWNWEBGPU_DIR}/emdawnwebgpu.port.py") + if(NOT EMDAWNWEBGPU_DIR) + # default built-in port + target_compile_options(ggml-webgpu PRIVATE "--use-port=emdawnwebgpu") + target_link_options(ggml-webgpu INTERFACE "--use-port=emdawnwebgpu") + else() + # custom port + target_compile_options(ggml-webgpu PRIVATE "--use-port=${EMDAWNWEBGPU_DIR}/emdawnwebgpu.port.py") + target_link_options(ggml-webgpu INTERFACE "--use-port=${EMDAWNWEBGPU_DIR}/emdawnwebgpu.port.py") + endif() + + if (GGML_WEBGPU_JSPI) + target_compile_options(ggml-webgpu PRIVATE "-fwasm-exceptions") + target_link_options(ggml-webgpu INTERFACE "-sJSPI" "-fwasm-exceptions") + else() + target_compile_options(ggml-webgpu PRIVATE "-fexceptions") + target_link_options(ggml-webgpu INTERFACE "-sASYNCIFY" "-exceptions") + endif() else() find_package(Dawn REQUIRED) set(DawnWebGPU_TARGET dawn::webgpu_dawn) @@ -48,6 +63,9 @@ endif() if (GGML_WEBGPU_DEBUG) target_compile_definitions(ggml-webgpu PRIVATE GGML_WEBGPU_DEBUG=1) + if(EMSCRIPTEN) + target_link_options(ggml-webgpu INTERFACE "-sASSERTIONS=2") + endif() endif() if (GGML_WEBGPU_CPU_PROFILE) diff --git a/ggml/src/ggml-webgpu/ggml-webgpu.cpp b/ggml/src/ggml-webgpu/ggml-webgpu.cpp index 9e8cbc477e..d0e99b6fe2 100644 --- a/ggml/src/ggml-webgpu/ggml-webgpu.cpp +++ b/ggml/src/ggml-webgpu/ggml-webgpu.cpp @@ -9,6 +9,10 @@ #include "ggml-impl.h" #include "ggml-wgsl-shaders.hpp" +#ifdef __EMSCRIPTEN__ +# include +#endif + #include #include @@ -21,6 +25,9 @@ #include #include +#define ROUNDUP_POW2(x, pow2) (((x) + ((pow2) - 1)) & ~((pow2) - 1)) +#define CEIL_DIV(M, N) (((M) + (N) - 1) / (N)) + #ifdef GGML_WEBGPU_DEBUG # define WEBGPU_LOG_DEBUG(msg) std::cout << msg << std::endl # define WEBGPU_DEBUG_BUF_ELEMS 32 @@ -60,6 +67,9 @@ /* Constants */ +// Track https://github.com/gpuweb/gpuweb/issues/5315 for fixes to implementations so this can be removed. +#define WEBGPU_MAX_WG_SIZE 288 + #define WEBGPU_MUL_MAT_WG_SIZE 256 #define WEBGPU_NUM_PARAM_BUFS 32u #define WEBGPU_COMMAND_SUBMIT_BATCH_SIZE 8u @@ -261,13 +271,12 @@ struct webgpu_context_struct { wgpu::Queue queue; wgpu::Limits limits; - bool supports_subgroup_matrix = false; - uint32_t subgroup_size; - wgpu::SubgroupMatrixConfig subgroup_matrix_config; + uint32_t subgroup_size; - // Separate this out from limits since on some Metal systems, the limit returned by - // querying the limits is higher than the actual allowed maximum. - uint32_t max_wg_size_x; +#ifndef __EMSCRIPTEN__ + bool supports_subgroup_matrix = false; + wgpu::SubgroupMatrixConfig subgroup_matrix_config; +#endif std::recursive_mutex mutex; std::atomic_uint inflight_threads = 0; @@ -275,26 +284,27 @@ struct webgpu_context_struct { webgpu_buf_pool param_buf_pool; webgpu_buf_pool set_rows_error_buf_pool; - webgpu_pipeline memset_pipeline; + std::map memset_pipelines; // variant or type index std::map>> mul_mat_pipelines; // src0_type, src1_type, vectorized std::map>> mul_mat_vec_pipelines; // src0_type, src1_type, vectorized - webgpu_pipeline mul_mat_pipeline[30][2]; - webgpu_pipeline set_rows_pipeline[1][2]; // dst->type, vectorized - webgpu_pipeline get_rows_pipeline[30]; - webgpu_pipeline get_rows_f32_no_vec_pipeline; - webgpu_pipeline cpy_pipeline[2][2]; // src type, dst type - webgpu_pipeline add_pipeline[2][2]; // type, inplace - webgpu_pipeline sub_pipeline[2][2]; // type, inplace - webgpu_pipeline mul_pipeline[2][2]; // type, inplace - webgpu_pipeline div_pipeline[2][2]; // type, inplace - webgpu_pipeline rms_norm_pipeline[2]; // inplace - webgpu_pipeline rope_pipeline[2][2][2]; // type, ff, inplace - webgpu_pipeline glu_pipeline[7][2][2]; // glu-op, type, split - webgpu_pipeline scale_pipeline[2]; // inplace - webgpu_pipeline soft_max_pipeline[3][2][2]; // (no_mask, f32_mask, f16_mask), has_sink, inplace + std::map> set_rows_pipelines; // dst_type, vectorized + std::map> get_rows_pipelines; // src_type, vectorized + + std::map> cpy_pipelines; // src_type, dst_type + std::map> add_pipelines; // type, inplace + std::map> sub_pipelines; // type, inplace + std::map> mul_pipelines; // type, inplace + std::map> div_pipelines; // type, inplace + + std::map rms_norm_pipelines; // inplace + std::map>> rope_pipelines; // type, ff, inplace + std::map>> glu_pipelines; // glu_op, type, split + std::map scale_pipelines; // inplace + std::map>> soft_max_pipelines; // mask_type, has_sink, inplace + std::map>> unary_pipelines; // unary_op, type, inplace size_t memset_bytes_per_thread; @@ -374,35 +384,10 @@ static std::string ggml_webgpu_process_shader_repls(const char * return s; } -static void ggml_webgpu_create_pipeline(wgpu::Device & device, - webgpu_pipeline & pipeline, - const char * shader_code, - const char * label, - const std::vector & constants = {}) { - wgpu::ShaderSourceWGSL shader_source; - shader_source.code = shader_code; - - wgpu::ShaderModuleDescriptor shader_desc; - shader_desc.nextInChain = &shader_source; - - wgpu::ShaderModule shader_module = device.CreateShaderModule(&shader_desc); - - wgpu::ComputePipelineDescriptor pipeline_desc; - pipeline_desc.label = label; - pipeline_desc.compute.module = shader_module; - pipeline_desc.compute.entryPoint = "main"; // Entry point in the WGSL code - pipeline_desc.layout = nullptr; // nullptr means auto layout - if (constants.size() > 0) { - pipeline_desc.compute.constants = constants.data(); - pipeline_desc.compute.constantCount = constants.size(); - } - pipeline = { device.CreateComputePipeline(&pipeline_desc), label }; -} - -static webgpu_pipeline ggml_webgpu_create_pipeline2(wgpu::Device & device, - const char * shader_code, - const char * label, - const std::vector & constants = {}) { +static webgpu_pipeline ggml_webgpu_create_pipeline(wgpu::Device & device, + const char * shader_code, + const char * label, + const std::vector & constants = {}) { wgpu::ShaderSourceWGSL shader_source; shader_source.code = shader_code; @@ -449,8 +434,8 @@ static void ggml_backend_webgpu_wait(webgpu_context & ct // If we have too many in-flight submissions, wait on the oldest one first. If there are many threads, // inflight_max may be 0, meaning that we must wait on all futures. uint64_t timeout_ms = block ? UINT64_MAX : 0; - uint inflight_threads = ctx->inflight_threads; - uint inflight_max = WEBGPU_MAX_INFLIGHT_SUBS_PER_THREAD / std::max(inflight_threads, 1u); + uint32_t inflight_threads = ctx->inflight_threads; + uint32_t inflight_max = WEBGPU_MAX_INFLIGHT_SUBS_PER_THREAD / std::max(inflight_threads, 1u); while (futures.size() >= inflight_max && futures.size() > 0) { ctx->instance.WaitAny(futures[0].futures.size(), futures[0].futures.data(), UINT64_MAX); futures.erase(futures.begin()); @@ -671,10 +656,10 @@ static void ggml_backend_webgpu_buffer_memset(webgpu_context & ctx, std::vector entries = { { .binding = 0, .buffer = buf, .offset = 0, .size = buf.GetSize() } }; - size_t bytes_per_wg = ctx->max_wg_size_x * ctx->memset_bytes_per_thread; - uint32_t wg_x = ((size + 3) + bytes_per_wg - 1) / bytes_per_wg; + size_t bytes_per_wg = WEBGPU_MAX_WG_SIZE * ctx->memset_bytes_per_thread; + uint32_t wg_x = CEIL_DIV(size + 3, bytes_per_wg); - webgpu_command command = ggml_backend_webgpu_build(ctx, ctx->memset_pipeline, params, entries, wg_x); + webgpu_command command = ggml_backend_webgpu_build(ctx, ctx->memset_pipelines[0], params, entries, wg_x); std::vector futures = { ggml_backend_webgpu_submit(ctx, { command }) }; ggml_backend_webgpu_wait(ctx, futures); } @@ -756,8 +741,7 @@ static size_t ggml_webgpu_tensor_align_offset(webgpu_context & ctx, ggml_tensor } static size_t ggml_webgpu_tensor_binding_size(webgpu_context & ctx, ggml_tensor * t) { - return (ggml_nbytes(t) + ggml_webgpu_tensor_misalignment(ctx, t) + WEBGPU_STORAGE_BUF_BINDING_MULT - 1) & - ~(WEBGPU_STORAGE_BUF_BINDING_MULT - 1); + return ROUNDUP_POW2(ggml_nbytes(t) + ggml_webgpu_tensor_misalignment(ctx, t), WEBGPU_STORAGE_BUF_BINDING_MULT); } // Used to determine if two tensors are the same for in-place operations @@ -793,9 +777,8 @@ static webgpu_command ggml_webgpu_cpy(webgpu_context & ctx, ggml_tensor * src, g .size = ggml_webgpu_tensor_binding_size(ctx, dst) } }; - size_t max_wg_size = ctx->max_wg_size_x; - uint32_t wg_x = (ne + max_wg_size - 1) / max_wg_size; - return ggml_backend_webgpu_build(ctx, ctx->cpy_pipeline[src->type][dst->type], params, entries, wg_x); + uint32_t wg_x = CEIL_DIV(ne, WEBGPU_MAX_WG_SIZE); + return ggml_backend_webgpu_build(ctx, ctx->cpy_pipelines[src->type][dst->type], params, entries, wg_x); } static std::optional ggml_webgpu_set_rows(webgpu_context & ctx, @@ -844,10 +827,8 @@ static std::optional ggml_webgpu_set_rows(webgpu_context & ctx, { .binding = 3, .buffer = error_bufs.dev_buf, .offset = 0, .size = error_bufs.dev_buf.GetSize() } }; - size_t max_wg_size = ctx->max_wg_size_x; - int vectorized = src->ne[0] % 4 == 0; - webgpu_pipeline pipeline = ctx->set_rows_pipeline[0][vectorized]; + webgpu_pipeline pipeline = ctx->set_rows_pipelines[0][vectorized]; uint32_t threads; if (vectorized) { threads = (src->ne[1] * src->ne[2] * src->ne[3]) * (src->ne[0] / 4); @@ -855,7 +836,7 @@ static std::optional ggml_webgpu_set_rows(webgpu_context & ctx, threads = src->ne[0] * src->ne[1] * src->ne[2] * src->ne[3]; } - uint32_t wg_x = (threads + max_wg_size - 1) / max_wg_size; + uint32_t wg_x = CEIL_DIV(threads, WEBGPU_MAX_WG_SIZE); return ggml_backend_webgpu_build(ctx, pipeline, params, entries, wg_x, 1, error_bufs); } @@ -895,13 +876,10 @@ static webgpu_command ggml_webgpu_get_rows(webgpu_context & ctx, .size = ggml_webgpu_tensor_binding_size(ctx, dst) } }; - size_t max_wg_size = ctx->max_wg_size_x; - uint32_t wg_x = (dst->ne[1] * dst->ne[2] * dst->ne[3] + max_wg_size - 1) / max_wg_size; + uint32_t wg_x = CEIL_DIV(dst->ne[1] * dst->ne[2] * dst->ne[3], WEBGPU_MAX_WG_SIZE); - webgpu_pipeline pipeline = ctx->get_rows_pipeline[src->type]; - if (src->type == GGML_TYPE_F32 && dst->ne[0] % 4 != 0) { - pipeline = ctx->get_rows_f32_no_vec_pipeline; - } + uint32_t vectorized = src->type == GGML_TYPE_F32 && dst->ne[0] % 4 == 0; + webgpu_pipeline pipeline = ctx->get_rows_pipelines[src->type][vectorized]; return ggml_backend_webgpu_build(ctx, pipeline, params, entries, wg_x); } @@ -943,10 +921,9 @@ static webgpu_command ggml_webgpu_mul_mat(webgpu_context & ctx, .size = ggml_webgpu_tensor_binding_size(ctx, dst) }, }; - webgpu_pipeline pipeline = ctx->mul_mat_pipeline[src0->type][src1->type]; + webgpu_pipeline pipeline = ctx->mul_mat_pipelines[src0->type][src1->type][0]; - uint32_t wg_x = - (dst->ne[0] * dst->ne[1] * dst->ne[2] * dst->ne[3] + WEBGPU_MUL_MAT_WG_SIZE - 1) / WEBGPU_MUL_MAT_WG_SIZE; + uint32_t wg_x = CEIL_DIV(dst->ne[0] * dst->ne[1] * dst->ne[2] * dst->ne[3], WEBGPU_MUL_MAT_WG_SIZE); uint32_t wg_y = 1; bool use_fast = false; @@ -973,39 +950,96 @@ static webgpu_command ggml_webgpu_mul_mat(webgpu_context & ctx, int vectorized = src0->ne[0] % 4 == 0 && dst->ne[0] % 4 == 0 && dst->ne[1] % 4 == 0; if (dst->ne[1] == 1) { // We don't support vectorized mul_mat_vec for quantized types - vectorized = vectorized && (src0->type < 2); - pipeline = ctx->mul_mat_vec_pipelines[src0->type][src1->type][vectorized]; - uint32_t batches = dst->ne[2] * dst->ne[3]; - uint32_t output_groups = - (dst->ne[0] + WEBGPU_MUL_MAT_VEC_OUTPUTS_PER_WG - 1) / WEBGPU_MUL_MAT_VEC_OUTPUTS_PER_WG; - uint32_t total_wg = output_groups * batches; - wg_x = total_wg % ctx->limits.maxComputeWorkgroupsPerDimension; - wg_y = (total_wg + ctx->limits.maxComputeWorkgroupsPerDimension - 1) / - ctx->limits.maxComputeWorkgroupsPerDimension; + vectorized = vectorized && (src0->type < 2); + pipeline = ctx->mul_mat_vec_pipelines[src0->type][src1->type][vectorized]; + uint32_t batches = dst->ne[2] * dst->ne[3]; + uint32_t output_groups = CEIL_DIV(dst->ne[0], WEBGPU_MUL_MAT_VEC_OUTPUTS_PER_WG); + uint32_t total_wg = output_groups * batches; + wg_x = total_wg % ctx->limits.maxComputeWorkgroupsPerDimension; + wg_y = CEIL_DIV(total_wg, ctx->limits.maxComputeWorkgroupsPerDimension); } else { pipeline = ctx->mul_mat_pipelines[src0->type][src1->type][vectorized]; uint32_t wg_m; uint32_t wg_n; +#ifndef __EMSCRIPTEN__ if (ctx->supports_subgroup_matrix) { // The total number of subgroups/workgroups needed per matrix. uint32_t wg_m_sg_tile = WEBGPU_MUL_MAT_SUBGROUP_M * WEBGPU_MUL_MAT_SUBGROUP_MATRIX_M * ctx->subgroup_matrix_config.M; - wg_m = (dst->ne[0] + wg_m_sg_tile - 1) / wg_m_sg_tile; + wg_m = CEIL_DIV(dst->ne[0], wg_m_sg_tile); uint32_t wg_n_sg_tile = WEBGPU_MUL_MAT_SUBGROUP_N * WEBGPU_MUL_MAT_SUBGROUP_MATRIX_N * ctx->subgroup_matrix_config.N; - wg_n = (dst->ne[1] + wg_n_sg_tile - 1) / wg_n_sg_tile; + wg_n = CEIL_DIV(dst->ne[1], wg_n_sg_tile); } else { +#endif uint32_t tile_m_s = WEBGPU_MUL_MAT_TILE_M * WEBGPU_MUL_MAT_WG_SIZE_M; uint32_t tile_n_s = WEBGPU_MUL_MAT_TILE_N * WEBGPU_MUL_MAT_WG_SIZE_N; - wg_m = (dst->ne[0] + tile_m_s - 1) / tile_m_s; - wg_n = (dst->ne[1] + tile_n_s - 1) / tile_n_s; + wg_m = CEIL_DIV(dst->ne[0], tile_m_s); + wg_n = CEIL_DIV(dst->ne[1], tile_n_s); +#ifndef __EMSCRIPTEN__ } +#endif + wg_x = wg_m * wg_n * dst->ne[2] * dst->ne[3]; } } return ggml_backend_webgpu_build(ctx, pipeline, params, entries, wg_x, wg_y); } +static webgpu_command ggml_webgpu_unary_op(webgpu_context & ctx, ggml_tensor * src, ggml_tensor * dst) { + uint32_t ne = (uint32_t) ggml_nelements(dst); + ggml_unary_op unary_op = ggml_get_unary_op(dst); + uint32_t inplace = ggml_webgpu_tensor_equal(src, dst); + + std::vector params = { + ne, (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, src) / ggml_type_size(src->type)), + (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, dst) / ggml_type_size(dst->type)), + // Convert byte-strides to element-strides + (uint32_t) (src->nb[0] / ggml_type_size(src->type)), (uint32_t) (src->nb[1] / ggml_type_size(src->type)), + (uint32_t) (src->nb[2] / ggml_type_size(src->type)), (uint32_t) (src->nb[3] / ggml_type_size(src->type)), + (uint32_t) (dst->nb[0] / ggml_type_size(dst->type)), (uint32_t) (dst->nb[1] / ggml_type_size(dst->type)), + (uint32_t) (dst->nb[2] / ggml_type_size(dst->type)), (uint32_t) (dst->nb[3] / ggml_type_size(dst->type)), + // Logical shapes + (uint32_t) src->ne[0], (uint32_t) src->ne[1], (uint32_t) src->ne[2], (uint32_t) dst->ne[0], + (uint32_t) dst->ne[1], (uint32_t) dst->ne[2] + }; + + switch (unary_op) { + case GGML_UNARY_OP_XIELU: + { + // Get float parameters and reinterpret their bit patterns as uint32_t + // for passing through the params buffer + float alpha_n = ggml_get_op_params_f32(dst, 1); + float alpha_p = ggml_get_op_params_f32(dst, 2); + float beta = ggml_get_op_params_f32(dst, 3); + float eps = ggml_get_op_params_f32(dst, 4); + params.push_back(*reinterpret_cast(&alpha_n)); + params.push_back(*reinterpret_cast(&alpha_p)); + params.push_back(*reinterpret_cast(&beta)); + params.push_back(*reinterpret_cast(&eps)); + break; + } + default: + break; + } + + std::vector entries = { + { .binding = 0, + .buffer = ggml_webgpu_tensor_buf(src), + .offset = ggml_webgpu_tensor_align_offset(ctx, src), + .size = ggml_webgpu_tensor_binding_size(ctx, src) }, + }; + if (!inplace) { + entries.push_back({ .binding = 1, + .buffer = ggml_webgpu_tensor_buf(dst), + .offset = ggml_webgpu_tensor_align_offset(ctx, dst), + .size = ggml_webgpu_tensor_binding_size(ctx, dst) }); + } + + uint32_t wg_x = CEIL_DIV(ne, WEBGPU_MAX_WG_SIZE); + return ggml_backend_webgpu_build(ctx, ctx->unary_pipelines[unary_op][dst->type][inplace], params, entries, wg_x); +} + static webgpu_command ggml_webgpu_binary_op(webgpu_context & ctx, ggml_tensor * src0, ggml_tensor * src1, @@ -1047,8 +1081,7 @@ static webgpu_command ggml_webgpu_binary_op(webgpu_context & ctx, .size = ggml_webgpu_tensor_binding_size(ctx, dst) }); } - size_t max_wg_size = ctx->max_wg_size_x; - uint32_t wg_x = (ggml_nelements(dst) + max_wg_size - 1) / max_wg_size; + uint32_t wg_x = CEIL_DIV(ggml_nelements(dst), WEBGPU_MAX_WG_SIZE); return ggml_backend_webgpu_build(ctx, pipeline, params, entries, wg_x); } @@ -1084,7 +1117,7 @@ static webgpu_command ggml_webgpu_rms_norm(webgpu_context & ctx, ggml_tensor * s .size = ggml_webgpu_tensor_binding_size(ctx, dst) }); } - return ggml_backend_webgpu_build(ctx, ctx->rms_norm_pipeline[inplace], params, entries, ggml_nrows(src)); + return ggml_backend_webgpu_build(ctx, ctx->rms_norm_pipelines[inplace], params, entries, ggml_nrows(src)); } static webgpu_command ggml_webgpu_rope(webgpu_context & ctx, @@ -1169,9 +1202,8 @@ static webgpu_command ggml_webgpu_rope(webgpu_context & ctx, .size = ggml_webgpu_tensor_binding_size(ctx, dst) }); } - webgpu_pipeline pipeline = ctx->rope_pipeline[dst->type][has_freq_factor][inplace]; - size_t max_wg_size = ctx->max_wg_size_x; - uint32_t wg_x = (ggml_nelements(src0) / 2 + max_wg_size - 1) / max_wg_size; + webgpu_pipeline pipeline = ctx->rope_pipelines[dst->type][has_freq_factor][inplace]; + uint32_t wg_x = CEIL_DIV(ggml_nelements(dst), WEBGPU_MAX_WG_SIZE); return ggml_backend_webgpu_build(ctx, pipeline, params, entries, wg_x); } @@ -1222,9 +1254,8 @@ static webgpu_command ggml_webgpu_glu(webgpu_context & ctx, ggml_tensor * src0, .offset = ggml_webgpu_tensor_align_offset(ctx, dst), .size = ggml_webgpu_tensor_binding_size(ctx, dst) }); - webgpu_pipeline pipeline = ctx->glu_pipeline[ggml_get_glu_op(dst)][dst->type][split]; - size_t max_wg_size = ctx->max_wg_size_x; - uint32_t wg_x = (ggml_nelements(dst) + max_wg_size - 1) / max_wg_size; + webgpu_pipeline pipeline = ctx->glu_pipelines[ggml_get_glu_op(dst)][dst->type][split]; + uint32_t wg_x = CEIL_DIV(ggml_nelements(dst), WEBGPU_MAX_WG_SIZE); return ggml_backend_webgpu_build(ctx, pipeline, params, entries, wg_x); } @@ -1261,9 +1292,8 @@ static webgpu_command ggml_webgpu_scale(webgpu_context & ctx, ggml_tensor * src, .size = ggml_webgpu_tensor_binding_size(ctx, dst) }); } - size_t max_wg_size = ctx->max_wg_size_x; - uint32_t wg_x = (ggml_nelements(dst) + max_wg_size - 1) / max_wg_size; - return ggml_backend_webgpu_build(ctx, ctx->scale_pipeline[inplace], params, entries, wg_x); + uint32_t wg_x = CEIL_DIV(ggml_nelements(dst), WEBGPU_MAX_WG_SIZE); + return ggml_backend_webgpu_build(ctx, ctx->scale_pipelines[inplace], params, entries, wg_x); } static webgpu_command ggml_webgpu_soft_max(webgpu_context & ctx, @@ -1335,7 +1365,7 @@ static webgpu_command ggml_webgpu_soft_max(webgpu_context & ctx, .size = ggml_webgpu_tensor_binding_size(ctx, dst) }); } - return ggml_backend_webgpu_build(ctx, ctx->soft_max_pipeline[mask_type][has_sink][inplace], params, entries, + return ggml_backend_webgpu_build(ctx, ctx->soft_max_pipelines[mask_type][has_sink][inplace], params, entries, ggml_nrows(dst)); } @@ -1370,22 +1400,22 @@ static std::optional ggml_webgpu_encode_node(webgpu_context ctx, case GGML_OP_ADD: { int inplace = ggml_webgpu_tensor_equal(src0, node); - return ggml_webgpu_binary_op(ctx, src0, src1, node, ctx->add_pipeline[node->type][inplace], inplace); + return ggml_webgpu_binary_op(ctx, src0, src1, node, ctx->add_pipelines[node->type][inplace], inplace); } case GGML_OP_SUB: { int inplace = ggml_webgpu_tensor_equal(src0, node); - return ggml_webgpu_binary_op(ctx, src0, src1, node, ctx->sub_pipeline[node->type][inplace], inplace); + return ggml_webgpu_binary_op(ctx, src0, src1, node, ctx->sub_pipelines[node->type][inplace], inplace); } case GGML_OP_MUL: { int inplace = ggml_webgpu_tensor_equal(src0, node); - return ggml_webgpu_binary_op(ctx, src0, src1, node, ctx->mul_pipeline[node->type][inplace], inplace); + return ggml_webgpu_binary_op(ctx, src0, src1, node, ctx->mul_pipelines[node->type][inplace], inplace); } case GGML_OP_DIV: { int inplace = ggml_webgpu_tensor_equal(src0, node); - return ggml_webgpu_binary_op(ctx, src0, src1, node, ctx->div_pipeline[node->type][inplace], inplace); + return ggml_webgpu_binary_op(ctx, src0, src1, node, ctx->div_pipelines[node->type][inplace], inplace); } case GGML_OP_RMS_NORM: return ggml_webgpu_rms_norm(ctx, src0, node); @@ -1397,6 +1427,8 @@ static std::optional ggml_webgpu_encode_node(webgpu_context ctx, return ggml_webgpu_scale(ctx, src0, node); case GGML_OP_SOFT_MAX: return ggml_webgpu_soft_max(ctx, src0, src1, src2, node); + case GGML_OP_UNARY: + return ggml_webgpu_unary_op(ctx, src0, node); default: return std::nullopt; } @@ -1419,9 +1451,9 @@ static ggml_status ggml_backend_webgpu_graph_compute(ggml_backend_t backend, str commands.push_back(*cmd); } // compute the batch size based on the number of inflight threads - uint inflight_threads = ctx->inflight_threads; - uint batch_size = std::min(std::max(1u, WEBGPU_NUM_PARAM_BUFS / std::max(inflight_threads, 1u)), - WEBGPU_COMMAND_SUBMIT_BATCH_SIZE); + uint32_t inflight_threads = ctx->inflight_threads; + uint32_t batch_size = std::min(std::max(1u, WEBGPU_NUM_PARAM_BUFS / std::max(inflight_threads, 1u)), + WEBGPU_COMMAND_SUBMIT_BATCH_SIZE); if (commands.size() >= batch_size) { futures.push_back(ggml_backend_webgpu_submit(ctx, commands)); // Process events and check for completed submissions @@ -1629,8 +1661,7 @@ static ggml_backend_buffer_t ggml_backend_webgpu_buffer_type_alloc_buffer(ggml_b ggml_backend_webgpu_device_context * ctx = static_cast(buft->device->context); wgpu::Buffer buf; - ggml_webgpu_create_buffer(ctx->webgpu_ctx->device, buf, - (size + WEBGPU_STORAGE_BUF_BINDING_MULT - 1) & ~(WEBGPU_STORAGE_BUF_BINDING_MULT - 1), + ggml_webgpu_create_buffer(ctx->webgpu_ctx->device, buf, ROUNDUP_POW2(size, WEBGPU_STORAGE_BUF_BINDING_MULT), wgpu::BufferUsage::Storage | wgpu::BufferUsage::CopySrc | wgpu::BufferUsage::CopyDst, buf_name.c_str()); @@ -1705,59 +1736,76 @@ static std::vector ggml_webgpu_wg_size_entry(uint32_t wg_si static void ggml_webgpu_init_memset_pipeline(webgpu_context & webgpu_ctx) { // we use the maximum workgroup size for the memset pipeline - size_t max_wg_size = webgpu_ctx->max_wg_size_x; - size_t max_threads = max_wg_size * webgpu_ctx->limits.maxComputeWorkgroupsPerDimension; + size_t max_threads = WEBGPU_MAX_WG_SIZE * webgpu_ctx->limits.maxComputeWorkgroupsPerDimension; // Size the bytes_per_thread so that the largest buffer size can be handled - webgpu_ctx->memset_bytes_per_thread = - (webgpu_ctx->limits.maxStorageBufferBindingSize + max_threads - 1) / max_threads; + webgpu_ctx->memset_bytes_per_thread = CEIL_DIV(webgpu_ctx->limits.maxStorageBufferBindingSize, max_threads); std::vector constants(2); - constants[0].key = "wg_size"; - constants[0].value = max_wg_size; - constants[1].key = "bytes_per_thread"; - constants[1].value = webgpu_ctx->memset_bytes_per_thread; - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->memset_pipeline, wgsl_memset, "memset", constants); + constants[0].key = "wg_size"; + constants[0].value = WEBGPU_MAX_WG_SIZE; + constants[1].key = "bytes_per_thread"; + constants[1].value = webgpu_ctx->memset_bytes_per_thread; + webgpu_ctx->memset_pipelines[0] = ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_memset, "memset", constants); } static void ggml_webgpu_init_mul_mat_pipeline(webgpu_context & webgpu_ctx) { - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_Q4_0][GGML_TYPE_F32], - wgsl_mul_mat_q4_0_f32, "mul_mat_q4_0_f32"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_Q4_1][GGML_TYPE_F32], - wgsl_mul_mat_q4_1_f32, "mul_mat_q4_1_f32"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_Q5_0][GGML_TYPE_F32], - wgsl_mul_mat_q5_0_f32, "mul_mat_q5_0_f32"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_Q5_1][GGML_TYPE_F32], - wgsl_mul_mat_q5_1_f32, "mul_mat_q5_1_f32"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_Q8_0][GGML_TYPE_F32], - wgsl_mul_mat_q8_0_f32, "mul_mat_q8_0_f32"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_Q2_K][GGML_TYPE_F32], - wgsl_mul_mat_q2_k_f32, "mul_mat_q2_k_f32"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_Q3_K][GGML_TYPE_F32], - wgsl_mul_mat_q3_k_f32, "mul_mat_q3_k_f32"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_Q4_K][GGML_TYPE_F32], - wgsl_mul_mat_q4_k_f32, "mul_mat_q4_k_f32"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_Q5_K][GGML_TYPE_F32], - wgsl_mul_mat_q5_k_f32, "mul_mat_q5_k_f32"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_Q6_K][GGML_TYPE_F32], - wgsl_mul_mat_q6_k_f32, "mul_mat_q6_k_f32"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_IQ2_XXS][GGML_TYPE_F32], - wgsl_mul_mat_iq2_xxs_f32, "mul_mat_iq2_xxs_f32"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_IQ2_XS][GGML_TYPE_F32], - wgsl_mul_mat_iq2_xs_f32, "mul_mat_iq2_xs_f32"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_IQ2_S][GGML_TYPE_F32], - wgsl_mul_mat_iq2_s_f32, "mul_mat_iq2_s_f32"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_IQ3_XXS][GGML_TYPE_F32], - wgsl_mul_mat_iq3_xxs_f32, "mul_mat_iq3_xxs_f32"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_IQ3_S][GGML_TYPE_F32], - wgsl_mul_mat_iq3_s_f32, "mul_mat_iq3_s_f32"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_IQ1_S][GGML_TYPE_F32], - wgsl_mul_mat_iq1_s_f32, "mul_mat_iq1_s_f32"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_IQ1_M][GGML_TYPE_F32], - wgsl_mul_mat_iq1_m_f32, "mul_mat_iq1_m_f32"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_IQ4_NL][GGML_TYPE_F32], - wgsl_mul_mat_iq4_nl_f32, "mul_mat_iq4_nl_f32"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_IQ4_XS][GGML_TYPE_F32], - wgsl_mul_mat_iq4_xs_f32, "mul_mat_iq4_xs_f32"); + // Q4/Q5/Q8 classic quantizations + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_Q4_0][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_mat_q4_0_f32, "mul_mat_q4_0_f32"); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_Q4_1][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_mat_q4_1_f32, "mul_mat_q4_1_f32"); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_Q5_0][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_mat_q5_0_f32, "mul_mat_q5_0_f32"); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_Q5_1][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_mat_q5_1_f32, "mul_mat_q5_1_f32"); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_Q8_0][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_mat_q8_0_f32, "mul_mat_q8_0_f32"); + // K-quantizations + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_Q2_K][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_mat_q2_k_f32, "mul_mat_q2_k_f32"); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_Q3_K][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_mat_q3_k_f32, "mul_mat_q3_k_f32"); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_Q4_K][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_mat_q4_k_f32, "mul_mat_q4_k_f32"); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_Q5_K][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_mat_q5_k_f32, "mul_mat_q5_k_f32"); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_Q6_K][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_mat_q6_k_f32, "mul_mat_q6_k_f32"); + + // IQ quantizations (2-, 3-, 4-bit variants) + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_IQ2_XXS][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_mat_iq2_xxs_f32, "mul_mat_iq2_xxs_f32"); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_IQ2_XS][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_mat_iq2_xs_f32, "mul_mat_iq2_xs_f32"); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_IQ2_S][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_mat_iq2_s_f32, "mul_mat_iq2_s_f32"); + + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_IQ3_XXS][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_mat_iq3_xxs_f32, "mul_mat_iq3_xxs_f32"); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_IQ3_S][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_mat_iq3_s_f32, "mul_mat_iq3_s_f32"); + + // 1-bit and 4-bit IQ variants + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_IQ1_S][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_mat_iq1_s_f32, "mul_mat_iq1_s_f32"); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_IQ1_M][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_mat_iq1_m_f32, "mul_mat_iq1_m_f32"); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_IQ4_NL][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_mat_iq4_nl_f32, "mul_mat_iq4_nl_f32"); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_IQ4_XS][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_mat_iq4_xs_f32, "mul_mat_iq4_xs_f32"); + + std::string proc_mul_mat_f32_f32; + std::string proc_mul_mat_f32_f32_vec; + std::string proc_mul_mat_f16_f32; + std::string proc_mul_mat_f16_f32_vec; + std::string proc_mul_mat_f16_f16; + std::string proc_mul_mat_f16_f16_vec; + std::string proc_mul_mat_q4_0_f32; + std::string proc_mul_mat_q4_0_f32_vec; + + std::vector mul_mat_constants; +#ifndef __EMSCRIPTEN__ if (webgpu_ctx->supports_subgroup_matrix) { std::map sg_matrix_repls; sg_matrix_repls["WEBGPU_MAX_SUBGROUP_SIZE"] = std::to_string(webgpu_ctx->subgroup_size); @@ -1770,100 +1818,57 @@ static void ggml_webgpu_init_mul_mat_pipeline(webgpu_context & webgpu_ctx) { sg_matrix_repls["WEBGPU_SG_MAT_N_SIZE"] = std::to_string(webgpu_ctx->subgroup_matrix_config.N); sg_matrix_repls["WEBGPU_SG_MAT_K_SIZE"] = std::to_string(webgpu_ctx->subgroup_matrix_config.K); - std::string proc_mul_mat_subgroup_matrix_f32_f32 = - ggml_webgpu_process_shader_repls(wgsl_mul_mat_subgroup_matrix_f32_f32, sg_matrix_repls); - std::string proc_mul_mat_subgroup_matrix_f32_f32_vec = + proc_mul_mat_f32_f32 = ggml_webgpu_process_shader_repls(wgsl_mul_mat_subgroup_matrix_f32_f32, sg_matrix_repls); + proc_mul_mat_f32_f32_vec = ggml_webgpu_process_shader_repls(wgsl_mul_mat_subgroup_matrix_f32_f32_vec, sg_matrix_repls); - std::string proc_mul_mat_subgroup_matrix_f16_f32 = - ggml_webgpu_process_shader_repls(wgsl_mul_mat_subgroup_matrix_f16_f32, sg_matrix_repls); - std::string proc_mul_mat_subgroup_matrix_f16_f32_vec = + proc_mul_mat_f16_f32 = ggml_webgpu_process_shader_repls(wgsl_mul_mat_subgroup_matrix_f16_f32, sg_matrix_repls); + proc_mul_mat_f16_f32_vec = ggml_webgpu_process_shader_repls(wgsl_mul_mat_subgroup_matrix_f16_f32_vec, sg_matrix_repls); - std::string proc_mul_mat_subgroup_matrix_f16_f16 = - ggml_webgpu_process_shader_repls(wgsl_mul_mat_subgroup_matrix_f16_f16, sg_matrix_repls); - std::string proc_mul_mat_subgroup_matrix_f16_f16_vec = + proc_mul_mat_f16_f16 = ggml_webgpu_process_shader_repls(wgsl_mul_mat_subgroup_matrix_f16_f16, sg_matrix_repls); + proc_mul_mat_f16_f16_vec = ggml_webgpu_process_shader_repls(wgsl_mul_mat_subgroup_matrix_f16_f16_vec, sg_matrix_repls); - std::string proc_mul_mat_subgroup_matrix_q4_0_f32 = + proc_mul_mat_q4_0_f32 = ggml_webgpu_process_shader_repls(wgsl_mul_mat_subgroup_matrix_q4_0_f32, sg_matrix_repls); - std::string proc_mul_mat_subgroup_matrix_q4_0_f32_vec = + proc_mul_mat_q4_0_f32_vec = ggml_webgpu_process_shader_repls(wgsl_mul_mat_subgroup_matrix_q4_0_f32_vec, sg_matrix_repls); - - webgpu_ctx->mul_mat_pipelines[GGML_TYPE_F32][GGML_TYPE_F32][0] = ggml_webgpu_create_pipeline2( - webgpu_ctx->device, proc_mul_mat_subgroup_matrix_f32_f32.c_str(), "mul_mat_subgroup_matrix_f32_f32"); - webgpu_ctx->mul_mat_pipelines[GGML_TYPE_F32][GGML_TYPE_F32][1] = - ggml_webgpu_create_pipeline2(webgpu_ctx->device, proc_mul_mat_subgroup_matrix_f32_f32_vec.c_str(), - "mul_mat_subgroup_matrix_f32_f32_vec"); - webgpu_ctx->mul_mat_pipelines[GGML_TYPE_F16][GGML_TYPE_F32][0] = ggml_webgpu_create_pipeline2( - webgpu_ctx->device, proc_mul_mat_subgroup_matrix_f16_f32.c_str(), "mul_mat_subgroup_matrix_f16_f32"); - webgpu_ctx->mul_mat_pipelines[GGML_TYPE_F16][GGML_TYPE_F32][1] = - ggml_webgpu_create_pipeline2(webgpu_ctx->device, proc_mul_mat_subgroup_matrix_f16_f32_vec.c_str(), - "mul_mat_subgroup_matrix_f16_f32_vec"); - webgpu_ctx->mul_mat_pipelines[GGML_TYPE_F16][GGML_TYPE_F16][0] = ggml_webgpu_create_pipeline2( - webgpu_ctx->device, proc_mul_mat_subgroup_matrix_f16_f16.c_str(), "mul_mat_subgroup_matrix_f16_f16"); - webgpu_ctx->mul_mat_pipelines[GGML_TYPE_F16][GGML_TYPE_F16][1] = - ggml_webgpu_create_pipeline2(webgpu_ctx->device, proc_mul_mat_subgroup_matrix_f16_f16_vec.c_str(), - "mul_mat_subgroup_matrix_f16_f16_vec"); - webgpu_ctx->mul_mat_pipelines[GGML_TYPE_Q4_0][GGML_TYPE_F32][0] = ggml_webgpu_create_pipeline2( - webgpu_ctx->device, proc_mul_mat_subgroup_matrix_q4_0_f32.c_str(), "mul_mat_subgroup_matrix_q4_0_f32"); - webgpu_ctx->mul_mat_pipelines[GGML_TYPE_Q4_0][GGML_TYPE_F32][1] = - ggml_webgpu_create_pipeline2(webgpu_ctx->device, proc_mul_mat_subgroup_matrix_q4_0_f32_vec.c_str(), - "mul_mat_subgroup_matrix_q4_0_f32_vec"); } else { - std::vector mul_mat_reg_tile_constants(3); - mul_mat_reg_tile_constants[0].key = "TILE_K"; - mul_mat_reg_tile_constants[0].value = WEBGPU_MUL_MAT_TILE_K; - mul_mat_reg_tile_constants[1].key = "WORKGROUP_SIZE_M"; - mul_mat_reg_tile_constants[1].value = WEBGPU_MUL_MAT_WG_SIZE_M; - mul_mat_reg_tile_constants[2].key = "WORKGROUP_SIZE_N"; - mul_mat_reg_tile_constants[2].value = WEBGPU_MUL_MAT_WG_SIZE_N; +#endif + mul_mat_constants.push_back({ .key = "TILE_K", .value = WEBGPU_MUL_MAT_TILE_K }); + mul_mat_constants.push_back({ .key = "WORKGROUP_SIZE_M", .value = WEBGPU_MUL_MAT_WG_SIZE_M }); + mul_mat_constants.push_back({ .key = "WORKGROUP_SIZE_N", .value = WEBGPU_MUL_MAT_WG_SIZE_N }); std::map reg_repls; reg_repls["WEBGPU_TILE_M"] = std::to_string(WEBGPU_MUL_MAT_TILE_M); reg_repls["WEBGPU_TILE_N"] = std::to_string(WEBGPU_MUL_MAT_TILE_N); - // Process each reg-tile shader with tile replacements. - // Keep the processed strings in-scope so .c_str() remains valid. - std::string proc_mul_mat_reg_tile_f32_f32 = - ggml_webgpu_process_shader_repls(wgsl_mul_mat_reg_tile_f32_f32, reg_repls); - std::string proc_mul_mat_reg_tile_f32_f32_vec = - ggml_webgpu_process_shader_repls(wgsl_mul_mat_reg_tile_f32_f32_vec, reg_repls); - std::string proc_mul_mat_reg_tile_f16_f32 = - ggml_webgpu_process_shader_repls(wgsl_mul_mat_reg_tile_f16_f32, reg_repls); - std::string proc_mul_mat_reg_tile_f16_f32_vec = - ggml_webgpu_process_shader_repls(wgsl_mul_mat_reg_tile_f16_f32_vec, reg_repls); - std::string proc_mul_mat_reg_tile_f16_f16 = - ggml_webgpu_process_shader_repls(wgsl_mul_mat_reg_tile_f16_f16, reg_repls); - std::string proc_mul_mat_reg_tile_f16_f16_vec = - ggml_webgpu_process_shader_repls(wgsl_mul_mat_reg_tile_f16_f16_vec, reg_repls); - std::string proc_mul_mat_reg_tile_q4_0_f32 = - ggml_webgpu_process_shader_repls(wgsl_mul_mat_reg_tile_q4_0_f32, reg_repls); - std::string proc_mul_mat_reg_tile_q4_0_f32_vec = - ggml_webgpu_process_shader_repls(wgsl_mul_mat_reg_tile_q4_0_f32_vec, reg_repls); - - webgpu_ctx->mul_mat_pipelines[GGML_TYPE_F32][GGML_TYPE_F32][0] = - ggml_webgpu_create_pipeline2(webgpu_ctx->device, proc_mul_mat_reg_tile_f32_f32.c_str(), - "mul_mat_reg_tile_f32_f32", mul_mat_reg_tile_constants); - webgpu_ctx->mul_mat_pipelines[GGML_TYPE_F32][GGML_TYPE_F32][1] = - ggml_webgpu_create_pipeline2(webgpu_ctx->device, proc_mul_mat_reg_tile_f32_f32_vec.c_str(), - "mul_mat_reg_tile_f32_f32_vec", mul_mat_reg_tile_constants); - webgpu_ctx->mul_mat_pipelines[GGML_TYPE_F16][GGML_TYPE_F32][0] = - ggml_webgpu_create_pipeline2(webgpu_ctx->device, proc_mul_mat_reg_tile_f16_f32.c_str(), - "mul_mat_reg_tile_f16_f32", mul_mat_reg_tile_constants); - webgpu_ctx->mul_mat_pipelines[GGML_TYPE_F16][GGML_TYPE_F32][1] = - ggml_webgpu_create_pipeline2(webgpu_ctx->device, proc_mul_mat_reg_tile_f16_f32_vec.c_str(), - "mul_mat_reg_tile_f16_f32_vec", mul_mat_reg_tile_constants); - webgpu_ctx->mul_mat_pipelines[GGML_TYPE_F16][GGML_TYPE_F16][0] = - ggml_webgpu_create_pipeline2(webgpu_ctx->device, proc_mul_mat_reg_tile_f16_f16.c_str(), - "mul_mat_reg_tile_f16_f16", mul_mat_reg_tile_constants); - webgpu_ctx->mul_mat_pipelines[GGML_TYPE_F16][GGML_TYPE_F16][1] = - ggml_webgpu_create_pipeline2(webgpu_ctx->device, proc_mul_mat_reg_tile_f16_f16_vec.c_str(), - "mul_mat_reg_tile_f16_f16_vec", mul_mat_reg_tile_constants); - webgpu_ctx->mul_mat_pipelines[GGML_TYPE_Q4_0][GGML_TYPE_F32][0] = - ggml_webgpu_create_pipeline2(webgpu_ctx->device, proc_mul_mat_reg_tile_q4_0_f32.c_str(), - "mul_mat_reg_tile_q4_0_f32", mul_mat_reg_tile_constants); - webgpu_ctx->mul_mat_pipelines[GGML_TYPE_Q4_0][GGML_TYPE_F32][1] = - ggml_webgpu_create_pipeline2(webgpu_ctx->device, proc_mul_mat_reg_tile_q4_0_f32_vec.c_str(), - "mul_mat_reg_tile_q4_0_f32_vec", mul_mat_reg_tile_constants); + proc_mul_mat_f32_f32 = ggml_webgpu_process_shader_repls(wgsl_mul_mat_reg_tile_f32_f32, reg_repls); + proc_mul_mat_f32_f32_vec = ggml_webgpu_process_shader_repls(wgsl_mul_mat_reg_tile_f32_f32_vec, reg_repls); + proc_mul_mat_f16_f32 = ggml_webgpu_process_shader_repls(wgsl_mul_mat_reg_tile_f16_f32, reg_repls); + proc_mul_mat_f16_f32_vec = ggml_webgpu_process_shader_repls(wgsl_mul_mat_reg_tile_f16_f32_vec, reg_repls); + proc_mul_mat_f16_f16 = ggml_webgpu_process_shader_repls(wgsl_mul_mat_reg_tile_f16_f16, reg_repls); + proc_mul_mat_f16_f16_vec = ggml_webgpu_process_shader_repls(wgsl_mul_mat_reg_tile_f16_f16_vec, reg_repls); + proc_mul_mat_q4_0_f32 = ggml_webgpu_process_shader_repls(wgsl_mul_mat_reg_tile_q4_0_f32, reg_repls); + proc_mul_mat_q4_0_f32_vec = ggml_webgpu_process_shader_repls(wgsl_mul_mat_reg_tile_q4_0_f32_vec, reg_repls); +#ifndef __EMSCRIPTEN__ } +#endif + + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_F32][GGML_TYPE_F32][0] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, proc_mul_mat_f32_f32.c_str(), "mul_mat_f32_f32", mul_mat_constants); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_F32][GGML_TYPE_F32][1] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, proc_mul_mat_f32_f32_vec.c_str(), "mul_mat_f32_f32_vec", mul_mat_constants); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_F16][GGML_TYPE_F32][0] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, proc_mul_mat_f16_f32.c_str(), "mul_mat_f16_f32", mul_mat_constants); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_F16][GGML_TYPE_F32][1] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, proc_mul_mat_f16_f32_vec.c_str(), "mul_mat_f16_f32_vec", mul_mat_constants); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_F16][GGML_TYPE_F16][0] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, proc_mul_mat_f16_f16.c_str(), "mul_mat_f16_f16", mul_mat_constants); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_F16][GGML_TYPE_F16][1] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, proc_mul_mat_f16_f16_vec.c_str(), "mul_mat_f16_f16_vec", mul_mat_constants); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_Q4_0][GGML_TYPE_F32][0] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, proc_mul_mat_q4_0_f32.c_str(), "mul_mat_q4_0_f32", mul_mat_constants); + webgpu_ctx->mul_mat_pipelines[GGML_TYPE_Q4_0][GGML_TYPE_F32][1] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, proc_mul_mat_q4_0_f32_vec.c_str(), "mul_mat_q4_0_f32_vec", mul_mat_constants); std::vector mul_mat_vec_constants(3); mul_mat_vec_constants[0].key = "WORKGROUP_SIZE"; @@ -1873,257 +1878,444 @@ static void ggml_webgpu_init_mul_mat_pipeline(webgpu_context & webgpu_ctx) { mul_mat_vec_constants[2].key = "OUTPUTS_PER_WG"; mul_mat_vec_constants[2].value = WEBGPU_MUL_MAT_VEC_OUTPUTS_PER_WG; - webgpu_ctx->mul_mat_vec_pipelines[GGML_TYPE_F32][GGML_TYPE_F32][0] = ggml_webgpu_create_pipeline2( + webgpu_ctx->mul_mat_vec_pipelines[GGML_TYPE_F32][GGML_TYPE_F32][0] = ggml_webgpu_create_pipeline( webgpu_ctx->device, wgsl_mul_mat_vec_f32_f32, "mul_mat_vec_f32_f32", mul_mat_vec_constants); - webgpu_ctx->mul_mat_vec_pipelines[GGML_TYPE_F32][GGML_TYPE_F32][1] = ggml_webgpu_create_pipeline2( + webgpu_ctx->mul_mat_vec_pipelines[GGML_TYPE_F32][GGML_TYPE_F32][1] = ggml_webgpu_create_pipeline( webgpu_ctx->device, wgsl_mul_mat_vec_f32_f32_vec, "mul_mat_vec_f32_f32_vec", mul_mat_vec_constants); - webgpu_ctx->mul_mat_vec_pipelines[GGML_TYPE_F16][GGML_TYPE_F32][0] = ggml_webgpu_create_pipeline2( + webgpu_ctx->mul_mat_vec_pipelines[GGML_TYPE_F16][GGML_TYPE_F32][0] = ggml_webgpu_create_pipeline( webgpu_ctx->device, wgsl_mul_mat_vec_f16_f32, "mul_mat_vec_f16_f32", mul_mat_vec_constants); - webgpu_ctx->mul_mat_vec_pipelines[GGML_TYPE_F16][GGML_TYPE_F32][1] = ggml_webgpu_create_pipeline2( + webgpu_ctx->mul_mat_vec_pipelines[GGML_TYPE_F16][GGML_TYPE_F32][1] = ggml_webgpu_create_pipeline( webgpu_ctx->device, wgsl_mul_mat_vec_f16_f32_vec, "mul_mat_vec_f16_f32_vec", mul_mat_vec_constants); - webgpu_ctx->mul_mat_vec_pipelines[GGML_TYPE_F16][GGML_TYPE_F16][0] = ggml_webgpu_create_pipeline2( + webgpu_ctx->mul_mat_vec_pipelines[GGML_TYPE_F16][GGML_TYPE_F16][0] = ggml_webgpu_create_pipeline( webgpu_ctx->device, wgsl_mul_mat_vec_f16_f16, "mul_mat_vec_f16_f16", mul_mat_vec_constants); - webgpu_ctx->mul_mat_vec_pipelines[GGML_TYPE_F16][GGML_TYPE_F16][1] = ggml_webgpu_create_pipeline2( + webgpu_ctx->mul_mat_vec_pipelines[GGML_TYPE_F16][GGML_TYPE_F16][1] = ggml_webgpu_create_pipeline( webgpu_ctx->device, wgsl_mul_mat_vec_f16_f16_vec, "mul_mat_vec_f16_f16_vec", mul_mat_vec_constants); - webgpu_ctx->mul_mat_vec_pipelines[GGML_TYPE_Q4_0][GGML_TYPE_F32][0] = ggml_webgpu_create_pipeline2( + webgpu_ctx->mul_mat_vec_pipelines[GGML_TYPE_Q4_0][GGML_TYPE_F32][0] = ggml_webgpu_create_pipeline( webgpu_ctx->device, wgsl_mul_mat_vec_q4_0_f32, "mul_mat_vec_q4_0_f32", mul_mat_vec_constants); } static void ggml_webgpu_init_set_rows_pipeline(webgpu_context & webgpu_ctx) { - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->set_rows_pipeline[0][0], wgsl_set_rows_f16, - "set_rows_f16", ggml_webgpu_wg_size_entry(webgpu_ctx->max_wg_size_x)); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->set_rows_pipeline[0][1], wgsl_set_rows_f16_vec, - "set_rows_f16_vec", ggml_webgpu_wg_size_entry(webgpu_ctx->max_wg_size_x)); + webgpu_ctx->set_rows_pipelines[0][0] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, wgsl_set_rows_f16, "set_rows_f16", ggml_webgpu_wg_size_entry(WEBGPU_MAX_WG_SIZE)); + webgpu_ctx->set_rows_pipelines[0][1] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, wgsl_set_rows_f16_vec, "set_rows_f16_vec", ggml_webgpu_wg_size_entry(WEBGPU_MAX_WG_SIZE)); } static void ggml_webgpu_init_get_rows_pipeline(webgpu_context & webgpu_ctx) { - std::vector constants = ggml_webgpu_wg_size_entry(webgpu_ctx->max_wg_size_x); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_F32], wgsl_get_rows_f32_vec, - "get_rows_f32_vec", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_f32_no_vec_pipeline, wgsl_get_rows_f32, - "get_rows_f32", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_F16], wgsl_get_rows_f16, - "get_rows_f16", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_I32], wgsl_get_rows_i32, - "get_rows_i32", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_Q4_0], wgsl_get_rows_q4_0, - "get_rows_q4_0", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_Q4_1], wgsl_get_rows_q4_1, - "get_rows_q4_1", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_Q5_0], wgsl_get_rows_q5_0, - "get_rows_q5_0", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_Q5_1], wgsl_get_rows_q5_1, - "get_rows_q5_1", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_Q8_0], wgsl_get_rows_q8_0, - "get_rows_q8_0", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_Q2_K], wgsl_get_rows_q2_k, - "get_rows_q2_k", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_Q3_K], wgsl_get_rows_q3_k, - "get_rows_q3_k", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_Q4_K], wgsl_get_rows_q4_k, - "get_rows_q4_k", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_Q5_K], wgsl_get_rows_q5_k, - "get_rows_q5_k", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_Q6_K], wgsl_get_rows_q6_k, - "get_rows_q6_k", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_IQ2_XXS], - wgsl_get_rows_iq2_xxs, "get_rows_iq2_xxs", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_IQ2_XS], - wgsl_get_rows_iq2_xs, "get_rows_iq2_xs", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_IQ2_S], wgsl_get_rows_iq2_s, - "get_rows_iq2_s", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_IQ3_XXS], - wgsl_get_rows_iq3_xxs, "get_rows_iq3_xxs", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_IQ3_S], wgsl_get_rows_iq3_s, - "get_rows_iq3_s", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_IQ1_S], wgsl_get_rows_iq1_s, - "get_rows_iq1_s", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_IQ1_M], wgsl_get_rows_iq1_m, - "get_rows_iq1_m", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_IQ4_NL], - wgsl_get_rows_iq4_nl, "get_rows_iq4_nl", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->get_rows_pipeline[GGML_TYPE_IQ4_XS], - wgsl_get_rows_iq4_xs, "get_rows_iq4_xs", constants); + std::vector constants = ggml_webgpu_wg_size_entry(WEBGPU_MAX_WG_SIZE); + + webgpu_ctx->get_rows_pipelines[GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_f32, "get_rows_f32", constants); + webgpu_ctx->get_rows_pipelines[GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_f32_vec, "get_rows_f32_vec", constants); + + webgpu_ctx->get_rows_pipelines[GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_f16, "get_rows_f16", constants); + webgpu_ctx->get_rows_pipelines[GGML_TYPE_I32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_i32, "get_rows_i32", constants); + webgpu_ctx->get_rows_pipelines[GGML_TYPE_Q4_0][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_q4_0, "get_rows_q4_0", constants); + webgpu_ctx->get_rows_pipelines[GGML_TYPE_Q4_1][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_q4_1, "get_rows_q4_1", constants); + webgpu_ctx->get_rows_pipelines[GGML_TYPE_Q5_0][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_q5_0, "get_rows_q5_0", constants); + webgpu_ctx->get_rows_pipelines[GGML_TYPE_Q5_1][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_q5_1, "get_rows_q5_1", constants); + webgpu_ctx->get_rows_pipelines[GGML_TYPE_Q8_0][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_q8_0, "get_rows_q8_0", constants); + + webgpu_ctx->get_rows_pipelines[GGML_TYPE_Q2_K][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_q2_k, "get_rows_q2_k", constants); + webgpu_ctx->get_rows_pipelines[GGML_TYPE_Q3_K][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_q3_k, "get_rows_q3_k", constants); + webgpu_ctx->get_rows_pipelines[GGML_TYPE_Q4_K][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_q4_k, "get_rows_q4_k", constants); + webgpu_ctx->get_rows_pipelines[GGML_TYPE_Q5_K][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_q5_k, "get_rows_q5_k", constants); + webgpu_ctx->get_rows_pipelines[GGML_TYPE_Q6_K][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_q6_k, "get_rows_q6_k", constants); + + webgpu_ctx->get_rows_pipelines[GGML_TYPE_IQ2_XXS][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_iq2_xxs, "get_rows_iq2_xxs", constants); + webgpu_ctx->get_rows_pipelines[GGML_TYPE_IQ2_XS][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_iq2_xs, "get_rows_iq2_xs", constants); + webgpu_ctx->get_rows_pipelines[GGML_TYPE_IQ2_S][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_iq2_s, "get_rows_iq2_s", constants); + webgpu_ctx->get_rows_pipelines[GGML_TYPE_IQ3_XXS][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_iq3_xxs, "get_rows_iq3_xxs", constants); + webgpu_ctx->get_rows_pipelines[GGML_TYPE_IQ3_S][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_iq3_s, "get_rows_iq3_s", constants); + webgpu_ctx->get_rows_pipelines[GGML_TYPE_IQ1_S][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_iq1_s, "get_rows_iq1_s", constants); + webgpu_ctx->get_rows_pipelines[GGML_TYPE_IQ1_M][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_iq1_m, "get_rows_iq1_m", constants); + webgpu_ctx->get_rows_pipelines[GGML_TYPE_IQ4_NL][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_iq4_nl, "get_rows_iq4_nl", constants); + webgpu_ctx->get_rows_pipelines[GGML_TYPE_IQ4_XS][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_get_rows_iq4_xs, "get_rows_iq4_xs", constants); } static void ggml_webgpu_init_cpy_pipeline(webgpu_context & webgpu_ctx) { - std::vector constants = ggml_webgpu_wg_size_entry(webgpu_ctx->max_wg_size_x); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->cpy_pipeline[GGML_TYPE_F32][GGML_TYPE_F32], - wgsl_cpy_f32_f32, "cpy_f32_f32", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->cpy_pipeline[GGML_TYPE_F32][GGML_TYPE_F16], - wgsl_cpy_f32_f16, "cpy_f32_f16", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->cpy_pipeline[GGML_TYPE_F16][GGML_TYPE_F32], - wgsl_cpy_f16_f32, "cpy_f16_f32", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->cpy_pipeline[GGML_TYPE_F16][GGML_TYPE_F16], - wgsl_cpy_f16_f16, "cpy_f16_f16", constants); + std::vector constants = ggml_webgpu_wg_size_entry(WEBGPU_MAX_WG_SIZE); + + webgpu_ctx->cpy_pipelines[GGML_TYPE_F32][GGML_TYPE_F32] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_cpy_f32_f32, "cpy_f32_f32", constants); + webgpu_ctx->cpy_pipelines[GGML_TYPE_F32][GGML_TYPE_F16] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_cpy_f32_f16, "cpy_f32_f16", constants); + webgpu_ctx->cpy_pipelines[GGML_TYPE_F16][GGML_TYPE_F32] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_cpy_f16_f32, "cpy_f16_f32", constants); + webgpu_ctx->cpy_pipelines[GGML_TYPE_F16][GGML_TYPE_F16] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_cpy_f16_f16, "cpy_f16_f16", constants); } static void ggml_webgpu_init_add_pipeline(webgpu_context & webgpu_ctx) { - std::vector constants = ggml_webgpu_wg_size_entry(webgpu_ctx->max_wg_size_x); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->add_pipeline[GGML_TYPE_F32][0], wgsl_add_f32, "add_f32", - constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->add_pipeline[GGML_TYPE_F16][0], wgsl_add_f16, "add_f16", - constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->add_pipeline[GGML_TYPE_F32][1], wgsl_add_f32_inplace, - "add_f32_inplace", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->add_pipeline[GGML_TYPE_F16][1], wgsl_add_f16_inplace, - "add_f16_inplace", constants); + std::vector constants = ggml_webgpu_wg_size_entry(WEBGPU_MAX_WG_SIZE); + + webgpu_ctx->add_pipelines[GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_add_f32, "add_f32", constants); + webgpu_ctx->add_pipelines[GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_add_f16, "add_f16", constants); + webgpu_ctx->add_pipelines[GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_add_f32_inplace, "add_f32_inplace", constants); + webgpu_ctx->add_pipelines[GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_add_f16_inplace, "add_f16_inplace", constants); } static void ggml_webgpu_init_sub_pipeline(webgpu_context & webgpu_ctx) { - std::vector constants = ggml_webgpu_wg_size_entry(webgpu_ctx->max_wg_size_x); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->sub_pipeline[GGML_TYPE_F32][0], wgsl_sub_f32, "sub_f32", - constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->sub_pipeline[GGML_TYPE_F16][0], wgsl_sub_f16, "sub_f16", - constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->sub_pipeline[GGML_TYPE_F32][1], wgsl_sub_f32_inplace, - "sub_f32_inplace", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->sub_pipeline[GGML_TYPE_F16][1], wgsl_sub_f16_inplace, - "sub_f16_inplace", constants); + std::vector constants = ggml_webgpu_wg_size_entry(WEBGPU_MAX_WG_SIZE); + + webgpu_ctx->sub_pipelines[GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_sub_f32, "sub_f32", constants); + webgpu_ctx->sub_pipelines[GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_sub_f16, "sub_f16", constants); + webgpu_ctx->sub_pipelines[GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_sub_f32_inplace, "sub_f32_inplace", constants); + webgpu_ctx->sub_pipelines[GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_sub_f16_inplace, "sub_f16_inplace", constants); } static void ggml_webgpu_init_mul_pipeline(webgpu_context & webgpu_ctx) { - std::vector constants = ggml_webgpu_wg_size_entry(webgpu_ctx->max_wg_size_x); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_pipeline[GGML_TYPE_F32][0], wgsl_mul_f32, "mul_f32", - constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_pipeline[GGML_TYPE_F16][0], wgsl_mul_f16, "mul_f16", - constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_pipeline[GGML_TYPE_F32][1], wgsl_mul_f32_inplace, - "mul_f32_inplace", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_pipeline[GGML_TYPE_F16][1], wgsl_mul_f16_inplace, - "mul_f16_inplace", constants); + std::vector constants = ggml_webgpu_wg_size_entry(WEBGPU_MAX_WG_SIZE); + + webgpu_ctx->mul_pipelines[GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_f32, "mul_f32", constants); + webgpu_ctx->mul_pipelines[GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_f16, "mul_f16", constants); + webgpu_ctx->mul_pipelines[GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_f32_inplace, "mul_f32_inplace", constants); + webgpu_ctx->mul_pipelines[GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_mul_f16_inplace, "mul_f16_inplace", constants); } static void ggml_webgpu_init_div_pipeline(webgpu_context & webgpu_ctx) { - std::vector constants = ggml_webgpu_wg_size_entry(webgpu_ctx->max_wg_size_x); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->div_pipeline[GGML_TYPE_F32][0], wgsl_div_f32, "div_f32", - constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->div_pipeline[GGML_TYPE_F16][0], wgsl_div_f16, "div_f16", - constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->div_pipeline[GGML_TYPE_F32][1], wgsl_div_f32_inplace, - "div_f32_inplace", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->div_pipeline[GGML_TYPE_F16][1], wgsl_div_f16_inplace, - "div_f16_inplace", constants); + std::vector constants = ggml_webgpu_wg_size_entry(WEBGPU_MAX_WG_SIZE); + + webgpu_ctx->div_pipelines[GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_div_f32, "div_f32", constants); + webgpu_ctx->div_pipelines[GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_div_f16, "div_f16", constants); + webgpu_ctx->div_pipelines[GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_div_f32_inplace, "div_f32_inplace", constants); + webgpu_ctx->div_pipelines[GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_div_f16_inplace, "div_f16_inplace", constants); } static void ggml_webgpu_init_rms_norm_pipeline(webgpu_context & webgpu_ctx) { std::vector constants = ggml_webgpu_wg_size_entry(WEBGPU_ROW_SPLIT_WG_SIZE); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->rms_norm_pipeline[0], wgsl_rms_norm, "rms_norm", - constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->rms_norm_pipeline[1], wgsl_rms_norm_inplace, - "rms_norm_inplace", constants); + + webgpu_ctx->rms_norm_pipelines[0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_rms_norm, "rms_norm", constants); + webgpu_ctx->rms_norm_pipelines[1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_rms_norm_inplace, "rms_norm_inplace", constants); } static void ggml_webgpu_init_rope_pipeline(webgpu_context & webgpu_ctx) { - std::vector constants = ggml_webgpu_wg_size_entry(webgpu_ctx->max_wg_size_x); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->rope_pipeline[GGML_TYPE_F32][0][0], wgsl_rope_f32, - "rope_f32", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->rope_pipeline[GGML_TYPE_F32][0][1], - wgsl_rope_f32_inplace, "rope_f32_inplace", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->rope_pipeline[GGML_TYPE_F32][1][0], wgsl_rope_f32_ff, - "rope_f32_ff", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->rope_pipeline[GGML_TYPE_F32][1][1], - wgsl_rope_f32_ff_inplace, "rope_f32_ff_inplace", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->rope_pipeline[GGML_TYPE_F16][0][0], wgsl_rope_f16, - "rope_f16", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->rope_pipeline[GGML_TYPE_F16][0][1], - wgsl_rope_f16_inplace, "rope_f16_inplace", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->rope_pipeline[GGML_TYPE_F16][1][0], wgsl_rope_f16_ff, - "rope_f16_ff", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->rope_pipeline[GGML_TYPE_F16][1][1], - wgsl_rope_f16_ff_inplace, "rope_f16_ff_inplace", constants); + std::vector constants = ggml_webgpu_wg_size_entry(WEBGPU_MAX_WG_SIZE); + + webgpu_ctx->rope_pipelines[GGML_TYPE_F32][0][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_rope_f32, "rope_f32", constants); + webgpu_ctx->rope_pipelines[GGML_TYPE_F32][0][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_rope_f32_inplace, "rope_f32_inplace", constants); + webgpu_ctx->rope_pipelines[GGML_TYPE_F32][1][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_rope_f32_ff, "rope_f32_ff", constants); + webgpu_ctx->rope_pipelines[GGML_TYPE_F32][1][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_rope_f32_ff_inplace, "rope_f32_ff_inplace", constants); + + webgpu_ctx->rope_pipelines[GGML_TYPE_F16][0][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_rope_f16, "rope_f16", constants); + webgpu_ctx->rope_pipelines[GGML_TYPE_F16][0][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_rope_f16_inplace, "rope_f16_inplace", constants); + webgpu_ctx->rope_pipelines[GGML_TYPE_F16][1][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_rope_f16_ff, "rope_f16_ff", constants); + webgpu_ctx->rope_pipelines[GGML_TYPE_F16][1][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_rope_f16_ff_inplace, "rope_f16_ff_inplace", constants); } static void ggml_webgpu_init_glu_pipeline(webgpu_context & webgpu_ctx) { - std::vector constants = ggml_webgpu_wg_size_entry(webgpu_ctx->max_wg_size_x); - // reglu - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_REGLU][GGML_TYPE_F32][0], - wgsl_reglu_f32, "reglu_f32", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_REGLU][GGML_TYPE_F16][0], - wgsl_reglu_f16, "reglu_f16", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_REGLU][GGML_TYPE_F32][1], - wgsl_reglu_f32_split, "reglu_f32_split", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_REGLU][GGML_TYPE_F16][1], - wgsl_reglu_f16_split, "reglu_f16_split", constants); - // geglu - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_GEGLU][GGML_TYPE_F32][0], - wgsl_geglu_f32, "geglu_f32", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_GEGLU][GGML_TYPE_F16][0], - wgsl_geglu_f16, "geglu_f16", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_GEGLU][GGML_TYPE_F32][1], - wgsl_geglu_f32_split, "geglu_f32_split", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_GEGLU][GGML_TYPE_F16][1], - wgsl_geglu_f16_split, "geglu_f16_split", constants); - // swiglu - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_SWIGLU][GGML_TYPE_F32][0], - wgsl_swiglu_f32, "swiglu_f32", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_SWIGLU][GGML_TYPE_F16][0], - wgsl_swiglu_f16, "swiglu_f16", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_SWIGLU][GGML_TYPE_F32][1], - wgsl_swiglu_f32_split, "swiglu_f32_split", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_SWIGLU][GGML_TYPE_F16][1], - wgsl_swiglu_f16_split, "swiglu_f16_split", constants); - // swiglu_oai - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_SWIGLU_OAI][GGML_TYPE_F32][0], - wgsl_swiglu_oai_f32, "swiglu_oai_f32", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_SWIGLU_OAI][GGML_TYPE_F32][1], - wgsl_swiglu_oai_f32_split, "swiglu_oai_f32_split", constants); - // geglu_erf - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_GEGLU_ERF][GGML_TYPE_F32][0], - wgsl_geglu_erf_f32, "geglu_erf_f32", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_GEGLU_ERF][GGML_TYPE_F16][0], - wgsl_geglu_erf_f16, "geglu_erf_f16", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_GEGLU_ERF][GGML_TYPE_F32][1], - wgsl_geglu_erf_f32_split, "geglu_erf_f32_split", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_GEGLU_ERF][GGML_TYPE_F16][1], - wgsl_geglu_erf_f16_split, "geglu_erf_f16_split", constants); - // geglu_quick - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_GEGLU_QUICK][GGML_TYPE_F32][0], - wgsl_geglu_quick_f32, "geglu_quick_f32", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_GEGLU_QUICK][GGML_TYPE_F16][0], - wgsl_geglu_quick_f16, "geglu_quick_f16", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_GEGLU_QUICK][GGML_TYPE_F32][1], - wgsl_geglu_quick_f32_split, "geglu_quick_f32_split", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->glu_pipeline[GGML_GLU_OP_GEGLU_QUICK][GGML_TYPE_F16][1], - wgsl_geglu_quick_f16_split, "geglu_quick_f16_split", constants); + std::vector constants = ggml_webgpu_wg_size_entry(WEBGPU_MAX_WG_SIZE); + + // REGLU + webgpu_ctx->glu_pipelines[GGML_GLU_OP_REGLU][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_reglu_f32, "reglu_f32", constants); + webgpu_ctx->glu_pipelines[GGML_GLU_OP_REGLU][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_reglu_f16, "reglu_f16", constants); + webgpu_ctx->glu_pipelines[GGML_GLU_OP_REGLU][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_reglu_f32_split, "reglu_f32_split", constants); + webgpu_ctx->glu_pipelines[GGML_GLU_OP_REGLU][GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_reglu_f16_split, "reglu_f16_split", constants); + + // GEGLU + webgpu_ctx->glu_pipelines[GGML_GLU_OP_GEGLU][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_geglu_f32, "geglu_f32", constants); + webgpu_ctx->glu_pipelines[GGML_GLU_OP_GEGLU][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_geglu_f16, "geglu_f16", constants); + webgpu_ctx->glu_pipelines[GGML_GLU_OP_GEGLU][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_geglu_f32_split, "geglu_f32_split", constants); + webgpu_ctx->glu_pipelines[GGML_GLU_OP_GEGLU][GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_geglu_f16_split, "geglu_f16_split", constants); + + // SWIGLU + webgpu_ctx->glu_pipelines[GGML_GLU_OP_SWIGLU][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_swiglu_f32, "swiglu_f32", constants); + webgpu_ctx->glu_pipelines[GGML_GLU_OP_SWIGLU][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_swiglu_f16, "swiglu_f16", constants); + webgpu_ctx->glu_pipelines[GGML_GLU_OP_SWIGLU][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_swiglu_f32_split, "swiglu_f32_split", constants); + webgpu_ctx->glu_pipelines[GGML_GLU_OP_SWIGLU][GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_swiglu_f16_split, "swiglu_f16_split", constants); + + // SWIGLU_OAI + webgpu_ctx->glu_pipelines[GGML_GLU_OP_SWIGLU_OAI][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_swiglu_oai_f32, "swiglu_oai_f32", constants); + webgpu_ctx->glu_pipelines[GGML_GLU_OP_SWIGLU_OAI][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_swiglu_oai_f32_split, "swiglu_oai_f32_split", constants); + + // GEGLU_ERF + webgpu_ctx->glu_pipelines[GGML_GLU_OP_GEGLU_ERF][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_geglu_erf_f32, "geglu_erf_f32", constants); + webgpu_ctx->glu_pipelines[GGML_GLU_OP_GEGLU_ERF][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_geglu_erf_f16, "geglu_erf_f16", constants); + webgpu_ctx->glu_pipelines[GGML_GLU_OP_GEGLU_ERF][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_geglu_erf_f32_split, "geglu_erf_f32_split", constants); + webgpu_ctx->glu_pipelines[GGML_GLU_OP_GEGLU_ERF][GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_geglu_erf_f16_split, "geglu_erf_f16_split", constants); + + // GEGLU_QUICK + webgpu_ctx->glu_pipelines[GGML_GLU_OP_GEGLU_QUICK][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_geglu_quick_f32, "geglu_quick_f32", constants); + webgpu_ctx->glu_pipelines[GGML_GLU_OP_GEGLU_QUICK][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_geglu_quick_f16, "geglu_quick_f16", constants); + webgpu_ctx->glu_pipelines[GGML_GLU_OP_GEGLU_QUICK][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_geglu_quick_f32_split, "geglu_quick_f32_split", constants); + webgpu_ctx->glu_pipelines[GGML_GLU_OP_GEGLU_QUICK][GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_geglu_quick_f16_split, "geglu_quick_f16_split", constants); +} + +static void ggml_webgpu_init_unary_pipeline(webgpu_context & webgpu_ctx) { + std::vector constants = ggml_webgpu_wg_size_entry(WEBGPU_MAX_WG_SIZE); + + // ABS + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_ABS][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_abs_f32, "abs_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_ABS][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_abs_f16, "abs_f16", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_ABS][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_abs_inplace_f32, "abs_inplace_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_ABS][GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_abs_inplace_f16, "abs_inplace_f16", constants); + + // SGN + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_SGN][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_sgn_f32, "sgn_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_SGN][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_sgn_f16, "sgn_f16", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_SGN][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_sgn_inplace_f32, "sgn_inplace_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_SGN][GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_sgn_inplace_f16, "sgn_inplace_f16", constants); + + // NEG + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_NEG][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_neg_f32, "neg_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_NEG][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_neg_f16, "neg_f16", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_NEG][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_neg_inplace_f32, "neg_inplace_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_NEG][GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_neg_inplace_f16, "neg_inplace_f16", constants); + + // STEP + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_STEP][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_step_f32, "step_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_STEP][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_step_f16, "step_f16", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_STEP][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_step_inplace_f32, "step_inplace_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_STEP][GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_step_inplace_f16, "step_inplace_f16", constants); + + // TANH + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_TANH][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_tanh_f32, "tanh_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_TANH][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_tanh_f16, "tanh_f16", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_TANH][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_tanh_inplace_f32, "tanh_inplace_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_TANH][GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_tanh_inplace_f16, "tanh_inplace_f16", constants); + + // ELU + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_ELU][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_elu_f32, "elu_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_ELU][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_elu_f16, "elu_f16", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_ELU][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_elu_inplace_f32, "elu_inplace_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_ELU][GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_elu_inplace_f16, "elu_inplace_f16", constants); + + // RELU + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_RELU][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_relu_f32, "relu_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_RELU][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_relu_f16, "relu_f16", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_RELU][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_relu_inplace_f32, "relu_inplace_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_RELU][GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_relu_inplace_f16, "relu_inplace_f16", constants); + + // SIGMOID + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_SIGMOID][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_sigmoid_f32, "sigmoid_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_SIGMOID][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_sigmoid_f16, "sigmoid_f16", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_SIGMOID][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_sigmoid_inplace_f32, "sigmoid_inplace_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_SIGMOID][GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_sigmoid_inplace_f16, "sigmoid_inplace_f16", constants); + + // GELU + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_GELU][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_gelu_f32, "gelu_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_GELU][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_gelu_f16, "gelu_f16", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_GELU][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_gelu_inplace_f32, "gelu_inplace_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_GELU][GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_gelu_inplace_f16, "gelu_inplace_f16", constants); + + // GELU_QUICK + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_GELU_QUICK][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_gelu_quick_f32, "gelu_quick_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_GELU_QUICK][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_gelu_quick_f16, "gelu_quick_f16", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_GELU_QUICK][GGML_TYPE_F32][1] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, wgsl_gelu_quick_inplace_f32, "gelu_quick_inplace_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_GELU_QUICK][GGML_TYPE_F16][1] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, wgsl_gelu_quick_inplace_f16, "gelu_quick_inplace_f16", constants); + + // SILU + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_SILU][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_silu_f32, "silu_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_SILU][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_silu_f16, "silu_f16", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_SILU][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_silu_inplace_f32, "silu_inplace_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_SILU][GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_silu_inplace_f16, "silu_inplace_f16", constants); + + // HARDSWISH + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_HARDSWISH][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_hardswish_f32, "hardswish_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_HARDSWISH][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_hardswish_f16, "hardswish_f16", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_HARDSWISH][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_hardswish_inplace_f32, "hardswish_inplace_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_HARDSWISH][GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_hardswish_inplace_f16, "hardswish_inplace_f16", constants); + + // HARDSIGMOID + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_HARDSIGMOID][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_hardsigmoid_f32, "hardsigmoid_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_HARDSIGMOID][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_hardsigmoid_f16, "hardsigmoid_f16", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_HARDSIGMOID][GGML_TYPE_F32][1] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, wgsl_hardsigmoid_inplace_f32, "hardsigmoid_inplace_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_HARDSIGMOID][GGML_TYPE_F16][1] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, wgsl_hardsigmoid_inplace_f16, "hardsigmoid_inplace_f16", constants); + + // EXP + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_EXP][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_exp_f32, "exp_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_EXP][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_exp_f16, "exp_f16", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_EXP][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_exp_inplace_f32, "exp_inplace_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_EXP][GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_exp_inplace_f16, "exp_inplace_f16", constants); + + // GELU_ERF + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_GELU_ERF][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_gelu_erf_f32, "gelu_erf_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_GELU_ERF][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_gelu_erf_f16, "gelu_erf_f16", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_GELU_ERF][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_gelu_erf_inplace_f32, "gelu_erf_inplace_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_GELU_ERF][GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_gelu_erf_inplace_f16, "gelu_erf_inplace_f16", constants); + + // XIELU + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_XIELU][GGML_TYPE_F32][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_xielu_f32, "xielu_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_XIELU][GGML_TYPE_F16][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_xielu_f16, "xielu_f16", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_XIELU][GGML_TYPE_F32][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_xielu_inplace_f32, "xielu_inplace_f32", constants); + webgpu_ctx->unary_pipelines[GGML_UNARY_OP_XIELU][GGML_TYPE_F16][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_xielu_inplace_f16, "xielu_inplace_f16", constants); } static void ggml_webgpu_init_scale_pipeline(webgpu_context & webgpu_ctx) { - std::vector constants = ggml_webgpu_wg_size_entry(webgpu_ctx->max_wg_size_x); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->scale_pipeline[0], wgsl_scale_f32, "scale_f32", - constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->scale_pipeline[1], wgsl_scale_f32_inplace, - "scale_f32_inplace", constants); + std::vector constants = ggml_webgpu_wg_size_entry(WEBGPU_MAX_WG_SIZE); + + webgpu_ctx->scale_pipelines[0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_scale_f32, "scale_f32", constants); + webgpu_ctx->scale_pipelines[1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_scale_f32_inplace, "scale_f32_inplace", constants); } static void ggml_webgpu_init_soft_max_pipeline(webgpu_context & webgpu_ctx) { std::vector constants = ggml_webgpu_wg_size_entry(WEBGPU_ROW_SPLIT_WG_SIZE); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->soft_max_pipeline[2][0][0], wgsl_soft_max_f32, - "soft_max_f32", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->soft_max_pipeline[2][0][1], wgsl_soft_max_f32_inplace, - "soft_max_f32_inplace", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->soft_max_pipeline[2][1][0], wgsl_soft_max_f32_sink, - "soft_max_f32_sink", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->soft_max_pipeline[2][1][1], - wgsl_soft_max_f32_sink_inplace, "soft_max_f32_sink_inplace", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->soft_max_pipeline[0][0][0], wgsl_soft_max_f32_mask_f32, - "soft_max_f32_mask_f32", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->soft_max_pipeline[0][0][1], - wgsl_soft_max_f32_mask_f32_inplace, "soft_max_f32_mask_f32_inplace", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->soft_max_pipeline[1][0][0], wgsl_soft_max_f32_mask_f16, - "soft_max_f32_mask_f16", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->soft_max_pipeline[1][0][1], - wgsl_soft_max_f32_mask_f16_inplace, "soft_max_f32_mask_f16_inplace", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->soft_max_pipeline[0][1][0], - wgsl_soft_max_f32_mask_f32_sink, "soft_max_f32_mask_f32_sink", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->soft_max_pipeline[0][1][1], - wgsl_soft_max_f32_mask_f32_sink_inplace, "soft_max_f32_mask_f32_sink_inplace", - constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->soft_max_pipeline[1][1][0], - wgsl_soft_max_f32_mask_f16_sink, "soft_max_f32_mask_f16_sink", constants); - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->soft_max_pipeline[1][1][1], - wgsl_soft_max_f32_mask_f16_sink_inplace, "soft_max_f32_mask_f16_sink_inplace", - constants); + + // f32 (no mask) + webgpu_ctx->soft_max_pipelines[2][0][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_soft_max_f32, "soft_max_f32", constants); + webgpu_ctx->soft_max_pipelines[2][0][1] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_soft_max_f32_inplace, "soft_max_f32_inplace", constants); + webgpu_ctx->soft_max_pipelines[2][1][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_soft_max_f32_sink, "soft_max_f32_sink", constants); + webgpu_ctx->soft_max_pipelines[2][1][1] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, wgsl_soft_max_f32_sink_inplace, "soft_max_f32_sink_inplace", constants); + + // f32 mask (mask_type = 0) + webgpu_ctx->soft_max_pipelines[0][0][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_soft_max_f32_mask_f32, "soft_max_f32_mask_f32", constants); + webgpu_ctx->soft_max_pipelines[0][0][1] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, wgsl_soft_max_f32_mask_f32_inplace, "soft_max_f32_mask_f32_inplace", constants); + webgpu_ctx->soft_max_pipelines[0][1][0] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, wgsl_soft_max_f32_mask_f32_sink, "soft_max_f32_mask_f32_sink", constants); + webgpu_ctx->soft_max_pipelines[0][1][1] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, wgsl_soft_max_f32_mask_f32_sink_inplace, "soft_max_f32_mask_f32_sink_inplace", constants); + + // f16 mask (mask_type = 1) + webgpu_ctx->soft_max_pipelines[1][0][0] = + ggml_webgpu_create_pipeline(webgpu_ctx->device, wgsl_soft_max_f32_mask_f16, "soft_max_f32_mask_f16", constants); + webgpu_ctx->soft_max_pipelines[1][0][1] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, wgsl_soft_max_f32_mask_f16_inplace, "soft_max_f32_mask_f16_inplace", constants); + webgpu_ctx->soft_max_pipelines[1][1][0] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, wgsl_soft_max_f32_mask_f16_sink, "soft_max_f32_mask_f16_sink", constants); + webgpu_ctx->soft_max_pipelines[1][1][1] = ggml_webgpu_create_pipeline( + webgpu_ctx->device, wgsl_soft_max_f32_mask_f16_sink_inplace, "soft_max_f32_mask_f16_sink_inplace", constants); } static ggml_backend_t ggml_backend_webgpu_device_init(ggml_backend_dev_t dev, const char * params) { @@ -2145,12 +2337,12 @@ static ggml_backend_t ggml_backend_webgpu_device_init(ggml_backend_dev_t dev, co /* .device = */ dev, /* .context = */ &backend_ctx, }; - return &backend; } static ggml_backend_buffer_type_t ggml_backend_webgpu_device_get_buffer_type(ggml_backend_dev_t dev) { // See GGML Backend Buffer Type Interface section + static struct ggml_backend_buffer_type ggml_backend_webgpu_buffer_type = { /* .iface = */ { /* .get_name = */ ggml_backend_webgpu_buffer_type_get_name, @@ -2315,6 +2507,36 @@ static bool ggml_backend_webgpu_device_supports_op(ggml_backend_dev_t dev, const case GGML_OP_SOFT_MAX: supports_op = op->type == GGML_TYPE_F32; break; + case GGML_OP_UNARY: + { + const ggml_unary_op UNARY_OP = ggml_get_unary_op(op); + + switch (UNARY_OP) { + case GGML_UNARY_OP_ABS: + case GGML_UNARY_OP_SGN: + case GGML_UNARY_OP_NEG: + case GGML_UNARY_OP_STEP: + case GGML_UNARY_OP_TANH: + case GGML_UNARY_OP_ELU: + case GGML_UNARY_OP_RELU: + case GGML_UNARY_OP_SIGMOID: + case GGML_UNARY_OP_GELU: + case GGML_UNARY_OP_GELU_QUICK: + case GGML_UNARY_OP_SILU: + case GGML_UNARY_OP_HARDSWISH: + case GGML_UNARY_OP_HARDSIGMOID: + case GGML_UNARY_OP_EXP: + case GGML_UNARY_OP_GELU_ERF: + case GGML_UNARY_OP_XIELU: + supports_op = supports_op = + (op->type == GGML_TYPE_F32 || op->type == GGML_TYPE_F16) && (src0->type == op->type); + break; + default: + break; + } + } + break; + default: break; } @@ -2384,13 +2606,17 @@ static ggml_backend_dev_t ggml_backend_webgpu_reg_get_device(ggml_backend_reg_t webgpu_context ctx = reg_ctx->webgpu_ctx; + wgpu::RequestAdapterOptions options = {}; + +#ifndef __EMSCRIPTEN__ // TODO: track need for these toggles: https://issues.chromium.org/issues/42251215 const char * const adapterEnabledToggles[] = { "vulkan_enable_f16_on_nvidia", "use_vulkan_memory_model" }; wgpu::DawnTogglesDescriptor adapterTogglesDesc; adapterTogglesDesc.enabledToggles = adapterEnabledToggles; adapterTogglesDesc.enabledToggleCount = 2; - wgpu::RequestAdapterOptions options = {}; options.nextInChain = &adapterTogglesDesc; +#endif + ctx->instance.WaitAny(ctx->instance.RequestAdapter( &options, wgpu::CallbackMode::AllowSpontaneous, [&ctx](wgpu::RequestAdapterStatus status, wgpu::Adapter adapter, const char * message) { @@ -2404,13 +2630,14 @@ static ggml_backend_dev_t ggml_backend_webgpu_reg_get_device(ggml_backend_reg_t GGML_ASSERT(ctx->adapter != nullptr); ctx->adapter.GetLimits(&ctx->limits); - ctx->max_wg_size_x = 288; // default value - wgpu::AdapterInfo info{}; + wgpu::AdapterInfo info{}; +#ifndef __EMSCRIPTEN__ wgpu::AdapterPropertiesSubgroupMatrixConfigs subgroup_matrix_configs{}; if (ctx->adapter.HasFeature(wgpu::FeatureName::ChromiumExperimentalSubgroupMatrix)) { info.nextInChain = &subgroup_matrix_configs; } +#endif ctx->adapter.GetInfo(&info); wgpu::SupportedFeatures features; @@ -2418,6 +2645,7 @@ static ggml_backend_dev_t ggml_backend_webgpu_reg_get_device(ggml_backend_reg_t // we require f16 support GGML_ASSERT(ctx->adapter.HasFeature(wgpu::FeatureName::ShaderF16)); +#ifndef __EMSCRIPTEN__ // Only support square f16 matrices of size 8 or 16 for now bool valid_subgroup_matrix_config = false; if (ctx->adapter.HasFeature(wgpu::FeatureName::ChromiumExperimentalSubgroupMatrix)) { @@ -2433,36 +2661,27 @@ static ggml_backend_dev_t ggml_backend_webgpu_reg_get_device(ggml_backend_reg_t } } + ctx->supports_subgroup_matrix = valid_subgroup_matrix_config; +#endif // For subgroup matrix code to be the most efficient, we would like the subgroup size to be consistent and accurate. // Unfortunately, that is not possible, so we use the maximum subgroup size reported by the adapter. - ctx->subgroup_size = info.subgroupMaxSize; - ctx->supports_subgroup_matrix = valid_subgroup_matrix_config; + ctx->subgroup_size = info.subgroupMaxSize; // Initialize device - std::vector required_features = { wgpu::FeatureName::ShaderF16, - wgpu::FeatureName::ImplicitDeviceSynchronization }; + std::vector required_features = { wgpu::FeatureName::ShaderF16 }; + +#ifndef __EMSCRIPTEN__ + required_features.push_back(wgpu::FeatureName::ImplicitDeviceSynchronization); if (ctx->supports_subgroup_matrix) { required_features.push_back(wgpu::FeatureName::Subgroups); required_features.push_back(wgpu::FeatureName::ChromiumExperimentalSubgroupMatrix); } +#endif #ifdef GGML_WEBGPU_GPU_PROFILE required_features.push_back(wgpu::FeatureName::TimestampQuery); #endif - // Enable Dawn-specific toggles to increase native performance - // TODO: Don't enable for WASM builds, they won't have an effect anyways - // TODO: Maybe WebGPU needs a "fast" mode where you can request compilers skip adding checks like these, - // only for native performance? - const char * const deviceEnabledToggles[] = { "skip_validation", "disable_robustness", "disable_workgroup_init", - "disable_polyfills_on_integer_div_and_mod" }; - const char * const deviceDisabledToggles[] = { "timestamp_quantization" }; - wgpu::DawnTogglesDescriptor deviceTogglesDesc; - deviceTogglesDesc.enabledToggles = deviceEnabledToggles; - deviceTogglesDesc.enabledToggleCount = 4; - deviceTogglesDesc.disabledToggles = deviceDisabledToggles; - deviceTogglesDesc.disabledToggleCount = 1; - wgpu::DeviceDescriptor dev_desc; dev_desc.requiredLimits = &ctx->limits; dev_desc.requiredFeatures = required_features.data(); @@ -2480,7 +2699,23 @@ static ggml_backend_dev_t ggml_backend_webgpu_reg_get_device(ggml_backend_reg_t GGML_ABORT("ggml_webgpu: Device error! Reason: %d, Message: %s\n", static_cast(reason), std::string(message).c_str()); }); + +#ifndef __EMSCRIPTEN__ + // Enable Dawn-specific toggles to increase native performance + // TODO: Maybe WebGPU needs a "fast" mode where you can request compilers skip adding checks like these, + // only for native performance? + const char * const deviceEnabledToggles[] = { "skip_validation", "disable_robustness", "disable_workgroup_init", + "disable_polyfills_on_integer_div_and_mod" }; + const char * const deviceDisabledToggles[] = { "timestamp_quantization" }; + wgpu::DawnTogglesDescriptor deviceTogglesDesc; + deviceTogglesDesc.enabledToggles = deviceEnabledToggles; + deviceTogglesDesc.enabledToggleCount = 4; + deviceTogglesDesc.disabledToggles = deviceDisabledToggles; + deviceTogglesDesc.disabledToggleCount = 1; + dev_desc.nextInChain = &deviceTogglesDesc; +#endif + ctx->instance.WaitAny(ctx->adapter.RequestDevice( &dev_desc, wgpu::CallbackMode::AllowSpontaneous, [ctx](wgpu::RequestDeviceStatus status, wgpu::Device device, wgpu::StringView message) { @@ -2528,6 +2763,7 @@ static ggml_backend_dev_t ggml_backend_webgpu_reg_get_device(ggml_backend_reg_t ggml_webgpu_init_glu_pipeline(ctx); ggml_webgpu_init_scale_pipeline(ctx); ggml_webgpu_init_soft_max_pipeline(ctx); + ggml_webgpu_init_unary_pipeline(ctx); #ifdef GGML_WEBGPU_DEBUG // Initialize debug buffers @@ -2578,18 +2814,27 @@ ggml_backend_reg_t ggml_backend_webgpu_reg() { ctx.name = GGML_WEBGPU_NAME; ctx.device_count = 1; - const char * const instanceEnabledToggles[] = { "allow_unsafe_apis" }; - - wgpu::DawnTogglesDescriptor instanceTogglesDesc; - instanceTogglesDesc.enabledToggles = instanceEnabledToggles; - instanceTogglesDesc.enabledToggleCount = 1; wgpu::InstanceDescriptor instance_descriptor{}; std::vector instance_features = { wgpu::InstanceFeatureName::TimedWaitAny }; instance_descriptor.requiredFeatures = instance_features.data(); instance_descriptor.requiredFeatureCount = instance_features.size(); - instance_descriptor.nextInChain = &instanceTogglesDesc; + +#ifndef __EMSCRIPTEN__ + const char * const instanceEnabledToggles[] = { "allow_unsafe_apis" }; + wgpu::DawnTogglesDescriptor instanceTogglesDesc; + instanceTogglesDesc.enabledToggles = instanceEnabledToggles; + instanceTogglesDesc.enabledToggleCount = 1; + instance_descriptor.nextInChain = &instanceTogglesDesc; +#endif webgpu_ctx->instance = wgpu::CreateInstance(&instance_descriptor); + +#ifdef __EMSCRIPTEN__ + if (webgpu_ctx->instance == nullptr) { + GGML_LOG_ERROR("ggml_webgpu: Failed to create WebGPU instance. Make sure either -sASYNCIFY or -sJSPI is set\n"); + return nullptr; + } +#endif GGML_ASSERT(webgpu_ctx->instance != nullptr); static ggml_backend_reg reg = { diff --git a/ggml/src/ggml-webgpu/wgsl-shaders/embed_wgsl.py b/ggml/src/ggml-webgpu/wgsl-shaders/embed_wgsl.py index ed8068d416..d61df5bb9e 100755 --- a/ggml/src/ggml-webgpu/wgsl-shaders/embed_wgsl.py +++ b/ggml/src/ggml-webgpu/wgsl-shaders/embed_wgsl.py @@ -19,6 +19,15 @@ def parse_decls(decls_text): return decls +def replace_repl_placeholders(variant, template_map): + for repl, code in variant["REPLS"].items(): + for key, val in template_map.items(): + # Match "key" and avoid matching subsequences using by using \b + code = re.sub(rf'\b{re.escape(str(key))}\b', str(val), code) + variant["REPLS"][repl] = code + return variant + + def replace_placeholders(shader_text, replacements): for key, val in replacements.items(): # Match {{KEY}} literally, where KEY is escaped @@ -71,6 +80,10 @@ def generate_variants(fname, input_dir, output_dir, outfile): decls_map = parse_decls(extract_block(text, "DECLS")) except ValueError: decls_map = {} + try: + templates_map = ast.literal_eval(extract_block(text, "REPL_TEMPLATES")) + except ValueError: + templates_map = {} for fname in sorted(os.listdir(input_dir)): if fname.endswith(".tmpl"): @@ -90,9 +103,11 @@ def generate_variants(fname, input_dir, output_dir, outfile): if key not in decls_map: raise ValueError(f"DECLS key '{key}' not found.") decls_code += decls_map[key] + "\n\n" - final_shader = re.sub(r'\bDECLS\b', decls_code, shader_template) if "REPLS" in variant: + variant = replace_repl_placeholders(variant, templates_map) + final_shader = replace_placeholders(final_shader, variant["REPLS"]) + # second run to expand placeholders in repl_template final_shader = replace_placeholders(final_shader, variant["REPLS"]) final_shader = expand_includes(final_shader, input_dir) diff --git a/ggml/src/ggml-webgpu/wgsl-shaders/unary_op.wgsl b/ggml/src/ggml-webgpu/wgsl-shaders/unary_op.wgsl new file mode 100644 index 0000000000..d474ab107b --- /dev/null +++ b/ggml/src/ggml-webgpu/wgsl-shaders/unary_op.wgsl @@ -0,0 +1,461 @@ +#define(REPL_TEMPLATES) + +{ + "XIELU_FUNC": "{{MUTATE}}[dst_i] = select(((exp(min(src[src_i], {{TYPE}}(params.eps))) - 1.0) - src[src_i]) * {{TYPE}}(params.alpha_n) + {{TYPE}}(params.beta) * src[src_i], {{TYPE}}(params.alpha_p) * src[src_i] * src[src_i] + {{TYPE}}(params.beta) * src[src_i], src[src_i] > 0.0);", + "ABS_FUNC": "{{MUTATE}}[dst_i] = abs(src[src_i]);", + "SGN_FUNC": "{{MUTATE}}[dst_i] = select({{TYPE}}(select(0.0, -1.0, src[src_i] < 0.0)), {{TYPE}}(1.0), src[src_i] > 0.0);", + "NEG_FUNC": "{{MUTATE}}[dst_i] = -src[src_i];", + "STEP_FUNC": "{{MUTATE}}[dst_i] = {{TYPE}}(select(0.0, 1.0, src[src_i] > 0.0));", + "TANH_FUNC": "{{MUTATE}}[dst_i] = tanh(clamp(src[src_i], -9.010913, 9.010913)); // Regarding tanh() domain restrictions in wgsl https://github.com/gpuweb/gpuweb/issues/4458", + "RELU_FUNC": "{{MUTATE}}[dst_i] = select(0.0, src[src_i], src[src_i] > 0.0);", + "ELU_FUNC": "{{MUTATE}}[dst_i] = select(exp(src[src_i]) - 1.0, src[src_i], src[src_i] > 0.0);", + "HARDSIGMOID_FUNC": "{{MUTATE}}[dst_i] = min(1.0, max(0.0, (src[src_i] + 3.0) / 6.0));", + "SIGMOID_FUNC": "{{MUTATE}}[dst_i] = 1.0 / (1.0 + exp(-src[src_i]));", + "SILU_FUNC": "{{MUTATE}}[dst_i] = src[src_i] / (1.0 + exp(-src[src_i]));", + "EXP_FUNC": "{{MUTATE}}[dst_i] = exp(src[src_i]);", + "HARDSWISH_FUNC": "{{MUTATE}}[dst_i] = src[src_i] * min(1.0, max(0.0, (src[src_i] + 3.0) / 6.0));", + "GELU_FUNC": "{{MUTATE}}[dst_i] = 0.5 * src[src_i] * (1.0 + tanh(clamp(sqrt(2.0 / 3.14159265) * (src[src_i] + 0.044715 * pow(src[src_i], 3.0)), -9.010913, 9.010913))); // Regarding tanh() domain restrictions in wgsl https://github.com/gpuweb/gpuweb/issues/4458", + "GELU_QUICK_FUNC": "{{MUTATE}}[dst_i] = src[src_i] * 0.5 * (1.0 + tanh(clamp(0.79788456 * (src[src_i] + 0.044715 * src[src_i] * src[src_i] * src[src_i]), -9.010913, 9.010913))); // Regarding tanh() domain restrictions in wgsl https://github.com/gpuweb/gpuweb/issues/4458", + "GELU_ERF_FUNC": "{{MUTATE}}[dst_i] = 0.5 * src[src_i] * (1.0 + tanh(clamp(0.79788456 * (src[src_i] + 0.044715 * src[src_i] * src[src_i] * src[src_i]), -9.010913, 9.010913))); // Regarding tanh() domain restrictions in wgsl https://github.com/gpuweb/gpuweb/issues/4458" +} + +#end(REPL_TEMPLATES) + +#define(VARIANTS) + +[ + { + "SHADER_NAME": "abs_f32", + "REPLS": { "TYPE": "f32", "FUNC": "ABS_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "abs_f16", + "REPLS": { "TYPE": "f16", "FUNC": "ABS_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "abs_inplace_f32", + "REPLS": { "TYPE": "f32", "FUNC": "ABS_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + { + "SHADER_NAME": "abs_inplace_f16", + "REPLS": { "TYPE": "f16", "FUNC": "ABS_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + + { + "SHADER_NAME": "sgn_f32", + "REPLS": { "TYPE": "f32", "FUNC": "SGN_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "sgn_f16", + "REPLS": { "TYPE": "f16", "FUNC": "SGN_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "sgn_inplace_f32", + "REPLS": { "TYPE": "f32", "FUNC": "SGN_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + { + "SHADER_NAME": "sgn_inplace_f16", + "REPLS": { "TYPE": "f16", "FUNC": "SGN_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + + { + "SHADER_NAME": "neg_f32", + "REPLS": { "TYPE": "f32", "FUNC": "NEG_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "neg_f16", + "REPLS": { "TYPE": "f16", "FUNC": "NEG_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "neg_inplace_f32", + "REPLS": { "TYPE": "f32", "FUNC": "NEG_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + { + "SHADER_NAME": "neg_inplace_f16", + "REPLS": { "TYPE": "f16", "FUNC": "NEG_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + + { + "SHADER_NAME": "step_f32", + "REPLS": { "TYPE": "f32", "FUNC": "STEP_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "step_f16", + "REPLS": { "TYPE": "f16", "FUNC": "STEP_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "step_inplace_f32", + "REPLS": { "TYPE": "f32", "FUNC": "STEP_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + { + "SHADER_NAME": "step_inplace_f16", + "REPLS": { "TYPE": "f16", "FUNC": "STEP_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + + { + "SHADER_NAME": "tanh_f32", + "REPLS": { "TYPE": "f32", "FUNC": "TANH_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "tanh_f16", + "REPLS": { "TYPE": "f16", "FUNC": "TANH_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "tanh_inplace_f32", + "REPLS": { "TYPE": "f32", "FUNC": "TANH_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + { + "SHADER_NAME": "tanh_inplace_f16", + "REPLS": { "TYPE": "f16", "FUNC": "TANH_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + + { + "SHADER_NAME": "elu_f32", + "REPLS": { "TYPE": "f32", "FUNC": "ELU_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "elu_f16", + "REPLS": { "TYPE": "f16", "FUNC": "ELU_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "elu_inplace_f32", + "REPLS": { "TYPE": "f32", "FUNC": "ELU_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + { + "SHADER_NAME": "elu_inplace_f16", + "REPLS": { "TYPE": "f16", "FUNC": "ELU_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + + { + "SHADER_NAME": "relu_f32", + "REPLS": { "TYPE": "f32", "FUNC": "RELU_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "relu_f16", + "REPLS": { "TYPE": "f16", "FUNC": "RELU_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "relu_inplace_f32", + "REPLS": { "TYPE": "f32", "FUNC": "RELU_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + { + "SHADER_NAME": "relu_inplace_f16", + "REPLS": { "TYPE": "f16", "FUNC": "RELU_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + + { + "SHADER_NAME": "sigmoid_f32", + "REPLS": { "TYPE": "f32", "FUNC": "SIGMOID_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "sigmoid_f16", + "REPLS": { "TYPE": "f16", "FUNC": "SIGMOID_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "sigmoid_inplace_f32", + "REPLS": { "TYPE": "f32", "FUNC": "SIGMOID_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + { + "SHADER_NAME": "sigmoid_inplace_f16", + "REPLS": { "TYPE": "f16", "FUNC": "SIGMOID_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + + { + "SHADER_NAME": "silu_f32", + "REPLS": { "TYPE": "f32", "FUNC": "SILU_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "silu_f16", + "REPLS": { "TYPE": "f16", "FUNC": "SILU_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "silu_inplace_f32", + "REPLS": { "TYPE": "f32", "FUNC": "SILU_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + { + "SHADER_NAME": "silu_inplace_f16", + "REPLS": { "TYPE": "f16", "FUNC": "SILU_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + + { + "SHADER_NAME": "exp_f32", + "REPLS": { "TYPE": "f32", "FUNC": "EXP_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "exp_f16", + "REPLS": { "TYPE": "f16", "FUNC": "EXP_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "exp_inplace_f32", + "REPLS": { "TYPE": "f32", "FUNC": "EXP_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + { + "SHADER_NAME": "exp_inplace_f16", + "REPLS": { "TYPE": "f16", "FUNC": "EXP_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + + { + "SHADER_NAME": "hardsigmoid_f32", + "REPLS": { "TYPE": "f32", "FUNC": "HARDSIGMOID_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "hardsigmoid_f16", + "REPLS": { "TYPE": "f16", "FUNC": "HARDSIGMOID_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "hardsigmoid_inplace_f32", + "REPLS": { "TYPE": "f32", "FUNC": "HARDSIGMOID_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + { + "SHADER_NAME": "hardsigmoid_inplace_f16", + "REPLS": { "TYPE": "f16", "FUNC": "HARDSIGMOID_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + + { + "SHADER_NAME": "hardswish_f32", + "REPLS": { "TYPE": "f32", "FUNC": "HARDSWISH_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "hardswish_f16", + "REPLS": { "TYPE": "f16", "FUNC": "HARDSWISH_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "hardswish_inplace_f32", + "REPLS": { "TYPE": "f32", "FUNC": "HARDSWISH_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + { + "SHADER_NAME": "hardswish_inplace_f16", + "REPLS": { "TYPE": "f16", "FUNC": "HARDSWISH_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + + { + "SHADER_NAME": "gelu_f32", + "REPLS": { "TYPE": "f32", "FUNC": "GELU_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "gelu_f16", + "REPLS": { "TYPE": "f16", "FUNC": "GELU_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "gelu_inplace_f32", + "REPLS": { "TYPE": "f32", "FUNC": "GELU_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + { + "SHADER_NAME": "gelu_inplace_f16", + "REPLS": { "TYPE": "f16", "FUNC": "GELU_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + + { + "SHADER_NAME": "gelu_quick_f32", + "REPLS": { "TYPE": "f32", "FUNC": "GELU_QUICK_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "gelu_quick_f16", + "REPLS": { "TYPE": "f16", "FUNC": "GELU_QUICK_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "gelu_quick_inplace_f32", + "REPLS": { "TYPE": "f32", "FUNC": "GELU_QUICK_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + { + "SHADER_NAME": "gelu_quick_inplace_f16", + "REPLS": { "TYPE": "f16", "FUNC": "GELU_QUICK_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + + { + "SHADER_NAME": "xielu_f32", + "REPLS": { "TYPE": "f32", "FUNC": "XIELU_FUNC", "EXT_PARAMS": "alpha_n: f32, alpha_p: f32, beta: f32, eps: f32", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "xielu_f16", + "REPLS": { "TYPE": "f16", "FUNC": "XIELU_FUNC", "EXT_PARAMS": "alpha_n: f32, alpha_p: f32, beta: f32, eps: f32", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "xielu_inplace_f32", + "REPLS": { "TYPE": "f32", "FUNC": "XIELU_FUNC", "EXT_PARAMS": "alpha_n: f32, alpha_p: f32, beta: f32, eps: f32", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + { + "SHADER_NAME": "xielu_inplace_f16", + "REPLS": { "TYPE": "f16", "FUNC": "XIELU_FUNC", "EXT_PARAMS": "alpha_n: f32, alpha_p: f32, beta: f32, eps: f32", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + { + "SHADER_NAME": "gelu_erf_f32", + "REPLS": { "TYPE": "f32", "FUNC": "GELU_ERF_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "gelu_erf_f16", + "REPLS": { "TYPE": "f16", "FUNC": "GELU_ERF_FUNC", "EXT_PARAMS": "", "MUTATE": "dst" }, + "DECLS": ["NOT_INPLACE"] + }, + { + "SHADER_NAME": "gelu_erf_inplace_f32", + "REPLS": { "TYPE": "f32", "FUNC": "GELU_ERF_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + }, + { + "SHADER_NAME": "gelu_erf_inplace_f16", + "REPLS": { "TYPE": "f16", "FUNC": "GELU_ERF_FUNC", "EXT_PARAMS": "", "MUTATE": "src" }, + "DECLS": ["INPLACE"] + } +] + +#end(VARIANTS) + +#define(DECLS) + +#decl(INPLACE) + +@group(0) @binding(1) +var params: Params; + +#enddecl(INPLACE) + +#decl(NOT_INPLACE) + +@group(0) @binding(1) +var dst: array<{{TYPE}}>; + +@group(0) @binding(2) +var params: Params; + +#enddecl(NOT_INPLACE) + +#end(DECLS) + +#define(SHADER) + +enable f16; + +fn update(dst_i: u32, src_i: u32) { + {{FUNC}} +} + +@group(0) @binding(0) +var src: array<{{TYPE}}>; + +DECLS + +struct Params { + ne: u32, // total number of elements + offset_src: u32, // in elements + offset_dst: u32, // in elements + + // Strides (in elements) — may be permuted + stride_src0: u32, + stride_src1: u32, + stride_src2: u32, + stride_src3: u32, + + stride_dst0: u32, + stride_dst1: u32, + stride_dst2: u32, + stride_dst3: u32, + + // Logical shapes + src_ne0: u32, + src_ne1: u32, + src_ne2: u32, + + dst_ne0: u32, + dst_ne1: u32, + dst_ne2: u32, + + {{EXT_PARAMS}} +}; + +override wg_size: u32; +@compute @workgroup_size(wg_size) +fn main(@builtin(global_invocation_id) gid: vec3) { + if (gid.x >= params.ne) { + return; + } + + var i = gid.x; + let i3 = i / (params.src_ne2 * params.src_ne1 * params.src_ne0); + i = i % (params.src_ne2 * params.src_ne1 * params.src_ne0); + let i2 = i / (params.src_ne1 * params.src_ne0); + i = i % (params.src_ne1 * params.src_ne0); + let i1 = i / params.src_ne0; + let i0 = i % params.src_ne0; + + var j = gid.x; + let j3 = j / (params.dst_ne2 * params.dst_ne1 * params.dst_ne0); + j = j % (params.dst_ne2 * params.dst_ne1 * params.dst_ne0); + let j2 = j / (params.dst_ne1 * params.dst_ne0); + j = j % (params.dst_ne1 * params.dst_ne0); + let j1 = j / params.dst_ne0; + let j0 = j % params.dst_ne0; + + let src_idx = i0 * params.stride_src0 + i1 * params.stride_src1 + + i2 * params.stride_src2 + i3 * params.stride_src3; + + let dst_idx = j0 * params.stride_dst0 + j1 * params.stride_dst1 + + j2 * params.stride_dst2 + j3 * params.stride_dst3; + + + update(params.offset_dst + dst_idx, params.offset_src + src_idx); +} + +#end(SHADER) + diff --git a/ggml/src/ggml-zendnn/CMakeLists.txt b/ggml/src/ggml-zendnn/CMakeLists.txt new file mode 100644 index 0000000000..bdbfc74369 --- /dev/null +++ b/ggml/src/ggml-zendnn/CMakeLists.txt @@ -0,0 +1,92 @@ +ggml_add_backend_library(ggml-zendnn + ggml-zendnn.cpp) + +# Get ZenDNN path +if (NOT DEFINED ZENDNN_ROOT OR ZENDNN_ROOT STREQUAL "") + set(ZENDNN_ROOT "$ENV{ZENDNN_ROOT}") +endif() + +# Check if path is still empty or OFF +if (NOT ZENDNN_ROOT OR ZENDNN_ROOT STREQUAL "" OR ZENDNN_ROOT STREQUAL "OFF") + message(STATUS "ZENDNN_ROOT not set. Automatically downloading and building ZenDNN...") + message(STATUS "This will take several minutes on first build...") + + include(ExternalProject) + + set(ZENDNN_PREFIX ${CMAKE_BINARY_DIR}/_deps/zendnn-prefix) + set(ZENDNN_SOURCE_DIR ${ZENDNN_PREFIX}/src/zendnn) + set(ZENDNN_BUILD_DIR ${ZENDNN_PREFIX}/build) + set(ZENDNN_INSTALL_DIR ${ZENDNN_BUILD_DIR}/install) + + ExternalProject_Add( + zendnn + GIT_REPOSITORY https://github.com/amd/ZenDNN.git + GIT_TAG zendnnl + PREFIX ${ZENDNN_PREFIX} + SOURCE_DIR ${ZENDNN_SOURCE_DIR} + BINARY_DIR ${ZENDNN_BUILD_DIR} + CMAKE_ARGS + -DCMAKE_BUILD_TYPE=Release + -DCMAKE_INSTALL_PREFIX=${ZENDNN_INSTALL_DIR} + -DZENDNNL_BUILD_EXAMPLES=OFF + -DZENDNNL_BUILD_DOXYGEN=OFF + -DZENDNNL_BUILD_GTEST=OFF + -DZENDNNL_BUILD_BENCHDNN=OFF + # Enable ALL matmul algorithm backends + -DZENDNNL_DEPENDS_AOCLDLP=ON + -DZENDNNL_DEPENDS_ONEDNN=ON + -DZENDNNL_DEPENDS_LIBXSMM=ON + BUILD_COMMAND ${CMAKE_COMMAND} --build ${ZENDNN_BUILD_DIR} --target zendnnl + INSTALL_COMMAND ${CMAKE_COMMAND} --build ${ZENDNN_BUILD_DIR} --target install + BUILD_ALWAYS OFF + LOG_DOWNLOAD ON + LOG_CONFIGURE ON + LOG_BUILD ON + LOG_INSTALL ON + ) + + # Add dependency so ZenDNN builds before our library + add_dependencies(ggml-zendnn zendnn) + + # Set ZENDNN_ROOT to the installation directory + set(ZENDNN_ROOT ${ZENDNN_INSTALL_DIR}) + + message(STATUS "ZenDNN will be built to: ${ZENDNN_ROOT}") +else() + message(STATUS "Using custom ZenDNN installation at: ${ZENDNN_ROOT}") +endif() + +# ZenDNN headers + libs +target_include_directories(ggml-zendnn PRIVATE + ${ZENDNN_ROOT}/zendnnl/include + ${ZENDNN_ROOT}/deps/aocldlp/include + ${ZENDNN_ROOT}/deps/aoclutils/include + ${ZENDNN_ROOT}/deps/json/include + ${ZENDNN_ROOT}/deps/libxsmm/include + ${ZENDNN_ROOT}/deps/onednn/include +) + +target_link_directories(ggml-zendnn PRIVATE + ${ZENDNN_ROOT}/zendnnl/lib + ${ZENDNN_ROOT}/deps/aocldlp/lib + ${ZENDNN_ROOT}/deps/aoclutils/lib + ${ZENDNN_ROOT}/deps/libxsmm/lib + ${ZENDNN_ROOT}/deps/onednn/lib +) + +target_link_libraries(ggml-zendnn PRIVATE + zendnnl_archive # ZenDNN main + aocl-dlp # AOCL libraries + aoclutils + au_cpuid + dnnl # OneDNN + xsmm # libxsmm small matrix math + xsmmext + xsmmnoblas + m + pthread +) + +if (GGML_OPENMP) + target_link_libraries(ggml-zendnn PRIVATE OpenMP::OpenMP_CXX) +endif() diff --git a/ggml/src/ggml-zendnn/ggml-zendnn.cpp b/ggml/src/ggml-zendnn/ggml-zendnn.cpp new file mode 100644 index 0000000000..fd07f983da --- /dev/null +++ b/ggml/src/ggml-zendnn/ggml-zendnn.cpp @@ -0,0 +1,466 @@ +#include "ggml-zendnn.h" + +#include "ggml-backend-impl.h" +#include "ggml-impl.h" +#include "ggml-cpu.h" +#include "zendnnl.hpp" + +#include + + +struct ggml_backend_zendnn_context { + int n_threads = GGML_DEFAULT_N_THREADS; + std::unique_ptr work_data; + size_t work_size = 0; +}; + +template +zendnnl::common::data_type_t ggml_to_zendnn_type() { + if constexpr (std::is_same_v) { + return zendnnl::common::data_type_t::f32; + } else if constexpr (std::is_same_v) { + return zendnnl::common::data_type_t::bf16; + } else { + return zendnnl::common::data_type_t::none; + } +} + +/** + * ZenDNN matmul: computes C = B * A. + * + * - A: weights, shape (k, m), column-major (each column is a weight vector for one output). + * - B: input, shape (n, k), row-major (each row is an input sample). + * - C: output, shape (n, m), row-major. + * + * Dimensions: + * m = output features (columns of C, columns of A) + * n = batch size (rows of C, rows of B) + * k = inner dimension (columns of B, rows of A) + */ +template +static bool ggml_zendnn_matmul(ggml_backend_zendnn_context * ctx, int64_t m, int64_t n, int64_t k, + const TA * A, int64_t lda, const TB * B, int64_t ldb, TC * C, + int64_t ldc) { + + zendnnl::lowoha::lowoha_params params; + params.dtypes.src = ggml_to_zendnn_type(); + params.dtypes.wei = ggml_to_zendnn_type(); + params.dtypes.dst = ggml_to_zendnn_type(); + params.num_threads = ctx->n_threads; + + zendnnl::lowoha::status_t status = zendnnl::lowoha::matmul_direct( + 'r', false, true, // row-major, don't transpose B, transpose A (because it's column-major) + n, // M: rows of B and C + m, // N: cols of A^T and C + k, // K: cols of B, rows of A + 1.0f, // alpha + B, ldb, // src: B[n,k] + A, lda, // weight: A[k,m] column-major (transposed) + nullptr, // bias + 0.0f, // beta + C, ldc, // output C[n,m] + true, // is_weights_const + {}, // batch_params + params // params + ); + + if (status != zendnnl::lowoha::status_t::success) { + GGML_LOG_ERROR("%s, ZenDNN matmul failed: status=%d\n", __func__, static_cast(status)); + return false; + } + return true; +} + +static bool ggml_zendnn_sgemm(ggml_backend_zendnn_context * ctx, int64_t m, int64_t n, int64_t k, + const void * A, int64_t lda, const void * B, int64_t ldb, void * C, + int64_t ldc, int Atype, int Btype, int Ctype) { + + assert(m >= 0); + assert(n >= 0); + assert(k >= 0); + assert(lda >= k); + assert(ldb >= k); + assert(ldc >= m); + + // categorize types + switch (Atype) { + case GGML_TYPE_F32: + if (Btype != GGML_TYPE_F32 || Ctype != GGML_TYPE_F32) + return false; + return ggml_zendnn_matmul( + ctx, m, n, k, + (const float *)A, lda, + (const float *)B, ldb, + (float *)C, ldc); + case GGML_TYPE_BF16: + if (Btype != GGML_TYPE_BF16) + return false; + if (Ctype == GGML_TYPE_BF16) + return ggml_zendnn_matmul( + ctx, m, n, k, + (const ggml_bf16_t *)A, lda, + (const ggml_bf16_t *)B, ldb, + (ggml_bf16_t *)C, ldc); + if (Ctype == GGML_TYPE_F32) + return ggml_zendnn_matmul( + ctx, m, n, k, + (const ggml_bf16_t *)A, lda, + (const ggml_bf16_t *)B, ldb, + (float *)C, ldc); + return false; + default: + return false; // unsupported type + } +} + +static void ggml_zendnn_compute_forward_mul_mat( + ggml_backend_zendnn_context * ctx, + ggml_tensor * dst) { + + const ggml_tensor * src0 = dst->src[0]; // weights + const ggml_tensor * src1 = dst->src[1]; // inputs + + GGML_TENSOR_BINARY_OP_LOCALS + + ggml_type const vec_dot_type = ggml_get_type_traits_cpu(src0->type)->vec_dot_type; + ggml_from_float_t const from_float = ggml_get_type_traits_cpu(vec_dot_type)->from_float; + + GGML_ASSERT(ne0 == ne01); + GGML_ASSERT(ne1 == ne11); + GGML_ASSERT(ne2 == ne12); + GGML_ASSERT(ne3 == ne13); + + // we don't support permuted src0 or src1 + GGML_ASSERT(nb00 == ggml_type_size(src0->type)); + GGML_ASSERT(nb10 == ggml_type_size(src1->type)); + + // dst cannot be transposed or permuted + GGML_ASSERT(nb0 == sizeof(float)); + GGML_ASSERT(nb0 <= nb1); + GGML_ASSERT(nb1 <= nb2); + GGML_ASSERT(nb2 <= nb3); + + // broadcast factors + const int64_t r2 = ne12/ne02; + const int64_t r3 = ne13/ne03; + + void * work_data = ctx->work_data.get(); + if (src1->type != vec_dot_type) { + const size_t nbw1 = ggml_row_size(vec_dot_type, ne10); + const size_t nbw2 = nbw1 * ne11; + const size_t nbw3 = nbw2 * ne12; + const size_t desired_wsize = ne13 * nbw3; + if (ctx->work_size < desired_wsize) { + ctx->work_data.reset(new char[desired_wsize]); + ctx->work_size = desired_wsize; + } + work_data = ctx->work_data.get(); + + // #pragma omp parallel for num_threads(ctx->n_threads) + #pragma omp parallel for collapse(3) num_threads(ctx->n_threads) schedule(static) + for (int64_t i13 = 0; i13 < ne13; ++i13) { + for (int64_t i12 = 0; i12 < ne12; ++i12) { + for (int64_t i11 = 0; i11 < ne11; ++i11) { + const float * src1_f32 = (float *)((char *)src1->data + i11*nb11 + i12*nb12 + i13*nb13); + void * src1_conv = (char *)work_data + i11*nbw1 + i12*nbw2 + i13*nbw3; + from_float(src1_f32, src1_conv, ne10); + } + } + } + } + + for (int64_t i13 = 0; i13 < ne13; i13++) { + for (int64_t i12 = 0; i12 < ne12; i12++) { + const void* wdata = src1->type == vec_dot_type ? src1->data : work_data; + const size_t row_size = ggml_row_size(vec_dot_type, ne10); + if (!ggml_zendnn_sgemm(ctx, + ne01, // m + ne11, // n + ne10, // k + static_cast(src0->data) + (i12/r2)*nb02 + (i13/r3)*nb03, + ne00, // lda + static_cast(wdata) + (i12*ne11 + i13*ne12*ne11)*row_size, + ne10, // ldb + static_cast(dst->data) + i12*nb2 + i13*nb3, + ne01, // ldc + src0->type, + vec_dot_type, + dst->type)) + GGML_ABORT("%s: ZenDNN sgemm failed\n", __func__); + } + } +} + +// backend interface + +static const char * ggml_backend_zendnn_get_name(ggml_backend_t backend) { + return "ZenDNN"; + + GGML_UNUSED(backend); +} + +static void ggml_backend_zendnn_free(ggml_backend_t backend) { + ggml_backend_zendnn_context * ctx = (ggml_backend_zendnn_context *)backend->context; + delete ctx; + delete backend; +} + +static ggml_status ggml_backend_zendnn_graph_compute(ggml_backend_t backend, ggml_cgraph * cgraph) { + ggml_backend_zendnn_context * ctx = (ggml_backend_zendnn_context *)backend->context; + + for (int i = 0; i < cgraph->n_nodes; i++) { + struct ggml_tensor * node = cgraph->nodes[i]; + + switch (node->op) { + case GGML_OP_MUL_MAT: + ggml_zendnn_compute_forward_mul_mat(ctx, node); + break; + case GGML_OP_NONE: + case GGML_OP_RESHAPE: + case GGML_OP_VIEW: + case GGML_OP_PERMUTE: + case GGML_OP_TRANSPOSE: + break; + + default: + GGML_ABORT("%s: unsupported op %s\n", __func__, ggml_op_desc(node)); + } + } + + return GGML_STATUS_SUCCESS; + + GGML_UNUSED(backend); +} + +static struct ggml_backend_i ggml_backend_zendnn_i = { + /* .get_name = */ ggml_backend_zendnn_get_name, + /* .free = */ ggml_backend_zendnn_free, + /* .set_tensor_async = */ NULL, + /* .get_tensor_async = */ NULL, + /* .cpy_tensor_async = */ NULL, + /* .synchronize = */ NULL, + /* .graph_plan_create = */ NULL, + /* .graph_plan_free = */ NULL, + /* .graph_plan_update = */ NULL, + /* .graph_plan_compute = */ NULL, + /* .graph_compute = */ ggml_backend_zendnn_graph_compute, + /* .event_record = */ NULL, + /* .event_wait = */ NULL, + /* .graph_optimize = */ NULL, +}; + +static ggml_guid_t ggml_backend_zendnn_guid(void) { + static const char * guid_str = "AMD-ZENDNN-ACCEL"; + return reinterpret_cast(const_cast(guid_str)); +} + +ggml_backend_t ggml_backend_zendnn_init(void) { + ggml_backend_zendnn_context * ctx = new ggml_backend_zendnn_context; + + ggml_backend_t backend = new ggml_backend { + /* .guid = */ ggml_backend_zendnn_guid(), + /* .iface = */ ggml_backend_zendnn_i, + /* .device = */ ggml_backend_reg_dev_get(ggml_backend_zendnn_reg(), 0), + /* .context = */ ctx, + }; + + return backend; +} + +bool ggml_backend_is_zendnn(ggml_backend_t backend) { + return backend != NULL && ggml_guid_matches(backend->guid, ggml_backend_zendnn_guid()); +} + +void ggml_backend_zendnn_set_n_threads(ggml_backend_t backend_zendnn, int n_threads) { + GGML_ASSERT(ggml_backend_is_zendnn(backend_zendnn)); + + ggml_backend_zendnn_context * ctx = (ggml_backend_zendnn_context *)backend_zendnn->context; + ctx->n_threads = n_threads; +} + +// device interface +static const char * ggml_backend_zendnn_device_get_name(ggml_backend_dev_t dev) { + return "ZenDNN"; + + GGML_UNUSED(dev); +} +/** + * ZenDNN is AMD's performance library providing optimized primitives and implementations + * for deep learning workloads on AMD CPUs. It targets improved performance for common + * neural network operations on AMD architectures. For more information, see: + * https://www.amd.com/en/developer/zendnn.html + */ +static const char * ggml_backend_zendnn_device_get_description(ggml_backend_dev_t dev) { + return "ZenDNN: AMD optimized primitives backend for GGML (optimized for AMD CPUs)"; + + GGML_UNUSED(dev); +} + +static void ggml_backend_zendnn_device_get_memory(ggml_backend_dev_t dev, size_t * free, size_t * total) { + *free = 0; + *total = 0; + + GGML_UNUSED(dev); +} + +static enum ggml_backend_dev_type ggml_backend_zendnn_device_get_type(ggml_backend_dev_t dev) { + return GGML_BACKEND_DEVICE_TYPE_ACCEL; + + GGML_UNUSED(dev); +} + +static void ggml_backend_zendnn_device_get_props(ggml_backend_dev_t dev, struct ggml_backend_dev_props * props) { + props->name = ggml_backend_zendnn_device_get_name(dev); + props->description = ggml_backend_zendnn_device_get_description(dev); + props->type = ggml_backend_zendnn_device_get_type(dev); + ggml_backend_zendnn_device_get_memory(dev, &props->memory_free, &props->memory_total); + props->caps = { + /* .async = */ false, + /* .host_buffer = */ false, + /* .buffer_from_host_ptr = */ true, + /* .events = */ false + }; +} + +static ggml_backend_t ggml_backend_zendnn_device_init_backend(ggml_backend_dev_t dev, const char * params) { + ggml_backend_t backend = ggml_backend_zendnn_init(); + if (backend == NULL) { + GGML_LOG_ERROR("%s: error: failed to initialize ZenDNN backend\n", __func__); + return NULL; + } + + return backend; + + GGML_UNUSED(dev); + GGML_UNUSED(params); +} + +static ggml_backend_buffer_type_t ggml_backend_zendnn_device_get_buffer_type(ggml_backend_dev_t dev) { + return ggml_backend_cpu_buffer_type(); + + GGML_UNUSED(dev); +} + +static ggml_backend_buffer_t ggml_backend_zendnn_device_buffer_from_host_ptr(ggml_backend_dev_t dev, void * ptr, size_t size, size_t max_tensor_size) { + return ggml_backend_cpu_buffer_from_ptr(ptr, size); + + GGML_UNUSED(dev); + GGML_UNUSED(max_tensor_size); +} + +static bool ggml_backend_zendnn_device_supports_op(ggml_backend_dev_t dev, const struct ggml_tensor * op) { + switch (op->op) { + case GGML_OP_NONE: + case GGML_OP_RESHAPE: + case GGML_OP_VIEW: + case GGML_OP_PERMUTE: + case GGML_OP_TRANSPOSE: + return true; + + case GGML_OP_MUL_MAT: + { + const ggml_tensor * weights = op->src[0]; + const ggml_tensor * inputs = op->src[1]; + + const int64_t ne10 = inputs->ne[0]; + const int64_t ne0 = op->ne[0]; + const int64_t ne1 = op->ne[1]; + + const int64_t min_batch = 1; + if (!ggml_is_contiguous(weights) || !ggml_is_contiguous(inputs) || + ne0 < min_batch || ne1 < min_batch || ne10 < min_batch) { + return false; + } + switch (weights->type) { + case GGML_TYPE_F32: + case GGML_TYPE_BF16: + return true; + default: + return false; + } + } break; + + default: + return false; + } + + GGML_UNUSED(dev); +} + +static bool ggml_backend_zendnn_device_supports_buft(ggml_backend_dev_t dev, ggml_backend_buffer_type_t buft) { + return ggml_backend_buft_is_host(buft); + + GGML_UNUSED(dev); +} + +static const struct ggml_backend_device_i ggml_backend_zendnn_device_i = { + /* .get_name = */ ggml_backend_zendnn_device_get_name, + /* .get_description = */ ggml_backend_zendnn_device_get_description, + /* .get_memory = */ ggml_backend_zendnn_device_get_memory, + /* .get_type = */ ggml_backend_zendnn_device_get_type, + /* .get_props = */ ggml_backend_zendnn_device_get_props, + /* .init_backend = */ ggml_backend_zendnn_device_init_backend, + /* .get_buffer_type = */ ggml_backend_zendnn_device_get_buffer_type, + /* .get_host_buffer_type = */ NULL, + /* .buffer_from_host_ptr = */ ggml_backend_zendnn_device_buffer_from_host_ptr, + /* .supports_op = */ ggml_backend_zendnn_device_supports_op, + /* .supports_buft = */ ggml_backend_zendnn_device_supports_buft, + /* .offload_op = */ NULL, + /* .event_new = */ NULL, + /* .event_free = */ NULL, + /* .event_synchronize = */ NULL, +}; + +// backend reg interface +static const char * ggml_backend_zendnn_reg_get_name(ggml_backend_reg_t reg) { + return "ZenDNN"; + + GGML_UNUSED(reg); +} + +static size_t ggml_backend_zendnn_reg_get_device_count(ggml_backend_reg_t reg) { + return 1; + + GGML_UNUSED(reg); +} + +static ggml_backend_dev_t ggml_backend_zendnn_reg_get_device(ggml_backend_reg_t reg, size_t index) { + GGML_ASSERT(index == 0); + + static ggml_backend_device ggml_backend_zendnn_device = { + /* .iface = */ ggml_backend_zendnn_device_i, + /* .reg = */ reg, + /* .context = */ nullptr, + }; + + return &ggml_backend_zendnn_device; +} + +static void * ggml_backend_zendnn_get_proc_address(ggml_backend_reg_t reg, const char * name) { + if (std::strcmp(name, "ggml_backend_set_n_threads") == 0) { + return (void *) ggml_backend_zendnn_set_n_threads; + } + return NULL; + + GGML_UNUSED(reg); + GGML_UNUSED(name); +} + +static const struct ggml_backend_reg_i ggml_backend_zendnn_reg_i = { + /* .get_name = */ ggml_backend_zendnn_reg_get_name, + /* .get_device_count = */ ggml_backend_zendnn_reg_get_device_count, + /* .get_device = */ ggml_backend_zendnn_reg_get_device, + /* .get_proc_address = */ ggml_backend_zendnn_get_proc_address, +}; + +ggml_backend_reg_t ggml_backend_zendnn_reg(void) { + static struct ggml_backend_reg ggml_backend_zendnn_reg = { + /* .api_version = */ GGML_BACKEND_API_VERSION, + /* .iface = */ ggml_backend_zendnn_reg_i, + /* .context = */ NULL, + }; + + return &ggml_backend_zendnn_reg; +} + +GGML_BACKEND_DL_IMPL(ggml_backend_zendnn_reg) diff --git a/ggml/src/ggml.c b/ggml/src/ggml.c index 17cf4d84bb..9f5cdc1398 100644 --- a/ggml/src/ggml.c +++ b/ggml/src/ggml.c @@ -4947,6 +4947,18 @@ struct ggml_tensor * ggml_pad( return ggml_pad_ext(ctx, a, 0, p0, 0, p1, 0, p2, 0, p3); } +// ggml_pad_circular + +struct ggml_tensor * ggml_pad_circular( + struct ggml_context * ctx, + struct ggml_tensor * a, + int p0, + int p1, + int p2, + int p3) { + return ggml_pad_ext_circular(ctx, a, 0, p0, 0, p1, 0, p2, 0, p3); +} + struct ggml_tensor * ggml_pad_ext( struct ggml_context * ctx, struct ggml_tensor * a, @@ -4973,6 +4985,7 @@ struct ggml_tensor * ggml_pad_ext( ggml_set_op_params_i32(result, 5, rp2); ggml_set_op_params_i32(result, 6, lp3); ggml_set_op_params_i32(result, 7, rp3); + ggml_set_op_params_i32(result, 8, 0); // not circular by default result->op = GGML_OP_PAD; @@ -4981,6 +4994,25 @@ struct ggml_tensor * ggml_pad_ext( return result; } +// ggml_pad_ext_circular + +struct ggml_tensor * ggml_pad_ext_circular( + struct ggml_context * ctx, + struct ggml_tensor * a, + int lp0, + int rp0, + int lp1, + int rp1, + int lp2, + int rp2, + int lp3, + int rp3 + ) { + struct ggml_tensor * result = ggml_pad_ext(ctx, a, lp0, rp0, lp1, rp1, lp2, rp2, lp3, rp3); + ggml_set_op_params_i32(result, 8, 1); // circular + return result; +} + // ggml_pad_reflect_1d struct ggml_tensor * ggml_pad_reflect_1d( diff --git a/ggml/src/gguf.cpp b/ggml/src/gguf.cpp index 8cc4ef1cf4..b165d8bdc6 100644 --- a/ggml/src/gguf.cpp +++ b/ggml/src/gguf.cpp @@ -1169,7 +1169,7 @@ void gguf_set_tensor_data(struct gguf_context * ctx, const char * name, const vo struct gguf_writer_base { size_t written_bytes {0u}; - ~gguf_writer_base(void) {} + ~gguf_writer_base(void) = default; // we bet on devirtualization virtual void write(int8_t val) = 0; diff --git a/gguf-py/gguf/tensor_mapping.py b/gguf-py/gguf/tensor_mapping.py index a7b0973979..d9c87da194 100644 --- a/gguf-py/gguf/tensor_mapping.py +++ b/gguf-py/gguf/tensor_mapping.py @@ -376,6 +376,7 @@ class TensorNameMap: "model.layers.{bid}.block_sparse_moe.primary_router", # smallthinker "model.layers.{bid}.feed_forward.gate", # lfm2moe "model.layers.{bid}.mlp.router.gate", # afmoe + "layers.{bid}.gate", # mistral-large ), MODEL_TENSOR.FFN_GATE_INP_SHEXP: ( @@ -450,6 +451,7 @@ class TensorNameMap: "model.layers.{bid}.feed_forward.shared_expert.up_proj", # llama4 "model.layers.{bid}.feed_forward.down_proj", "model.layers.{bid}.mlp.shared_mlp.up_proj", # hunyuan + "layers.{bid}.shared_experts.w3", # mistral-large ), MODEL_TENSOR.FFN_UP_CHEXP: ( @@ -496,6 +498,7 @@ class TensorNameMap: "model.layers.{bid}.mlp.shared_experts.gate_proj", # deepseek deepseek2 "model.layers.{bid}.feed_forward.shared_expert.gate_proj", # llama4 "model.layers.{bid}.mlp.shared_mlp.gate_proj", # hunyuan + "layers.{bid}.shared_experts.w1", # mistral-large ), MODEL_TENSOR.FFN_GATE_CHEXP: ( @@ -557,6 +560,7 @@ class TensorNameMap: "model.layers.{bid}.feed_forward.shared_expert.down_proj", # llama4 "model.layers.{bid}.shared_mlp.output_linear", # granitemoe "model.layers.{bid}.mlp.shared_mlp.down_proj", # hunyuan + "layers.{bid}.shared_experts.w2", # mistral-large ), MODEL_TENSOR.FFN_DOWN_CHEXP: ( @@ -924,14 +928,17 @@ class TensorNameMap: MODEL_TENSOR.ATTN_Q_A: ( "model.layers.{bid}.self_attn.q_a_proj", # deepseek2 + "layers.{bid}.attention.wq_a", # mistral-large ), MODEL_TENSOR.ATTN_Q_B: ( "model.layers.{bid}.self_attn.q_b_proj", # deepseek2 + "layers.{bid}.attention.wq_b", # mistral-large ), MODEL_TENSOR.ATTN_KV_A_MQA: ( "model.layers.{bid}.self_attn.kv_a_proj_with_mqa", # deepseek2 + "layers.{bid}.attention.wkv_a_with_mqa", # mistral-large ), MODEL_TENSOR.ATTN_KV_B: ( @@ -940,18 +947,22 @@ class TensorNameMap: MODEL_TENSOR.ATTN_K_B: ( "model.layers.{bid}.self_attn.k_b_proj", # deepseek2 + "layers.{bid}.attention.k_b_proj", # mistral-large ), MODEL_TENSOR.ATTN_V_B: ( "model.layers.{bid}.self_attn.v_b_proj", # deepseek2 + "layers.{bid}.attention.v_b_proj", # mistral-large ), MODEL_TENSOR.ATTN_Q_A_NORM: ( "model.layers.{bid}.self_attn.q_a_layernorm", # deepseek2 + "layers.{bid}.attention.q_a_norm", # mistral-large ), MODEL_TENSOR.ATTN_KV_A_NORM: ( "model.layers.{bid}.self_attn.kv_a_layernorm", # deepseek2 + "layers.{bid}.attention.kv_a_norm", # mistral-large ), MODEL_TENSOR.ATTN_SUB_NORM: ( diff --git a/gguf-py/gguf/vocab.py b/gguf-py/gguf/vocab.py index 5c6817109b..028e5748e4 100644 --- a/gguf-py/gguf/vocab.py +++ b/gguf-py/gguf/vocab.py @@ -31,6 +31,14 @@ except ImportError: else: _mistral_common_installed = True +try: + from mistral_common.tokens.tokenizers.utils import ( # pyright: ignore[reportMissingImports] + get_one_valid_tokenizer_file, + ) +except ImportError: + # We still want the conversion to work with older mistral-common versions. + get_one_valid_tokenizer_file = None + import gguf @@ -673,24 +681,30 @@ class MistralVocab(Vocab): # Find the tokenizer files all_files = [f.as_posix() for f in base_path.glob("**/*") if f.is_file()] - valid_tokenizer_files = _filter_valid_tokenizer_files(all_files) - if len(valid_tokenizer_files) == 0: - raise ValueError(f"No tokenizer file found in the directory: {base_path}") - # If there are multiple tokenizer files, we use tekken.json if it exists, otherwise the versioned one. - if len(valid_tokenizer_files) > 1: - if "tekken.json" in valid_tokenizer_files: - tokenizer_file = "tekken.json" - else: - tokenizer_file = sorted(valid_tokenizer_files)[-1] - logger.warning( - f"Multiple tokenizer files found in {base_path}. Using {tokenizer_file}" - ) + if get_one_valid_tokenizer_file is not None: + tokenizer_file_path = get_one_valid_tokenizer_file(all_files) else: - tokenizer_file = valid_tokenizer_files[0] + valid_tokenizer_files = _filter_valid_tokenizer_files(all_files) + + if len(valid_tokenizer_files) == 0: + raise ValueError(f"No tokenizer file found in the directory: {base_path}") + # If there are multiple tokenizer files, we use tekken.json if it exists, otherwise the versioned one. + if len(valid_tokenizer_files) > 1: + if "tekken.json" in valid_tokenizer_files: + tokenizer_file = "tekken.json" + else: + tokenizer_file = sorted(valid_tokenizer_files)[-1] + logger.warning( + f"Multiple tokenizer files found in {base_path}. Using {tokenizer_file}" + ) + else: + tokenizer_file = valid_tokenizer_files[0] + + tokenizer_file_path = base_path / tokenizer_file self.tokenizer = MistralTokenizer.from_file( - base_path / tokenizer_file + tokenizer_file_path ).instruct_tokenizer.tokenizer self.tokenizer_type = ( MistralTokenizerType.tekken @@ -698,7 +712,7 @@ class MistralVocab(Vocab): else MistralTokenizerType.spm ) self.vocab_size = self.tokenizer.n_words - self.fname_tokenizer = base_path / tokenizer_file + self.fname_tokenizer = tokenizer_file_path self._name = ( "mistral-" + self.tokenizer_type.value + "-" + self.tokenizer.version ) diff --git a/scripts/serve-static.js b/scripts/serve-static.js new file mode 100644 index 0000000000..8ddc04aad9 --- /dev/null +++ b/scripts/serve-static.js @@ -0,0 +1,110 @@ +const http = require('http'); +const fs = require('fs').promises; +const path = require('path'); + +// This file is used for testing wasm build from emscripten +// Example build command: +// emcmake cmake -B build-wasm -DGGML_WEBGPU=ON -DLLAMA_CURL=OFF +// cmake --build build-wasm --target test-backend-ops -j + +const PORT = 8080; +const STATIC_DIR = path.join(__dirname, '../build-wasm/bin'); +console.log(`Serving static files from: ${STATIC_DIR}`); + +const mimeTypes = { + '.html': 'text/html', + '.js': 'text/javascript', + '.css': 'text/css', + '.png': 'image/png', + '.jpg': 'image/jpeg', + '.gif': 'image/gif', + '.svg': 'image/svg+xml', + '.json': 'application/json', + '.woff': 'font/woff', + '.woff2': 'font/woff2', +}; + +async function generateDirListing(dirPath, reqUrl) { + const files = await fs.readdir(dirPath); + let html = ` + + + + Directory Listing + + + +

Directory: ${reqUrl}

+
    + `; + + if (reqUrl !== '/') { + html += `
  • ../ (Parent Directory)
    • `; + } + + for (const file of files) { + const filePath = path.join(dirPath, file); + const stats = await fs.stat(filePath); + const link = encodeURIComponent(file) + (stats.isDirectory() ? '/' : ''); + html += `
  • ${file}${stats.isDirectory() ? '/' : ''}
    • `; + } + + html += ` +
+ + + `; + return html; +} + +const server = http.createServer(async (req, res) => { + try { + // Set COOP and COEP headers + res.setHeader('Cross-Origin-Opener-Policy', 'same-origin'); + res.setHeader('Cross-Origin-Embedder-Policy', 'require-corp'); + res.setHeader('Cache-Control', 'no-store, no-cache, must-revalidate, proxy-revalidate'); + res.setHeader('Pragma', 'no-cache'); + res.setHeader('Expires', '0'); + + const filePath = path.join(STATIC_DIR, decodeURIComponent(req.url)); + const stats = await fs.stat(filePath); + + if (stats.isDirectory()) { + const indexPath = path.join(filePath, 'index.html'); + try { + const indexData = await fs.readFile(indexPath); + res.writeHeader(200, { 'Content-Type': 'text/html' }); + res.end(indexData); + } catch { + // No index.html, generate directory listing + const dirListing = await generateDirListing(filePath, req.url); + res.writeHeader(200, { 'Content-Type': 'text/html' }); + res.end(dirListing); + } + } else { + const ext = path.extname(filePath).toLowerCase(); + const contentType = mimeTypes[ext] || 'application/octet-stream'; + const data = await fs.readFile(filePath); + res.writeHeader(200, { 'Content-Type': contentType }); + res.end(data); + } + } catch (err) { + if (err.code === 'ENOENT') { + res.writeHeader(404, { 'Content-Type': 'text/plain' }); + res.end('404 Not Found'); + } else { + res.writeHeader(500, { 'Content-Type': 'text/plain' }); + res.end('500 Internal Server Error'); + } + } +}); + +server.listen(PORT, () => { + console.log(`Server running at http://localhost:${PORT}/`); +}); diff --git a/src/llama-context.cpp b/src/llama-context.cpp index e04f0fc4f9..4171400713 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -248,7 +248,10 @@ llama_context::llama_context( LLAMA_LOG_DEBUG("%s: backend_ptrs.size() = %zu\n", __func__, backend_ptrs.size()); - const size_t max_nodes = this->graph_max_nodes(); + const uint32_t n_seqs = cparams.n_seq_max; + const uint32_t n_tokens = std::min(cparams.n_ctx, cparams.n_ubatch); + + const size_t max_nodes = this->graph_max_nodes(n_tokens); LLAMA_LOG_DEBUG("%s: max_nodes = %zu\n", __func__, max_nodes); @@ -300,9 +303,6 @@ llama_context::llama_context( cross.v_embd.clear(); - const uint32_t n_seqs = cparams.n_seq_max; - const uint32_t n_tokens = std::min(cparams.n_ctx, cparams.n_ubatch); - // avoid reserving graphs with zero outputs - assume one output per sequence n_outputs = n_seqs; @@ -1386,9 +1386,9 @@ void llama_context::output_reorder() { // graph // -uint32_t llama_context::graph_max_nodes() const { +uint32_t llama_context::graph_max_nodes(uint32_t n_tokens) const { if (model.arch == LLM_ARCH_QWEN3NEXT) { - return std::max(8192u, 32u*model.n_tensors()); + return std::max(n_tokens * 40, 32u * model.n_tensors()); } return std::max(1024u, 8u*model.n_tensors()); } diff --git a/src/llama-context.h b/src/llama-context.h index 20cbd78955..cd26eafe18 100644 --- a/src/llama-context.h +++ b/src/llama-context.h @@ -197,7 +197,7 @@ private: // public: - uint32_t graph_max_nodes() const; + uint32_t graph_max_nodes(uint32_t n_tokens) const; // can reuse the llm_graph_result instance of the context (for example to update a memory module) llm_graph_result * get_gf_res_reserve() const; diff --git a/src/llama-graph.cpp b/src/llama-graph.cpp index 42ccb5b76a..43620df780 100644 --- a/src/llama-graph.cpp +++ b/src/llama-graph.cpp @@ -973,7 +973,7 @@ ggml_tensor * llm_graph_context::build_moe_ffn( // mask out the other groups selection_probs = ggml_get_rows(ctx0, selection_groups, expert_groups); // [n_exp_per_group, n_group_used, n_tokens] - selection_probs = ggml_set_rows(ctx0, ggml_scale_bias(ctx0, selection_groups, 0.0f, -INFINITY), selection_probs, expert_groups); // [n_exp_per_group, n_expert_groups, n_tokens] + selection_probs = ggml_set_rows(ctx0, ggml_fill(ctx0, selection_groups, -INFINITY), selection_probs, expert_groups); // [n_exp_per_group, n_expert_groups, n_tokens] selection_probs = ggml_reshape_2d(ctx0, selection_probs, n_expert, n_tokens); // [n_expert, n_tokens] cb(selection_probs, "ffn_moe_probs_masked", il); } diff --git a/src/llama-impl.h b/src/llama-impl.h index c5163e9225..c3391e79f5 100644 --- a/src/llama-impl.h +++ b/src/llama-impl.h @@ -37,7 +37,7 @@ void llama_log_callback_default(ggml_log_level level, const char * text, void * template struct no_init { T value; - no_init() { /* do nothing */ } + no_init() = default; }; struct time_meas { diff --git a/src/llama-mmap.cpp b/src/llama-mmap.cpp index 47497cf953..0641c2d22f 100644 --- a/src/llama-mmap.cpp +++ b/src/llama-mmap.cpp @@ -485,7 +485,7 @@ struct llama_mlock::impl { if (suggest && getrlimit(RLIMIT_MEMLOCK, &lock_limit)) { suggest = false; } - if (suggest && (lock_limit.rlim_max > lock_limit.rlim_cur + size)) { + if (suggest && ((uint64_t)lock_limit.rlim_max > (uint64_t)lock_limit.rlim_cur + size)) { suggest = false; } #endif diff --git a/src/llama-model.cpp b/src/llama-model.cpp index e281dc760b..7d09d7abd5 100644 --- a/src/llama-model.cpp +++ b/src/llama-model.cpp @@ -423,8 +423,8 @@ static buft_list_t make_gpu_buft_list(ggml_backend_dev_t dev, llama_split_mode s } struct llama_model::impl { - impl() {} - ~impl() {} + impl() = default; + ~impl() = default; uint64_t n_elements = 0; @@ -461,7 +461,7 @@ llama_model::llama_model(const llama_model_params & params) : params(params), pi pimpl->has_tensor_overrides = params.tensor_buft_overrides && params.tensor_buft_overrides[0].pattern; } -llama_model::~llama_model() {} +llama_model::~llama_model() = default; void llama_model::load_stats(llama_model_loader & ml) { pimpl->n_elements = ml.n_elements; @@ -1628,6 +1628,10 @@ void llama_model::load_hparams(llama_model_loader & ml) { } ml.get_key(LLM_KV_ROPE_SCALING_YARN_LOG_MUL, hparams.rope_yarn_log_mul, false); + // (optional) temperature tuning - used by mistral-large + ml.get_key(LLM_KV_ATTENTION_TEMPERATURE_SCALE, hparams.f_attn_temp_scale, false); + ml.get_key(LLM_KV_ATTENTION_TEMPERATURE_LENGTH, hparams.n_attn_temp_floor_scale, false); + switch (hparams.n_layer) { case 27: type = LLM_TYPE_16B; break; case 60: type = LLM_TYPE_236B; break; diff --git a/src/llama-quant.cpp b/src/llama-quant.cpp index 0b23eaef3a..351dcb7baa 100644 --- a/src/llama-quant.cpp +++ b/src/llama-quant.cpp @@ -666,7 +666,6 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std:: std::map mapped; int blk_id = 0; - int pruned_attention_w = 0; // make a list of weights std::vector tensors; @@ -674,11 +673,6 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std:: for (const auto & it : ml.weights_map) { const std::string remapped_name(remap_layer(it.first, prune_list, mapped, blk_id)); if (remapped_name.empty()) { - if (it.first.find("attn_v.weight") != std::string::npos || - it.first.find("attn_qkv.weight") != std::string::npos || - it.first.find("attn_kv_b.weight") != std::string::npos) { - pruned_attention_w++; - } LLAMA_LOG_DEBUG("%s: pruning tensor %s\n", __func__, it.first.c_str()); continue; } @@ -703,7 +697,6 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std:: }); } - bool is_clip_model = false; for (const auto * it : tensors) { const struct ggml_tensor * tensor = it->tensor; @@ -717,32 +710,10 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std:: } else if (name == LLM_TN(model.arch)(LLM_TENSOR_OUTPUT, "weight")) { qs.has_output = true; } - - is_clip_model |= name.rfind("mm.", 0) == 0; // check the "mm." prefix } qs.n_ffn_down = qs.n_ffn_gate = qs.n_ffn_up = (int)model.hparams.n_layer; - // sanity checks for models that have attention layers - if (qs.n_attention_wv != 0 && !is_clip_model) - { - const auto & n_head_kv_iter = model.hparams.n_head_kv_arr.begin(); - // attention layers have a non-zero number of kv heads - int32_t n_layer_attn = model.hparams.n_layer - std::count(n_head_kv_iter, n_head_kv_iter + model.hparams.n_layer, 0); - if (llama_model_has_encoder(&model)) { - // now n_layer_attn is the number of attention layers in the encoder - // for each decoder block, there are 2 attention layers - n_layer_attn += 2 * model.hparams.dec_n_layer; - } - - // note: for linear-attention models (such as Qwen3 Next) this is the number of linear layers - const int32_t n_layer_recr = std::count(model.hparams.recurrent_layer_arr.begin(), model.hparams.recurrent_layer_arr.end(), true); - - LLAMA_LOG_INFO("%s: n_layer_attn = %d, n_layer_recr = %d, pruned_attention_w = %d\n", __func__, n_layer_attn, n_layer_recr, pruned_attention_w); - - GGML_ASSERT((qs.n_attention_wv == n_layer_attn - pruned_attention_w - n_layer_recr) && "n_attention_wv is unexpected"); - } - size_t total_size_org = 0; size_t total_size_new = 0; diff --git a/src/llama-vocab.cpp b/src/llama-vocab.cpp index a73c4c448b..e2cca66e48 100644 --- a/src/llama-vocab.cpp +++ b/src/llama-vocab.cpp @@ -3253,8 +3253,7 @@ void llama_vocab::impl::print_info() const { llama_vocab::llama_vocab() : pimpl(new impl(*this)) { } -llama_vocab::~llama_vocab() { -} +llama_vocab::~llama_vocab() = default; void llama_vocab::load(llama_model_loader & ml, const LLM_KV & kv) { pimpl->load(ml, kv); diff --git a/src/models/deepseek2.cpp b/src/models/deepseek2.cpp index 0b41f7ba8e..dbaa8297be 100644 --- a/src/models/deepseek2.cpp +++ b/src/models/deepseek2.cpp @@ -30,6 +30,12 @@ llm_build_deepseek2::llm_build_deepseek2(const llama_model & model, const llm_gr // {n_embd, n_tokens} inpL = build_inp_embd(model.tok_embd); + // (optional) temperature tuning - used by mistral-large + ggml_tensor * inp_attn_scale = nullptr; + if (hparams.f_attn_temp_scale != 0.0f) { + inp_attn_scale = build_inp_attn_scale(); + } + // inp_pos - contains the positions ggml_tensor * inp_pos = build_inp_pos(); @@ -128,6 +134,12 @@ llm_build_deepseek2::llm_build_deepseek2(const llama_model & model, const llm_gr ggml_tensor * Vcur = kv_cmpr; cb(Vcur, "Vcur", il); + if (inp_attn_scale) { + // apply llama 4 temperature scaling + Qcur = ggml_mul(ctx0, Qcur, inp_attn_scale); + cb(Qcur, "Qcur_attn_temp_scaled", il); + } + // note: MLA with the absorption optimzation converts into MQA (ie: GQA with 1 group) cur = build_attn(inp_attn, model.layers[il].wo, NULL, @@ -160,6 +172,12 @@ llm_build_deepseek2::llm_build_deepseek2(const llama_model & model, const llm_gr ggml_tensor * Kcur = ggml_concat(ctx0, ggml_repeat(ctx0, k_pe, q_pe), k_nope, 0); cb(Kcur, "Kcur", il); + if (inp_attn_scale) { + // apply llama 4 temperature scaling + Qcur = ggml_mul(ctx0, Qcur, inp_attn_scale); + cb(Qcur, "Qcur_attn_temp_scaled", il); + } + // note: MLA without the absorption optimization converts into MHA (ie: GQA with full n_head groups) cur = build_attn(inp_attn, model.layers[il].wo, NULL, diff --git a/src/unicode.cpp b/src/unicode.cpp index 77ba4fc46b..bb44edfadd 100644 --- a/src/unicode.cpp +++ b/src/unicode.cpp @@ -499,7 +499,7 @@ static std::vector unicode_regex_split_custom_llama3(const std::string & // use std::wregex to split the text static std::vector unicode_regex_split_stl(const std::wstring & wtext, const std::wstring & regex_expr, const std::vector & offsets) { - std::wregex expr(regex_expr); + std::wregex expr(regex_expr, std::regex_constants::optimize | std::regex_constants::nosubs); std::vector bpe_offsets; // store the offset of each word bpe_offsets.reserve(offsets.size()); // Reserve memory for the approximate size size_t start = 0; @@ -529,7 +529,7 @@ static std::vector unicode_regex_split_stl(const std::wstring & wtext, c // use std::regex to split the text static std::vector unicode_regex_split_stl(const std::string & text, const std::string & regex_expr, const std::vector & offsets) { - std::regex expr(regex_expr); + std::regex expr(regex_expr, std::regex_constants::optimize | std::regex_constants::nosubs); std::vector bpe_offsets; // store the offset of each word bpe_offsets.reserve(offsets.size()); // Reserve memory for the approximate size size_t start = 0; diff --git a/tests/.gitignore b/tests/.gitignore index cbc381606c..ba2b164fac 100644 --- a/tests/.gitignore +++ b/tests/.gitignore @@ -3,3 +3,4 @@ *.o ggml-common.h **/*.swp +!peg-parser diff --git a/tests/CMakeLists.txt b/tests/CMakeLists.txt index 9361a113a1..9ba559c8df 100644 --- a/tests/CMakeLists.txt +++ b/tests/CMakeLists.txt @@ -1,13 +1,15 @@ llama_add_compile_flags() function(llama_build source) + set(TEST_SOURCES ${source} ${ARGN}) + if (DEFINED LLAMA_TEST_NAME) set(TEST_TARGET ${LLAMA_TEST_NAME}) else() get_filename_component(TEST_TARGET ${source} NAME_WE) endif() - add_executable(${TEST_TARGET} ${source}) + add_executable(${TEST_TARGET} ${TEST_SOURCES}) target_link_libraries(${TEST_TARGET} PRIVATE common) install(TARGETS ${TEST_TARGET} RUNTIME) endfunction() @@ -83,6 +85,8 @@ function(llama_build_and_test source) set(multiValueArgs ARGS) cmake_parse_arguments(LLAMA_TEST "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN}) + set(TEST_SOURCES ${source} ${LLAMA_TEST_UNPARSED_ARGUMENTS} get-model.cpp) + if (NOT DEFINED LLAMA_TEST_LABEL) set(LLAMA_TEST_LABEL "main") endif() @@ -95,7 +99,7 @@ function(llama_build_and_test source) get_filename_component(TEST_TARGET ${source} NAME_WE) endif() - add_executable(${TEST_TARGET} ${source} get-model.cpp) + add_executable(${TEST_TARGET} ${TEST_SOURCES}) install(TARGETS ${TEST_TARGET} RUNTIME) target_link_libraries(${TEST_TARGET} PRIVATE common) @@ -180,9 +184,21 @@ if (NOT WIN32 OR NOT BUILD_SHARED_LIBS) endif() llama_build_and_test(test-chat-parser.cpp) +llama_build_and_test(test-chat-peg-parser.cpp peg-parser/simple-tokenize.cpp) llama_build_and_test(test-chat-template.cpp) llama_build_and_test(test-json-partial.cpp) llama_build_and_test(test-log.cpp) +llama_build_and_test( + test-peg-parser.cpp + peg-parser/simple-tokenize.cpp + peg-parser/test-basic.cpp + peg-parser/test-gbnf-generation.cpp + peg-parser/test-json-parser.cpp + peg-parser/test-json-serialization.cpp + peg-parser/test-unicode.cpp + peg-parser/testing.h + peg-parser/tests.h +) llama_build_and_test(test-regex-partial.cpp) if (NOT ${CMAKE_SYSTEM_PROCESSOR} MATCHES "s390x") diff --git a/tests/peg-parser/simple-tokenize.cpp b/tests/peg-parser/simple-tokenize.cpp new file mode 100644 index 0000000000..9abfa0448f --- /dev/null +++ b/tests/peg-parser/simple-tokenize.cpp @@ -0,0 +1,37 @@ +#include "simple-tokenize.h" + +std::vector simple_tokenize(const std::string & input) { + std::vector result; + std::string current; + + for (size_t i = 0; i < input.size(); i++) { + switch (input[i]) { + case ' ': + case '\n': + case '\t': + case '{': + case '}': + case ',': + case '[': + case '"': + case ']': + case '.': + case '<': + case '>': + case '=': + case '/': + if (!current.empty()) { + result.push_back(current); + current.clear(); + } + default:; + } + current += input[i]; + } + + if (!current.empty()) { + result.push_back(current); + } + + return result; +} diff --git a/tests/peg-parser/simple-tokenize.h b/tests/peg-parser/simple-tokenize.h new file mode 100644 index 0000000000..1772432c5a --- /dev/null +++ b/tests/peg-parser/simple-tokenize.h @@ -0,0 +1,6 @@ +#pragma once + +#include +#include + +std::vector simple_tokenize(const std::string &); diff --git a/tests/peg-parser/test-basic.cpp b/tests/peg-parser/test-basic.cpp new file mode 100644 index 0000000000..1bda6f2e69 --- /dev/null +++ b/tests/peg-parser/test-basic.cpp @@ -0,0 +1,454 @@ +#include "tests.h" + +void test_basic(testing & t) { + t.test("chars", [](testing & t) { + // Test common escape sequences - newline + t.test("escape_sequence_newline", [](testing &t) { + auto common_chat_combinator_parser = build_peg_parser([](common_peg_parser_builder & p) { return p.chars("[\\n\\t\\\\]"); }); + + common_peg_parse_context ctx; + common_peg_parse_result result; + + ctx = common_peg_parse_context("\n"); + result = common_chat_combinator_parser.parse(ctx); + t.assert_equal("escape_sequence_newline", true, result.success()); + }); + + // Test common escape sequences - tab + t.test("escape_sequence_tab", [](testing &t) { + auto common_chat_combinator_parser = build_peg_parser([](common_peg_parser_builder & p) { return p.chars("[\\n\\t\\\\]"); }); + + common_peg_parse_context ctx; + common_peg_parse_result result; + + ctx = common_peg_parse_context("\t"); + result = common_chat_combinator_parser.parse(ctx); + t.assert_equal("escape_sequence_tab", true, result.success()); + }); + + // Test common escape sequences - backslash + t.test("escape_sequence_backslash", [](testing &t) { + auto common_chat_combinator_parser = build_peg_parser([](common_peg_parser_builder & p) { return p.chars("[\\n\\t\\\\]"); }); + + common_peg_parse_context ctx; + common_peg_parse_result result; + + ctx = common_peg_parse_context("\\"); + result = common_chat_combinator_parser.parse(ctx); + t.assert_equal("escape_sequence_backslash", true, result.success()); + }); + + // Test common escape sequences - space (should ()) + t.test("escape_sequence_space_fail", [](testing &t) { + auto common_chat_combinator_parser = build_peg_parser([](common_peg_parser_builder & p) { return p.chars("[\\n\\t\\\\]"); }); + + common_peg_parse_context ctx; + common_peg_parse_result result; + + ctx = common_peg_parse_context(" "); + result = common_chat_combinator_parser.parse(ctx); + t.assert_equal("escape_sequence_space_fail", true, result.fail()); + }); + + // Test escaped dash - 'a' should succeed + t.test("escaped_dash_a", [](testing &t) { + auto common_chat_combinator_parser = build_peg_parser([](common_peg_parser_builder & p) { return p.chars("[a\\-z]"); }); + + common_peg_parse_context ctx; + common_peg_parse_result result; + + ctx = common_peg_parse_context("a"); + result = common_chat_combinator_parser.parse(ctx); + t.assert_equal("escaped_dash_a", true, result.success()); + }); + + // Test escaped dash - '-' should succeed (literal dash) + t.test("escaped_dash_literal", [](testing &t) { + auto common_chat_combinator_parser = build_peg_parser([](common_peg_parser_builder & p) { return p.chars("[a\\-z]"); }); + + common_peg_parse_context ctx; + common_peg_parse_result result; + + ctx = common_peg_parse_context("-"); + result = common_chat_combinator_parser.parse(ctx); + t.assert_equal("escaped_dash_literal", true, result.success()); + }); + + // Test escaped dash - 'z' should succeed + t.test("escaped_dash_z", [](testing &t) { + auto common_chat_combinator_parser = build_peg_parser([](common_peg_parser_builder & p) { return p.chars("[a\\-z]"); }); + + common_peg_parse_context ctx; + common_peg_parse_result result; + + ctx = common_peg_parse_context("z"); + result = common_chat_combinator_parser.parse(ctx); + t.assert_equal("escaped_dash_z", true, result.success()); + }); + + // Test escaped dash - 'b' should NOT match (since \- is literal dash, not range) + t.test("escaped_dash_b_fail", [](testing &t) { + auto common_chat_combinator_parser = build_peg_parser([](common_peg_parser_builder & p) { return p.chars("[a\\-z]"); }); + + common_peg_parse_context ctx; + common_peg_parse_result result; + + ctx = common_peg_parse_context("b"); + result = common_chat_combinator_parser.parse(ctx); + t.assert_equal("escaped_dash_b_fail", true, result.fail()); + }); + }); + + + t.test("optional", [](testing & t) { + // Full match with optional part present + t.test("optional_present", [](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { + return p.literal("hello") + p.optional(p.literal(" world")); + }); + + auto ctx = common_peg_parse_context("hello world"); + auto result = parser.parse(ctx); + t.assert_equal("optional_present", true, result.success()); + t.assert_equal("optional_present_end", 11u, result.end); + }); + + // Full match with optional part absent + t.test("optional_absent", [](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { + return p.literal("hello") + p.optional(p.literal(" world")); + }); + + auto ctx = common_peg_parse_context("hello", false); + auto result = parser.parse(ctx); + t.assert_equal("optional_absent", true, result.success()); + t.assert_equal("optional_absent_end", 5u, result.end); + }); + + // Partial match - waiting for more input to determine if optional matches + t.test("partial_match_need_more", [](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { + return p.literal("hello") + p.optional(p.literal(" world")); + }); + + auto ctx = common_peg_parse_context("hello ", true); + auto result = parser.parse(ctx); + t.assert_equal("partial_match_need_more", true, result.need_more_input()); + }); + }); + + t.test("partial parsing", [](testing & t) { + // Literals - Basic Success + t.test("literal_success", [&](testing & t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { return p.literal("hello"); }); + + common_peg_parse_context ctx; + common_peg_parse_result result; + + ctx = common_peg_parse_context("hello"); + result = parser.parse(ctx); + t.assert_equal("literal_success", true, result.success()); + }); + + // Char Classes - Basic Lowercase Success + t.test("char_class_lowercase_success", [&](testing & t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { return p.chars("a-z"); }); + + common_peg_parse_context ctx; + common_peg_parse_result result; + + ctx = common_peg_parse_context("a"); + result = parser.parse(ctx); + t.assert_equal("char_class_lowercase_success", true, result.success()); + }); + + // Char Classes - Uppercase Fail + t.test("char_class_uppercase_fail", [&](testing & t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { return p.chars("a-z"); }); + + common_peg_parse_context ctx; + common_peg_parse_result result; + + ctx = common_peg_parse_context("A"); + result = parser.parse(ctx); + t.assert_equal("char_class_uppercase_fail", true, result.fail()); + }); + + // Char Classes with Dash - Lowercase Success + t.test("char_class_with_dash_lowercase", [&](testing & t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { return p.chars("a-z-"); }); + + common_peg_parse_context ctx; + common_peg_parse_result result; + + ctx = common_peg_parse_context("f"); + result = parser.parse(ctx); + t.assert_equal("char_class_with_dash_lowercase", true, result.success()); + }); + + // Char Classes with Dash - Literal Dash Success + t.test("char_class_with_dash_literal_dash", [&](testing & t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { return p.chars("a-z-"); }); + + common_peg_parse_context ctx; + common_peg_parse_result result; + + ctx = common_peg_parse_context("-"); + result = parser.parse(ctx); + t.assert_equal("char_class_with_dash_literal_dash", true, result.success()); + }); + + // Char Classes with Dash - Uppercase Fail + t.test("char_class_with_dash_uppercase_fail", [&](testing & t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { return p.chars("a-z-"); }); + + common_peg_parse_context ctx; + common_peg_parse_result result; + + ctx = common_peg_parse_context("A"); + result = parser.parse(ctx); + t.assert_equal("char_class_with_dash_uppercase_fail", true, result.fail()); + }); + + // Sequences - Partial Match 1 + t.test("sequence_partial_match_1", [&](testing & t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { return p.literal("") + p.literal(""); }); + + auto ctx = common_peg_parse_context("") + p.literal(""); }); + + auto ctx = common_peg_parse_context("") + p.literal(""); }); + + auto ctx = common_peg_parse_context("I am common_chat_combinator_parser", true); + auto result = parser.parse(ctx); + t.assert_equal("sequence_no_match", true, result.fail()); + }); + + // Choices - Partial Match 1 + t.test("choices_partial_match_1", [&](testing & t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { return p.literal("option1") | p.literal("option2"); }); + + auto ctx = common_peg_parse_context("opt", true); + auto result = parser.parse(ctx); + t.assert_equal("choices_partial_match_1", true, result.need_more_input()); + }); + + // Choices - Partial Match 2 + t.test("choices_partial_match_2", [&](testing & t) { + auto parser = + build_peg_parser([](common_peg_parser_builder & p) { return p.literal("choice_a") | p.literal("choice_b"); }); + + auto ctx = common_peg_parse_context("choice", true); + auto result = parser.parse(ctx); + t.assert_equal("choices_partial_match_2", true, result.need_more_input()); + }); + + // Choices - Full Match 1 + t.test("choices_full_match_1", [&](testing & t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { return p.literal("first") | p.literal("second"); }); + + auto ctx = common_peg_parse_context("first", false); + auto result = parser.parse(ctx); + t.assert_equal("choices_full_match_1", true, result.success()); + }); + + // Choices - Full Match 2 + t.test("choices_full_match_2", [&](testing & t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { return p.literal("alpha") | p.literal("beta"); }); + + auto ctx = common_peg_parse_context("beta", false); + auto result = parser.parse(ctx); + t.assert_equal("choices_full_match_2", true, result.success()); + }); + + // Choices - No Match + t.test("choices_no_match", [&](testing & t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { return p.literal("good") | p.literal("better"); }); + + auto ctx = common_peg_parse_context("best", false); + auto result = parser.parse(ctx); + t.assert_equal("choices_no_match", true, result.fail()); + }); + + // Zero or More - Partial Match 1 + t.test("zero_or_more_partial_match_1", [&](testing & t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { return p.zero_or_more(p.literal("ab")); }); + + auto ctx = common_peg_parse_context("a", true); + auto result = parser.parse(ctx); + t.assert_equal("zero_or_more_partial_match_1", true, result.need_more_input()); + }); + + // Zero or More - Partial Match 2 + t.test("zero_or_more_partial_match_2", [&](testing & t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { return p.zero_or_more(p.literal("xy")); }); + + auto ctx = common_peg_parse_context("xyx", true); + auto result = parser.parse(ctx); + t.assert_equal("zero_or_more_partial_match_2", true, result.need_more_input()); + }); + + // Zero or More - Full Match + t.test("zero_or_more_full_match", [&](testing & t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { return p.zero_or_more(p.literal("test")); }); + + auto ctx = common_peg_parse_context("test", false); + auto result = parser.parse(ctx); + t.assert_equal("zero_or_more_full_match", true, result.success()); + }); + + // One or More - Partial Match 1 + t.test("one_or_more_partial_match_1", [&](testing & t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { return p.one_or_more(p.literal("repeat")); }); + + auto ctx = common_peg_parse_context("rep", true); + auto result = parser.parse(ctx); + t.assert_equal("one_or_more_partial_match_1", true, result.need_more_input()); + }); + + // One or More - Partial Match 2 + t.test("one_or_more_partial_match_2", [&](testing & t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { return p.one_or_more(p.literal("ab")); }); + + auto ctx = common_peg_parse_context("aba", true); + auto result = parser.parse(ctx); + t.assert_equal("one_or_more_partial_match_2", true, result.need_more_input()); + }); + + // One or More - Full Match + t.test("one_or_more_full_match", [&](testing & t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { return p.one_or_more(p.literal("single")); }); + + auto ctx = common_peg_parse_context("single", false); + auto result = parser.parse(ctx); + t.assert_equal("one_or_more_full_match", true, result.success()); + }); + + // One or More - No Match + t.test("one_or_more_no_match", [&](testing & t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { return p.one_or_more(p.literal("()")); }); + + auto ctx = common_peg_parse_context("success", false); + auto result = parser.parse(ctx); + t.assert_equal("one_or_more_no_match", true, result.fail()); + }); + }); + + + t.test("recursive rules", [](testing &t) { + // Test simple number + t.test("simple_number", [](testing &t) { + auto value_parser = build_peg_parser([](common_peg_parser_builder & p) { + p.rule("number", p.chars("0-9")); + p.rule("list", p.literal("[") + p.ref("value") + p.literal("]")); + return p.rule("value", p.ref("number") | p.ref("list")); + }); + + common_peg_parse_context ctx("1", false); + auto result = value_parser.parse(ctx); + + t.assert_equal("result_is_success", true, result.success()); + }); + + // Test simple list + t.test("simple_list", [](testing &t) { + auto value_parser = build_peg_parser([](common_peg_parser_builder & p) { + p.rule("number", p.chars("0-9")); + p.rule("list", p.literal("[") + p.ref("value") + p.literal("]")); + return p.rule("value", p.ref("number") | p.ref("list")); + }); + + common_peg_parse_context ctx("[1]", false); + auto result = value_parser.parse(ctx); + + t.assert_equal("result_is_success", true, result.success()); + }); + + // Test nested list + t.test("nested_list", [](testing &t) { + auto value_parser = build_peg_parser([](common_peg_parser_builder & p) { + p.rule("number", p.chars("0-9")); + p.rule("list", p.literal("[") + p.ref("value") + p.literal("]")); + return p.rule("value", p.ref("number") | p.ref("list")); + }); + + common_peg_parse_context ctx("[[2]]", false); + auto result = value_parser.parse(ctx); + + t.assert_equal("result_is_success", true, result.success()); + }); + + // Test deeply nested list + t.test("deeply_nested_list", [](testing &t) { + auto value_parser = build_peg_parser([](common_peg_parser_builder & p) { + p.rule("number", p.chars("0-9")); + p.rule("list", p.literal("[") + p.ref("value") + p.literal("]")); + return p.rule("value", p.ref("number") | p.ref("list")); + }); + + common_peg_parse_context ctx("[[[3]]]", false); + auto result = value_parser.parse(ctx); + + t.assert_equal("result_is_success", true, result.success()); + }); + + // Test need_more_input match + t.test("need_more_input_match", [](testing &t) { + auto value_parser = build_peg_parser([](common_peg_parser_builder & p) { + p.rule("number", p.chars("0-9")); + p.rule("list", p.literal("[") + p.ref("value") + p.literal("]")); + return p.rule("value", p.ref("number") | p.ref("list")); + }); + + common_peg_parse_context ctx("[[", true); + auto result = value_parser.parse(ctx); + + t.assert_equal("result_is_need_more_input", true, result.need_more_input()); + }); + + // Test no match + t.test("no_match", [](testing &t) { + auto value_parser = build_peg_parser([](common_peg_parser_builder & p) { + p.rule("number", p.chars("0-9")); + p.rule("list", p.literal("[") + p.ref("value") + p.literal("]")); + return p.rule("value", p.ref("number") | p.ref("list")); + }); + + common_peg_parse_context ctx("[a]", false); + auto result = value_parser.parse(ctx); + + t.assert_equal("result_is_fail", true, result.fail()); + }); + }); +} diff --git a/tests/peg-parser/test-gbnf-generation.cpp b/tests/peg-parser/test-gbnf-generation.cpp new file mode 100644 index 0000000000..68857a5e88 --- /dev/null +++ b/tests/peg-parser/test-gbnf-generation.cpp @@ -0,0 +1,250 @@ +#include "tests.h" + +#include "json-schema-to-grammar.h" + +#include + +static std::string trim_leading_space(const std::string & s) { + static const std::regex leading_ws_re = std::regex(R"((^|\n)\s+)"); + return std::regex_replace(s, leading_ws_re, "$1"); +} + +static void assert_gbnf_equal(testing & t, const std::string & expected, const std::string & actual) { + t.assert_equal("gbnf are equal", trim_leading_space(expected), trim_leading_space(actual)); +} + +void test_gbnf_generation(testing &t) { + t.test("literal grammar generation", [](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { + return p.literal("hello"); + }); + + auto gbnf = build_grammar([&](const common_grammar_builder & builder) { + parser.build_grammar(builder); + }); + + assert_gbnf_equal(t, R"""( + root ::= "hello" + space ::= | " " | "\n"{1,2} [ \t]{0,20} + )""", gbnf); + }); + + t.test("char class grammar", [](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { + return p.chars("[a-z]", 1, 1); + }); + + auto gbnf = build_grammar([&](const common_grammar_builder & builder) { + parser.build_grammar(builder); + }); + + assert_gbnf_equal(t, R"""( + root ::= [a-z] + space ::= | " " | "\n"{1,2} [ \t]{0,20} + )""", gbnf); + }); + + t.test("sequence grammar", [](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { + return p.literal("hello") + p.literal(" ") + p.literal("world"); + }); + + auto gbnf = build_grammar([&](const common_grammar_builder & builder) { + parser.build_grammar(builder); + }); + + assert_gbnf_equal(t, R"""( + root ::= "hello" " " "world" + space ::= | " " | "\n"{1,2} [ \t]{0,20} + )""", gbnf); + }); + + t.test("choice grammar", [](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { + return p.literal("cat") | p.literal("dog"); + }); + + auto gbnf = build_grammar([&](const common_grammar_builder & builder) { + parser.build_grammar(builder); + }); + + assert_gbnf_equal(t, R"""( + root ::= "cat" | "dog" + space ::= | " " | "\n"{1,2} [ \t]{0,20} + )""", gbnf); + }); + + t.test("one_or_more grammar", [](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { + return p.one_or_more(p.literal("a")); + }); + + auto gbnf = build_grammar([&](const common_grammar_builder & builder) { + parser.build_grammar(builder); + }); + + assert_gbnf_equal(t, R"""( + root ::= "a"+ + space ::= | " " | "\n"{1,2} [ \t]{0,20} + )""", gbnf); + }); + + t.test("zero_or_more grammar", [](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { + return p.zero_or_more(p.literal("a")); + }); + + auto gbnf = build_grammar([&](const common_grammar_builder & builder) { + parser.build_grammar(builder); + }); + + assert_gbnf_equal(t, R"""( + root ::= "a"* + space ::= | " " | "\n"{1,2} [ \t]{0,20} + )""", gbnf); + }); + + t.test("optional grammar", [](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { + return p.literal("hello") + p.optional(p.literal(" world")); + }); + + auto gbnf = build_grammar([&](const common_grammar_builder & builder) { + parser.build_grammar(builder); + }); + + assert_gbnf_equal(t, R"""( + root ::= "hello" " world"? + space ::= | " " | "\n"{1,2} [ \t]{0,20} + )""", gbnf); + }); + + t.test("until grammar", [](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { + return p.until(""); + }); + + auto gbnf = build_grammar([&](const common_grammar_builder & builder) { + parser.build_grammar(builder); + }); + + assert_gbnf_equal(t, R"""( + root ::= ([^<] | "<" [^/] | "])* + space ::= | " " | "\n"{1,2} [ \t]{0,20} + )""", gbnf); + }); + + t.test("complex expressions with parentheses", [](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { + return p.one_or_more(p.literal("a") | p.literal("b")); + }); + + auto gbnf = build_grammar([&](const common_grammar_builder & builder) { + parser.build_grammar(builder); + }); + + assert_gbnf_equal(t, R"""( + root ::= ("a" | "b")+ + space ::= | " " | "\n"{1,2} [ \t]{0,20} + )""", gbnf); + }); + + t.test("rule references", [](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { + auto digit = p.rule("digit", p.chars("[0-9]", 1, 1)); + return p.one_or_more(digit); + }); + + auto gbnf = build_grammar([&](const common_grammar_builder & builder) { + parser.build_grammar(builder); + }); + + assert_gbnf_equal(t, R"""( + digit ::= [0-9] + root ::= digit+ + space ::= | " " | "\n"{1,2} [ \t]{0,20} + )""", gbnf); + }); + + t.test("escaping in literals", [](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { + return p.literal("hello\nworld\n!"); + }); + + auto gbnf = build_grammar([&](const common_grammar_builder & builder) { + parser.build_grammar(builder); + }); + + assert_gbnf_equal(t, R"""( + root ::= "hello\nworld\n!" + space ::= | " " | "\n"{1,2} [ \t]{0,20} + )""", gbnf); + }); + + t.test("operator<< (whitespace insertion)", [](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { + return p.literal("hello") << p.literal("world"); + }); + + auto gbnf = build_grammar([&](const common_grammar_builder & builder) { + parser.build_grammar(builder); + }); + + assert_gbnf_equal(t, R"""( + root ::= "hello" space "world" + space ::= | " " | "\n"{1,2} [ \t]{0,20} + )""", gbnf); + }); + + t.test("emit only reachable rules", [](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { + p.rule("orphan", p.literal("orphan")); + return p.literal("hello") + p.rule("child", p.literal(" world")); + }); + + auto gbnf = build_grammar([&](const common_grammar_builder & builder) { + parser.build_grammar(builder); + }); + + assert_gbnf_equal(t, R"""( + child ::= " world" + root ::= "hello" child + space ::= | " " | "\n"{1,2} [ \t]{0,20} + )""", gbnf); + }); + + t.test("emit only trigger rules (and references)", [](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { + auto rule1 = p.rule("rule-1", p.literal("a") + p.ref("rule-2")); + p.rule("rule-2", p.literal("b") + p.ref("rule-3"), true); + p.rule("rule-3", p.literal("c") + p.ref("rule-4")); + p.rule("rule-4", p.literal("d"), true); + return rule1; + }); + + auto gbnf = build_grammar([&](const common_grammar_builder & builder) { + parser.build_grammar(builder); + }); + + assert_gbnf_equal(t, R"""( + root ::= rule-1 + rule-1 ::= "a" rule-2 + rule-2 ::= "b" rule-3 + rule-3 ::= "c" rule-4 + rule-4 ::= "d" + space ::= | " " | "\n"{1,2} [ \t]{0,20} + )""", gbnf); + + auto gbnf_lazy = build_grammar([&](const common_grammar_builder & builder) { + parser.build_grammar(builder, true); + }); + + assert_gbnf_equal(t, R"""( + root ::= rule-2 | rule-4 + rule-2 ::= "b" rule-3 + rule-3 ::= "c" rule-4 + rule-4 ::= "d" + space ::= | " " | "\n"{1,2} [ \t]{0,20} + )""", gbnf_lazy); + }); +} diff --git a/tests/peg-parser/test-json-parser.cpp b/tests/peg-parser/test-json-parser.cpp new file mode 100644 index 0000000000..48351cd66f --- /dev/null +++ b/tests/peg-parser/test-json-parser.cpp @@ -0,0 +1,109 @@ +#include "tests.h" + +void test_json_parser(testing &t) { + // Test parsing a simple JSON object + t.test("simple JSON object parsing", [](testing &t) { + auto json = build_peg_parser([](common_peg_parser_builder & p) { return p.json(); }); + + std::string input = R"({"name": "test", "value": 42, "flag": true})"; + common_peg_parse_context ctx(input); + + auto result = json.parse(ctx); + + t.assert_equal("result_is_success", true, result.success()); + t.assert_equal("result_end", input.size(), result.end); + }); + + // Test parsing a JSON array with mixed types + t.test("JSON array with mixed types", [](testing &t) { + auto json = build_peg_parser([](common_peg_parser_builder & p) { return p.json(); }); + + std::string input = R"([1, "hello", true, null, 3.14])"; + common_peg_parse_context ctx(input); + + auto result = json.parse(ctx); + + t.assert_equal("result_is_success", true, result.success()); + t.assert_equal("result_end", input.size(), result.end); + }); + + // Test parsing nested JSON with objects and arrays + t.test("nested JSON with objects and arrays", [](testing &t) { + auto json = build_peg_parser([](common_peg_parser_builder & p) { return p.json(); }); + + std::string input = + R"({"users": [{"id": 1, "name": "Alice"}, {"id": 2, "name": "Bob"}], "count": 2, "metadata": {"version": "1.0", "tags": ["admin", "user"]}})"; + common_peg_parse_context ctx(input); + + auto result = json.parse(ctx); + + t.assert_equal("result_is_success", true, result.success()); + t.assert_equal("result_end", input.size(), result.end); + }); + + // Test need_more_input() parsing - incomplete object + t.test("need_more_input() parsing - incomplete object", [](testing &t) { + auto json = build_peg_parser([](common_peg_parser_builder & p) { return p.json(); }); + + std::string input = R"({"name": "test", "value": )"; + common_peg_parse_context ctx(input, true); + + auto result = json.parse(ctx); + + t.assert_equal("result_is_need_more_input", true, result.need_more_input()); + }); + + // Test need_more_input() parsing - incomplete array + t.test("need_more_input() parsing - incomplete array", [](testing &t) { + auto json = build_peg_parser([](common_peg_parser_builder & p) { return p.json(); }); + + std::string input = R"([1, 2, 3, )"; + common_peg_parse_context ctx(input, true); + + auto result = json.parse(ctx); + + t.assert_equal("result_is_need_more_input", true, result.need_more_input()); + }); + + // Test need_more_input() parsing - incomplete nested structure + t.test("need_more_input() parsing - incomplete nested structure", [](testing &t) { + auto json = build_peg_parser([](common_peg_parser_builder & p) { return p.json(); }); + + std::string input = R"({"data": {"nested": )"; + common_peg_parse_context ctx(input, true); + + auto result = json.parse(ctx); + + t.assert_equal("result_is_need_more_input", true, result.need_more_input()); + }); + + t.test("object member", [](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder & p) { + return p.json_member("name", "\"" + p.chars("[a-z]") + "\""); + }); + + t.test("success", [&](testing &t) { + std::string input = R"("name": "bob")"; + common_peg_parse_context ctx(input, false); + + auto result = parser.parse(ctx); + t.assert_true("success", result.success()); + }); + + t.test("partial", [&](testing &t) { + std::string input = R"("name": "bo)"; + common_peg_parse_context ctx(input, true); + + auto result = parser.parse(ctx); + t.assert_true("need more input", result.need_more_input()); + }); + + t.test("failed", [&](testing &t) { + std::string input = R"([])"; + common_peg_parse_context ctx(input, false); + + auto result = parser.parse(ctx); + t.assert_true("fail", result.fail()); + }); + }); +} diff --git a/tests/peg-parser/test-json-serialization.cpp b/tests/peg-parser/test-json-serialization.cpp new file mode 100644 index 0000000000..a85801060c --- /dev/null +++ b/tests/peg-parser/test-json-serialization.cpp @@ -0,0 +1,28 @@ +#include "tests.h" + +void test_json_serialization(testing &t) { + auto original = build_peg_parser([](common_peg_parser_builder & p) { + return "" + p.json() + ""; + }); + + auto json_serialized = original.to_json().dump(); + + t.test("compare before/after", [&](testing &t) { + auto deserialized = common_peg_arena::from_json(nlohmann::json::parse(json_serialized)); + + // Test complex JSON + std::string input = R"({"name": "test", "values": [1, 2, 3], "nested": {"a": true}})"; + common_peg_parse_context ctx1(input); + common_peg_parse_context ctx2(input); + + auto result1 = original.parse(ctx1); + auto result2 = deserialized.parse(ctx2); + + t.assert_equal("both_succeed", result1.success(), result2.success()); + t.assert_equal("same_end_pos", result1.end, result2.end); + }); + + t.bench("deserialize", [&]() { + auto deserialized = common_peg_arena::from_json(nlohmann::json::parse(json_serialized)); + }, 100); +} diff --git a/tests/peg-parser/test-unicode.cpp b/tests/peg-parser/test-unicode.cpp new file mode 100644 index 0000000000..19d9b9e41c --- /dev/null +++ b/tests/peg-parser/test-unicode.cpp @@ -0,0 +1,449 @@ +#include "tests.h" + +#include "peg-parser.h" + +#include +#include +#include +#include + +static void assert_result_equal(testing & t, common_peg_parse_result_type expected, common_peg_parse_result_type actual) { + t.assert_equal(common_peg_parse_result_type_name(expected), common_peg_parse_result_type_name(actual)); +} + +static std::string hex_dump(const std::string& str) { + std::ostringstream oss; + for (unsigned char c : str) { + if (std::isprint(c)) { + oss << c; + } else { + oss << "\\x" << std::hex << std::setw(2) << std::setfill('0') << static_cast(c); + } + } + return oss.str(); +} + +void test_unicode(testing &t) { + struct test_case { + std::string input; + std::string expected_text; + common_peg_parse_result_type expected_result; + }; + + t.test("any", [](testing &t) { + std::vector test_cases { + // Valid UTF-8 sequences + {"Hello", "Hello", COMMON_PEG_PARSE_RESULT_SUCCESS}, + {std::string("Caf\xC3\xA9"), std::string("Caf\xC3\xA9"), COMMON_PEG_PARSE_RESULT_SUCCESS}, + {std::string("\xE4\xBD\xA0\xE5\xA5\xBD"), std::string("\xE4\xBD\xA0\xE5\xA5\xBD"), COMMON_PEG_PARSE_RESULT_SUCCESS}, + {std::string("\xF0\x9F\x9A\x80"), std::string("\xF0\x9F\x9A\x80"), COMMON_PEG_PARSE_RESULT_SUCCESS}, + + // Incomplete UTF-8 sequences (partial bytes at end) + {std::string("Caf\xC3"), "Caf", COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT}, + {std::string("\xE4\xBD"), "", COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT}, + {std::string("\xF0\x9F\x9A"), "", COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT}, + + // Invalid/malformed UTF-8 sequences + {std::string("\xFF\xFE"), "", COMMON_PEG_PARSE_RESULT_FAIL}, + {std::string("Hello\x80World"), "Hello", COMMON_PEG_PARSE_RESULT_FAIL}, + {std::string("\xC3\x28"), "", COMMON_PEG_PARSE_RESULT_FAIL}, + }; + + auto parser = build_peg_parser([](common_peg_parser_builder& p) { + return p.sequence({p.one_or_more(p.any()), p.end()}); + }); + + for (size_t i = 0; i < test_cases.size(); i++) { + const auto & tc = test_cases[i]; + std::string test_name = "case " + std::to_string(i) + ": " + hex_dump(tc.input); + + t.test(test_name, [&](testing &t) { + common_peg_parse_context ctx(tc.input, true); + auto result = parser.parse(ctx); + + // Assert result type matches + assert_result_equal(t, tc.expected_result, result.type); + + // Assert matched text if success or need_more_input + if (result.success() || result.need_more_input()) { + std::string matched = tc.input.substr(result.start, result.end - result.start); + t.assert_equal(tc.expected_text, matched); + } + }); + } + }); + + t.test("char classes", [](testing &t) { + t.test("unicode range U+4E00-U+9FFF (CJK)", [](testing &t) { + std::vector test_cases { + // Within range - CJK Unified Ideographs + {std::string("\xE4\xB8\x80"), std::string("\xE4\xB8\x80"), COMMON_PEG_PARSE_RESULT_SUCCESS}, // U+4E00 + {std::string("\xE4\xBD\xA0"), std::string("\xE4\xBD\xA0"), COMMON_PEG_PARSE_RESULT_SUCCESS}, // U+4F60 + {std::string("\xE5\xA5\xBD"), std::string("\xE5\xA5\xBD"), COMMON_PEG_PARSE_RESULT_SUCCESS}, // U+597D + {std::string("\xE9\xBF\xBF"), std::string("\xE9\xBF\xBF"), COMMON_PEG_PARSE_RESULT_SUCCESS}, // U+9FFF + + // Outside range - should fail + {"a", "", COMMON_PEG_PARSE_RESULT_FAIL}, // ASCII + {std::string("\xE4\xB7\xBF"), "", COMMON_PEG_PARSE_RESULT_FAIL}, // U+4DFF (before range) + {std::string("\xEA\x80\x80"), "", COMMON_PEG_PARSE_RESULT_FAIL}, // U+A000 (after range) + + // Incomplete sequences in range + {std::string("\xE4\xB8"), "", COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT}, // Incomplete U+4E00 + {std::string("\xE5\xA5"), "", COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT}, // Incomplete U+597D + }; + + auto parser = build_peg_parser([](common_peg_parser_builder& p) { + return p.sequence({p.chars(R"([\u4E00-\u9FFF])"), p.end()}); + }); + + for (size_t i = 0; i < test_cases.size(); i++) { + const auto & tc = test_cases[i]; + std::string test_name = "case " + std::to_string(i) + ": " + hex_dump(tc.input); + + t.test(test_name, [&](testing &t) { + common_peg_parse_context ctx(tc.input, true); + auto result = parser.parse(ctx); + + // Assert result type matches + assert_result_equal(t, tc.expected_result, result.type); + + // Assert matched text if success or need_more_input + if (result.success() || result.need_more_input()) { + std::string matched = tc.input.substr(result.start, result.end - result.start); + t.assert_equal(tc.expected_text, matched); + } + }); + } + }); + + t.test("unicode range U+1F600-U+1F64F (emoticons)", [](testing &t) { + std::vector test_cases { + // Within range - Emoticons (all 4-byte UTF-8) + {std::string("\xF0\x9F\x98\x80"), std::string("\xF0\x9F\x98\x80"), COMMON_PEG_PARSE_RESULT_SUCCESS}, // U+1F600 + {std::string("\xF0\x9F\x98\x81"), std::string("\xF0\x9F\x98\x81"), COMMON_PEG_PARSE_RESULT_SUCCESS}, // U+1F601 + {std::string("\xF0\x9F\x99\x8F"), std::string("\xF0\x9F\x99\x8F"), COMMON_PEG_PARSE_RESULT_SUCCESS}, // U+1F64F + + // Outside range + {std::string("\xF0\x9F\x97\xBF"), "", COMMON_PEG_PARSE_RESULT_FAIL}, // U+1F5FF (before range) + {std::string("\xF0\x9F\x99\x90"), "", COMMON_PEG_PARSE_RESULT_FAIL}, // U+1F650 (after range) + {std::string("\xF0\x9F\x9A\x80"), "", COMMON_PEG_PARSE_RESULT_FAIL}, // U+1F680 (outside range) + + // Incomplete sequences + {std::string("\xF0\x9F\x98"), "", COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT}, // Incomplete emoji + {std::string("\xF0\x9F"), "", COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT}, // Very incomplete + }; + + auto parser = build_peg_parser([](common_peg_parser_builder& p) { + return p.sequence({p.chars(R"([\U0001F600-\U0001F64F])"), p.end()}); + }); + + for (size_t i = 0; i < test_cases.size(); i++) { + const auto & tc = test_cases[i]; + std::string test_name = "case " + std::to_string(i) + ": " + hex_dump(tc.input); + + t.test(test_name, [&](testing &t) { + common_peg_parse_context ctx(tc.input, true); + auto result = parser.parse(ctx); + + // Assert result type matches + assert_result_equal(t, tc.expected_result, result.type); + + // Assert matched text if success or need_more_input + if (result.success() || result.need_more_input()) { + std::string matched = tc.input.substr(result.start, result.end - result.start); + t.assert_equal(tc.expected_text, matched); + } + }); + } + }); + + t.test("mixed unicode ranges", [](testing &t) { + std::vector test_cases { + // Match CJK + {std::string("\xE4\xB8\x80"), std::string("\xE4\xB8\x80"), COMMON_PEG_PARSE_RESULT_SUCCESS}, // U+4E00 + {std::string("\xE4\xBD\xA0"), std::string("\xE4\xBD\xA0"), COMMON_PEG_PARSE_RESULT_SUCCESS}, // U+4F60 + + // Match emoticons + {std::string("\xF0\x9F\x98\x80"), std::string("\xF0\x9F\x98\x80"), COMMON_PEG_PARSE_RESULT_SUCCESS}, // U+1F600 + + // Match ASCII digits + {"5", "5", COMMON_PEG_PARSE_RESULT_SUCCESS}, + + // Don't match outside any range + {"a", "", COMMON_PEG_PARSE_RESULT_FAIL}, + {std::string("\xF0\x9F\x9A\x80"), "", COMMON_PEG_PARSE_RESULT_FAIL}, // U+1F680 + + // Incomplete + {std::string("\xE4\xB8"), "", COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT}, + {std::string("\xF0\x9F\x98"), "", COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT}, + }; + + auto parser = build_peg_parser([](common_peg_parser_builder& p) { + return p.sequence({p.chars(R"([\u4E00-\u9FFF\U0001F600-\U0001F64F0-9])"), p.end()}); + }); + + for (size_t i = 0; i < test_cases.size(); i++) { + const auto & tc = test_cases[i]; + std::string test_name = "case " + std::to_string(i) + ": " + hex_dump(tc.input); + + t.test(test_name, [&](testing &t) { + common_peg_parse_context ctx(tc.input, true); + auto result = parser.parse(ctx); + + // Assert result type matches + assert_result_equal(t, tc.expected_result, result.type); + + // Assert matched text if success or need_more_input + if (result.success() || result.need_more_input()) { + std::string matched = tc.input.substr(result.start, result.end - result.start); + t.assert_equal(tc.expected_text, matched); + } + }); + } + }); + }); + + t.test("until parser", [](testing &t) { + t.test("ASCII delimiter with Unicode content", [](testing &t) { + std::vector test_cases { + // CJK characters before delimiter + {std::string("\xE4\xBD\xA0\xE5\xA5\xBD"), std::string("\xE4\xBD\xA0\xE5\xA5\xBD"), COMMON_PEG_PARSE_RESULT_SUCCESS}, + + // Emoji before delimiter + {std::string("\xF0\x9F\x98\x80"), std::string("\xF0\x9F\x98\x80"), COMMON_PEG_PARSE_RESULT_SUCCESS}, + + // Mixed content + {std::string("Hello \xE4\xB8\x96\xE7\x95\x8C!"), std::string("Hello \xE4\xB8\x96\xE7\x95\x8C!"), COMMON_PEG_PARSE_RESULT_SUCCESS}, + }; + + auto parser = build_peg_parser([](common_peg_parser_builder& p) { + return p.until(""); + }); + + for (size_t i = 0; i < test_cases.size(); i++) { + const auto & tc = test_cases[i]; + std::string test_name = "case " + std::to_string(i) + ": " + hex_dump(tc.input); + + t.test(test_name, [&](testing &t) { + common_peg_parse_context ctx(tc.input, false); + auto result = parser.parse(ctx); + + assert_result_equal(t, tc.expected_result, result.type); + + if (result.success()) { + std::string matched = tc.input.substr(result.start, result.end - result.start); + t.assert_equal(tc.expected_text, matched); + } + }); + } + }); + + t.test("incomplete UTF-8 at end", [](testing &t) { + std::vector test_cases { + // Incomplete emoji at end, no delimiter + {std::string("content\xF0\x9F\x98"), std::string("content"), COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT}, + + // Incomplete CJK at end, no delimiter + {std::string("hello\xE4\xB8"), std::string("hello"), COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT}, + + // Complete content, no delimiter (should consume all valid UTF-8) + {std::string("\xE4\xBD\xA0\xE5\xA5\xBD"), std::string("\xE4\xBD\xA0\xE5\xA5\xBD"), COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT}, + }; + + auto parser = build_peg_parser([](common_peg_parser_builder& p) { + return p.until(""); + }); + + for (size_t i = 0; i < test_cases.size(); i++) { + const auto & tc = test_cases[i]; + std::string test_name = "case " + std::to_string(i) + ": " + hex_dump(tc.input); + + t.test(test_name, [&](testing &t) { + common_peg_parse_context ctx(tc.input, true); + auto result = parser.parse(ctx); + + assert_result_equal(t, tc.expected_result, result.type); + + if (result.success() || result.need_more_input()) { + std::string matched = tc.input.substr(result.start, result.end - result.start); + t.assert_equal(tc.expected_text, matched); + } + }); + } + }); + + t.test("malformed UTF-8", [](testing &t) { + std::vector test_cases { + // Invalid UTF-8 bytes + {std::string("Hello\xFF\xFE"), "", COMMON_PEG_PARSE_RESULT_FAIL}, + + // Continuation byte without lead byte + {std::string("Hello\x80World"), "", COMMON_PEG_PARSE_RESULT_FAIL}, + + // Invalid continuation byte + {std::string("\xC3\x28"), "", COMMON_PEG_PARSE_RESULT_FAIL}, + }; + + auto parser = build_peg_parser([](common_peg_parser_builder& p) { + return p.until(""); + }); + + for (size_t i = 0; i < test_cases.size(); i++) { + const auto & tc = test_cases[i]; + std::string test_name = "case " + std::to_string(i) + ": " + hex_dump(tc.input); + + t.test(test_name, [&](testing &t) { + common_peg_parse_context ctx(tc.input, false); + auto result = parser.parse(ctx); + + assert_result_equal(t, tc.expected_result, result.type); + }); + } + }); + }); + + t.test("json_string parser", [](testing &t) { + t.test("valid UTF-8 characters", [](testing &t) { + std::vector test_cases { + // ASCII only + {"Hello World\"", "Hello World", COMMON_PEG_PARSE_RESULT_SUCCESS}, + + // 2-byte UTF-8 (accented characters) + {std::string("Caf\xC3\xA9\""), std::string("Caf\xC3\xA9"), COMMON_PEG_PARSE_RESULT_SUCCESS}, + + // 3-byte UTF-8 (CJK) + {std::string("\xE4\xBD\xA0\xE5\xA5\xBD\""), std::string("\xE4\xBD\xA0\xE5\xA5\xBD"), COMMON_PEG_PARSE_RESULT_SUCCESS}, + + // 4-byte UTF-8 (emoji) + {std::string("\xF0\x9F\x98\x80\""), std::string("\xF0\x9F\x98\x80"), COMMON_PEG_PARSE_RESULT_SUCCESS}, + + // Mixed content + {std::string("Hello \xE4\xB8\x96\xE7\x95\x8C!\""), std::string("Hello \xE4\xB8\x96\xE7\x95\x8C!"), COMMON_PEG_PARSE_RESULT_SUCCESS}, + }; + + for (size_t i = 0; i < test_cases.size(); i++) { + const auto & tc = test_cases[i]; + std::string test_name = "case " + std::to_string(i) + ": " + hex_dump(tc.input); + + t.test(test_name, [&](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder& p) { + return p.sequence({p.json_string_content(), p.literal("\"")}); + }); + + common_peg_parse_context ctx(tc.input, false); + auto result = parser.parse(ctx); + + assert_result_equal(t, tc.expected_result, result.type); + + if (result.success()) { + std::string matched = tc.input.substr(result.start, result.end - result.start - 1); // -1 to exclude closing quote + t.assert_equal(tc.expected_text, matched); + } + }); + } + }); + + t.test("incomplete UTF-8", [](testing &t) { + std::vector test_cases { + // Incomplete 2-byte sequence + {std::string("Caf\xC3"), std::string("Caf"), COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT}, + + // Incomplete 3-byte sequence + {std::string("Hello\xE4\xB8"), std::string("Hello"), COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT}, + + // Incomplete 4-byte sequence + {std::string("Text\xF0\x9F\x98"), std::string("Text"), COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT}, + + // Incomplete at very start + {std::string("\xE4\xBD"), std::string(""), COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT}, + }; + + for (size_t i = 0; i < test_cases.size(); i++) { + const auto & tc = test_cases[i]; + std::string test_name = "case " + std::to_string(i) + ": " + hex_dump(tc.input); + + t.test(test_name, [&](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder& p) { + return p.json_string_content(); + }); + + common_peg_parse_context ctx(tc.input, true); + auto result = parser.parse(ctx); + + assert_result_equal(t, tc.expected_result, result.type); + + if (result.need_more_input()) { + std::string matched = tc.input.substr(result.start, result.end - result.start); + t.assert_equal(tc.expected_text, matched); + } + }); + } + }); + + t.test("malformed UTF-8", [](testing &t) { + std::vector test_cases { + // Invalid UTF-8 bytes + {std::string("Hello\xFF\xFE"), "", COMMON_PEG_PARSE_RESULT_FAIL}, + + // Continuation byte without lead byte + {std::string("Hello\x80World"), "", COMMON_PEG_PARSE_RESULT_FAIL}, + + // Invalid continuation byte + {std::string("\xC3\x28"), "", COMMON_PEG_PARSE_RESULT_FAIL}, + + // Overlong encoding (security issue) + {std::string("\xC0\x80"), "", COMMON_PEG_PARSE_RESULT_FAIL}, + }; + + for (size_t i = 0; i < test_cases.size(); i++) { + const auto & tc = test_cases[i]; + std::string test_name = "case " + std::to_string(i) + ": " + hex_dump(tc.input); + + t.test(test_name, [&](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder& p) { + return p.json_string_content(); + }); + + common_peg_parse_context ctx(tc.input, false); + auto result = parser.parse(ctx); + + assert_result_equal(t, tc.expected_result, result.type); + }); + } + }); + + t.test("escape sequences with UTF-8", [](testing &t) { + std::vector test_cases { + // Unicode escape sequence + {"Hello\\u0041\"", "Hello\\u0041", COMMON_PEG_PARSE_RESULT_SUCCESS}, + + // Mix of UTF-8 and escape sequences + {std::string("\xE4\xBD\xA0\\n\xE5\xA5\xBD\""), std::string("\xE4\xBD\xA0\\n\xE5\xA5\xBD"), COMMON_PEG_PARSE_RESULT_SUCCESS}, + + // Escaped quote in UTF-8 string + {std::string("\xE4\xBD\xA0\\\"\xE5\xA5\xBD\""), std::string("\xE4\xBD\xA0\\\"\xE5\xA5\xBD"), COMMON_PEG_PARSE_RESULT_SUCCESS}, + }; + + for (size_t i = 0; i < test_cases.size(); i++) { + const auto & tc = test_cases[i]; + std::string test_name = "case " + std::to_string(i) + ": " + hex_dump(tc.input); + + t.test(test_name, [&](testing &t) { + auto parser = build_peg_parser([](common_peg_parser_builder& p) { + return p.sequence({p.json_string_content(), p.literal("\"")}); + }); + + common_peg_parse_context ctx(tc.input, false); + auto result = parser.parse(ctx); + + assert_result_equal(t, tc.expected_result, result.type); + + if (result.success()) { + std::string matched = tc.input.substr(result.start, result.end - result.start - 1); // -1 to exclude closing quote + t.assert_equal(tc.expected_text, matched); + } + }); + } + }); + }); +} diff --git a/tests/peg-parser/testing.h b/tests/peg-parser/testing.h new file mode 100644 index 0000000000..45ac4ca784 --- /dev/null +++ b/tests/peg-parser/testing.h @@ -0,0 +1,243 @@ +#pragma once + +#include "common.h" + +#include +#include +#include +#include +#include +#include + +struct testing { + std::ostream &out; + std::vector stack; + std::regex filter; + bool filter_tests = false; + bool throw_exception = false; + bool verbose = false; + int tests = 0; + int assertions = 0; + int failures = 0; + int unnamed = 0; + int exceptions = 0; + + static constexpr std::size_t status_column = 80; + + explicit testing(std::ostream &os = std::cout) : out(os) {} + + std::string indent() const { + if (stack.empty()) { + return ""; + } + return std::string((stack.size() - 1) * 2, ' '); + } + + std::string full_name() const { + return string_join(stack, "."); + } + + void log(const std::string & msg) { + if (verbose) { + out << indent() << " " << msg << "\n"; + } + } + + void set_filter(const std::string & re) { + filter = std::regex(re); + filter_tests = true; + } + + bool should_run() const { + if (filter_tests) { + if (!std::regex_match(full_name(), filter)) { + return false; + } + } + return true; + } + + template + void run_with_exceptions(F &&f, const char *ctx) { + try { + f(); + } catch (const std::exception &e) { + ++failures; + ++exceptions; + out << indent() << "UNHANDLED EXCEPTION (" << ctx << "): " << e.what() << "\n"; + if (throw_exception) { + throw; + } + } catch (...) { + ++failures; + ++exceptions; + out << indent() << "UNHANDLED EXCEPTION (" << ctx << "): unknown\n"; + if (throw_exception) { + throw; + } + } + } + + void print_result(const std::string &label, int new_failures, int new_assertions, const std::string &extra = "") const { + std::string line = indent() + label; + + std::string details; + if (new_assertions > 0) { + if (new_failures == 0) { + details = std::to_string(new_assertions) + " assertion(s)"; + } else { + details = std::to_string(new_failures) + " of " + + std::to_string(new_assertions) + " assertion(s) failed"; + } + } + if (!extra.empty()) { + if (!details.empty()) { + details += ", "; + } + details += extra; + } + + if (!details.empty()) { + line += " (" + details + ")"; + } + + std::string status = (new_failures == 0) ? "[PASS]" : "[FAIL]"; + + if (line.size() + 1 < status_column) { + line.append(status_column - line.size(), ' '); + } else { + line.push_back(' '); + } + + out << line << status << "\n"; + } + + template + void test(const std::string &name, F f) { + stack.push_back(name); + if (!should_run()) { + stack.pop_back(); + return; + } + + ++tests; + out << indent() << name << "\n"; + + int before_failures = failures; + int before_assertions = assertions; + + run_with_exceptions([&] { f(*this); }, "test"); + + int new_failures = failures - before_failures; + int new_assertions = assertions - before_assertions; + + print_result(name, new_failures, new_assertions); + + stack.pop_back(); + } + + template + void test(F f) { + test("test #" + std::to_string(++unnamed), f); + } + + template + void bench(const std::string &name, F f, int iterations = 100) { + stack.push_back(name); + if (!should_run()) { + stack.pop_back(); + return; + } + + ++tests; + out << indent() << "[bench] " << name << "\n"; + + int before_failures = failures; + int before_assertions = assertions; + + using clock = std::chrono::high_resolution_clock; + + std::chrono::microseconds duration(0); + + run_with_exceptions([&] { + for (auto i = 0; i < iterations; i++) { + auto start = clock::now(); + f(); + duration += std::chrono::duration_cast(clock::now() - start); + } + }, "bench"); + + auto avg_elapsed = duration.count() / iterations; + auto avg_elapsed_s = std::chrono::duration_cast>(duration).count() / iterations; + auto rate = (avg_elapsed_s > 0.0) ? (1.0 / avg_elapsed_s) : 0.0; + + int new_failures = failures - before_failures; + int new_assertions = assertions - before_assertions; + + std::string extra = + "n=" + std::to_string(iterations) + + " avg=" + std::to_string(avg_elapsed) + "us" + + " rate=" + std::to_string(int(rate)) + "/s"; + + print_result("[bench] " + name, new_failures, new_assertions, extra); + + stack.pop_back(); + } + + template + void bench(F f, int iterations = 100) { + bench("bench #" + std::to_string(++unnamed), f, iterations); + } + + // Assertions + bool assert_true(bool cond) { + return assert_true("", cond); + } + + bool assert_true(const std::string &msg, bool cond) { + ++assertions; + if (!cond) { + ++failures; + out << indent() << "ASSERT TRUE FAILED"; + if (!msg.empty()) { + out << " : " << msg; + } + out << "\n"; + return false; + } + return true; + } + + template + bool assert_equal(const A &expected, const B &actual) { + return assert_equal("", expected, actual); + } + + template + bool assert_equal(const std::string &msg, const A &expected, const B &actual) { + ++assertions; + if (!(actual == expected)) { + ++failures; + out << indent() << "ASSERT EQUAL FAILED"; + if (!msg.empty()) { + out << " : " << msg; + } + out << "\n"; + + out << indent() << " expected: " << expected << "\n"; + out << indent() << " actual : " << actual << "\n"; + return false; + } + return true; + } + + // Print summary and return an exit code + int summary() const { + out << "\n"; + out << "tests : " << tests << "\n"; + out << "assertions : " << assertions << "\n"; + out << "failures : " << failures << "\n"; + out << "exceptions : " << exceptions << "\n"; + return failures == 0 ? 0 : 1; + } +}; diff --git a/tests/peg-parser/tests.h b/tests/peg-parser/tests.h new file mode 100644 index 0000000000..25727682c8 --- /dev/null +++ b/tests/peg-parser/tests.h @@ -0,0 +1,24 @@ +#pragma once + +// Common includes for all test files +#include +#include +#include + +#include "testing.h" +#include "peg-parser.h" +#include "chat-peg-parser.h" +#include "simple-tokenize.h" + +struct bench_tool_call { + std::string id; + std::string name; + nlohmann::ordered_json args; +}; + +// Test function declarations +void test_basic(testing &t); +void test_json_parser(testing &t); +void test_gbnf_generation(testing &t); +void test_unicode(testing &t); +void test_json_serialization(testing &t); diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp index 9645d0b390..2e94a53da2 100644 --- a/tests/test-backend-ops.cpp +++ b/tests/test-backend-ops.cpp @@ -41,12 +41,18 @@ #include #include +#ifdef __EMSCRIPTEN__ +# define N_THREADS 1 +#else +# define N_THREADS std::thread::hardware_concurrency() +#endif + static void init_tensor_uniform(ggml_tensor * tensor, float min = -1.0f, float max = 1.0f) { size_t nels = ggml_nelements(tensor); std::vector data(nels); { // parallel initialization - static const size_t n_threads = std::thread::hardware_concurrency(); + static const size_t n_threads = N_THREADS; // static RNG initialization (revisit if n_threads stops being constant) static std::vector generators = []() { std::random_device rd; @@ -65,15 +71,19 @@ static void init_tensor_uniform(ggml_tensor * tensor, float min = -1.0f, float m } }; - std::vector> tasks; - tasks.reserve(n_threads); - for (size_t i = 0; i < n_threads; i++) { - size_t start = i*nels/n_threads; - size_t end = (i+1)*nels/n_threads; - tasks.push_back(std::async(std::launch::async, init_thread, i, start, end)); - } - for (auto & t : tasks) { - t.get(); + if (n_threads == 1) { + init_thread(0, 0, nels); + } else { + std::vector> tasks; + tasks.reserve(n_threads); + for (size_t i = 0; i < n_threads; i++) { + size_t start = i*nels/n_threads; + size_t end = (i+1)*nels/n_threads; + tasks.push_back(std::async(std::launch::async, init_thread, i, start, end)); + } + for (auto & t : tasks) { + t.get(); + } } } @@ -105,17 +115,23 @@ static void init_tensor_uniform(ggml_tensor * tensor, float min = -1.0f, float m }; const size_t min_blocks_per_thread = 1; - const size_t n_threads = std::min(std::thread::hardware_concurrency()/2, - std::max(1, n_blocks / min_blocks_per_thread)); - std::vector> tasks; - tasks.reserve(n_threads); - for (size_t i = 0; i < n_threads; i++) { - size_t start = i*n_blocks/n_threads; - size_t end = (i+1)*n_blocks/n_threads; - tasks.push_back(std::async(std::launch::async, quantize_thread, start, end)); - } - for (auto & t : tasks) { - t.get(); + const size_t n_quant_threads = std::min(std::max(N_THREADS/2, 1), + std::max(1, n_blocks / min_blocks_per_thread)); + + if (n_quant_threads == 1) { + // single-threaded quantization: do all blocks in the current thread + quantize_thread(0, n_blocks); + } else { + std::vector> tasks; + tasks.reserve(n_quant_threads); + for (size_t i = 0; i < n_quant_threads; i++) { + size_t start = i*n_blocks/n_quant_threads; + size_t end = (i+1)*n_blocks/n_quant_threads; + tasks.push_back(std::async(std::launch::async, quantize_thread, start, end)); + } + for (auto & t : tasks) { + t.get(); + } } } ggml_backend_tensor_set(tensor, dataq.data(), 0, dataq.size()); @@ -270,10 +286,11 @@ static double nmse(const float * a, const float * b, size_t n) { return mse_a_b / mse_a_0; } -// difference between 2 integer sets (Jaccard distance, 0 - no difference, 1 - no overlap) -static double jdst(const int32_t * a, const int32_t * b, size_t n) { - std::unordered_map set_a; - std::unordered_map set_b; +// difference between 2 sets (Jaccard distance, 0 - no difference, 1 - no overlap) +template +static double jdst(const T * a, const T * b, size_t n) { + std::unordered_map set_a; + std::unordered_map set_b; for (size_t i = 0; i < n; ++i) { set_a[a[i]]++; @@ -4985,42 +5002,94 @@ struct test_top_k : public test_case { const ggml_type type; const std::array ne; const int k; + const bool ties; + ggml_tensor * input {}; std::string vars() override { - return VARS_TO_STR3(type, ne, k); + return VARS_TO_STR4(type, ne, k, ties); } test_top_k(ggml_type type = GGML_TYPE_F32, std::array ne = {16, 10, 10, 10}, - int k = 4) - : type(type), ne(ne), k(k) {} + int k = 4, bool ties = false) + : type(type), ne(ne), k(k), ties(ties) {} double max_err() override { return 0.0; } + // When there are ties, only validate the final result. + // The logic in err can't handle the sentinel tensors. + bool run_whole_graph() override { return ties; } + double err(const float * a, const float * b, size_t n) override { - std::vector ia(n); - std::vector ib(n); + // When there are no ties, we expect the exact same set of indices, + // but possibly in a different order. When there are ties, the indices + // can be different but the input values they correspond to should be + // the same. The logic for ties could work for non-ties, but only for + // the output tensor, not for the sentinel tensors. + if (ties) { + std::vector src(ggml_nelements(input)); - double diff = 0.0f; + ggml_backend_tensor_get(input, src.data(), 0, ggml_nelements(input) * ggml_type_size(type)); - for (size_t i = 0; i < n; i++) { - ia[i] = (int32_t) a[i]; - ib[i] = (int32_t) b[i]; + double diff = 0.0f; - // penalize the result if the data is not integer valued - diff += std::fabs(a[i] - ia[i]); - diff += std::fabs(b[i] - ib[i]); + GGML_ASSERT(n == (size_t)(ggml_nrows(input) * k)); + int64_t cols = input->ne[0]; + std::vector ia(k); + std::vector ib(k); + std::vector asrc(k); + std::vector bsrc(k); + for (int64_t r = 0; r < ggml_nrows(input); r++) { + // Convert indices for the row back to integer + for (int64_t c = 0; c < k; c++) { + ia[c] = (int32_t)a[r * k + c]; + ib[c] = (int32_t)b[r * k + c]; + } + // The src values for each row should match. + for (int64_t c = 0; c < k; c++) { + asrc[c] = src[r * cols + ia[c]]; + bsrc[c] = src[r * cols + ib[c]]; + } + diff += jdst(asrc.data(), bsrc.data(), k); + // There should be no duplicate indices + std::sort(ia.begin(), ia.end()); + std::sort(ib.begin(), ib.end()); + if (std::adjacent_find(ia.begin(), ia.end()) != ia.end()) { + diff += 1; + } + if (std::adjacent_find(ib.begin(), ib.end()) != ib.end()) { + diff += 1; + } + } + return diff; + } else { + std::vector ia(n); + std::vector ib(n); + + double diff = 0.0f; + + for (size_t i = 0; i < n; i++) { + ia[i] = (int32_t) a[i]; + ib[i] = (int32_t) b[i]; + + // penalize the result if the data is not integer valued + diff += std::fabs(a[i] - ia[i]); + diff += std::fabs(b[i] - ib[i]); + } + + return diff + jdst(ia.data(), ib.data(), n); } - - return diff + jdst(ia.data(), ib.data(), n); } ggml_tensor * build_graph(ggml_context * ctx) override { ggml_tensor * a = ggml_new_tensor(ctx, type, 4, ne.data()); ggml_set_name(a, "a"); + // Save 'a' for err() + input = a; + ggml_tensor * out = ggml_top_k(ctx, a, k); ggml_set_name(out, "out"); @@ -5031,11 +5100,16 @@ struct test_top_k : public test_case { std::random_device rd; std::default_random_engine rng(rd()); for (ggml_tensor * t = ggml_get_first_tensor(ctx); t != NULL; t = ggml_get_next_tensor(ctx, t)) { - // initialize with unique values to avoid ties + int tie_denom = std::max(1, std::min(10, k / 2)); for (int64_t r = 0; r < ggml_nrows(t); r++) { std::vector data(t->ne[0]); for (int i = 0; i < t->ne[0]; i++) { - data[i] = i; + if (ties) { + // integer division to introduce duplicates + data[i] = i / tie_denom; + } else { + data[i] = i; + } } std::shuffle(data.begin(), data.end(), rng); ggml_backend_tensor_set(t, data.data(), r * t->nb[1], t->ne[0] * sizeof(float)); @@ -5530,21 +5604,24 @@ struct test_pad : public test_case { const std::array ne_a; const int pad_0; const int pad_1; + const bool circular; std::string vars() override { - return VARS_TO_STR4(type, ne_a, pad_0, pad_1); + return VARS_TO_STR5(type, ne_a, pad_0, pad_1, circular); } test_pad(ggml_type type = GGML_TYPE_F32, std::array ne_a = {512, 512, 1, 1}, - int pad_0 = 1, int pad_1 = 1) - : type(type), ne_a(ne_a), pad_0(pad_0), pad_1(pad_1) {} + int pad_0 = 1, int pad_1 = 1, bool circular = false) + : type(type), ne_a(ne_a), pad_0(pad_0), pad_1(pad_1), circular(circular) {} ggml_tensor * build_graph(ggml_context * ctx) override { ggml_tensor * a = ggml_new_tensor(ctx, type, 4, ne_a.data()); ggml_set_name(a, "a"); - ggml_tensor * out = ggml_pad(ctx, a, pad_0, pad_1, 0, 0); + ggml_tensor * out = circular + ? ggml_pad_circular(ctx, a, pad_0, pad_1, 0, 0) + : ggml_pad(ctx, a, pad_0, pad_1, 0, 0); ggml_set_name(out, "out"); return out; @@ -5564,17 +5641,19 @@ struct test_pad_ext : public test_case { const int lp3; const int rp3; const bool v; + const bool circular; std::string vars() override { - return VARS_TO_STR11(type, ne_a, lp0, rp0, lp1, rp1, lp2, rp2, lp3, rp3, v); + return VARS_TO_STR12(type, ne_a, lp0, rp0, lp1, rp1, lp2, rp2, lp3, rp3, v, circular); } test_pad_ext(ggml_type type = GGML_TYPE_F32, std::array ne_a = {512, 512, 3, 1}, int lp0 = 1, int rp0 = 1, int lp1 = 1, int rp1 = 1, int lp2 = 1, int rp2 = 1, int lp3 = 1, int rp3 = 1, - bool v = false) - : type(type), ne_a(ne_a), lp0(lp0), rp0(rp0), lp1(lp1), rp1(rp1), lp2(lp2), rp2(rp2), lp3(lp3), rp3(rp3), v(v) {} + bool v = false, bool circular = false) + : type(type), ne_a(ne_a), lp0(lp0), rp0(rp0), lp1(lp1), rp1(rp1), lp2(lp2), rp2(rp2), lp3(lp3), rp3(rp3), + v(v), circular(circular) {} ggml_tensor * build_graph(ggml_context * ctx) override { ggml_tensor * a = ggml_new_tensor(ctx, type, 4, ne_a.data()); @@ -5585,7 +5664,9 @@ struct test_pad_ext : public test_case { ggml_set_name(a, "view of a"); } - ggml_tensor * out = ggml_pad_ext(ctx, a, lp0, rp0, lp1, rp1, lp2, rp2, lp3, rp3); + ggml_tensor * out = circular + ? ggml_pad_ext_circular(ctx, a, lp0, rp0, lp1, rp1, lp2, rp2, lp3, rp3) + : ggml_pad_ext(ctx, a, lp0, rp0, lp1, rp1, lp2, rp2, lp3, rp3); ggml_set_name(out, "out"); return out; @@ -6130,6 +6211,15 @@ struct test_solve_tri : public test_case { std::string vars() override { return VARS_TO_STR3(type, ne_lhs, ne_rhs); } + uint64_t op_flops(ggml_tensor * t) override { + GGML_UNUSED(t); + int64_t n = ne_lhs[0]; + int64_t k = ne_rhs[0]; + int64_t batch = ne_lhs[2] * ne_lhs[3]; + // n * (n + 1) / 2 non-zero elements of lhs, 2 flops each, for each col of rhs + return n * (n + 1) * k * batch; + } + test_solve_tri(ggml_type type = GGML_TYPE_F32, std::array ne_lhs = { 10, 10, 4, 3 }, std::array ne_rhs = { 3, 10, 4, 3 } @@ -6966,6 +7056,7 @@ static std::vector> make_test_cases_eval() { test_cases.emplace_back(new test_conv_transpose_2d({3, 2, 3, 1}, {2, 2, 1, 3}, 1)); test_cases.emplace_back(new test_conv_transpose_2d({10, 10, 9, 1}, {3, 3, 1, 9}, 2)); + test_cases.emplace_back(new test_conv_transpose_2d({129, 63, 35, 1}, {3, 3, 48, 35}, 1)); test_cases.emplace_back(new test_count_equal(GGML_TYPE_F32, {4, 500, 1, 1})); test_cases.emplace_back(new test_count_equal(GGML_TYPE_F32, {4, 5000, 1, 1})); @@ -7640,6 +7731,7 @@ static std::vector> make_test_cases_eval() { if (k <= 1<> make_test_cases_eval() { test_cases.emplace_back(new test_group_norm_mul_add(GGML_TYPE_F32, {9, 9, 1280, 1})); test_cases.emplace_back(new test_acc()); test_cases.emplace_back(new test_pad()); + test_cases.emplace_back(new test_pad(GGML_TYPE_F32, {33, 17, 2, 1}, 4, 3, true)); // circular test_cases.emplace_back(new test_pad_ext()); test_cases.emplace_back(new test_pad_reflect_1d()); test_cases.emplace_back(new test_pad_reflect_1d(GGML_TYPE_F32, {3000, 384, 4, 1})); @@ -7709,6 +7802,7 @@ static std::vector> make_test_cases_eval() { test_cases.emplace_back(new test_cumsum(GGML_TYPE_F32, { 10, 5, 4, 3 })); test_cases.emplace_back(new test_cumsum(GGML_TYPE_F32, { 127, 5, 4, 3 })); test_cases.emplace_back(new test_cumsum(GGML_TYPE_F32, { 128, 5, 4, 3 })); + test_cases.emplace_back(new test_cumsum(GGML_TYPE_F32, { 128, 128, 4, 4 })); test_cases.emplace_back(new test_cumsum(GGML_TYPE_F32, { 255, 5, 4, 3 })); test_cases.emplace_back(new test_cumsum(GGML_TYPE_F32, { 256, 5, 4, 3 })); test_cases.emplace_back(new test_cumsum(GGML_TYPE_F32, { 511, 5, 4, 3 })); @@ -7739,10 +7833,14 @@ static std::vector> make_test_cases_eval() { test_cases.emplace_back(new test_solve_tri(GGML_TYPE_F32, { 42, 42, 5, 2 }, { 10, 42, 5, 2 })); test_cases.emplace_back(new test_solve_tri(GGML_TYPE_F32, { 64, 64, 2, 2 }, { 10, 64, 2, 2 })); test_cases.emplace_back(new test_solve_tri(GGML_TYPE_F32, { 100, 100, 4, 4 }, { 41, 100, 4, 4 })); + test_cases.emplace_back(new test_solve_tri(GGML_TYPE_F32, { 128, 128, 4, 4 }, { 31, 128, 4, 4 })); + test_cases.emplace_back(new test_solve_tri(GGML_TYPE_F32, { 64, 64, 4, 4 }, { 300, 64, 4, 4 })); for (bool v : {false, true}) { - test_cases.emplace_back(new test_pad_ext(GGML_TYPE_F32, {512, 512, 1, 1}, 0, 1, 0, 1, 0, 0, 0, 0, v)); - test_cases.emplace_back(new test_pad_ext(GGML_TYPE_F32, {11, 22, 33, 44}, 1, 2, 3, 4, 5, 6, 7, 8, v)); + for (bool circular : {false, true}) { + test_cases.emplace_back(new test_pad_ext(GGML_TYPE_F32, {512, 512, 1, 1}, 0, 1, 0, 1, 0, 0, 0, 0, v, circular)); + test_cases.emplace_back(new test_pad_ext(GGML_TYPE_F32, {11, 22, 33, 44}, 1, 2, 3, 4, 5, 6, 7, 8, v, circular)); + } } for (int hsk : { 40, 64, 72, 80, 96, 128, 192, 256, 576 }) { @@ -7880,6 +7978,8 @@ static std::vector> make_test_cases_perf() { { 58, 3, 64, 32, 8 }, // A deep layer of a ConvNet, several images in the batch { 16, 3, 512, 128, 8 }, + // High resolution output (large NPQ) + {1536, 3, 64, 32, 1 }, }; for (auto kernel_type : {GGML_TYPE_F32, GGML_TYPE_F16}) { @@ -7937,6 +8037,17 @@ static std::vector> make_test_cases_perf() { test_cases.emplace_back(new test_solve_tri(GGML_TYPE_F32, { 64, 64, 4, 2 }, { 6, 64, 4, 2 })); test_cases.emplace_back(new test_solve_tri(GGML_TYPE_F32, { 128, 128, 4, 1 }, { 8, 128, 4, 1 })); + // qwen3next with CHUNK_SIZE 64 + test_cases.emplace_back(new test_solve_tri(GGML_TYPE_F32, { 64, 64, 8, 32 }, { 64, 64, 8, 32 })); + // qwen3next with CHUNK_SIZE 128 + test_cases.emplace_back(new test_solve_tri(GGML_TYPE_F32, { 128, 128, 4, 32 }, { 128, 128, 4, 32 })); + + test_cases.emplace_back(new test_tri(GGML_TRI_TYPE_LOWER, GGML_TYPE_F32, { 256, 256, 4, 4 })); + test_cases.emplace_back(new test_tri(GGML_TRI_TYPE_UPPER_DIAG, GGML_TYPE_F32, { 1024, 1024, 8, 4 })); + + test_cases.emplace_back(new test_cumsum(GGML_TYPE_F32, { 128, 128, 4, 4 })); + test_cases.emplace_back(new test_cumsum(GGML_TYPE_F32, { 2048, 16, 5, 4 })); + test_cases.emplace_back(new test_cumsum(GGML_TYPE_F32, { 20000, 10, 4, 1 })); for (int bs : {1, 2, 3, 4, 5, 8, 512}) { for (ggml_type type_a : all_types) { @@ -8363,7 +8474,7 @@ int main(int argc, char ** argv) { auto ggml_backend_set_n_threads_fn = (ggml_backend_set_n_threads_t) ggml_backend_reg_get_proc_address(reg, "ggml_backend_set_n_threads"); if (ggml_backend_set_n_threads_fn) { // TODO: better value for n_threads - ggml_backend_set_n_threads_fn(backend, std::thread::hardware_concurrency()); + ggml_backend_set_n_threads_fn(backend, N_THREADS); } size_t free, total; // NOLINT diff --git a/tests/test-chat-peg-parser.cpp b/tests/test-chat-peg-parser.cpp new file mode 100644 index 0000000000..fbbb9c82ef --- /dev/null +++ b/tests/test-chat-peg-parser.cpp @@ -0,0 +1,768 @@ +#include +#include +#include + +#include "chat-parser.h" +#include "chat-peg-parser.h" +#include "chat.h" +#include "common.h" +#include "json-schema-to-grammar.h" +#include "peg-parser.h" +#include "peg-parser/testing.h" +#include "peg-parser/simple-tokenize.h" +#include "nlohmann/json.hpp" + +using json = nlohmann::ordered_json; + +static json create_tools(); +static void test_example_native(testing & t); +static void test_example_qwen3_coder(testing & t); +static void test_command7_parser_compare(testing & t); + +int main(int argc, char *argv[]) { + testing t(std::cout); + if (argc >= 2) { + t.set_filter(argv[1]); + } + + const char * verbose = getenv("LLAMA_TEST_VERBOSE"); + if (verbose) { + t.verbose = std::string(verbose) == "1"; + } + + t.test("native", test_example_native); + t.test("qwen3 coder", test_example_qwen3_coder); + t.test("comparison", test_command7_parser_compare); + + return t.summary(); +} + +static json create_tools() { + json tools = json::array(); + + json tool_weather = { + {"type", "function"}, + {"function", { + {"name", "get_current_weather"}, + {"description", "Get the current weather in a given location"}, + {"parameters", { + {"type", "object"}, + {"properties", { + {"location", { + {"type", "string"}, + {"description", "The city and state, e.g. San Francisco, CA"} + }}, + {"unit", { + {"type", "string"}, + {"enum", {"celsius", "fahrenheit"}}, + {"description", "The temperature unit to use. Infer this from the users location."} + }} + }}, + {"required", {"location", "unit"}}, + }}, + }} + }; + tools.push_back(tool_weather); + + json tool_forecast = { + {"type", "function"}, + {"function", { + {"name", "get_forecast"}, + {"description", "Get the weather forecast for a given location"}, + {"parameters", { + {"type", "object"}, + {"properties", { + {"location", { + {"type", "string"}, + {"description", "The city and state, e.g. San Francisco, CA"} + }}, + {"unit", { + {"type", "string"}, + {"enum", {"celsius", "fahrenheit"}}, + {"description", "The temperature unit to use. Infer this from the users location."} + }}, + {"days", { + {"type", "integer"}, + {"description", "Number of days to forecast (1-10)"}, + {"minimum", 1}, + {"maximum", 10} + }} + }}, + {"required", {"location", "unit"}}, + }}, + }} + }; + tools.push_back(tool_forecast); + + json tool_search = { + {"type", "function"}, + {"function", { + {"name", "search_knowledge_base"}, + {"description", "Search the internal technical documentation knowledge base."}, + {"parameters", { + {"type", "object"}, + {"properties", { + {"query", { + {"type", "string"}, + {"description", "The search query string."} + }}, + {"max_results", { + {"type", "integer"}, + {"description", "The maximum number of results to return."}, + {"default", 5} + }}, + {"category", { + {"type", "string"}, + {"enum", {"api", "troubleshooting", "billing", "general"}}, + {"description", "Filter search by specific category."} + }} + }}, + {"required", {"query", "category"}}, + {"additionalProperties", false} + }}, + {"strict", true} + }} + }; + tools.push_back(tool_search); + + return tools; +} + +struct tool_argument { + std::string name; + std::string type; + bool is_required; + json schema; +}; + +struct tool_definition { + std::string name; + std::vector arguments; + json schema; +}; + +// Test fictitious model output that emits arguments as JSON. +static void test_example_native(testing & t) { + struct test_case { + // Parameters + std::string name; + json tools; + common_chat_tool_choice tool_choice; + common_reasoning_format reasoning_format; + json json_schema; + bool parallel_tool_calls; + bool thinking_forced_open; + std::string input; + + // Expect + std::string expect_reasoning; + std::string expect_content; + std::vector expect_tool_calls; + }; + + auto build_parser = [](const test_case & tc) { + return build_chat_peg_native_parser([&](common_chat_peg_native_builder & p) { + auto reasoning_in_content = (tc.reasoning_format == COMMON_REASONING_FORMAT_NONE); + auto reasoning = p.eps(); + if (tc.thinking_forced_open) { + // If thinking is forced open, expect a closing tag + reasoning = p.reasoning(p.until("")) + "" + p.space(); + } else { + // Otherwise, optionally accept thinking wrapped in tags + reasoning = p.optional("" + p.reasoning(p.until("")) + "" + p.space()); + } + + // tool calling parser + if (tc.tools.is_array() && !tc.tools.empty()) { + auto tools = p.choice(); + for (const auto & tool : tc.tools) { + const auto & function = tool.at("function"); + std::string name = function.at("name"); + const auto & schema = function.at("parameters"); + + auto tool_name = p.json_member("name", "\"" + p.tool_name(p.literal(name)) + "\""); + auto tool_args = p.json_member("arguments", p.tool_args(p.schema(p.json(), "tool-" + name + "-schema", schema))); + + tools |= p.rule("tool-" + name, p.tool_open(p.literal("{")) << tool_name << "," << tool_args << "}"); + }; + + auto parallel_calls = p.eps(); + if (tc.parallel_tool_calls) { + parallel_calls = p.zero_or_more("," << tools); + } + + auto tool_call = p.trigger_rule("tool-call", + p.sequence({ + p.literal("["), + tools, + parallel_calls, + p.literal("]") + }) + ); + + return p.sequence({ + (reasoning_in_content ? p.eps() : reasoning), + p.content(p.until("")), + p.optional(p.space() + tool_call), + p.space(), + p.end() + }); + } + + // response_format parser + if (tc.json_schema.is_object() && !tc.json_schema.empty()) { + return p.sequence({ + (reasoning_in_content ? p.eps() : reasoning), + p.content(p.schema(p.json(), "response-output", tc.json_schema)), + p.space(), + p.end() + }); + } + + // Content-only parser + return p.sequence({ + (reasoning_in_content ? p.eps() : reasoning), + p.content(p.rest()), + p.end() + }); + }); + }; + + std::vector test_cases = std::vector{ + { + /* .name = */ "content with thinking_forced_open = false", + /* .tools = */ {}, + /* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_NONE, + /* .reasoning_format = */ COMMON_REASONING_FORMAT_AUTO, + /* .json_schema = */ {}, + /* .parallel_tool_calls = */ false, + /* .thinking_forced_open = */ false, + /* .input = */ ( + "The user said hello, I must say hello back\nHello" + ), + /* .expect_reasoning = */ "The user said hello, I must say hello back", + /* .expect_content = */ "Hello", + /* .expect_tool_calls = */ {}, + }, + { + /* .name = */ "content with thinking_forced_open = false and no reasoning", + /* .tools = */ {}, + /* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_NONE, + /* .reasoning_format = */ COMMON_REASONING_FORMAT_AUTO, + /* .json_schema = */ {}, + /* .parallel_tool_calls = */ false, + /* .thinking_forced_open = */ false, + /* .input = */ ( + "Hello" + ), + /* .expect_reasoning = */ "", + /* .expect_content = */ "Hello", + /* .expect_tool_calls = */ {}, + }, + { + /* .name = */ "content with thinking_forced_open = false and reasoning_format = none", + /* .tools = */ {}, + /* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_NONE, + /* .reasoning_format = */ COMMON_REASONING_FORMAT_NONE, + /* .json_schema = */ {}, + /* .parallel_tool_calls = */ false, + /* .thinking_forced_open = */ true, + /* .input = */ ( + "The user said hello, I must say hello back\nHello" + ), + /* .expect_reasoning = */ "", + /* .expect_content = */ "The user said hello, I must say hello back\nHello", + /* .expect_tool_calls = */ {}, + }, + { + /* .name = */ "content with thinking_forced_open = true", + /* .tools = */ {}, + /* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_NONE, + /* .reasoning_format = */ COMMON_REASONING_FORMAT_AUTO, + /* .json_schema = */ {}, + /* .parallel_tool_calls = */ false, + /* .thinking_forced_open = */ true, + /* .input = */ ( + "The user said hello, I must say hello back\nHello" + ), + /* .expect_reasoning = */ "The user said hello, I must say hello back", + /* .expect_content = */ "Hello", + /* .expect_tool_calls = */ {}, + }, + { + /* .name = */ "content with thinking_forced_open = true and reasoning_format = none", + /* .tools = */ {}, + /* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_NONE, + /* .reasoning_format = */ COMMON_REASONING_FORMAT_NONE, + /* .json_schema = */ {}, + /* .parallel_tool_calls = */ false, + /* .thinking_forced_open = */ true, + /* .input = */ ( + "The user said hello, I must say hello back\nHello" + ), + /* .expect_reasoning = */ "", + /* .expect_content = */ "The user said hello, I must say hello back\nHello", + /* .expect_tool_calls = */ {}, + }, + { + /* .name = */ "tools with tool_choice = auto and no parallel_tool_calls", + /* .tools = */ create_tools(), + /* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_AUTO, + /* .reasoning_format = */ COMMON_REASONING_FORMAT_AUTO, + /* .json_schema = */ {}, + /* .parallel_tool_calls = */ false, + /* .thinking_forced_open = */ true, + /* .input = */ ( + "I must get the weather in New York\n" + "[" + R"({"name": "get_current_weather", "arguments": {"location": "New York City, NY", "unit": "fahrenheit"}})" + "]" + ), + /* .expect_reasoning = */ "I must get the weather in New York", + /* .expect_content = */ "", + /* .expect_tool_calls = */ {{ + /* .name = */ "get_current_weather", + /* .arguments = */ R"({"location": "New York City, NY", "unit": "fahrenheit"})", + /* .id = */ "", + }}, + }, + { + /* .name = */ "tools with tool_choice = auto and parallel_tool_calls", + /* .tools = */ create_tools(), + /* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_AUTO, + /* .reasoning_format = */ COMMON_REASONING_FORMAT_AUTO, + /* .json_schema = */ {}, + /* .parallel_tool_calls = */ true, + /* .thinking_forced_open = */ true, + /* .input = */ ( + "I must get the weather in New York and San Francisco and a 3 day forecast of each.\nLet me search that for you." + "[" + R"({"name": "get_current_weather", "arguments": {"location": "New York City, NY", "unit": "fahrenheit"}})" + ", " + R"({"name": "get_current_weather", "arguments": {"location": "San Francisco, CA", "unit": "fahrenheit"}})" + ", " + R"({"name": "get_forecast", "arguments": {"location": "New York City, NY", "unit": "fahrenheit", "days": 3}})" + ", " + R"({"name": "get_forecast", "arguments": {"location": "San Francisco, CA", "unit": "fahrenheit", "days": 3}})" + "]" + ), + /* .expect_reasoning = */ "I must get the weather in New York and San Francisco and a 3 day forecast of each.", + /* .expect_content = */ "Let me search that for you.", + /* .expect_tool_calls = */ {{ + /* .name = */ "get_current_weather", + /* .arguments = */ R"({"location": "New York City, NY", "unit": "fahrenheit"})", + /* .id = */ "", + }, { + /* .name = */ "get_current_weather", + /* .arguments = */ R"({"location": "San Francisco, CA", "unit": "fahrenheit"})", + /* .id = */ "", + }, { + /* .name = */ "get_forecast", + /* .arguments = */ R"({"location": "New York City, NY", "unit": "fahrenheit", "days": 3})", + /* .id = */ "", + }, { + /* .name = */ "get_forecast", + /* .arguments = */ R"({"location": "San Francisco, CA", "unit": "fahrenheit", "days": 3})", + /* .id = */ "", + }}, + }, + { + /* .name = */ "response_format with thinking_forced_open = true", + /* .tools = */ {}, + /* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_NONE, + /* .reasoning_format = */ COMMON_REASONING_FORMAT_AUTO, + /* .json_schema = */ { + {"type", "object"}, + {"properties", { + {"invoice_number", {{"type", "string"}}}, + {"amount", {{"type", "number"}}}, + {"due_date", {{"type", "string"}}} + }}, + {"required", {"invoice_number", "amount", "due_date"}} + }, + /* .parallel_tool_calls = */ false, + /* .thinking_forced_open = */ true, + /* .input = */ ( + "I must produce the invoice in the requested format\n" + R"({"invoice_number": "INV-2025-001", "amount": 1250.50, "due_date": "2025-12-31"})" + ), + /* .expect_reasoning = */ "I must produce the invoice in the requested format", + /* .expect_content = */ R"({"invoice_number": "INV-2025-001", "amount": 1250.50, "due_date": "2025-12-31"})", + /* .expect_tool_calls = */ {}, + }, + }; + + for (const auto & tc : test_cases) { + t.test(tc.name, [&](testing & t) { + auto parser = build_parser(tc); + auto lazy = !tc.tools.empty() && tc.tool_choice != COMMON_CHAT_TOOL_CHOICE_REQUIRED; + auto grammar = build_grammar([&](const common_grammar_builder & builder) { + for (auto const & def : tc.tools) { + auto function = def.at("function"); + auto parameters = function.at("parameters"); + builder.resolve_refs(parameters); + }; + parser.build_grammar(builder, lazy); + }); + + t.log("Grammar:"); + for (auto const & line : string_split(grammar, "\n")) { + t.log(line); + } + + common_peg_parse_context ctx(tc.input, false); + auto result = parser.parse(ctx); + + t.assert_true("success", result.success()); + + common_chat_msg msg; + auto mapper = common_chat_peg_native_mapper(msg); + mapper.from_ast(ctx.ast, result); + + t.assert_equal("content equal", tc.expect_content, msg.content); + t.assert_equal("reasoning equal", tc.expect_reasoning, msg.reasoning_content); + t.assert_equal("number of tool calls", tc.expect_tool_calls.size(), msg.tool_calls.size()); + for (auto i = 0u; i < std::min(tc.expect_tool_calls.size(), msg.tool_calls.size()); i++) { + t.assert_equal("tool name", tc.expect_tool_calls[i].name, msg.tool_calls[i].name); + t.assert_equal("tool args", tc.expect_tool_calls[i].arguments, msg.tool_calls[i].arguments); + } + }); + } +} + +static void test_example_qwen3_coder(testing & t) { + auto tools = create_tools(); + auto parser = build_chat_peg_constructed_parser([&](common_chat_peg_constructed_builder & p) { + auto content = p.rule("content", p.content(p.until(""))); + + std::vector tool_parsers; + for (auto const & def : tools) { + auto function = def.at("function"); + std::string name = function.at("name"); + auto parameters = function.at("parameters"); + auto properties = parameters.at("properties"); + + std::set required_properties; + if (function.contains("required")) { + function.at("required").get_to(required_properties); + } + + std::vector arg_parsers; + for (const auto & [param_name, param_schema] : properties.items()) { + bool is_required = required_properties.find(param_name) != required_properties.end(); + auto type = param_schema.value("type", "object"); + + auto arg = p.tool_arg(p.sequence({ + p.tool_arg_open(""), + (type == "string" ? + p.tool_arg_string_value( + p.schema( + p.until_one_of({ + "\n\n" + }), + "tool-" + name + "-arg-" + param_name + "-schema", + param_schema, + true + ) + ) : p.tool_arg_json_value( + p.schema( + p.json(), + "tool-" + name + "-arg-" + param_name + "-schema", + param_schema + ) + ) + ), + p.tool_arg_close( + "\n" + + p.peek(p.literal("")) + ) + })); + + arg_parsers.push_back(is_required ? + p.rule("tool-" + name + "-arg-" + param_name, arg) : + p.optional(p.rule("tool-" + name + "-arg-" + param_name, arg))); + } + + tool_parsers.push_back(p.rule("tool-" + name, + p.tool_open("") + << p.sequence(arg_parsers) + << p.tool_close(p.literal("")) + )); + }; + + auto tool_call = p.trigger_rule("tool-call", + "" + << p.choice(tool_parsers) + << "" + ); + + return content + p.zero_or_more(p.space() + tool_call) + p.end(); + }); + + auto grammar = build_grammar([&](const common_grammar_builder & builder) { + for (auto const & def : tools) { + auto function = def.at("function"); + auto parameters = function.at("parameters"); + builder.resolve_refs(parameters); + }; + parser.build_grammar(builder); + }); + + t.log("Grammar:"); + for (auto const & line : string_split(grammar, "\n")) { + t.log(line); + } + + t.test("incremental parsing", [&](testing &t) { + std::string input = + "Let me search the knowledge base for cat pictures." + "\n" + "\n" + "cat pictures\n" + "general\n" + "\n" + ""; + + std::vector tokens = simple_tokenize(input); + + common_chat_msg prev; + for (auto it = tokens.begin(); it != tokens.end(); it++) { + std::string in = std::accumulate(tokens.begin(), it + 1, std::string()); + + common_peg_parse_context ctx(in, it + 1 < tokens.end()); + + auto result = parser.parse(ctx); + if (!t.assert_equal("not fail", false, result.fail())) { + t.log(in.substr(0, result.end) + "[failed->]" + in.substr(result.end)); + } + + common_chat_msg msg; + auto mapper = common_chat_peg_constructed_mapper(msg); + mapper.from_ast(ctx.ast, result); + + //t.log("Input: " + input); + t.log("==========================================="); + t.log("Iteration " + std::to_string(in.size())); + t.log("Reasoning: " + msg.reasoning_content); + t.log("Content : " + msg.content); + for (const auto & tc : msg.tool_calls) { + t.log("Tool name: " + tc.name); + t.log("Tool args: " + tc.arguments); + } + + try { + // This shouldn't emit any runtime errors + auto diffs = common_chat_msg_diff::compute_diffs(prev, msg); + } catch(const std::exception & e) { + t.log(in.substr(0, result.end) + "[failed->]" + in.substr(result.end)); + t.assert_true(std::string("failed with ") + e.what(), false); + } + + prev = msg; + } + }); +} + +void test_command7_parser_compare(testing & t) { + auto parser = build_chat_peg_native_parser([](common_chat_peg_native_builder & p) { + auto thinking = p.reasoning_block( + "<|START_THINKING|>" << p.reasoning(p.until("<|END_THINKING|>")) << "<|END_THINKING|>"); + + auto response = "<|START_RESPONSE|>" << p.content(p.until("<|END_RESPONSE|>")) << "<|END_RESPONSE|>"; + + auto tool_call_id = p.atomic("\"tool_call_id\"" << (":" << ("\"" + p.tool_id(p.json_string_content()) + "\""))); + auto tool_call_name = p.atomic("\"tool_name\"" << (":" << ("\"" + p.tool_name(p.json_string_content()) + "\""))); + auto tool_call_args = "\"parameters\"" << (":" << p.tool_args(p.json())); + + auto tool_call_fields = p.rule("tool-call-fields", tool_call_id | tool_call_name | tool_call_args); + auto tool_call = p.rule("tool-call", p.tool( + p.tool_open(p.literal("{")) + << tool_call_fields + << p.zero_or_more( p.literal(",") << tool_call_fields) + << p.tool_close(p.literal("}")) + )); + + auto tool_calls = p.rule("tool-calls", + "<|START_ACTION|>" + << ("[" << tool_call << p.zero_or_more(p.literal(",") << tool_call) << "]") + << "<|END_ACTION|>"); + + return p.optional(thinking) << (tool_calls | response) + p.end(); + }); + + auto test_current = [&](const common_peg_arena & p, const std::string & input, bool is_partial, bool print_results) { + common_peg_parse_context ctx(input, is_partial); + auto result = p.parse(ctx); + + common_chat_msg msg; + auto mapper = common_chat_peg_native_mapper(msg); + mapper.from_ast(ctx.ast, result); + + if (print_results) { + std::cout << "== Parsed (new) ==\n"; + std::cout << "=== Reasoning ===\n"; + std::cout << msg.reasoning_content << "\n"; + std::cout << "\n\n=== Content ===\n"; + std::cout << msg.content << "\n"; + std::cout << "\n\n=== Tool Calls ===\n"; + for (const auto & tc : msg.tool_calls) { + std::cout << "id: " << tc.id << "\n"; + std::cout << "name: " << tc.name << "\n"; + std::cout << "args: " << tc.arguments << "\n"; + } + } + }; + + auto test_legacy = [&](const std::string & input, bool need_more_input, bool print_results) { + // Original common_chat_combinator_parser taken from chat.cpp + common_chat_msg_parser builder( + input, + /* .is_partial = */ need_more_input, + { + /* .format = */ COMMON_CHAT_FORMAT_GENERIC, + /* .reasoning_format = */ COMMON_REASONING_FORMAT_AUTO, + /* .reasoning_in_content = */ false, + /* .thinking_forced_open = */ false, + } + ); + + builder.try_parse_reasoning("<|START_THINKING|>", "<|END_THINKING|>"); + + static const common_regex start_action_regex("<\\|START_ACTION\\|>"); + static const common_regex end_action_regex("<\\|END_ACTION\\|>"); + static const common_regex start_response_regex("<\\|START_RESPONSE\\|>"); + static const common_regex end_response_regex("<\\|END_RESPONSE\\|>"); + + if (auto res = builder.try_find_regex(start_action_regex)) { + // If we didn't extract thoughts, prelude includes them. + auto tool_calls = builder.consume_json_with_dumped_args({ { "parameters" } }); + for (const auto & tool_call : tool_calls.value) { + std::string name = tool_call.contains("tool_name") ? tool_call.at("tool_name") : ""; + std::string id = tool_call.contains("tool_call_id") ? tool_call.at("tool_call_id") : ""; + std::string arguments = tool_call.contains("parameters") ? tool_call.at("parameters") : ""; + if (!builder.add_tool_call(name, id, arguments) || tool_calls.is_partial) { + throw common_chat_msg_partial_exception("incomplete tool call"); + } + } + if (tool_calls.is_partial) { + throw common_chat_msg_partial_exception("incomplete tool call"); + } + builder.consume_regex(end_action_regex); + } else if (auto res = builder.try_find_regex(start_response_regex)) { + if (!builder.try_find_regex(end_response_regex)) { + builder.add_content(builder.consume_rest()); + throw common_chat_msg_partial_exception(end_response_regex.str()); + } + } else { + builder.add_content(builder.consume_rest()); + } + + if (print_results) { + std::cout << "== Parsed (legacy) ==\n"; + std::cout << "=== Reasoning ===\n"; + std::cout << builder.result().reasoning_content << "\n"; + std::cout << "\n\n=== Content ===\n"; + std::cout << builder.result().content << "\n"; + std::cout << "\n\n=== Tool Calls ===\n"; + for (const auto & tc : builder.result().tool_calls) { + std::cout << "id: " << tc.id << "\n"; + std::cout << "name: " << tc.name << "\n"; + std::cout << "args: " << tc.arguments << "\n"; + } + } + }; + + std::string reasoning = "To plan an effective trip to Japan that includes both historical sites and modern attractions within a " + "budget of $4000 for a two-week stay, we need to:\n\n" + "1. Identify key historical sites and modern attractions in Japan.\n" + "2. Find affordable accommodation options that provide a balance between comfort and cost.\n" + "3. Determine the best modes of transportation for getting around Japan.\n" + "4. Create a day-by-day itinerary that ensures the user gets to see a variety of attractions without " + "overspending.\n" + "5. Provide a detailed cost breakdown that includes accommodation, transportation, meals, and entry fees " + "to attractions."; + + std::vector> tool_calls = {{ + "call_0", + "plan_trip", + nlohmann::json::parse(R"({ + "destination": "Japan", + "duration": 14, + "budget": 4000, + "interests": ["historical sites", "modern attractions"], + "accommodation_preferences": "affordable", + "transportation_preferences": "efficient", + "meal_preferences": "local cuisine" + })") + }}; + + std::vector tokens; + + // Build tokens + if (!reasoning.empty()) { + auto tokenized = simple_tokenize(reasoning); + tokens.emplace_back("<|START_THINKING|>"); + tokens.insert(tokens.end(), tokenized.begin(), tokenized.end()); + tokens.emplace_back("<|END_THINKING|>"); + } + + if (!tool_calls.empty()) { + tokens.emplace_back("<|START_ACTION|>"); + + auto json = nlohmann::json::array(); + for (const auto & tc : tool_calls) { + auto tc_json = nlohmann::json::object(); + tc_json["tool_call_id"] = std::get<0>(tc); + tc_json["tool_name"] = std::get<1>(tc); + tc_json["parameters"] = std::get<2>(tc); + json.push_back(tc_json); + } + + auto tokenized = simple_tokenize(json.dump(-1, ' ', true)); + tokens.insert(tokens.end(), tokenized.begin(), tokenized.end()); + + tokens.emplace_back("<|END_ACTION|>"); + } + + std::string input = std::accumulate(tokens.begin(), tokens.end(), std::string()); + + // Run tests + t.test("legacy_parse", [&](testing & /* t */) { + test_legacy(input, false, false); + }); + + t.test("current_parse", [&](testing & /* t */) { + test_current(parser, input, false, false); + }); + + // Run benchmarks + t.bench("legacy_parse_benchmark complete", [&]() { + test_legacy(input, false, false); + }); + + t.bench("legacy_parse_benchmark incremental", [&]() { + std::string in; + for (auto i = 0u; i < tokens.size(); i++) { + in += tokens[i]; + + try { + test_legacy(in, i + 1 < tokens.size(), false); + } catch (common_chat_msg_partial_exception & /* e */) { + // Do nothing, this is expected + } + } + }, 20); + + t.bench("current_parse_benchmark complete", [&]() { + test_current(parser, input, false, false); + }, 100); + + t.bench("current_parse_benchmark incremental", [&]() { + std::string in; + for (auto i = 0u; i < tokens.size(); i++) { + in += tokens[i]; + test_current(parser, in, i + 1 < tokens.size(), false); + } + }, 20); +} diff --git a/tests/test-chat.cpp b/tests/test-chat.cpp index f8a9c9aadf..45ee7f8388 100644 --- a/tests/test-chat.cpp +++ b/tests/test-chat.cpp @@ -428,7 +428,7 @@ static void test_templates(const struct common_chat_templates * tmpls, const std */ template static void test_parser_with_streaming(const common_chat_msg & expected, const std::string & raw_message, T parse_msg) { - constexpr auto utf8_truncate_safe = [](const std::string_view s) -> size_t { + constexpr auto utf8_truncate_safe_len = [](const std::string_view s) -> size_t { auto len = s.size(); if (len == 0) return 0; auto i = len; @@ -452,8 +452,8 @@ static void test_parser_with_streaming(const common_chat_msg & expected, const s } return len - std::min(len, size_t(3)); }; - constexpr auto utf8_truncate_safe_view = [utf8_truncate_safe](const std::string_view s) { - return s.substr(0, utf8_truncate_safe(s)); + constexpr auto utf8_truncate_safe_view = [utf8_truncate_safe_len](const std::string_view s) { + return s.substr(0, utf8_truncate_safe_len(s)); }; auto merged = simple_assist_msg(""); diff --git a/tests/test-json-schema-to-grammar.cpp b/tests/test-json-schema-to-grammar.cpp index 1e568219d2..6a4bd8fb4d 100755 --- a/tests/test-json-schema-to-grammar.cpp +++ b/tests/test-json-schema-to-grammar.cpp @@ -1375,7 +1375,7 @@ int main() { try { tc.verify(json_schema_to_grammar(nlohmann::ordered_json::parse(tc.schema), true)); tc.verify_status(SUCCESS); - } catch (const std::runtime_error & ex) { + } catch (const std::invalid_argument & ex) { fprintf(stderr, "Error: %s\n", ex.what()); tc.verify_status(FAILURE); } diff --git a/tests/test-peg-parser.cpp b/tests/test-peg-parser.cpp new file mode 100644 index 0000000000..220745d029 --- /dev/null +++ b/tests/test-peg-parser.cpp @@ -0,0 +1,25 @@ +#include +#include +#include + +#include "peg-parser/tests.h" + +int main(int argc, char *argv[]) { + testing t(std::cout); + if (argc >= 2) { + t.set_filter(argv[1]); + } + + const char * verbose = getenv("LLAMA_TEST_VERBOSE"); + if (verbose) { + t.verbose = std::string(verbose) == "1"; + } + + t.test("basic", test_basic); + t.test("unicode", test_unicode); + t.test("json", test_json_parser); + t.test("gbnf", test_gbnf_generation); + t.test("serialization", test_json_serialization); + + return t.summary(); +} diff --git a/tools/llama-bench/llama-bench.cpp b/tools/llama-bench/llama-bench.cpp index 852a512451..0be6ed6948 100644 --- a/tools/llama-bench/llama-bench.cpp +++ b/tools/llama-bench/llama-bench.cpp @@ -1737,7 +1737,8 @@ struct markdown_printer : public printer { fields.emplace_back("params"); fields.emplace_back("backend"); bool is_cpu_backend = test::get_backend().find("CPU") != std::string::npos || - test::get_backend().find("BLAS") != std::string::npos; + test::get_backend().find("BLAS") != std::string::npos || + test::get_backend().find("ZenDNN") != std::string::npos; if (!is_cpu_backend) { fields.emplace_back("n_gpu_layers"); } diff --git a/tools/mtmd/clip.cpp b/tools/mtmd/clip.cpp index ea89259f92..3ed08a0fec 100644 --- a/tools/mtmd/clip.cpp +++ b/tools/mtmd/clip.cpp @@ -428,6 +428,7 @@ struct clip_ctx { int max_nodes = 8192; ggml_backend_sched_ptr sched; clip_flash_attn_type flash_attn_type = CLIP_FLASH_ATTN_TYPE_AUTO; + bool is_allocated = false; // for debugging bool debug_graph = false; @@ -3305,12 +3306,30 @@ struct clip_model_loader { }; static void warmup(clip_ctx & ctx_clip) { + // create a fake batch + const auto & hparams = ctx_clip.model.hparams; + clip_image_f32_batch batch; + clip_image_f32_ptr img(clip_image_f32_init()); + if (ctx_clip.model.modality == CLIP_MODALITY_VISION) { + img->nx = hparams.warmup_image_size; + img->ny = hparams.warmup_image_size; + LOG_INF("%s: warmup with image size = %d x %d\n", __func__, img->nx, img->ny); + } else { + img->nx = hparams.warmup_audio_size; + img->ny = hparams.n_mel_bins; + LOG_INF("%s: warmup with audio size = %d\n", __func__, img->nx); + } + batch.entries.push_back(std::move(img)); + warmup(ctx_clip, batch); + } + + static void warmup(clip_ctx & ctx_clip, const clip_image_f32_batch & batch) { support_info_graph info; if (ctx_clip.flash_attn_type == CLIP_FLASH_ATTN_TYPE_AUTO) { // try to enable flash attention to see if it's supported ctx_clip.flash_attn_type = CLIP_FLASH_ATTN_TYPE_ENABLED; - info = alloc_compute_meta(ctx_clip); + info = alloc_compute_meta(ctx_clip, batch); if (!info.fattn && info.fattn_op) { auto op = info.fattn_op; LOG_WRN("%s: *****************************************************************\n", __func__); @@ -3329,15 +3348,17 @@ struct clip_model_loader { LOG_WRN("%s: please report this on github as an issue\n", __func__); LOG_WRN("%s: *****************************************************************\n", __func__); ctx_clip.flash_attn_type = CLIP_FLASH_ATTN_TYPE_DISABLED; - alloc_compute_meta(ctx_clip); + alloc_compute_meta(ctx_clip, batch); } } else { - info = alloc_compute_meta(ctx_clip); + info = alloc_compute_meta(ctx_clip, batch); if (!info.fattn && ctx_clip.flash_attn_type == CLIP_FLASH_ATTN_TYPE_ENABLED) { LOG_WRN("%s: flash attention is not supported by the current backend; falling back to CPU (performance will be degraded)\n", __func__); } } + ctx_clip.is_allocated = true; // mark buffers as allocated + LOG_INF("%s: flash attention is %s\n", __func__, (ctx_clip.flash_attn_type == CLIP_FLASH_ATTN_TYPE_ENABLED) ? "enabled" : "disabled"); @@ -3369,24 +3390,9 @@ struct clip_model_loader { } } - static support_info_graph alloc_compute_meta(clip_ctx & ctx_clip) { - const auto & hparams = ctx_clip.model.hparams; + static support_info_graph alloc_compute_meta(clip_ctx & ctx_clip, const clip_image_f32_batch & batch) { ctx_clip.buf_compute_meta.resize(ctx_clip.max_nodes * ggml_tensor_overhead() + ggml_graph_overhead()); - // create a fake batch - clip_image_f32_batch batch; - clip_image_f32_ptr img(clip_image_f32_init()); - if (ctx_clip.model.modality == CLIP_MODALITY_VISION) { - img->nx = hparams.warmup_image_size; - img->ny = hparams.warmup_image_size; - LOG_INF("%s: warmup with image size = %d x %d\n", __func__, img->nx, img->ny); - } else { - img->nx = hparams.warmup_audio_size; - img->ny = hparams.n_mel_bins; - LOG_INF("%s: warmup with audio size = %d\n", __func__, img->nx); - } - batch.entries.push_back(std::move(img)); - ggml_cgraph * gf = clip_image_build_graph(&ctx_clip, batch); ggml_backend_sched_reserve(ctx_clip.sched.get(), gf); @@ -4630,6 +4636,11 @@ bool clip_image_batch_encode(clip_ctx * ctx, const int n_threads, const clip_ima return false; // only support batch size of 1 } + // if buffers are not allocated, we need to do a warmup run to allocate them + if (!ctx->is_allocated) { + clip_model_loader::warmup(*ctx, *imgs_c_ptr); + } + // build the inference graph ctx->debug_print_tensors.clear(); ggml_backend_sched_reset(ctx->sched.get()); diff --git a/tools/server/CMakeLists.txt b/tools/server/CMakeLists.txt index fb71c7aa7b..1aa659a906 100644 --- a/tools/server/CMakeLists.txt +++ b/tools/server/CMakeLists.txt @@ -2,11 +2,6 @@ set(TARGET llama-server) include_directories(${CMAKE_CURRENT_SOURCE_DIR} ${CMAKE_CURRENT_BINARY_DIR}) -if (MINGW) - # fix: https://github.com/ggml-org/llama.cpp/actions/runs/9651004652/job/26617901362?pr=8006 - add_compile_definitions(_WIN32_WINNT=${GGML_WIN_VER}) -endif() - if (NOT LLAMA_HTTPLIB) message(FATAL_ERROR "LLAMA_HTTPLIB is OFF, cannot build llama-server. Hint: to skip building server, set -DLLAMA_BUILD_SERVER=OFF") endif() diff --git a/tools/server/README-dev.md b/tools/server/README-dev.md new file mode 100644 index 0000000000..fbcd6bc1f9 --- /dev/null +++ b/tools/server/README-dev.md @@ -0,0 +1,177 @@ +# llama-server Development Documentation + +This document provides an in-depth technical overview of `llama-server`, intended for maintainers and contributors. + +If you are an end user consuming `llama-server` as a product, please refer to the main [README](./README.md) instead. + +## Backend + +### Overview + +The server supports two primary operating modes: + +- **Inference mode**: The default mode for performing inference with a single loaded GGUF model. +- **Router mode**: Enables management of multiple inference server instances behind a single API endpoint. Requests are automatically routed to the appropriate backend instance based on the requested model. + +The core architecture consists of the following components: + +- `server_context`: Holds the primary inference state, including the main `llama_context` and all active slots. +- `server_slot`: An abstraction over a single “sequence” in llama.cpp, responsible for managing individual parallel inference requests. +- `server_routes`: Middleware layer between `server_context` and the HTTP interface; handles JSON parsing/formatting and request routing logic. +- `server_http_context`: Implements the HTTP server using `cpp-httplib`. +- `server_queue`: Thread-safe queue used by HTTP workers to submit new tasks to `server_context`. +- `server_response`: Thread-safe queue used by `server_context` to return results to HTTP workers. +- `server_response_reader`: Higher-level wrapper around the two queues above for cleaner code. +- `server_task`: Unit of work pushed into `server_queue`. +- `server_task_result`: Unit of result pushed into `server_response`. +- `server_tokens`: Unified representation of token sequences (supports both text and multimodal tokens); used by `server_task` and `server_slot`. +- `server_prompt_checkpoint`: For recurrent (e.g., RWKV) and SWA models, stores snapshots of KV cache state. Enables reuse when subsequent requests share the same prompt prefix, saving redundant computation. +- `server_models`: Standalone component for managing multiple backend instances (used in router mode). It is completely independent of `server_context`. + +```mermaid +graph TD + API_User <--> server_http_context + server_http_context <-- router mode --> server_models + server_http_context <-- inference mode --> server_routes + server_routes -- server_task --> server_queue + subgraph server_context + server_queue --> server_slot + server_slot -- server_task_result --> server_response + server_slot[multiple server_slot] + end + server_response --> server_routes +``` + +### Batching + +The server context maintains a single batch shared across all slots. When `update_slots()` is invoked, the system iterates through all active slots to populate this batch. For each slot, either a generated token from the previous decoding step or available prompt tokens are added to the batch. + +Batching constraints apply: slots can only be batched together if they share compatible configurations. For instance, slots using a specific LoRA adapter can be batched with each other, but not with slots using a different LoRA adapter or no adapter at all. + +Once the batch reaches capacity or all slots have been processed, `llama_decode` is called to execute the inference. This operation represents the primary computational bottleneck in `update_slots()`. + +Following decoding, the system either retrieves embeddings or samples the next token using `common_sampler_sample`. If a slot has remaining prompt tokens to process, it yields until the next `update_slots()` iteration. + +### Thread Management + +`server_context` runs on a dedicated single thread. Because it is single-threaded, heavy post-processing (especially after token generation) should be avoided, as it directly impacts multi-sequence throughput. + +Each incoming HTTP request is handled by its own thread managed by the HTTP library. The following operations are performed in HTTP worker threads: + +- JSON request parsing +- Chat template application +- Tokenization +- Conversion of `server_task_result` into final JSON response +- Error formatting into JSON +- Tracking of partial/incremental responses (e.g., streaming tool calls or reasoning steps) + +**Best practices to follow:** + +- All JSON formatting and chat template logic must stay in the HTTP layer. +- Avoid passing raw JSON between the HTTP layer and `server_slot`. Instead, parse everything into native C++ types as early as possible. + +### Example trace of a request + +Here is an example trace of an API request for text completion: + +- A request arrives at the HTTP layer. +- The request is routed to the corresponding handler inside `server_routes`. In this case, `handle_completions_impl` is invoked. +- The handler parses the input request, constructs a new `server_task`, and passes it to `server_res_generator`. +- `server_res_generator` creates a new `task_result_state` for each task: + - `task_result_state` stays in the HTTP layer, responsible for keeping track of the current state of the response (e.g., parsing tool calls or thinking messages). + - `server_task` is moved into `server_queue` inside `server_context`. +- `server_context` launches the task by moving it into an available slot (see `launch_slot_with_task()`). +- `update_slot()` processes the task as described in the "Batching" section above. +- Results may be sent using `send_partial_response` or `send_final_response`, which creates a new `server_task_result` and pushes it to the response queue. +- At the same time, `server_res_generator` listens to the response queue and retrieves this response. +- As the response is stateless, `server_res_generator` calls `response->update()` to update the response with the current state. +- `server_res_generator` then calls `response->to_json()` and passes the response to the HTTP layer. + +### Testing + +`llama-server` includes an automated test suite based on `pytest`. + +The framework automatically starts a `llama-server` instance, sends requests, and validates responses. + +For detailed instructions, see the [test documentation](./tests/README.md). + +### Notable Related PRs + +- Initial server implementation: https://github.com/ggml-org/llama.cpp/pull/1443 +- Parallel decoding support: https://github.com/ggml-org/llama.cpp/pull/3228 +- Refactor introducing `server_queue` and `server_response`: https://github.com/ggml-org/llama.cpp/pull/5065 +- Reranking endpoint: https://github.com/ggml-org/llama.cpp/pull/9510 +- Multimodal model support (`libmtmd`): https://github.com/ggml-org/llama.cpp/pull/12898 +- Unified KV cache handling: https://github.com/ggml-org/llama.cpp/pull/16736 +- Separation of HTTP logic into dedicated files: https://github.com/ggml-org/llama.cpp/pull/17216 +- Large-scale code base split into smaller files: https://github.com/ggml-org/llama.cpp/pull/17362 +- Introduction of router mode: https://github.com/ggml-org/llama.cpp/pull/17470 +- Speculative decoding: https://github.com/ggml-org/llama.cpp/pull/17808 and rework in https://github.com/ggml-org/llama.cpp/pull/17808 + + + + +## Web UI + +The project includes a web-based user interface for interacting with `llama-server`. It supports both single-model (`MODEL` mode) and multi-model (`ROUTER` mode) operation. + +The SvelteKit-based Web UI is introduced in this PR: https://github.com/ggml-org/llama.cpp/pull/14839 + +### Features + +- **Chat interface** with streaming responses +- **Multi-model support** (ROUTER mode) - switch between models, auto-load on selection +- **Modality validation** - ensures selected model supports conversation's attachments (images, audio) +- **Conversation management** - branching, regeneration, editing with history preservation +- **Attachment support** - images, audio, PDFs (with vision/text fallback) +- **Configurable parameters** - temperature, top_p, etc. synced with server defaults +- **Dark/light theme** + +### Tech Stack + +- **SvelteKit** - frontend framework with Svelte 5 runes for reactive state +- **TailwindCSS** + **shadcn-svelte** - styling and UI components +- **Vite** - build tooling +- **IndexedDB** (Dexie) - local storage for conversations +- **LocalStorage** - user settings persistence + +### Architecture + +The WebUI follows a layered architecture: + +``` +Routes → Components → Hooks → Stores → Services → Storage/API +``` + +- **Stores** - reactive state management (`chatStore`, `conversationsStore`, `modelsStore`, `serverStore`, `settingsStore`) +- **Services** - stateless API/database communication (`ChatService`, `ModelsService`, `PropsService`, `DatabaseService`) +- **Hooks** - reusable logic (`useModelChangeValidation`, `useProcessingState`) + +For detailed architecture diagrams, see [`tools/server/webui/docs/`](webui/docs/): + +- `high-level-architecture.mmd` - full architecture with all modules +- `high-level-architecture-simplified.mmd` - simplified overview +- `data-flow-simplified-model-mode.mmd` - data flow for single-model mode +- `data-flow-simplified-router-mode.mmd` - data flow for multi-model mode +- `flows/*.mmd` - detailed per-domain flows (chat, conversations, models, etc.) + +### Development + +```sh +# make sure you have Node.js installed +cd tools/server/webui +npm i + +# run dev server (with hot reload) +npm run dev + +# run tests +npm run test + +# build production bundle +npm run build +``` + +After `public/index.html.gz` has been generated, rebuild `llama-server` as described in the [build](#build) section to include the updated UI. + +**Note:** The Vite dev server automatically proxies API requests to `http://localhost:8080`. Make sure `llama-server` is running on that port during development. diff --git a/tools/server/README.md b/tools/server/README.md index cb2fbcf8eb..f98fb44c7b 100644 --- a/tools/server/README.md +++ b/tools/server/README.md @@ -2,7 +2,7 @@ Fast, lightweight, pure C/C++ HTTP server based on [httplib](https://github.com/yhirose/cpp-httplib), [nlohmann::json](https://github.com/nlohmann/json) and **llama.cpp**. -Set of LLM REST APIs and a simple web front end to interact with llama.cpp. +Set of LLM REST APIs and a web UI to interact with llama.cpp. **Features:** * LLM inference of F16 and quantized models on GPU and CPU @@ -19,7 +19,7 @@ Set of LLM REST APIs and a simple web front end to interact with llama.cpp. * Speculative decoding * Easy-to-use web UI -The project is under active development, and we are [looking for feedback and contributors](https://github.com/ggml-org/llama.cpp/issues/4216). +For the ful list of features, please refer to [server's changelog](https://github.com/ggml-org/llama.cpp/issues/9291) ## Usage @@ -289,69 +289,6 @@ For more details, please refer to [multimodal documentation](../../docs/multimod cmake --build build --config Release -t llama-server ``` -## Web UI - -The project includes a web-based user interface for interacting with `llama-server`. It supports both single-model (`MODEL` mode) and multi-model (`ROUTER` mode) operation. - -### Features - -- **Chat interface** with streaming responses -- **Multi-model support** (ROUTER mode) - switch between models, auto-load on selection -- **Modality validation** - ensures selected model supports conversation's attachments (images, audio) -- **Conversation management** - branching, regeneration, editing with history preservation -- **Attachment support** - images, audio, PDFs (with vision/text fallback) -- **Configurable parameters** - temperature, top_p, etc. synced with server defaults -- **Dark/light theme** - -### Tech Stack - -- **SvelteKit** - frontend framework with Svelte 5 runes for reactive state -- **TailwindCSS** + **shadcn-svelte** - styling and UI components -- **Vite** - build tooling -- **IndexedDB** (Dexie) - local storage for conversations -- **LocalStorage** - user settings persistence - -### Architecture - -The WebUI follows a layered architecture: - -``` -Routes → Components → Hooks → Stores → Services → Storage/API -``` - -- **Stores** - reactive state management (`chatStore`, `conversationsStore`, `modelsStore`, `serverStore`, `settingsStore`) -- **Services** - stateless API/database communication (`ChatService`, `ModelsService`, `PropsService`, `DatabaseService`) -- **Hooks** - reusable logic (`useModelChangeValidation`, `useProcessingState`) - -For detailed architecture diagrams, see [`tools/server/webui/docs/`](webui/docs/): - -- `high-level-architecture.mmd` - full architecture with all modules -- `high-level-architecture-simplified.mmd` - simplified overview -- `data-flow-simplified-model-mode.mmd` - data flow for single-model mode -- `data-flow-simplified-router-mode.mmd` - data flow for multi-model mode -- `flows/*.mmd` - detailed per-domain flows (chat, conversations, models, etc.) - -### Development - -```sh -# make sure you have Node.js installed -cd tools/server/webui -npm i - -# run dev server (with hot reload) -npm run dev - -# run tests -npm run test - -# build production bundle -npm run build -``` - -After `public/index.html.gz` has been generated, rebuild `llama-server` as described in the [build](#build) section to include the updated UI. - -**Note:** The Vite dev server automatically proxies API requests to `http://localhost:8080`. Make sure `llama-server` is running on that port during development. - ## Quick Start To get started right away, run the following command, making sure to use the correct path for the model you have: @@ -380,7 +317,7 @@ docker run -p 8080:8080 -v /path/to/models:/models ghcr.io/ggml-org/llama.cpp:se docker run -p 8080:8080 -v /path/to/models:/models --gpus all ghcr.io/ggml-org/llama.cpp:server-cuda -m models/7B/ggml-model.gguf -c 512 --host 0.0.0.0 --port 8080 --n-gpu-layers 99 ``` -## Testing with CURL +## Using with CURL Using [curl](https://curl.se/). On Windows, `curl.exe` should be available in the base OS. @@ -391,46 +328,6 @@ curl --request POST \ --data '{"prompt": "Building a website can be done in 10 simple steps:","n_predict": 128}' ``` -## Advanced testing - -We implemented a [server test framework](./tests/README.md) using human-readable scenario. - -*Before submitting an issue, please try to reproduce it with this format.* - -## Node JS Test - -You need to have [Node.js](https://nodejs.org/en) installed. - -```bash -mkdir llama-client -cd llama-client -``` - -Create an index.js file and put this inside: - -```javascript -const prompt = "Building a website can be done in 10 simple steps:" - -async function test() { - let response = await fetch("http://127.0.0.1:8080/completion", { - method: "POST", - body: JSON.stringify({ - prompt, - n_predict: 64, - }) - }) - console.log((await response.json()).content) -} - -test() -``` - -And run it: - -```bash -node index.js -``` - ## API Endpoints ### GET `/health`: Returns health check result @@ -493,6 +390,10 @@ Note for `multimodal_data` in JSON object prompts. This should be an array of st `n_keep`: Specify the number of tokens from the prompt to retain when the context size is exceeded and tokens need to be discarded. The number excludes the BOS token. By default, this value is set to `0`, meaning no tokens are kept. Use `-1` to retain all tokens from the prompt. +`n_cmpl`: Number of completions to generate from the current prompt. If input has multiple prompts, the output will have N prompts times `n_cmpl` entries. + +`n_cache_reuse`: Min chunk size to attempt reusing from the cache via KV shifting. For more info, see `--cache-reuse` arg. Default: `0`, which is disabled. + `stream`: Allows receiving each predicted token in real-time instead of waiting for the completion to finish (uses a different response format). To enable this, set to `true`. `stop`: Specify a JSON array of stopping strings. @@ -1634,6 +1535,22 @@ Response: } ``` +## API errors + +`llama-server` returns errors in the same format as OAI: https://github.com/openai/openai-openapi + +Example of an error: + +```json +{ + "error": { + "code": 401, + "message": "Invalid API Key", + "type": "authentication_error" + } +} +``` + ## More examples ### Interactive mode @@ -1653,26 +1570,6 @@ Run with bash: bash chat.sh ``` -### OAI-like API - -The HTTP `llama-server` supports an OAI-like API: https://github.com/openai/openai-openapi - -### API errors - -`llama-server` returns errors in the same format as OAI: https://github.com/openai/openai-openapi - -Example of an error: - -```json -{ - "error": { - "code": 401, - "message": "Invalid API Key", - "type": "authentication_error" - } -} -``` - Apart from error types supported by OAI, we also have custom types that are specific to functionalities of llama.cpp: **When /metrics or /slots endpoint is disabled** diff --git a/tools/server/public/index.html.gz b/tools/server/public/index.html.gz index 9b58c25a66..2db04e9522 100644 Binary files a/tools/server/public/index.html.gz and b/tools/server/public/index.html.gz differ diff --git a/tools/server/server-common.cpp b/tools/server/server-common.cpp index 0bbc4e858f..b403864e0e 100644 --- a/tools/server/server-common.cpp +++ b/tools/server/server-common.cpp @@ -11,6 +11,7 @@ #include #include +#include json format_error_response(const std::string & message, const enum error_type type) { std::string type_str; @@ -493,6 +494,18 @@ int32_t server_tokens::process_chunk( return 0; } +server_tokens server_tokens::clone() const { + server_tokens res; + res.has_mtmd = has_mtmd; + res.tokens = tokens; + for (auto it = map_idx_to_media.begin(); it != map_idx_to_media.end(); ++it) { + size_t idx = it->first; + const mtmd::input_chunk_ptr & chunk = it->second; + res.map_idx_to_media[idx] = mtmd::input_chunk_ptr(mtmd_input_chunk_copy(chunk.get())); + } + return res; +} + // // tokenizer and input processing utils // @@ -744,12 +757,6 @@ json oaicompat_completion_params_parse(const json & body) { llama_params["stop"] = json_value(body, "stop", json::array()); } - // Handle "n" field - int n_choices = json_value(body, "n", 1); - if (n_choices != 1) { - throw std::runtime_error("Only one completion choice is allowed"); - } - // Handle "echo" field if (json_value(body, "echo", false)) { throw std::runtime_error("Only no echo is supported"); @@ -774,6 +781,65 @@ json oaicompat_completion_params_parse(const json & body) { return llama_params; } +// media_path always end with '/', see arg.cpp +static void handle_media( + std::vector & out_files, + json & media_obj, + const std::string & media_path) { + std::string url = json_value(media_obj, "url", std::string()); + if (string_starts_with(url, "http")) { + // download remote image + // TODO @ngxson : maybe make these params configurable + common_remote_params params; + params.headers.push_back("User-Agent: llama.cpp/" + build_info); + params.max_size = 1024 * 1024 * 10; // 10MB + params.timeout = 10; // seconds + SRV_INF("downloading image from '%s'\n", url.c_str()); + auto res = common_remote_get_content(url, params); + if (200 <= res.first && res.first < 300) { + SRV_INF("downloaded %zu bytes\n", res.second.size()); + raw_buffer data; + data.insert(data.end(), res.second.begin(), res.second.end()); + out_files.push_back(data); + } else { + throw std::runtime_error("Failed to download image"); + } + + } else if (string_starts_with(url, "file://")) { + if (media_path.empty()) { + throw std::invalid_argument("file:// URLs are not allowed unless --media-path is specified"); + } + // load local image file + std::string file_path = url.substr(7); // remove "file://" + raw_buffer data; + if (!fs_validate_filename(file_path, true)) { + throw std::invalid_argument("file path is not allowed: " + file_path); + } + SRV_INF("loading image from local file '%s'\n", (media_path + file_path).c_str()); + std::ifstream file(media_path + file_path, std::ios::binary); + if (!file) { + throw std::invalid_argument("file does not exist or cannot be opened: " + file_path); + } + data.assign((std::istreambuf_iterator(file)), std::istreambuf_iterator()); + out_files.push_back(data); + + } else { + // try to decode base64 image + std::vector parts = string_split(url, /*separator*/ ','); + if (parts.size() != 2) { + throw std::runtime_error("Invalid url value"); + } else if (!string_starts_with(parts[0], "data:image/")) { + throw std::runtime_error("Invalid url format: " + parts[0]); + } else if (!string_ends_with(parts[0], "base64")) { + throw std::runtime_error("url must be base64 encoded"); + } else { + auto base64_data = parts[1]; + auto decoded_data = base64_decode(base64_data); + out_files.push_back(decoded_data); + } + } +} + // used by /chat/completions endpoint json oaicompat_chat_params_parse( json & body, /* openai api json semantics */ @@ -819,26 +885,26 @@ json oaicompat_chat_params_parse( auto schema_wrapper = json_value(response_format, "json_schema", json::object()); json_schema = json_value(schema_wrapper, "schema", json::object()); } else if (!response_type.empty() && response_type != "text") { - throw std::runtime_error("response_format type must be one of \"text\" or \"json_object\", but got: " + response_type); + throw std::invalid_argument("response_format type must be one of \"text\" or \"json_object\", but got: " + response_type); } } // get input files if (!body.contains("messages")) { - throw std::runtime_error("'messages' is required"); + throw std::invalid_argument("'messages' is required"); } json & messages = body.at("messages"); if (!messages.is_array()) { - throw std::runtime_error("Expected 'messages' to be an array"); + throw std::invalid_argument("Expected 'messages' to be an array"); } for (auto & msg : messages) { std::string role = json_value(msg, "role", std::string()); if (role != "assistant" && !msg.contains("content")) { - throw std::runtime_error("All non-assistant messages must contain 'content'"); + throw std::invalid_argument("All non-assistant messages must contain 'content'"); } if (role == "assistant") { if (!msg.contains("content") && !msg.contains("tool_calls")) { - throw std::runtime_error("Assistant message must contain either 'content' or 'tool_calls'!"); + throw std::invalid_argument("Assistant message must contain either 'content' or 'tool_calls'!"); } if (!msg.contains("content")) { continue; // avoid errors with no content @@ -850,7 +916,7 @@ json oaicompat_chat_params_parse( } if (!content.is_array()) { - throw std::runtime_error("Expected 'content' to be a string or an array"); + throw std::invalid_argument("Expected 'content' to be a string or an array"); } for (auto & p : content) { @@ -860,41 +926,8 @@ json oaicompat_chat_params_parse( throw std::runtime_error("image input is not supported - hint: if this is unexpected, you may need to provide the mmproj"); } - json image_url = json_value(p, "image_url", json::object()); - std::string url = json_value(image_url, "url", std::string()); - if (string_starts_with(url, "http")) { - // download remote image - // TODO @ngxson : maybe make these params configurable - common_remote_params params; - params.headers.push_back("User-Agent: llama.cpp/" + build_info); - params.max_size = 1024 * 1024 * 10; // 10MB - params.timeout = 10; // seconds - SRV_INF("downloading image from '%s'\n", url.c_str()); - auto res = common_remote_get_content(url, params); - if (200 <= res.first && res.first < 300) { - SRV_INF("downloaded %ld bytes\n", res.second.size()); - raw_buffer data; - data.insert(data.end(), res.second.begin(), res.second.end()); - out_files.push_back(data); - } else { - throw std::runtime_error("Failed to download image"); - } - - } else { - // try to decode base64 image - std::vector parts = string_split(url, /*separator*/ ','); - if (parts.size() != 2) { - throw std::runtime_error("Invalid image_url.url value"); - } else if (!string_starts_with(parts[0], "data:image/")) { - throw std::runtime_error("Invalid image_url.url format: " + parts[0]); - } else if (!string_ends_with(parts[0], "base64")) { - throw std::runtime_error("image_url.url must be base64 encoded"); - } else { - auto base64_data = parts[1]; - auto decoded_data = base64_decode(base64_data); - out_files.push_back(decoded_data); - } - } + json image_url = json_value(p, "image_url", json::object()); + handle_media(out_files, image_url, opt.media_path); // replace this chunk with a marker p["type"] = "text"; @@ -911,18 +944,20 @@ json oaicompat_chat_params_parse( std::string format = json_value(input_audio, "format", std::string()); // while we also support flac, we don't allow it here so we matches the OAI spec if (format != "wav" && format != "mp3") { - throw std::runtime_error("input_audio.format must be either 'wav' or 'mp3'"); + throw std::invalid_argument("input_audio.format must be either 'wav' or 'mp3'"); } auto decoded_data = base64_decode(data); // expected to be base64 encoded out_files.push_back(decoded_data); + // TODO: add audio_url support by reusing handle_media() + // replace this chunk with a marker p["type"] = "text"; p["text"] = mtmd_default_marker(); p.erase("input_audio"); } else if (type != "text") { - throw std::runtime_error("unsupported content[].type"); + throw std::invalid_argument("unsupported content[].type"); } } } @@ -940,7 +975,7 @@ json oaicompat_chat_params_parse( inputs.enable_thinking = opt.enable_thinking; if (!inputs.tools.empty() && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE) { if (body.contains("grammar")) { - throw std::runtime_error("Cannot use custom grammar constraints with tools."); + throw std::invalid_argument("Cannot use custom grammar constraints with tools."); } llama_params["parse_tool_calls"] = true; } @@ -959,7 +994,7 @@ json oaicompat_chat_params_parse( } else if (enable_thinking_kwarg == "false") { inputs.enable_thinking = false; } else if (!enable_thinking_kwarg.empty() && enable_thinking_kwarg[0] == '"') { - throw std::runtime_error("invalid type for \"enable_thinking\" (expected boolean, got string)"); + throw std::invalid_argument("invalid type for \"enable_thinking\" (expected boolean, got string)"); } // if the assistant message appears at the end of list, we do not add end-of-turn token @@ -972,14 +1007,14 @@ json oaicompat_chat_params_parse( /* sanity check, max one assistant message at the end of the list */ if (!inputs.messages.empty() && inputs.messages.back().role == "assistant"){ - throw std::runtime_error("Cannot have 2 or more assistant messages at the end of the list."); + throw std::invalid_argument("Cannot have 2 or more assistant messages at the end of the list."); } /* TODO: test this properly */ inputs.reasoning_format = COMMON_REASONING_FORMAT_NONE; if ( inputs.enable_thinking ) { - throw std::runtime_error("Assistant response prefill is incompatible with enable_thinking."); + throw std::invalid_argument("Assistant response prefill is incompatible with enable_thinking."); } inputs.add_generation_prompt = true; @@ -1016,22 +1051,19 @@ json oaicompat_chat_params_parse( for (const auto & stop : chat_params.additional_stops) { llama_params["stop"].push_back(stop); } - - // Handle "n" field - int n_choices = json_value(body, "n", 1); - if (n_choices != 1) { - throw std::runtime_error("Only one completion choice is allowed"); + if (!chat_params.parser.empty()) { + llama_params["chat_parser"] = chat_params.parser; } // Handle "logprobs" field // TODO: The response format of this option is not yet OAI-compatible, but seems like no one really using it; We may need to fix it in the future if (json_value(body, "logprobs", false)) { if (has_tools && stream) { - throw std::runtime_error("logprobs is not supported with tools + stream"); + throw std::invalid_argument("logprobs is not supported with tools + stream"); } llama_params["n_probs"] = json_value(body, "top_logprobs", 20); } else if (body.contains("top_logprobs") && !body.at("top_logprobs").is_null()) { - throw std::runtime_error("top_logprobs requires logprobs to be set to true"); + throw std::invalid_argument("top_logprobs requires logprobs to be set to true"); } // Copy remaining properties to llama_params @@ -1263,7 +1295,11 @@ json convert_anthropic_to_oai(const json & body) { return oai_body; } -json format_embeddings_response_oaicompat(const json & request, const json & embeddings, bool use_base64) { +json format_embeddings_response_oaicompat( + const json & request, + const std::string & model_name, + const json & embeddings, + bool use_base64) { json data = json::array(); int32_t n_tokens = 0; int i = 0; @@ -1293,7 +1329,7 @@ json format_embeddings_response_oaicompat(const json & request, const json & emb } json res = json { - {"model", json_value(request, "model", std::string(DEFAULT_OAICOMPAT_MODEL))}, + {"model", json_value(request, "model", model_name)}, {"object", "list"}, {"usage", json { {"prompt_tokens", n_tokens}, @@ -1307,6 +1343,7 @@ json format_embeddings_response_oaicompat(const json & request, const json & emb json format_response_rerank( const json & request, + const std::string & model_name, const json & ranks, bool is_tei_format, std::vector & texts, @@ -1338,7 +1375,7 @@ json format_response_rerank( if (is_tei_format) return results; json res = json{ - {"model", json_value(request, "model", std::string(DEFAULT_OAICOMPAT_MODEL))}, + {"model", json_value(request, "model", model_name)}, {"object", "list"}, {"usage", json{ {"prompt_tokens", n_tokens}, diff --git a/tools/server/server-common.h b/tools/server/server-common.h index ab8aabbad0..0629bb5edd 100644 --- a/tools/server/server-common.h +++ b/tools/server/server-common.h @@ -13,18 +13,18 @@ #include #include -#define DEFAULT_OAICOMPAT_MODEL "gpt-3.5-turbo" - const static std::string build_info("b" + std::to_string(LLAMA_BUILD_NUMBER) + "-" + LLAMA_COMMIT); using json = nlohmann::ordered_json; #define SLT_INF(slot, fmt, ...) LOG_INF("slot %12.*s: id %2d | task %d | " fmt, 12, __func__, (slot).id, ((slot).task ? (slot).task->id : -1), __VA_ARGS__) +#define SLT_CNT(slot, fmt, ...) LOG_CNT("" fmt, __VA_ARGS__) #define SLT_WRN(slot, fmt, ...) LOG_WRN("slot %12.*s: id %2d | task %d | " fmt, 12, __func__, (slot).id, ((slot).task ? (slot).task->id : -1), __VA_ARGS__) #define SLT_ERR(slot, fmt, ...) LOG_ERR("slot %12.*s: id %2d | task %d | " fmt, 12, __func__, (slot).id, ((slot).task ? (slot).task->id : -1), __VA_ARGS__) #define SLT_DBG(slot, fmt, ...) LOG_DBG("slot %12.*s: id %2d | task %d | " fmt, 12, __func__, (slot).id, ((slot).task ? (slot).task->id : -1), __VA_ARGS__) #define SRV_INF(fmt, ...) LOG_INF("srv %12.*s: " fmt, 12, __func__, __VA_ARGS__) +#define SRV_CNT(fmt, ...) LOG_CNT("" fmt, __VA_ARGS__) #define SRV_WRN(fmt, ...) LOG_WRN("srv %12.*s: " fmt, 12, __func__, __VA_ARGS__) #define SRV_ERR(fmt, ...) LOG_ERR("srv %12.*s: " fmt, 12, __func__, __VA_ARGS__) #define SRV_DBG(fmt, ...) LOG_DBG("srv %12.*s: " fmt, 12, __func__, __VA_ARGS__) @@ -217,6 +217,8 @@ public: llama_pos pos, int32_t seq_id, size_t & n_tokens_out) const; + + server_tokens clone() const; }; @@ -286,6 +288,7 @@ struct oaicompat_parser_options { bool allow_image; bool allow_audio; bool enable_thinking = true; + std::string media_path; }; // used by /chat/completions endpoint @@ -298,11 +301,16 @@ json oaicompat_chat_params_parse( json convert_anthropic_to_oai(const json & body); // TODO: move it to server-task.cpp -json format_embeddings_response_oaicompat(const json & request, const json & embeddings, bool use_base64 = false); +json format_embeddings_response_oaicompat( + const json & request, + const std::string & model_name, + const json & embeddings, + bool use_base64 = false); // TODO: move it to server-task.cpp json format_response_rerank( const json & request, + const std::string & model_name, const json & ranks, bool is_tei_format, std::vector & texts, diff --git a/tools/server/server-context.cpp b/tools/server/server-context.cpp index e992db70f1..4578f8d7a9 100644 --- a/tools/server/server-context.cpp +++ b/tools/server/server-context.cpp @@ -17,6 +17,7 @@ #include #include #include +#include // fix problem with std::min and std::max #if defined(_WIN32) @@ -34,7 +35,8 @@ constexpr int HTTP_POLLING_SECONDS = 1; // state diagram: https://github.com/ggml-org/llama.cpp/pull/9283 enum slot_state { SLOT_STATE_IDLE, - SLOT_STATE_STARTED, // TODO: this state is only used for setting up the initial prompt processing; maybe merge it with launch_slot_with_task in the future + SLOT_STATE_WAIT_OTHER, // after assigning a task, but waiting for parent slot to process prompt + SLOT_STATE_STARTED, // after assigning a task and about to process prompt SLOT_STATE_PROCESSING_PROMPT, SLOT_STATE_DONE_PROMPT, SLOT_STATE_GENERATING, @@ -100,7 +102,10 @@ struct server_slot { std::string generated_text; llama_tokens generated_tokens; - common_chat_msg chat_msg; + // idx of draft tokens in the main batch + // non-empty if we went to evaluate draft tokens + // ref: https://github.com/ggml-org/llama.cpp/pull/17808 + std::vector i_batch_dft; std::vector generated_token_probs; @@ -150,10 +155,8 @@ struct server_slot { struct common_sampler * smpl = nullptr; - llama_token sampled; - - common_chat_format chat_format = COMMON_CHAT_FORMAT_CONTENT_ONLY; - std::vector generated_tool_call_ids; + llama_token sampled; // in speculative mode, this is the last accepted token + llama_tokens drafted; // stats size_t n_sent_text = 0; // number of sent text character @@ -182,13 +185,12 @@ struct server_slot { stop = STOP_TYPE_NONE; stopping_word = ""; n_sent_text = 0; - chat_format = COMMON_CHAT_FORMAT_CONTENT_ONLY; + drafted.clear(); + i_batch_dft.clear(); generated_tokens.clear(); generated_token_probs.clear(); - chat_msg = {}; json_schema = json(); - generated_tool_call_ids.clear(); // clear speculative decoding stats n_draft_total = 0; @@ -261,6 +263,40 @@ struct server_slot { generated_token_probs.push_back(token); } + int get_n_draft_max() const { + if (!can_speculate()) { + return 0; + } + + // determine the max draft that fits the current slot state + int n_draft_max = task->params.speculative.n_max; + + // note: slot.prompt is not yet expanded with the `id` token sampled above + // also, need to leave space for 1 extra token to allow context shifts + n_draft_max = std::min(n_draft_max, n_ctx - prompt.n_tokens() - 2); + + if (n_remaining > 0) { + n_draft_max = std::min(n_draft_max, n_remaining - 1); + } + + SLT_DBG(*this, "max possible draft: %d\n", n_draft_max); + + if (n_draft_max < task->params.speculative.n_min) { + SLT_DBG(*this, "the max possible draft is too small: %d < %d - skipping speculative decoding\n", n_draft_max, task->params.speculative.n_min); + n_draft_max = 0; + } + return n_draft_max; + } + + // note: a slot can also be either a parent or a child + bool is_parent() const { + return is_processing() && task->n_children > 0; + } + + bool is_child() const { + return is_processing() && task->id_parent >= 0; + } + void release() { if (is_processing()) { GGML_ASSERT(task); @@ -301,23 +337,6 @@ struct server_slot { return timings; } - const common_chat_msg & update_chat_msg(std::vector & diffs) { - GGML_ASSERT(task); - - auto previous_msg = chat_msg; - SRV_DBG("Parsing chat message: %s\n", generated_text.c_str()); - auto new_msg = common_chat_parse( - generated_text, - /* is_partial= */ stop != STOP_TYPE_EOS, - task->params.oaicompat_chat_syntax); - if (!new_msg.empty()) { - new_msg.set_tool_call_ids(generated_tool_call_ids, gen_tool_call_id); - chat_msg = new_msg; - diffs = common_chat_msg_diff::compute_diffs(previous_msg, new_msg.empty() ? previous_msg : new_msg); - } - return chat_msg; - } - size_t find_stopping_strings(const std::string & text, const size_t last_token_size, bool is_full_stop) { GGML_ASSERT(task); @@ -367,8 +386,7 @@ struct server_slot { if (n_draft_total > 0) { const float draft_ratio = (float) n_draft_accepted / n_draft_total; - SLT_INF(*this, - "\n" + SLT_CNT(*this, "draft acceptance rate = %0.5f (%5d accepted / %5d generated)\n", draft_ratio, n_draft_accepted, n_draft_total ); @@ -407,6 +425,17 @@ struct server_slot { return res; } + + void copy_state_to(server_slot & other) const { + llama_memory_seq_rm(llama_get_memory(ctx), other.id, 0, -1); + llama_memory_seq_cp(llama_get_memory(ctx), id, other.id, 0, -1); + other.n_decoded = n_decoded; + other.n_remaining = n_remaining; + other.i_batch = i_batch; + other.n_prompt_tokens_cache = n_prompt_tokens_cache; + other.n_prompt_tokens_processed = n_prompt_tokens_processed; + other.prompt = prompt.clone(); + } }; @@ -518,6 +547,8 @@ struct server_context_impl { // Necessary similarity of prompt for slot selection float slot_prompt_similarity = 0.0f; + std::string model_name; // name of the loaded model, to be used by API + common_chat_templates_ptr chat_templates; oaicompat_parser_options oai_parser_opt; @@ -758,6 +789,18 @@ struct server_context_impl { } SRV_WRN("%s", "for more info see https://github.com/ggml-org/llama.cpp/pull/16391\n"); + if (!params_base.model_alias.empty()) { + // user explicitly specified model name + model_name = params_base.model_alias; + } else if (!params_base.model.name.empty()) { + // use model name in registry format (for models in cache) + model_name = params_base.model.name; + } else { + // fallback: derive model name from file name + auto model_path = std::filesystem::path(params_base.model.path); + model_name = model_path.filename().string(); + } + // thinking is enabled if: // 1. It's not explicitly disabled (reasoning_budget == 0) // 2. The chat template supports it @@ -773,6 +816,7 @@ struct server_context_impl { /* allow_image */ mctx ? mtmd_support_vision(mctx) : false, /* allow_audio */ mctx ? mtmd_support_audio (mctx) : false, /* enable_thinking */ enable_thinking, + /* media_path */ params_base.media_path, }; // print sample chat example to make it clear which template is used @@ -1031,7 +1075,9 @@ struct server_context_impl { slot.task = std::make_unique(std::move(task)); - slot.state = SLOT_STATE_STARTED; + slot.state = slot.is_child() + ? SLOT_STATE_WAIT_OTHER // wait for the parent to process prompt + : SLOT_STATE_STARTED; SLT_INF(slot, "%s", "processing task\n"); @@ -1268,8 +1314,6 @@ struct server_context_impl { } else { res->content = tkn.text_to_send; res->tokens = { tkn.tok }; - - slot.update_chat_msg(res->oaicompat_msg_diffs); } res->n_decoded = slot.n_decoded; @@ -1301,8 +1345,14 @@ struct server_context_impl { res->id_slot = slot.id; res->index = slot.task->index; - res->content = slot.generated_text; - res->tokens = std::move(slot.generated_tokens); + // in stream mode, content and tokens are already in last partial chunk + if (slot.task->params.stream) { + res->content = ""; + res->tokens = llama_tokens{}; + } else { + res->content = std::move(slot.generated_text); + res->tokens = std::move(slot.generated_tokens); + } res->timings = slot.get_timings(); res->prompt = slot.task->tokens.detokenize(ctx, true); res->response_fields = std::move(slot.task->params.response_fields); @@ -1322,7 +1372,6 @@ struct server_context_impl { res->res_type = slot.task->params.res_type; res->oaicompat_model = slot.task->params.oaicompat_model; res->oaicompat_cmpl_id = slot.task->params.oaicompat_cmpl_id; - res->oaicompat_msg = slot.update_chat_msg(res->oaicompat_msg_diffs); // populate res.probs_output if (slot.task->params.sampling.n_probs > 0) { @@ -1690,6 +1739,12 @@ struct server_context_impl { GGML_ABORT("not supported by multimodal"); } + if (slot.is_parent() || slot.is_child()) { + send_error(slot, "context shift cannot be used for shared prompt", ERROR_TYPE_SERVER); + slot.release(); + continue; + } + // Shift context int n_keep = slot.task->params.n_keep < 0 ? slot.task->n_tokens() : slot.task->params.n_keep; @@ -1751,14 +1806,57 @@ struct server_context_impl { continue; } - slot.i_batch = batch.n_tokens; + // generate draft tokens in speculative decoding mode + // TODO: rework to have a single draft llama_context shared across all slots [TAG_SERVER_SPEC_REWORK] + // perform the speculative drafting for all sequences at the same time in a single batch + int n_draft_max = slot.get_n_draft_max(); + if (n_draft_max > 0) { + if (mctx) { + // we should never reach this, as speculative is automatically disabled if mmproj is loaded + GGML_ABORT("not supported by multimodal"); + } - common_batch_add(batch, slot.sampled, slot.prompt.tokens.pos_next(), { slot.id }, true); + struct common_speculative_params params_spec; + params_spec.n_draft = n_draft_max; + params_spec.n_reuse = llama_n_ctx(slot.ctx_dft) - slot.task->params.speculative.n_max; + params_spec.p_min = slot.task->params.speculative.p_min; + const llama_tokens & cached_text_tokens = slot.prompt.tokens.get_text_tokens(); + llama_tokens draft = common_speculative_gen_draft(slot.spec, params_spec, cached_text_tokens, slot.sampled); - slot.prompt.tokens.push_back(slot.sampled); + // add the sampled token to the batch + slot.i_batch_dft.push_back(batch.n_tokens); + common_batch_add(batch, slot.sampled, slot.prompt.tokens.pos_next(), { slot.id }, true); + slot.prompt.tokens.push_back(slot.sampled); - SLT_DBG(slot, "slot decode token, n_ctx = %d, n_tokens = %d, truncated = %d\n", - slot.n_ctx, slot.prompt.n_tokens(), slot.truncated); + if (slot.task->params.speculative.n_min > (int) draft.size()) { + SLT_DBG(slot, "ignoring small draft: %d < %d\n", (int) draft.size(), slot.task->params.speculative.n_min); + // fallback to normal decoding + slot.i_batch = slot.i_batch_dft[0]; + slot.drafted.clear(); + slot.i_batch_dft.clear(); + } else { + // keep track of total number of drafted tokens tested + slot.n_draft_total += draft.size(); + + // add all drafted tokens to the batch + for (size_t i = 0; i < draft.size(); i++) { + slot.i_batch_dft.push_back(batch.n_tokens); + common_batch_add(batch, draft[i], slot.prompt.tokens.pos_next(), { slot.id }, true); + slot.prompt.tokens.push_back(draft[i]); + } + slot.drafted = std::move(draft); + } + } else { + // no speculative decoding + slot.i_batch = batch.n_tokens; + + common_batch_add(batch, slot.sampled, slot.prompt.tokens.pos_next(), { slot.id }, true); + + slot.prompt.tokens.push_back(slot.sampled); + + SLT_DBG(slot, "slot decode token, n_ctx = %d, n_tokens = %d, truncated = %d\n", + slot.n_ctx, slot.prompt.n_tokens(), slot.truncated); + } } // process in chunks of params.n_batch @@ -1857,8 +1955,18 @@ struct server_context_impl { n_past = std::min(n_past, slot.alora_invocation_start - 1); } + const auto n_cache_reuse = slot.task->params.n_cache_reuse; + + const bool can_cache_reuse = + llama_memory_can_shift(llama_get_memory(ctx)) && + !slot.prompt.tokens.has_mtmd; + + if (!can_cache_reuse && n_cache_reuse > 0) { + SLT_WRN(slot, "cache reuse is not supported - ignoring n_cache_reuse = %d\n", n_cache_reuse); + } + // reuse chunks from the cached prompt by shifting their KV cache in the new position - if (params_base.n_cache_reuse > 0) { + if (can_cache_reuse && n_cache_reuse > 0) { GGML_ASSERT(!slot.prompt.tokens.has_mtmd); size_t head_c = n_past; // cache @@ -1869,7 +1977,7 @@ struct server_context_impl { GGML_ABORT("not supported by multimodal"); } - SLT_DBG(slot, "trying to reuse chunks with size > %d, n_past = %d\n", params_base.n_cache_reuse, n_past); + SLT_DBG(slot, "trying to reuse chunks with size > %d, n_past = %d\n", n_cache_reuse, n_past); while (head_c < slot.prompt.tokens.size() && head_p < input_tokens.size()) { @@ -1878,11 +1986,10 @@ struct server_context_impl { while (head_c + n_match < slot.prompt.tokens.size() && head_p + n_match < input_tokens.size() && slot.prompt.tokens[head_c + n_match] == input_tokens[head_p + n_match]) { - n_match++; } - if (n_match >= (size_t) params_base.n_cache_reuse) { + if (n_match >= (size_t) n_cache_reuse) { SLT_INF(slot, "reusing chunk with size %zu, shifting KV cache [%zu, %zu) -> [%zu, %zu)\n", n_match, head_c, head_c + n_match, head_p, head_p + n_match); //for (size_t i = head_p; i < head_p + n_match; i++) { // SLT_DBG(slot, "cache token %3zu: %6d '%s'\n", i, prompt_tokens[i], common_token_to_piece(ctx, prompt_tokens[i]).c_str()); @@ -2313,7 +2420,31 @@ struct server_context_impl { // on successful decode, restore the original batch size n_batch = llama_n_batch(ctx); + // technically, measuring the time here excludes the sampling time for the last batch + // but on the other hand, we don't want to do too many system calls to measure the time, so it's ok + const int64_t t_current = ggml_time_us(); + for (auto & slot : slots) { + // may need to copy state to other slots + if (slot.state == SLOT_STATE_DONE_PROMPT && slot.is_parent()) { + std::vector child_slots; + for (auto & other : slots) { + if (other.state == SLOT_STATE_WAIT_OTHER && slot.task->id == other.task->id_parent) { + child_slots.push_back(&other); + } + } + + // we can only proceed if all child slots are having the correct tasks + if (child_slots.size() == slot.task->n_children) { + // copy state to the child slots + for (auto & child : child_slots) { + SLT_INF(slot, "copying state to child %d\n", child->id); + slot.copy_state_to(*child); + child->state = SLOT_STATE_DONE_PROMPT; + } + } + } + // optionally send prompt processing progress if (slot.state == SLOT_STATE_PROCESSING_PROMPT || slot.state == SLOT_STATE_DONE_PROMPT) { if (slot.task->params.stream && slot.task->params.return_progress) { @@ -2347,6 +2478,10 @@ struct server_context_impl { continue; // continue loop of slots } + if (slot.i_batch_dft.size() > 0) { + continue; // sample using speculative decoding + } + const int tok_idx = slot.i_batch - i; llama_token id = common_sampler_sample(slot.smpl, ctx, tok_idx); @@ -2357,8 +2492,6 @@ struct server_context_impl { slot.n_decoded += 1; - const int64_t t_current = ggml_time_us(); - if (slot.n_decoded == 1) { slot.t_start_generation = t_current; slot.t_prompt_processing = (slot.t_start_generation - slot.t_start_process_prompt) / 1e3; @@ -2387,84 +2520,32 @@ struct server_context_impl { } } - // do speculative decoding - // TODO: rework to have a single draft llama_context shared across all slots [TAG_SERVER_SPEC_REWORK] - // perform the speculative drafting for all sequences at the same time in a single batch + // speculative decoding - main model sample and accept for (auto & slot : slots) { - if (!slot.is_processing() || !slot.can_speculate()) { + if (slot.state != SLOT_STATE_GENERATING || slot.i_batch_dft.empty()) { continue; } - if (slot.state != SLOT_STATE_GENERATING) { - continue; - } - - if (mctx) { - // we should never reach this, as speculative is automatically disabled if mmproj is loaded - GGML_ABORT("not supported by multimodal"); - } - - // determine the max draft that fits the current slot state - int n_draft_max = slot.task->params.speculative.n_max; - - // note: slot.prompt is not yet expanded with the `id` token sampled above - // also, need to leave space for 1 extra token to allow context shifts - n_draft_max = std::min(n_draft_max, slot.n_ctx - slot.prompt.n_tokens() - 2); - - if (slot.n_remaining > 0) { - n_draft_max = std::min(n_draft_max, slot.n_remaining - 1); - } - - SLT_DBG(slot, "max possible draft: %d\n", n_draft_max); - - if (n_draft_max < slot.task->params.speculative.n_min) { - SLT_DBG(slot, "the max possible draft is too small: %d < %d - skipping speculative decoding\n", n_draft_max, slot.task->params.speculative.n_min); - - continue; - } - - llama_token id = slot.sampled; - - struct common_speculative_params params_spec; - params_spec.n_draft = n_draft_max; - params_spec.n_reuse = llama_n_ctx(slot.ctx_dft) - slot.task->params.speculative.n_max; - params_spec.p_min = slot.task->params.speculative.p_min; - - const llama_tokens & cached_text_tokens = slot.prompt.tokens.get_text_tokens(); - llama_tokens draft = common_speculative_gen_draft(slot.spec, params_spec, cached_text_tokens, id); - - // ignore small drafts - if (slot.task->params.speculative.n_min > (int) draft.size()) { - SLT_DBG(slot, "ignoring small draft: %d < %d\n", (int) draft.size(), slot.task->params.speculative.n_min); - - continue; - } - - // keep track of total number of drafted tokens tested - slot.n_draft_total += draft.size(); - - // construct the speculation batch - common_batch_clear(slot.batch_spec); - common_batch_add (slot.batch_spec, id, slot.prompt.tokens.pos_next(), { slot.id }, true); - - for (size_t i = 0; i < draft.size(); ++i) { - common_batch_add(slot.batch_spec, draft[i], slot.prompt.tokens.pos_next() + 1 + i, { slot.id }, true); - } - - SLT_DBG(slot, "decoding speculative batch, size = %d\n", slot.batch_spec.n_tokens); - - llama_decode(ctx, slot.batch_spec); + size_t n_draft = slot.drafted.size(); // the accepted tokens from the speculation - const auto ids = common_sampler_sample_and_accept_n(slot.smpl, ctx, draft); + const auto ids = common_sampler_sample_and_accept_n(slot.smpl, ctx, slot.i_batch_dft, slot.drafted); + slot.i_batch_dft.clear(); + slot.drafted.clear(); slot.n_decoded += ids.size(); + slot.t_token_generation = std::max(1, t_current - slot.t_start_generation) / 1e3; + // update how many tokens out of those tested were accepted slot.n_draft_accepted += ids.size() - 1; - slot.prompt.tokens.push_back(id); + // rollback to the state before sampling the draft tokens + slot.prompt.tokens.keep_first(slot.prompt.n_tokens() - n_draft); + + // add accepted tokens to the prompt slot.prompt.tokens.insert({ids.begin(), ids.end() - 1}); + slot.sampled = ids.back(); // last accepted token llama_memory_seq_rm(llama_get_memory(ctx), slot.id, slot.prompt.n_tokens(), -1); @@ -2487,7 +2568,7 @@ struct server_context_impl { } } - SLT_DBG(slot, "accepted %d/%d draft tokens, new n_tokens = %d\n", (int) ids.size() - 1, (int) draft.size(), slot.prompt.n_tokens()); + SLT_DBG(slot, "accepted %d/%d draft tokens, new n_tokens = %d\n", (int) ids.size() - 1, (int) slot.drafted.size(), slot.prompt.n_tokens()); } } @@ -2508,6 +2589,10 @@ struct server_context_impl { int get_slot_n_ctx() { return slots.back().n_ctx; } + + server_response_reader get_response_reader() { + return server_response_reader(queue_tasks, queue_results, HTTP_POLLING_SECONDS); + } }; // @@ -2537,8 +2622,8 @@ llama_context * server_context::get_llama_context() const { return impl->ctx; } -std::pair server_context::get_queues() { - return { impl->queue_tasks, impl->queue_results }; +server_response_reader server_context::get_response_reader() { + return impl->get_response_reader(); } @@ -2547,7 +2632,7 @@ std::pair server_context::get_queues() { struct server_res_generator : server_http_res { server_response_reader rd; server_res_generator(server_context_impl & ctx_server) - : rd({ctx_server.queue_tasks, ctx_server.queue_results}, HTTP_POLLING_SECONDS) {} + : rd(ctx_server.queue_tasks, ctx_server.queue_results, HTTP_POLLING_SECONDS) {} void ok(const json & response_data) { status = 200; data = safe_json_to_str(response_data); @@ -2595,11 +2680,12 @@ static std::unique_ptr handle_completions_impl( inputs = tokenize_input_prompts(ctx_server.vocab, ctx_server.mctx, prompt, true, true); } tasks.reserve(inputs.size()); + int idx = 0; for (size_t i = 0; i < inputs.size(); i++) { server_task task = server_task(type); task.id = ctx_server.queue_tasks.get_new_id(); - task.index = i; + task.index = idx++; task.tokens = std::move(inputs[i]); task.params = server_task::params_from_json_cmpl( @@ -2611,7 +2697,18 @@ static std::unique_ptr handle_completions_impl( // OAI-compat task.params.res_type = res_type; task.params.oaicompat_cmpl_id = completion_id; - // oaicompat_model is already populated by params_from_json_cmpl + task.params.oaicompat_model = ctx_server.model_name; + + if (task.params.n_cmpl > 1) { + task.n_children = task.params.n_cmpl - 1; + for (size_t j = 0; j < task.n_children; j++) { + server_task child = task.create_child( + task.id, + ctx_server.queue_tasks.get_new_id(), + idx++); + tasks.push_back(std::move(child)); + } + } tasks.push_back(std::move(task)); } @@ -2638,10 +2735,22 @@ static std::unique_ptr handle_completions_impl( GGML_ASSERT(dynamic_cast(res.get()) != nullptr); arr.push_back(res->to_json()); } - // if single request, return single object instead of array - res->ok(arr.size() == 1 ? arr[0] : arr); + GGML_ASSERT(!arr.empty() && "empty results"); + if (arr.size() == 1) { + // if single request, return single object instead of array + res->ok(arr[0]); + } else if (res_type == TASK_RESPONSE_TYPE_OAI_CHAT || res_type == TASK_RESPONSE_TYPE_OAI_CMPL) { + // if multiple results in OAI format, we need to re-format them + json & choices = arr[0]["choices"]; + for (size_t i = 1; i < arr.size(); i++) { + choices.push_back(std::move(arr[i]["choices"][0])); + } + res->ok(arr[0]); + } else { + // multi-results, non-OAI compat + res->ok(arr); + } } - } else { // in streaming mode, the first error must be treated as non-stream response // this is to match the OAI API behavior @@ -2660,76 +2769,92 @@ static std::unique_ptr handle_completions_impl( } // next responses are streamed + // to be sent immediately + json first_result_json = first_result->to_json(); if (res_type == TASK_RESPONSE_TYPE_ANTHROPIC) { - res->data = format_anthropic_sse(first_result->to_json()); + res->data = format_anthropic_sse(first_result_json); } else { - res->data = format_oai_sse(first_result->to_json()); // to be sent immediately + res->data = format_oai_sse(first_result_json); } res->status = 200; res->content_type = "text/event-stream"; res->next = [res_this = res.get(), res_type, &should_stop](std::string & output) -> bool { - if (should_stop()) { - SRV_DBG("%s", "stopping streaming due to should_stop condition\n"); - return false; // should_stop condition met - } - - if (!res_this->data.empty()) { - // flush the first chunk - output = std::move(res_this->data); - res_this->data.clear(); - return true; - } - - server_response_reader & rd = res_this->rd; - - // check if there is more data - if (!rd.has_next()) { + static auto format_error = [](task_response_type res_type, const json & res_json) { if (res_type == TASK_RESPONSE_TYPE_ANTHROPIC) { - // Anthropic doesn't send [DONE], message_stop was already sent - output = ""; - } else if (res_type != TASK_RESPONSE_TYPE_NONE) { - output = "data: [DONE]\n\n"; - } else { - output = ""; - } - SRV_DBG("%s", "all results received, terminating stream\n"); - return false; // no more data, terminate - } - - // receive subsequent results - auto result = rd.next(should_stop); - if (result == nullptr) { - SRV_DBG("%s", "stopping streaming due to should_stop condition\n"); - return false; // should_stop condition met - } - - // send the results - json res_json = result->to_json(); - if (result->is_error()) { - if (res_type == TASK_RESPONSE_TYPE_ANTHROPIC) { - output = format_anthropic_sse({ + return format_anthropic_sse({ {"event", "error"}, {"data", res_json}, }); } else { - output = format_oai_sse(json {{ "error", res_json }}); + return format_oai_sse(json {{ "error", res_json }}); } - SRV_DBG("%s", "error received during streaming, terminating stream\n"); - return false; // terminate on error - } else { - GGML_ASSERT( - dynamic_cast(result.get()) != nullptr - || dynamic_cast(result.get()) != nullptr - ); - if (res_type == TASK_RESPONSE_TYPE_ANTHROPIC) { - output = format_anthropic_sse(res_json); - } else { - output = format_oai_sse(res_json); - } - } + }; - // has next data, continue - return true; + try { + if (should_stop()) { + SRV_DBG("%s", "stopping streaming due to should_stop condition\n"); + return false; // should_stop condition met + } + + if (!res_this->data.empty()) { + // flush the first chunk + output = std::move(res_this->data); + res_this->data.clear(); + return true; + } + + server_response_reader & rd = res_this->rd; + + // check if there is more data + if (!rd.has_next()) { + if (res_type == TASK_RESPONSE_TYPE_ANTHROPIC) { + // Anthropic doesn't send [DONE], message_stop was already sent + output = ""; + } else if (res_type != TASK_RESPONSE_TYPE_NONE) { + output = "data: [DONE]\n\n"; + } else { + output = ""; + } + SRV_DBG("%s", "all results received, terminating stream\n"); + return false; // no more data, terminate + } + + // receive subsequent results + auto result = rd.next(should_stop); + if (result == nullptr) { + SRV_DBG("%s", "stopping streaming due to should_stop condition\n"); + return false; // should_stop condition met + } + + // send the results + if (result->is_error()) { + json res_json = result->to_json(); + output = format_error(res_type, res_json); + SRV_DBG("%s", "error received during streaming, terminating stream\n"); + return false; // terminate on error + } else { + GGML_ASSERT( + dynamic_cast(result.get()) != nullptr + || dynamic_cast(result.get()) != nullptr + ); + json res_json = result->to_json(); + if (res_type == TASK_RESPONSE_TYPE_ANTHROPIC) { + output = format_anthropic_sse(res_json); + } else { + output = format_oai_sse(res_json); + } + } + + // has next data, continue + return true; + + } catch (const std::exception & e) { + json error_json = format_error_response(e.what(), ERROR_TYPE_SERVER); + output = format_error(res_type, error_json); + + // terminate on exception + return false; + } }; } @@ -2939,7 +3064,7 @@ void server_routes::init_routes() { json data = { { "default_generation_settings", default_generation_settings_for_props }, { "total_slots", ctx_server.params_base.n_parallel }, - { "model_alias", ctx_server.params_base.model_alias }, + { "model_alias", ctx_server.model_name }, { "model_path", ctx_server.params_base.model.path }, { "modalities", json { {"vision", ctx_server.oai_parser_opt.allow_image}, @@ -3181,8 +3306,8 @@ void server_routes::init_routes() { json models = { {"models", { { - {"name", params.model_alias.empty() ? params.model.path : params.model_alias}, - {"model", params.model_alias.empty() ? params.model.path : params.model_alias}, + {"name", ctx_server.model_name}, + {"model", ctx_server.model_name}, {"modified_at", ""}, {"size", ""}, {"digest", ""}, // dummy value, llama.cpp does not support managing model file's hash @@ -3204,7 +3329,7 @@ void server_routes::init_routes() { {"object", "list"}, {"data", { { - {"id", params.model_alias.empty() ? params.model.path : params.model_alias}, + {"id", ctx_server.model_name}, {"object", "model"}, {"created", std::time(0)}, {"owned_by", "llamacpp"}, @@ -3317,7 +3442,7 @@ void server_routes::init_routes() { // create and queue the task json responses = json::array(); - server_response_reader rd({ctx_server.queue_tasks, ctx_server.queue_results}, HTTP_POLLING_SECONDS); + server_response_reader rd = ctx_server.get_response_reader(); { std::vector tasks; tasks.reserve(documents.size()); @@ -3351,6 +3476,7 @@ void server_routes::init_routes() { // write JSON response json root = format_response_rerank( body, + ctx_server.model_name, responses, is_tei_format, documents, @@ -3576,7 +3702,7 @@ std::unique_ptr server_routes::handle_embeddings_impl(cons // create and queue the task json responses = json::array(); - server_response_reader rd({ctx_server.queue_tasks, ctx_server.queue_results}, HTTP_POLLING_SECONDS); + server_response_reader rd = ctx_server.get_response_reader(); { std::vector tasks; for (size_t i = 0; i < tokenized_prompts.size(); i++) { @@ -3613,7 +3739,7 @@ std::unique_ptr server_routes::handle_embeddings_impl(cons // write JSON response json root = res_type == TASK_RESPONSE_TYPE_OAI_EMBD - ? format_embeddings_response_oaicompat(body, responses, use_base64) + ? format_embeddings_response_oaicompat(body, ctx_server.model_name, responses, use_base64) : json(responses); res->ok(root); return res; diff --git a/tools/server/server-context.h b/tools/server/server-context.h index 05b4afaeeb..eaa1380877 100644 --- a/tools/server/server-context.h +++ b/tools/server/server-context.h @@ -31,9 +31,8 @@ struct server_context { // get the underlaying llama_context llama_context * get_llama_context() const; - // get the underlaying queue_tasks and queue_results - // used by CLI application - std::pair get_queues(); + // get a new response reader, used by CLI application + server_response_reader get_response_reader(); }; diff --git a/tools/server/server-models.cpp b/tools/server/server-models.cpp index 0f812ed411..6f88e93c4b 100644 --- a/tools/server/server-models.cpp +++ b/tools/server/server-models.cpp @@ -7,6 +7,7 @@ #include #include +#include #include #include #include @@ -24,8 +25,55 @@ #include #endif +#if defined(__APPLE__) && defined(__MACH__) +// macOS: use _NSGetExecutablePath to get the executable path +#include +#include +#endif + #define CMD_EXIT "exit" +static std::filesystem::path get_server_exec_path() { +#if defined(_WIN32) + wchar_t buf[32768] = { 0 }; // Large buffer to handle long paths + DWORD len = GetModuleFileNameW(nullptr, buf, _countof(buf)); + if (len == 0 || len >= _countof(buf)) { + throw std::runtime_error("GetModuleFileNameW failed or path too long"); + } + return std::filesystem::path(buf); +#elif defined(__APPLE__) && defined(__MACH__) + char small_path[PATH_MAX]; + uint32_t size = sizeof(small_path); + + if (_NSGetExecutablePath(small_path, &size) == 0) { + // resolve any symlinks to get absolute path + try { + return std::filesystem::canonical(std::filesystem::path(small_path)); + } catch (...) { + return std::filesystem::path(small_path); + } + } else { + // buffer was too small, allocate required size and call again + std::vector buf(size); + if (_NSGetExecutablePath(buf.data(), &size) == 0) { + try { + return std::filesystem::canonical(std::filesystem::path(buf.data())); + } catch (...) { + return std::filesystem::path(buf.data()); + } + } + throw std::runtime_error("_NSGetExecutablePath failed after buffer resize"); + } +#else + char path[FILENAME_MAX]; + ssize_t count = readlink("/proc/self/exe", path, FILENAME_MAX); + if (count <= 0) { + throw std::runtime_error("failed to resolve /proc/self/exe"); + } + return std::filesystem::path(std::string(path, count)); +#endif +} + struct local_model { std::string name; std::string path; @@ -99,6 +147,14 @@ server_models::server_models( for (char ** env = envp; *env != nullptr; env++) { base_env.push_back(std::string(*env)); } + GGML_ASSERT(!base_args.empty()); + // set binary path + try { + base_args[0] = get_server_exec_path().string(); + } catch (const std::exception & e) { + LOG_WRN("failed to get server executable path: %s\n", e.what()); + LOG_WRN("using original argv[0] as fallback: %s\n", base_args[0].c_str()); + } // TODO: allow refreshing cached model list // add cached models auto cached_models = common_list_cached_models(); @@ -587,26 +643,26 @@ static void res_ok(std::unique_ptr & res, const json & response res->data = safe_json_to_str(response_data); } -static void res_error(std::unique_ptr & res, const json & error_data) { +static void res_err(std::unique_ptr & res, const json & error_data) { res->status = json_value(error_data, "code", 500); res->data = safe_json_to_str({{ "error", error_data }}); } static bool router_validate_model(const std::string & name, server_models & models, bool models_autoload, std::unique_ptr & res) { if (name.empty()) { - res_error(res, format_error_response("model name is missing from the request", ERROR_TYPE_INVALID_REQUEST)); + res_err(res, format_error_response("model name is missing from the request", ERROR_TYPE_INVALID_REQUEST)); return false; } auto meta = models.get_meta(name); if (!meta.has_value()) { - res_error(res, format_error_response("model not found", ERROR_TYPE_INVALID_REQUEST)); + res_err(res, format_error_response("model not found", ERROR_TYPE_INVALID_REQUEST)); return false; } if (models_autoload) { models.ensure_model_loaded(name); } else { if (meta->status != SERVER_MODEL_STATUS_LOADED) { - res_error(res, format_error_response("model is not loaded", ERROR_TYPE_INVALID_REQUEST)); + res_err(res, format_error_response("model is not loaded", ERROR_TYPE_INVALID_REQUEST)); return false; } } @@ -706,11 +762,11 @@ void server_models_routes::init_routes() { std::string name = json_value(body, "model", std::string()); auto model = models.get_meta(name); if (!model.has_value()) { - res_error(res, format_error_response("model is not found", ERROR_TYPE_NOT_FOUND)); + res_err(res, format_error_response("model is not found", ERROR_TYPE_NOT_FOUND)); return res; } if (model->status == SERVER_MODEL_STATUS_LOADED) { - res_error(res, format_error_response("model is already loaded", ERROR_TYPE_INVALID_REQUEST)); + res_err(res, format_error_response("model is already loaded", ERROR_TYPE_INVALID_REQUEST)); return res; } models.load(name, false); @@ -768,11 +824,11 @@ void server_models_routes::init_routes() { std::string name = json_value(body, "model", std::string()); auto model = models.get_meta(name); if (!model.has_value()) { - res_error(res, format_error_response("model is not found", ERROR_TYPE_INVALID_REQUEST)); + res_err(res, format_error_response("model is not found", ERROR_TYPE_INVALID_REQUEST)); return res; } if (model->status != SERVER_MODEL_STATUS_LOADED) { - res_error(res, format_error_response("model is not loaded", ERROR_TYPE_INVALID_REQUEST)); + res_err(res, format_error_response("model is not loaded", ERROR_TYPE_INVALID_REQUEST)); return res; } models.unload(name); @@ -834,6 +890,29 @@ struct pipe_t { } }; +static std::string to_lower_copy(const std::string & value) { + std::string lowered(value.size(), '\0'); + std::transform(value.begin(), value.end(), lowered.begin(), [](unsigned char c) { return std::tolower(c); }); + return lowered; +} + +static bool should_strip_proxy_header(const std::string & header_name) { + // Headers that get duplicated when router forwards child responses + if (header_name == "server" || + header_name == "transfer-encoding" || + header_name == "content-length" || // quick fix for https://github.com/ggml-org/llama.cpp/issues/17710 + header_name == "keep-alive") { + return true; + } + + // Router injects CORS, child also sends them: duplicate + if (header_name.rfind("access-control-", 0) == 0) { + return true; + } + + return false; +} + server_http_proxy::server_http_proxy( const std::string & method, const std::string & host, @@ -870,6 +949,14 @@ server_http_proxy::server_http_proxy( msg_t msg; msg.status = response.status; for (const auto & [key, value] : response.headers) { + const auto lowered = to_lower_copy(key); + if (should_strip_proxy_header(lowered)) { + continue; + } + if (lowered == "content-type") { + msg.content_type = value; + continue; + } msg.headers[key] = value; } return pipe->write(std::move(msg)); // send headers first @@ -877,7 +964,7 @@ server_http_proxy::server_http_proxy( httplib::ContentReceiverWithProgress content_receiver = [pipe](const char * data, size_t data_length, size_t, size_t) { // send data chunks // returns false if pipe is closed / broken (signal to stop receiving) - return pipe->write({{}, 0, std::string(data, data_length)}); + return pipe->write({{}, 0, std::string(data, data_length), ""}); }; // prepare the request to destination server @@ -900,8 +987,8 @@ server_http_proxy::server_http_proxy( if (result.error() != httplib::Error::Success) { auto err_str = httplib::to_string(result.error()); SRV_ERR("http client error: %s\n", err_str.c_str()); - pipe->write({{}, 500, ""}); // header - pipe->write({{}, 0, "proxy error: " + err_str}); // body + pipe->write({{}, 500, "", ""}); // header + pipe->write({{}, 0, "proxy error: " + err_str, ""}); // body } pipe->close_write(); // signal EOF to reader SRV_DBG("%s", "client request thread ended\n"); @@ -909,12 +996,17 @@ server_http_proxy::server_http_proxy( this->thread.detach(); // wait for the first chunk (headers) - msg_t header; - if (pipe->read(header, should_stop)) { - SRV_DBG("%s", "received response headers\n"); - this->status = header.status; - this->headers = header.headers; - } else { - SRV_DBG("%s", "no response headers received (request cancelled?)\n"); + { + msg_t header; + if (pipe->read(header, should_stop)) { + SRV_DBG("%s", "received response headers\n"); + this->status = header.status; + this->headers = std::move(header.headers); + if (!header.content_type.empty()) { + this->content_type = std::move(header.content_type); + } + } else { + SRV_DBG("%s", "no response headers received (request cancelled?)\n"); + } } } diff --git a/tools/server/server-models.h b/tools/server/server-models.h index b9bec983ef..526e7488dc 100644 --- a/tools/server/server-models.h +++ b/tools/server/server-models.h @@ -170,5 +170,6 @@ private: std::map headers; int status = 0; std::string data; + std::string content_type; }; }; diff --git a/tools/server/server-queue.cpp b/tools/server/server-queue.cpp index 38a4858522..3cceb2bbe2 100644 --- a/tools/server/server-queue.cpp +++ b/tools/server/server-queue.cpp @@ -271,8 +271,21 @@ void server_response::terminate() { // server_response_reader // +void server_response_reader::post_task(server_task && task) { + GGML_ASSERT(id_tasks.empty() && "post_task() can only be called once per reader"); + id_tasks.insert(task.id); + states.push_back(task.create_state()); + queue_results.add_waiting_task_id(task.id); + queue_tasks.post(std::move(task)); +} + void server_response_reader::post_tasks(std::vector && tasks) { + GGML_ASSERT(id_tasks.empty() && "post_tasks() can only be called once per reader"); id_tasks = server_task::get_list_id(tasks); + states.reserve(tasks.size()); + for (size_t i = 0; i < tasks.size(); i++) { + states.push_back(tasks[i].create_state()); + } queue_results.add_waiting_tasks(tasks); queue_tasks.post(std::move(tasks)); } @@ -298,6 +311,12 @@ server_task_result_ptr server_response_reader::next(const std::function SRV_DBG("%s", "received error result, stopping further processing\n"); return result; } + if (!states.empty()) { + // update the generation state if needed + size_t idx = result->get_index(); + GGML_ASSERT(idx < states.size()); + result->update(states[idx]); + } if (result->is_stop()) { received_count++; } diff --git a/tools/server/server-queue.h b/tools/server/server-queue.h index 209d2017c7..726eadf4ef 100644 --- a/tools/server/server-queue.h +++ b/tools/server/server-queue.h @@ -7,6 +7,8 @@ #include #include +// struct for managing server tasks +// in most cases, use server_response_reader to post new tasks and retrieve results struct server_queue { private: int id = 0; @@ -67,6 +69,8 @@ private: void cleanup_pending_task(int id_target); }; +// struct for managing server responses +// in most cases, use server_response_reader to retrieve results struct server_response { private: bool running = true; @@ -120,13 +124,18 @@ struct server_response_reader { bool cancelled = false; int polling_interval_seconds; + // tracking generation state and partial tool calls + // only used by streaming completions + std::vector states; + // should_stop function will be called each polling_interval_seconds - server_response_reader(std::pair server_queues, int polling_interval_seconds) - : queue_tasks(server_queues.first), queue_results(server_queues.second), polling_interval_seconds(polling_interval_seconds) {} + server_response_reader(server_queue & queue_tasks, server_response & queue_results, int polling_interval_seconds) + : queue_tasks(queue_tasks), queue_results(queue_results), polling_interval_seconds(polling_interval_seconds) {} ~server_response_reader() { stop(); } + void post_task(server_task && tasks); void post_tasks(std::vector && tasks); bool has_next() const; diff --git a/tools/server/server-task.cpp b/tools/server/server-task.cpp index b447a1ef6d..360826062b 100644 --- a/tools/server/server-task.cpp +++ b/tools/server/server-task.cpp @@ -155,11 +155,12 @@ task_params server_task::params_from_json_cmpl( // Sampling parameter defaults are loaded from the global server context (but individual requests can still them) task_params defaults; - defaults.sampling = params_base.sampling; - defaults.speculative = params_base.speculative; - defaults.n_keep = params_base.n_keep; - defaults.n_predict = params_base.n_predict; - defaults.antiprompt = params_base.antiprompt; + defaults.sampling = params_base.sampling; + defaults.speculative = params_base.speculative; + defaults.n_keep = params_base.n_keep; + defaults.n_predict = params_base.n_predict; + defaults.n_cache_reuse = params_base.n_cache_reuse; + defaults.antiprompt = params_base.antiprompt; // enabling this will output extra debug information in the HTTP responses from the server params.verbose = params_base.verbosity > 9; @@ -175,6 +176,8 @@ task_params server_task::params_from_json_cmpl( params.n_indent = json_value(data, "n_indent", defaults.n_indent); params.n_keep = json_value(data, "n_keep", defaults.n_keep); params.n_discard = json_value(data, "n_discard", defaults.n_discard); + params.n_cmpl = json_value(data, "n_cmpl", json_value(data, "n", 1)); + params.n_cache_reuse = json_value(data, "n_cache_reuse", defaults.n_cache_reuse); //params.t_max_prompt_ms = json_value(data, "t_max_prompt_ms", defaults.t_max_prompt_ms); // TODO: implement params.t_max_predict_ms = json_value(data, "t_max_predict_ms", defaults.t_max_predict_ms); params.response_fields = json_value(data, "response_fields", std::vector()); @@ -297,6 +300,9 @@ task_params server_task::params_from_json_cmpl( params.oaicompat_chat_syntax.reasoning_in_content = params.stream && (reasoning_format == COMMON_REASONING_FORMAT_DEEPSEEK_LEGACY); params.oaicompat_chat_syntax.thinking_forced_open = json_value(data, "thinking_forced_open", false); params.oaicompat_chat_syntax.parse_tool_calls = json_value(data, "parse_tool_calls", false); + if (data.contains("chat_parser")) { + params.oaicompat_chat_syntax.parser.load(data.at("chat_parser").get()); + } } { @@ -450,8 +456,9 @@ task_params server_task::params_from_json_cmpl( } } - std::string model_name = params_base.model_alias.empty() ? DEFAULT_OAICOMPAT_MODEL : params_base.model_alias; - params.oaicompat_model = json_value(data, "model", model_name); + if (params.n_cmpl > params_base.n_parallel) { + throw std::runtime_error("n_cmpl cannot be greater than the number of slots, please increase -np"); + } return params; } @@ -565,6 +572,7 @@ std::vector completion_token_output::str_to_bytes(const std::stri // server_task_result_cmpl_final // json server_task_result_cmpl_final::to_json() { + GGML_ASSERT(is_updated && "update() must be called before to_json()"); switch (res_type) { case TASK_RESPONSE_TYPE_NONE: return to_json_non_oaicompat(); @@ -582,8 +590,8 @@ json server_task_result_cmpl_final::to_json() { json server_task_result_cmpl_final::to_json_non_oaicompat() { json res = json { {"index", index}, - {"content", stream ? "" : content}, // in stream mode, content is already in last partial chunk - {"tokens", stream ? llama_tokens {} : tokens}, + {"content", content}, + {"tokens", tokens}, {"id_slot", id_slot}, {"stop", true}, {"model", oaicompat_model}, @@ -619,7 +627,7 @@ json server_task_result_cmpl_final::to_json_oaicompat() { json res = json { {"choices", json::array({ json{ - {"text", stream ? "" : content}, // in stream mode, content is already in last partial chunk + {"text", content}, {"index", index}, {"logprobs", logprobs}, {"finish_reason", finish_reason}, @@ -663,7 +671,7 @@ json server_task_result_cmpl_final::to_json_oaicompat_chat() { json choice { {"finish_reason", finish_reason}, - {"index", 0}, + {"index", index}, {"message", msg.to_json_oaicompat()}, }; @@ -700,6 +708,25 @@ json server_task_result_cmpl_final::to_json_oaicompat_chat() { return res; } +common_chat_msg task_result_state::update_chat_msg( + const std::string & text_added, + bool is_partial, + std::vector & diffs) { + generated_text += text_added; + auto msg_prv_copy = chat_msg; + SRV_DBG("Parsing chat message: %s\n", generated_text.c_str()); + auto new_msg = common_chat_parse( + generated_text, + is_partial, + oaicompat_chat_syntax); + if (!new_msg.empty()) { + new_msg.set_tool_call_ids(generated_tool_call_ids, gen_tool_call_id); + chat_msg = new_msg; + diffs = common_chat_msg_diff::compute_diffs(msg_prv_copy, new_msg.empty() ? msg_prv_copy : new_msg); + } + return chat_msg; +} + json server_task_result_cmpl_final::to_json_oaicompat_chat_stream() { std::time_t t = std::time(0); std::string finish_reason = "length"; @@ -956,6 +983,7 @@ json server_task_result_cmpl_final::to_json_anthropic_stream() { // server_task_result_cmpl_partial // json server_task_result_cmpl_partial::to_json() { + GGML_ASSERT(is_updated && "update() must be called before to_json()"); switch (res_type) { case TASK_RESPONSE_TYPE_NONE: return to_json_non_oaicompat(); @@ -1043,7 +1071,7 @@ json server_task_result_cmpl_partial::to_json_oaicompat_chat() { {"choices", json::array({ json { {"finish_reason", nullptr}, - {"index", 0}, + {"index", index}, {"delta", delta}, }, })}, diff --git a/tools/server/server-task.h b/tools/server/server-task.h index a22d7cab11..9011ff944b 100644 --- a/tools/server/server-task.h +++ b/tools/server/server-task.h @@ -53,6 +53,9 @@ struct task_params { int32_t n_discard = 0; // number of tokens after n_keep that may be discarded when shifting context, 0 defaults to half int32_t n_predict = -1; // new tokens to predict int32_t n_indent = 0; // minimum line indentation for the generated text in number of whitespace characters + int32_t n_cmpl = 1; // number of completions to generate from this prompt + + int32_t n_cache_reuse = 0; // min chunk size to attempt reusing from the cache via KV shifting (0 = disabled) int64_t t_max_prompt_ms = -1; // TODO: implement int64_t t_max_predict_ms = -1; // if positive, limit the generation phase to this time limit @@ -61,18 +64,19 @@ struct task_params { std::vector antiprompt; std::vector response_fields; - bool timings_per_token = false; + + bool timings_per_token = false; bool post_sampling_probs = false; struct common_params_sampling sampling; struct common_params_speculative speculative; // response formatting - bool verbose = false; - task_response_type res_type = TASK_RESPONSE_TYPE_NONE; - std::string oaicompat_model; - std::string oaicompat_cmpl_id; - common_chat_syntax oaicompat_chat_syntax; + bool verbose = false; + task_response_type res_type = TASK_RESPONSE_TYPE_NONE; + std::string oaicompat_model; + std::string oaicompat_cmpl_id; + common_chat_syntax oaicompat_chat_syntax; // Embeddings int32_t embd_normalize = 2; // (-1=none, 0=max absolute int16, 1=taxicab, 2=Euclidean/L2, >2=p-norm) @@ -81,6 +85,25 @@ struct task_params { json to_json(bool only_metrics = false) const; }; +// struct for tracking the state of a task (e.g., for streaming) +struct task_result_state { + // tracking diffs for partial tool calls + std::vector diffs; + common_chat_syntax oaicompat_chat_syntax; + common_chat_msg chat_msg; + std::string generated_text; // append new chunks of generated text here + std::vector generated_tool_call_ids; + + task_result_state(const common_chat_syntax & oaicompat_chat_syntax) + : oaicompat_chat_syntax(oaicompat_chat_syntax) {} + + // parse partial tool calls and update the internal state + common_chat_msg update_chat_msg( + const std::string & text_added, + bool is_partial, + std::vector & diffs); +}; + struct server_task { int id = -1; // to be filled by server_queue int index = -1; // used when there are multiple prompts (batch request) @@ -89,6 +112,10 @@ struct server_task { int id_target = -1; int id_slot = -1; + // used by parallel sampling (multiple completions from same prompt) + size_t n_children = 0; // number of tasks reusing this prompt + int id_parent = -1; + // used by SERVER_TASK_TYPE_INFERENCE task_params params; server_tokens tokens; @@ -130,6 +157,23 @@ struct server_task { } return ids; } + + server_task create_child(int id_parent, int id_child, int idx) const { + server_task copy; + copy.id = id_child; + copy.index = idx; + copy.id_parent = id_parent; + copy.params = params; + copy.type = type; + copy.tokens = tokens.clone(); + return copy; + } + + // the task will be moved into queue, then onto slots + // however, the state must be kept by caller (e.g., HTTP thread) + task_result_state create_state() const { + return task_result_state(params.oaicompat_chat_syntax); + } }; struct result_timings { @@ -175,6 +219,9 @@ struct server_task_result { virtual int get_index() { return -1; } + virtual void update(task_result_state &) { + // only used by server_task_result_cmpl_* + } virtual json to_json() = 0; virtual ~server_task_result() = default; }; @@ -233,9 +280,10 @@ struct server_task_result_cmpl_final : server_task_result { task_response_type res_type = TASK_RESPONSE_TYPE_NONE; std::string oaicompat_model; std::string oaicompat_cmpl_id; - common_chat_msg oaicompat_msg; + common_chat_msg oaicompat_msg; // to be populated by update() - std::vector oaicompat_msg_diffs; + std::vector oaicompat_msg_diffs; // to be populated by update() + bool is_updated = false; virtual int get_index() override { return index; @@ -247,6 +295,11 @@ struct server_task_result_cmpl_final : server_task_result { virtual json to_json() override; + virtual void update(task_result_state & state) override { + is_updated = true; + oaicompat_msg = state.update_chat_msg(content, false, oaicompat_msg_diffs); + } + json to_json_non_oaicompat(); json to_json_oaicompat(); @@ -280,7 +333,8 @@ struct server_task_result_cmpl_partial : server_task_result { task_response_type res_type = TASK_RESPONSE_TYPE_NONE; std::string oaicompat_model; std::string oaicompat_cmpl_id; - std::vector oaicompat_msg_diffs; + std::vector oaicompat_msg_diffs; // to be populated by update() + bool is_updated = false; virtual int get_index() override { return index; @@ -292,6 +346,11 @@ struct server_task_result_cmpl_partial : server_task_result { virtual json to_json() override; + virtual void update(task_result_state & state) override { + is_updated = true; + state.update_chat_msg(content, true, oaicompat_msg_diffs); + } + json to_json_non_oaicompat(); json to_json_oaicompat(); @@ -432,6 +491,14 @@ struct server_prompt { int n_tokens() const { return tokens.size(); } + + server_prompt clone() const { + return server_prompt { + tokens.clone(), + data, + checkpoints + }; + } }; struct server_prompt_cache { diff --git a/tools/server/server.cpp b/tools/server/server.cpp index 950537d82d..d5bef3df44 100644 --- a/tools/server/server.cpp +++ b/tools/server/server.cpp @@ -34,18 +34,26 @@ static inline void signal_handler(int signal) { static server_http_context::handler_t ex_wrapper(server_http_context::handler_t func) { return [func = std::move(func)](const server_http_req & req) -> server_http_res_ptr { std::string message; + error_type error; try { return func(req); + } catch (const std::invalid_argument & e) { + // treat invalid_argument as invalid request (400) + error = ERROR_TYPE_INVALID_REQUEST; + message = e.what(); } catch (const std::exception & e) { + // treat other exceptions as server error (500) + error = ERROR_TYPE_SERVER; message = e.what(); } catch (...) { + error = ERROR_TYPE_SERVER; message = "unknown error"; } auto res = std::make_unique(); res->status = 500; try { - json error_data = format_error_response(message, ERROR_TYPE_SERVER); + json error_data = format_error_response(message, error); res->status = json_value(error_data, "code", 500); res->data = safe_json_to_str({{ "error", error_data }}); SRV_WRN("got exception: %s\n", res->data.c_str()); diff --git a/tools/server/tests/unit/test_basic.py b/tools/server/tests/unit/test_basic.py index cadaa91849..3405be3e25 100644 --- a/tools/server/tests/unit/test_basic.py +++ b/tools/server/tests/unit/test_basic.py @@ -65,6 +65,7 @@ def test_server_slots(): def test_load_split_model(): global server + server.offline = False server.model_hf_repo = "ggml-org/models" server.model_hf_file = "tinyllamas/split/stories15M-q8_0-00001-of-00003.gguf" server.model_alias = "tinyllama-split" diff --git a/tools/server/tests/unit/test_chat_completion.py b/tools/server/tests/unit/test_chat_completion.py index 392e0efecd..64f3158b98 100644 --- a/tools/server/tests/unit/test_chat_completion.py +++ b/tools/server/tests/unit/test_chat_completion.py @@ -41,7 +41,8 @@ def test_chat_completion(model, system_prompt, user_prompt, max_tokens, re_conte assert res.status_code == 200 assert "cmpl" in res.body["id"] # make sure the completion id has the expected format assert res.body["system_fingerprint"].startswith("b") - assert res.body["model"] == model if model is not None else server.model_alias + # we no longer reflect back the model name, see https://github.com/ggml-org/llama.cpp/pull/17668 + # assert res.body["model"] == model if model is not None else server.model_alias assert res.body["usage"]["prompt_tokens"] == n_prompt assert res.body["usage"]["completion_tokens"] == n_predicted choice = res.body["choices"][0] @@ -59,7 +60,7 @@ def test_chat_completion(model, system_prompt, user_prompt, max_tokens, re_conte ) def test_chat_completion_stream(system_prompt, user_prompt, max_tokens, re_content, n_prompt, n_predicted, finish_reason): global server - server.model_alias = None # try using DEFAULT_OAICOMPAT_MODEL + server.model_alias = "llama-test-model" server.start() res = server.make_stream_request("POST", "/chat/completions", data={ "max_tokens": max_tokens, @@ -81,7 +82,7 @@ def test_chat_completion_stream(system_prompt, user_prompt, max_tokens, re_conte else: assert "role" not in choice["delta"] assert data["system_fingerprint"].startswith("b") - assert "gpt-3.5" in data["model"] # DEFAULT_OAICOMPAT_MODEL, maybe changed in the future + assert data["model"] == "llama-test-model" if last_cmpl_id is None: last_cmpl_id = data["id"] assert last_cmpl_id == data["id"] # make sure the completion id is the same for all events in the stream @@ -198,7 +199,7 @@ def test_completion_with_response_format(response_format: dict, n_predicted: int choice = res.body["choices"][0] assert match_regex(re_content, choice["message"]["content"]) else: - assert res.status_code != 200 + assert res.status_code == 400 assert "error" in res.body @@ -476,3 +477,22 @@ def test_return_progress(n_batch, batch_count, reuse_cache): assert last_progress["total"] > 0 assert last_progress["processed"] == last_progress["total"] assert total_batch_count == batch_count + + +def test_chat_completions_multiple_choices(): + global server + server.start() + res = server.make_request("POST", "/chat/completions", data={ + "max_tokens": 8, + "n": 2, + "messages": [ + {"role": "system", "content": "Book"}, + {"role": "user", "content": "What is the best book"}, + ], + }) + assert res.status_code == 200 + assert len(res.body["choices"]) == 2 + for choice in res.body["choices"]: + assert "assistant" == choice["message"]["role"] + assert match_regex("Suddenly", choice["message"]["content"]) + assert choice["finish_reason"] == "length" diff --git a/tools/server/tests/unit/test_router.py b/tools/server/tests/unit/test_router.py index e6f3c6485c..e85f2c3382 100644 --- a/tools/server/tests/unit/test_router.py +++ b/tools/server/tests/unit/test_router.py @@ -17,7 +17,6 @@ def create_server(): ] ) def test_router_chat_completion_stream(model: str, success: bool): - # TODO: make sure the model is in cache (ie. ServerProcess.load_all()) before starting the router server global server server.start() content = "" @@ -48,3 +47,148 @@ def test_router_chat_completion_stream(model: str, success: bool): else: assert ex is not None assert content == "" + + +def _get_model_status(model_id: str) -> str: + res = server.make_request("GET", "/models") + assert res.status_code == 200 + for item in res.body.get("data", []): + if item.get("id") == model_id or item.get("model") == model_id: + return item["status"]["value"] + raise AssertionError(f"Model {model_id} not found in /models response") + + +def _wait_for_model_status(model_id: str, desired: set[str], timeout: int = 60) -> str: + deadline = time.time() + timeout + last_status = None + while time.time() < deadline: + last_status = _get_model_status(model_id) + if last_status in desired: + return last_status + time.sleep(1) + raise AssertionError( + f"Timed out waiting for {model_id} to reach {desired}, last status: {last_status}" + ) + + +def _load_model_and_wait( + model_id: str, timeout: int = 60, headers: dict | None = None +) -> None: + load_res = server.make_request( + "POST", "/models/load", data={"model": model_id}, headers=headers + ) + assert load_res.status_code == 200 + assert isinstance(load_res.body, dict) + assert load_res.body.get("success") is True + _wait_for_model_status(model_id, {"loaded"}, timeout=timeout) + + +def test_router_unload_model(): + global server + server.start() + model_id = "ggml-org/tinygemma3-GGUF:Q8_0" + + _load_model_and_wait(model_id) + + unload_res = server.make_request("POST", "/models/unload", data={"model": model_id}) + assert unload_res.status_code == 200 + assert unload_res.body.get("success") is True + _wait_for_model_status(model_id, {"unloaded"}) + + +def test_router_models_max_evicts_lru(): + global server + server.models_max = 2 + server.start() + + candidate_models = [ + "ggml-org/tinygemma3-GGUF:Q8_0", + "ggml-org/test-model-stories260K", + "ggml-org/test-model-stories260K-infill", + ] + + # Load only the first 2 models to fill the cache + first, second, third = candidate_models[:3] + + _load_model_and_wait(first, timeout=120) + _load_model_and_wait(second, timeout=120) + + # Verify both models are loaded + assert _get_model_status(first) == "loaded" + assert _get_model_status(second) == "loaded" + + # Load the third model - this should trigger LRU eviction of the first model + _load_model_and_wait(third, timeout=120) + + # Verify eviction: third is loaded, first was evicted + assert _get_model_status(third) == "loaded" + assert _get_model_status(first) == "unloaded" + + +def test_router_no_models_autoload(): + global server + server.no_models_autoload = True + server.start() + model_id = "ggml-org/tinygemma3-GGUF:Q8_0" + + res = server.make_request( + "POST", + "/v1/chat/completions", + data={ + "model": model_id, + "messages": [{"role": "user", "content": "hello"}], + "max_tokens": 4, + }, + ) + assert res.status_code == 400 + assert "error" in res.body + + _load_model_and_wait(model_id) + + success_res = server.make_request( + "POST", + "/v1/chat/completions", + data={ + "model": model_id, + "messages": [{"role": "user", "content": "hello"}], + "max_tokens": 4, + }, + ) + assert success_res.status_code == 200 + assert "error" not in success_res.body + + +def test_router_api_key_required(): + global server + server.api_key = "sk-router-secret" + server.start() + + model_id = "ggml-org/tinygemma3-GGUF:Q8_0" + auth_headers = {"Authorization": f"Bearer {server.api_key}"} + + res = server.make_request( + "POST", + "/v1/chat/completions", + data={ + "model": model_id, + "messages": [{"role": "user", "content": "hello"}], + "max_tokens": 4, + }, + ) + assert res.status_code == 401 + assert res.body.get("error", {}).get("type") == "authentication_error" + + _load_model_and_wait(model_id, headers=auth_headers) + + authed = server.make_request( + "POST", + "/v1/chat/completions", + headers=auth_headers, + data={ + "model": model_id, + "messages": [{"role": "user", "content": "hello"}], + "max_tokens": 4, + }, + ) + assert authed.status_code == 200 + assert "error" not in authed.body diff --git a/tools/server/tests/unit/test_security.py b/tools/server/tests/unit/test_security.py index e160a8e6d3..8c38b89d53 100644 --- a/tools/server/tests/unit/test_security.py +++ b/tools/server/tests/unit/test_security.py @@ -94,3 +94,34 @@ def test_cors_options(origin: str, cors_header: str, cors_header_value: str): assert res.status_code == 200 assert cors_header in res.headers assert res.headers[cors_header] == cors_header_value + + +@pytest.mark.parametrize( + "media_path, image_url, success", + [ + (None, "file://mtmd/test-1.jpeg", False), # disabled media path, should fail + ("../../../tools", "file://mtmd/test-1.jpeg", True), + ("../../../tools", "file:////mtmd//test-1.jpeg", True), # should be the same file as above + ("../../../tools", "file://mtmd/notfound.jpeg", False), # non-existent file + ("../../../tools", "file://../mtmd/test-1.jpeg", False), # no directory traversal + ] +) +def test_local_media_file(media_path, image_url, success,): + server = ServerPreset.tinygemma3() + server.media_path = media_path + server.start() + res = server.make_request("POST", "/chat/completions", data={ + "max_tokens": 1, + "messages": [ + {"role": "user", "content": [ + {"type": "text", "text": "test"}, + {"type": "image_url", "image_url": { + "url": image_url, + }}, + ]}, + ], + }) + if success: + assert res.status_code == 200 + else: + assert res.status_code == 400 diff --git a/tools/server/tests/utils.py b/tools/server/tests/utils.py index afe4f77d97..48e7403602 100644 --- a/tools/server/tests/utils.py +++ b/tools/server/tests/utils.py @@ -7,6 +7,7 @@ import subprocess import os import re import json +from json import JSONDecodeError import sys import requests import time @@ -83,6 +84,9 @@ class ServerProcess: pooling: str | None = None draft: int | None = None api_key: str | None = None + models_dir: str | None = None + models_max: int | None = None + no_models_autoload: bool | None = None lora_files: List[str] | None = None enable_ctx_shift: int | None = False draft_min: int | None = None @@ -95,6 +99,7 @@ class ServerProcess: chat_template_file: str | None = None server_path: str | None = None mmproj_url: str | None = None + media_path: str | None = None # session variables process: subprocess.Popen | None = None @@ -142,6 +147,10 @@ class ServerProcess: server_args.extend(["--hf-repo", self.model_hf_repo]) if self.model_hf_file: server_args.extend(["--hf-file", self.model_hf_file]) + if self.models_dir: + server_args.extend(["--models-dir", self.models_dir]) + if self.models_max is not None: + server_args.extend(["--models-max", self.models_max]) if self.n_batch: server_args.extend(["--batch-size", self.n_batch]) if self.n_ubatch: @@ -203,6 +212,8 @@ class ServerProcess: server_args.extend(["--draft-min", self.draft_min]) if self.no_webui: server_args.append("--no-webui") + if self.no_models_autoload: + server_args.append("--no-models-autoload") if self.jinja: server_args.append("--jinja") else: @@ -217,6 +228,8 @@ class ServerProcess: server_args.extend(["--chat-template-file", self.chat_template_file]) if self.mmproj_url: server_args.extend(["--mmproj-url", self.mmproj_url]) + if self.media_path: + server_args.extend(["--media-path", self.media_path]) args = [str(arg) for arg in [server_path, *server_args]] print(f"tests: starting server with: {' '.join(args)}") @@ -292,7 +305,13 @@ class ServerProcess: result = ServerResponse() result.headers = dict(response.headers) result.status_code = response.status_code - result.body = response.json() if parse_body else None + if parse_body: + try: + result.body = response.json() + except JSONDecodeError: + result.body = response.text + else: + result.body = None print("Response from server", json.dumps(result.body, indent=2)) return result @@ -431,8 +450,9 @@ class ServerPreset: @staticmethod def tinyllama2() -> ServerProcess: server = ServerProcess() - server.model_hf_repo = "ggml-org/models" - server.model_hf_file = "tinyllamas/stories260K.gguf" + server.offline = True # will be downloaded by load_all() + server.model_hf_repo = "ggml-org/test-model-stories260K" + server.model_hf_file = None server.model_alias = "tinyllama-2" server.n_ctx = 512 server.n_batch = 32 @@ -476,8 +496,8 @@ class ServerPreset: def tinyllama_infill() -> ServerProcess: server = ServerProcess() server.offline = True # will be downloaded by load_all() - server.model_hf_repo = "ggml-org/models" - server.model_hf_file = "tinyllamas/stories260K-infill.gguf" + server.model_hf_repo = "ggml-org/test-model-stories260K-infill" + server.model_hf_file = None server.model_alias = "tinyllama-infill" server.n_ctx = 2048 server.n_batch = 1024 @@ -534,6 +554,7 @@ class ServerPreset: @staticmethod def router() -> ServerProcess: server = ServerProcess() + server.offline = True # will be downloaded by load_all() # router server has no models server.model_file = None server.model_alias = None diff --git a/tools/server/webui/docs/flows/data-flow-simplified-router-mode.md b/tools/server/webui/docs/flows/data-flow-simplified-router-mode.md index f5c4f05edf..bccacf5684 100644 --- a/tools/server/webui/docs/flows/data-flow-simplified-router-mode.md +++ b/tools/server/webui/docs/flows/data-flow-simplified-router-mode.md @@ -15,7 +15,7 @@ sequenceDiagram Stores->>DB: load conversations Stores->>API: GET /props API-->>Stores: {role: "router"} - Stores->>API: GET /models + Stores->>API: GET /v1/models API-->>Stores: models[] with status (loaded/available) loop each loaded model Stores->>API: GET /props?model=X @@ -28,7 +28,7 @@ sequenceDiagram alt model not loaded Stores->>API: POST /models/load loop poll status - Stores->>API: GET /models + Stores->>API: GET /v1/models API-->>Stores: check if loaded end Stores->>API: GET /props?model=X diff --git a/tools/server/webui/docs/flows/models-flow.md b/tools/server/webui/docs/flows/models-flow.md index ce63da1b36..c3031b7292 100644 --- a/tools/server/webui/docs/flows/models-flow.md +++ b/tools/server/webui/docs/flows/models-flow.md @@ -56,7 +56,7 @@ sequenceDiagram UI->>modelsStore: fetchRouterModels() activate modelsStore modelsStore->>ModelsSvc: listRouter() - ModelsSvc->>API: GET /models + ModelsSvc->>API: GET /v1/models API-->>ModelsSvc: ApiRouterModelsListResponse Note right of API: {data: [{id, status, path, in_cache}]} modelsStore->>modelsStore: routerModels = $state(data) @@ -132,7 +132,7 @@ sequenceDiagram loop poll every 500ms (max 60 attempts) modelsStore->>modelsStore: fetchRouterModels() modelsStore->>ModelsSvc: listRouter() - ModelsSvc->>API: GET /models + ModelsSvc->>API: GET /v1/models API-->>ModelsSvc: models[] modelsStore->>modelsStore: getModelStatus(modelId) alt status === LOADED @@ -165,7 +165,7 @@ sequenceDiagram modelsStore->>modelsStore: pollForModelStatus(modelId, UNLOADED) loop poll until unloaded modelsStore->>ModelsSvc: listRouter() - ModelsSvc->>API: GET /models + ModelsSvc->>API: GET /v1/models end modelsStore->>modelsStore: modelLoadingStates.set(modelId, false) diff --git a/tools/server/webui/src/lib/components/app/chat/ChatForm/ChatForm.svelte b/tools/server/webui/src/lib/components/app/chat/ChatForm/ChatForm.svelte index 97dccd8be8..7f8e38286d 100644 --- a/tools/server/webui/src/lib/components/app/chat/ChatForm/ChatForm.svelte +++ b/tools/server/webui/src/lib/components/app/chat/ChatForm/ChatForm.svelte @@ -64,7 +64,10 @@ let fileInputRef: ChatFormFileInputInvisible | undefined = $state(undefined); let isRecording = $state(false); let message = $state(''); - let pasteLongTextToFileLength = $derived(Number(currentConfig.pasteLongTextToFileLen) || 2500); + let pasteLongTextToFileLength = $derived.by(() => { + const n = Number(currentConfig.pasteLongTextToFileLen); + return Number.isNaN(n) ? 2500 : n; + }); let previousIsLoading = $state(isLoading); let recordingSupported = $state(false); let textareaRef: ChatFormTextarea | undefined = $state(undefined); diff --git a/tools/server/webui/src/lib/components/app/chat/ChatMessages/ChatMessage.svelte b/tools/server/webui/src/lib/components/app/chat/ChatMessages/ChatMessage.svelte index 2315611361..96ed56a775 100644 --- a/tools/server/webui/src/lib/components/app/chat/ChatMessages/ChatMessage.svelte +++ b/tools/server/webui/src/lib/components/app/chat/ChatMessages/ChatMessage.svelte @@ -3,6 +3,7 @@ import { copyToClipboard, isIMEComposing } from '$lib/utils'; import ChatMessageAssistant from './ChatMessageAssistant.svelte'; import ChatMessageUser from './ChatMessageUser.svelte'; + import ChatMessageSystem from './ChatMessageSystem.svelte'; interface Props { class?: string; @@ -140,8 +141,7 @@ } function handleSaveEdit() { - if (message.role === 'user') { - // For user messages, trim to avoid accidental whitespace + if (message.role === 'user' || message.role === 'system') { onEditWithBranching?.(message, editedContent.trim()); } else { // For assistant messages, preserve exact content including trailing whitespace @@ -167,7 +167,28 @@ } -{#if message.role === 'user'} +{#if message.role === 'system'} + +{:else if message.role === 'user'} + import { Check, X } from '@lucide/svelte'; + import { Card } from '$lib/components/ui/card'; + import { Button } from '$lib/components/ui/button'; + import { MarkdownContent } from '$lib/components/app'; + import { INPUT_CLASSES } from '$lib/constants/input-classes'; + import { config } from '$lib/stores/settings.svelte'; + import ChatMessageActions from './ChatMessageActions.svelte'; + + interface Props { + class?: string; + message: DatabaseMessage; + isEditing: boolean; + editedContent: string; + siblingInfo?: ChatMessageSiblingInfo | null; + showDeleteDialog: boolean; + deletionInfo: { + totalCount: number; + userMessages: number; + assistantMessages: number; + messageTypes: string[]; + } | null; + onCancelEdit: () => void; + onSaveEdit: () => void; + onEditKeydown: (event: KeyboardEvent) => void; + onEditedContentChange: (content: string) => void; + onCopy: () => void; + onEdit: () => void; + onDelete: () => void; + onConfirmDelete: () => void; + onNavigateToSibling?: (siblingId: string) => void; + onShowDeleteDialogChange: (show: boolean) => void; + textareaElement?: HTMLTextAreaElement; + } + + let { + class: className = '', + message, + isEditing, + editedContent, + siblingInfo = null, + showDeleteDialog, + deletionInfo, + onCancelEdit, + onSaveEdit, + onEditKeydown, + onEditedContentChange, + onCopy, + onEdit, + onDelete, + onConfirmDelete, + onNavigateToSibling, + onShowDeleteDialogChange, + textareaElement = $bindable() + }: Props = $props(); + + let isMultiline = $state(false); + let messageElement: HTMLElement | undefined = $state(); + let isExpanded = $state(false); + let contentHeight = $state(0); + const MAX_HEIGHT = 200; // pixels + const currentConfig = config(); + + let showExpandButton = $derived(contentHeight > MAX_HEIGHT); + + $effect(() => { + if (!messageElement || !message.content.trim()) return; + + if (message.content.includes('\n')) { + isMultiline = true; + } + + const resizeObserver = new ResizeObserver((entries) => { + for (const entry of entries) { + const element = entry.target as HTMLElement; + const estimatedSingleLineHeight = 24; + + isMultiline = element.offsetHeight > estimatedSingleLineHeight * 1.5; + contentHeight = element.scrollHeight; + } + }); + + resizeObserver.observe(messageElement); + + return () => { + resizeObserver.disconnect(); + }; + }); + + function toggleExpand() { + isExpanded = !isExpanded; + } + + +
+ {#if isEditing} +
+ + +
+ + + +
+
+ {:else} + {#if message.content.trim()} +
+ +
+ {/if} +
+ + {#if isExpanded && showExpandButton} +
+ +
+ {/if} + + + + {/if} + + {#if message.timestamp} +
+ +
+ {/if} + {/if} + diff --git a/tools/server/webui/src/lib/components/app/chat/ChatMessages/ChatMessageUser.svelte b/tools/server/webui/src/lib/components/app/chat/ChatMessages/ChatMessageUser.svelte index 8556cbef5b..3d2b8dd35b 100644 --- a/tools/server/webui/src/lib/components/app/chat/ChatMessages/ChatMessageUser.svelte +++ b/tools/server/webui/src/lib/components/app/chat/ChatMessages/ChatMessageUser.svelte @@ -145,7 +145,7 @@ {#if message.content.trim()} {#if currentConfig.renderUserContentAsMarkdown} diff --git a/tools/server/webui/src/lib/components/app/chat/ChatMessages/ChatMessages.svelte b/tools/server/webui/src/lib/components/app/chat/ChatMessages/ChatMessages.svelte index 6024f66c8b..2e5f57cb61 100644 --- a/tools/server/webui/src/lib/components/app/chat/ChatMessages/ChatMessages.svelte +++ b/tools/server/webui/src/lib/components/app/chat/ChatMessages/ChatMessages.svelte @@ -1,8 +1,8 @@ @@ -132,6 +137,7 @@ onSelect={selectConversation} onEdit={handleEditConversation} onDelete={handleDeleteConversation} + onStop={handleStopGeneration} /> {/each} diff --git a/tools/server/webui/src/lib/components/app/chat/ChatSidebar/ChatSidebarConversationItem.svelte b/tools/server/webui/src/lib/components/app/chat/ChatSidebar/ChatSidebarConversationItem.svelte index 82685f83a5..bf2fa4f9e9 100644 --- a/tools/server/webui/src/lib/components/app/chat/ChatSidebar/ChatSidebarConversationItem.svelte +++ b/tools/server/webui/src/lib/components/app/chat/ChatSidebar/ChatSidebarConversationItem.svelte @@ -1,6 +1,7 @@ @@ -70,8 +55,8 @@
Loading model information...
- {:else if modelsData && modelsData.data.length > 0} - {@const modelMeta = modelsData.data[0].meta} + {:else if firstModel} + {@const modelMeta = firstModel.meta} {#if serverProps} diff --git a/tools/server/webui/src/lib/components/app/index.ts b/tools/server/webui/src/lib/components/app/index.ts index cf4d7495e2..87b24598b7 100644 --- a/tools/server/webui/src/lib/components/app/index.ts +++ b/tools/server/webui/src/lib/components/app/index.ts @@ -19,8 +19,10 @@ export { default as ChatMessage } from './chat/ChatMessages/ChatMessage.svelte'; export { default as ChatMessageActions } from './chat/ChatMessages/ChatMessageActions.svelte'; export { default as ChatMessageBranchingControls } from './chat/ChatMessages/ChatMessageBranchingControls.svelte'; export { default as ChatMessageStatistics } from './chat/ChatMessages/ChatMessageStatistics.svelte'; +export { default as ChatMessageSystem } from './chat/ChatMessages/ChatMessageSystem.svelte'; export { default as ChatMessageThinkingBlock } from './chat/ChatMessages/ChatMessageThinkingBlock.svelte'; export { default as ChatMessages } from './chat/ChatMessages/ChatMessages.svelte'; +export { default as MessageBranchingControls } from './chat/ChatMessages/ChatMessageBranchingControls.svelte'; export { default as ChatScreen } from './chat/ChatScreen/ChatScreen.svelte'; export { default as ChatScreenHeader } from './chat/ChatScreen/ChatScreenHeader.svelte'; diff --git a/tools/server/webui/src/lib/components/app/misc/MarkdownContent.svelte b/tools/server/webui/src/lib/components/app/misc/MarkdownContent.svelte index 99d6e21e13..9c37bde0d4 100644 --- a/tools/server/webui/src/lib/components/app/misc/MarkdownContent.svelte +++ b/tools/server/webui/src/lib/components/app/misc/MarkdownContent.svelte @@ -337,19 +337,23 @@ line-height: 1.75; } + div :global(:is(h1, h2, h3, h4, h5, h6):first-child) { + margin-top: 0; + } + /* Headers with consistent spacing */ div :global(h1) { font-size: 1.875rem; font-weight: 700; - margin: 1.5rem 0 0.75rem 0; line-height: 1.2; + margin: 1.5rem 0 0.75rem 0; } div :global(h2) { font-size: 1.5rem; font-weight: 600; - margin: 1.25rem 0 0.5rem 0; line-height: 1.3; + margin: 1.25rem 0 0.5rem 0; } div :global(h3) { diff --git a/tools/server/webui/src/lib/constants/settings-config.ts b/tools/server/webui/src/lib/constants/settings-config.ts index 1fc35b48c4..3764a2856b 100644 --- a/tools/server/webui/src/lib/constants/settings-config.ts +++ b/tools/server/webui/src/lib/constants/settings-config.ts @@ -3,6 +3,7 @@ export const SETTING_CONFIG_DEFAULT: Record = // Do not use nested objects, keep it single level. Prefix the key if you need to group them. apiKey: '', systemMessage: '', + showSystemMessage: true, theme: 'system', showThoughtInProgress: false, showToolCalls: false, @@ -42,8 +43,9 @@ export const SETTING_CONFIG_DEFAULT: Record = }; export const SETTING_CONFIG_INFO: Record = { - apiKey: 'Set the API Key if you are using --api-key option for the server.', + apiKey: 'Set the API Key if you are using --api-key option for the server.', systemMessage: 'The starting message that defines how model should behave.', + showSystemMessage: 'Display the system message at the top of each conversation.', theme: 'Choose the color theme for the interface. You can choose between System (follows your device settings), Light, or Dark.', pasteLongTextToFileLen: diff --git a/tools/server/webui/src/lib/constants/supported-file-types.ts b/tools/server/webui/src/lib/constants/supported-file-types.ts index 93bbab5d39..0d955ad147 100644 --- a/tools/server/webui/src/lib/constants/supported-file-types.ts +++ b/tools/server/webui/src/lib/constants/supported-file-types.ts @@ -126,8 +126,13 @@ export const TEXT_FILE_TYPES = { mimeTypes: [MimeTypeText.JAVA] }, [FileTypeText.CPP]: { - extensions: [FileExtensionText.CPP, FileExtensionText.C, FileExtensionText.H], - mimeTypes: [MimeTypeText.CPP_SRC, MimeTypeText.C_SRC, MimeTypeText.C_HDR] + extensions: [ + FileExtensionText.CPP, + FileExtensionText.C, + FileExtensionText.H, + FileExtensionText.HPP + ], + mimeTypes: [MimeTypeText.CPP_SRC, MimeTypeText.CPP_HDR, MimeTypeText.C_SRC, MimeTypeText.C_HDR] }, [FileTypeText.PHP]: { extensions: [FileExtensionText.PHP], @@ -183,10 +188,30 @@ export const TEXT_FILE_TYPES = { }, [FileTypeText.LATEX]: { extensions: [FileExtensionText.TEX], - mimeTypes: [MimeTypeText.LATEX] + mimeTypes: [MimeTypeText.LATEX, MimeTypeText.TEX, MimeTypeText.TEX_APP] }, [FileTypeText.BIBTEX]: { extensions: [FileExtensionText.BIB], mimeTypes: [MimeTypeText.BIBTEX] + }, + [FileTypeText.CUDA]: { + extensions: [FileExtensionText.CU, FileExtensionText.CUH], + mimeTypes: [MimeTypeText.CUDA] + }, + [FileTypeText.VULKAN]: { + extensions: [FileExtensionText.COMP], + mimeTypes: [MimeTypeText.PLAIN] + }, + [FileTypeText.HASKELL]: { + extensions: [FileExtensionText.HS], + mimeTypes: [MimeTypeText.HASKELL] + }, + [FileTypeText.CSHARP]: { + extensions: [FileExtensionText.CS], + mimeTypes: [MimeTypeText.CSHARP] + }, + [FileTypeText.PROPERTIES]: { + extensions: [FileExtensionText.PROPERTIES], + mimeTypes: [MimeTypeText.PROPERTIES] } } as const; diff --git a/tools/server/webui/src/lib/enums/files.ts b/tools/server/webui/src/lib/enums/files.ts index 45b0feea16..a4f079d405 100644 --- a/tools/server/webui/src/lib/enums/files.ts +++ b/tools/server/webui/src/lib/enums/files.ts @@ -62,7 +62,12 @@ export enum FileTypeText { VUE = 'vue', SVELTE = 'svelte', LATEX = 'latex', - BIBTEX = 'bibtex' + BIBTEX = 'bibtex', + CUDA = 'cuda', + VULKAN = 'vulkan', + HASKELL = 'haskell', + CSHARP = 'csharp', + PROPERTIES = 'properties' } // File extension enums @@ -121,7 +126,14 @@ export enum FileExtensionText { VUE = '.vue', SVELTE = '.svelte', TEX = '.tex', - BIB = '.bib' + BIB = '.bib', + CU = '.cu', + CUH = '.cuh', + COMP = '.comp', + HPP = '.hpp', + HS = '.hs', + PROPERTIES = '.properties', + CS = '.cs' } // MIME type enums @@ -165,7 +177,10 @@ export enum MimeTypeText { CSV = 'text/csv', PYTHON = 'text/x-python', JAVA = 'text/x-java-source', + CPP_HDR = 'text/x-c++hdr', CPP_SRC = 'text/x-c++src', + CSHARP = 'text/x-csharp', + HASKELL = 'text/x-haskell', C_SRC = 'text/x-csrc', C_HDR = 'text/x-chdr', PHP = 'text/x-php', @@ -182,6 +197,10 @@ export enum MimeTypeText { DART = 'text/x-dart', VUE = 'text/x-vue', SVELTE = 'text/x-svelte', - LATEX = 'text/x-tex', - BIBTEX = 'text/x-bibtex' + TEX = 'text/x-tex', + TEX_APP = 'application/x-tex', + LATEX = 'application/x-latex', + BIBTEX = 'text/x-bibtex', + CUDA = 'text/x-cuda', + PROPERTIES = 'text/properties' } diff --git a/tools/server/webui/src/lib/services/chat.ts b/tools/server/webui/src/lib/services/chat.ts index a14832ebd4..c03b764419 100644 --- a/tools/server/webui/src/lib/services/chat.ts +++ b/tools/server/webui/src/lib/services/chat.ts @@ -89,7 +89,6 @@ export class ChatService { custom, timings_per_token, // Config options - systemMessage, disableReasoningFormat } = options; @@ -103,6 +102,7 @@ export class ChatService { } }) .filter((msg) => { + // Filter out empty system messages if (msg.role === 'system') { const content = typeof msg.content === 'string' ? msg.content : ''; @@ -112,10 +112,8 @@ export class ChatService { return true; }); - const processedMessages = ChatService.injectSystemMessage(normalizedMessages, systemMessage); - const requestBody: ApiChatCompletionRequest = { - messages: processedMessages.map((msg: ApiChatMessageData) => ({ + messages: normalizedMessages.map((msg: ApiChatMessageData) => ({ role: msg.role, content: msg.content })), @@ -677,105 +675,38 @@ export class ChatService { // Utilities // ───────────────────────────────────────────────────────────────────────────── - /** - * Get server properties - static method for API compatibility (to be refactored) - */ - static async getServerProps(): Promise { - try { - const response = await fetch(`./props`, { - headers: getJsonHeaders() - }); - - if (!response.ok) { - throw new Error(`Failed to fetch server props: ${response.status}`); - } - - const data = await response.json(); - return data; - } catch (error) { - console.error('Error fetching server props:', error); - throw error; - } - } - - /** - * Get model information from /models endpoint (to be refactored) - */ - static async getModels(): Promise { - try { - const response = await fetch(`./models`, { - headers: getJsonHeaders() - }); - - if (!response.ok) { - throw new Error(`Failed to fetch models: ${response.status} ${response.statusText}`); - } - - const data = await response.json(); - return data; - } catch (error) { - console.error('Error fetching models:', error); - throw error; - } - } - - /** - * Injects a system message at the beginning of the conversation if provided. - * Checks for existing system messages to avoid duplication. - * - * @param messages - Array of chat messages to process - * @param systemMessage - Optional system message to inject - * @returns Array of messages with system message injected at the beginning if provided - * @private - */ - private static injectSystemMessage( - messages: ApiChatMessageData[], - systemMessage?: string - ): ApiChatMessageData[] { - const trimmedSystemMessage = systemMessage?.trim(); - - if (!trimmedSystemMessage) { - return messages; - } - - if (messages.length > 0 && messages[0].role === 'system') { - if (messages[0].content !== trimmedSystemMessage) { - const updatedMessages = [...messages]; - updatedMessages[0] = { - role: 'system', - content: trimmedSystemMessage - }; - return updatedMessages; - } - - return messages; - } - - const systemMsg: ApiChatMessageData = { - role: 'system', - content: trimmedSystemMessage - }; - - return [systemMsg, ...messages]; - } - /** * Parses error response and creates appropriate error with context information * @param response - HTTP response object * @returns Promise - Parsed error with context info if available */ - private static async parseErrorResponse(response: Response): Promise { + private static async parseErrorResponse( + response: Response + ): Promise { try { const errorText = await response.text(); const errorData: ApiErrorResponse = JSON.parse(errorText); const message = errorData.error?.message || 'Unknown server error'; - const error = new Error(message); + const error = new Error(message) as Error & { + contextInfo?: { n_prompt_tokens: number; n_ctx: number }; + }; error.name = response.status === 400 ? 'ServerError' : 'HttpError'; + if (errorData.error && 'n_prompt_tokens' in errorData.error && 'n_ctx' in errorData.error) { + error.contextInfo = { + n_prompt_tokens: errorData.error.n_prompt_tokens, + n_ctx: errorData.error.n_ctx + }; + } + return error; } catch { - const fallback = new Error(`Server error (${response.status}): ${response.statusText}`); + const fallback = new Error( + `Server error (${response.status}): ${response.statusText}` + ) as Error & { + contextInfo?: { n_prompt_tokens: number; n_ctx: number }; + }; fallback.name = 'HttpError'; return fallback; } diff --git a/tools/server/webui/src/lib/services/database.ts b/tools/server/webui/src/lib/services/database.ts index 185a598c3b..3b24628cff 100644 --- a/tools/server/webui/src/lib/services/database.ts +++ b/tools/server/webui/src/lib/services/database.ts @@ -166,6 +166,49 @@ export class DatabaseService { return rootMessage.id; } + /** + * Creates a system prompt message for a conversation. + * + * @param convId - Conversation ID + * @param systemPrompt - The system prompt content (must be non-empty) + * @param parentId - Parent message ID (typically the root message) + * @returns The created system message + * @throws Error if systemPrompt is empty + */ + static async createSystemMessage( + convId: string, + systemPrompt: string, + parentId: string + ): Promise { + const trimmedPrompt = systemPrompt.trim(); + if (!trimmedPrompt) { + throw new Error('Cannot create system message with empty content'); + } + + const systemMessage: DatabaseMessage = { + id: uuid(), + convId, + type: 'system', + timestamp: Date.now(), + role: 'system', + content: trimmedPrompt, + parent: parentId, + thinking: '', + children: [] + }; + + await db.messages.add(systemMessage); + + const parentMessage = await db.messages.get(parentId); + if (parentMessage) { + await db.messages.update(parentId, { + children: [...parentMessage.children, systemMessage.id] + }); + } + + return systemMessage; + } + /** * Deletes a conversation and all its messages. * diff --git a/tools/server/webui/src/lib/services/models.ts b/tools/server/webui/src/lib/services/models.ts index f031bd7497..eecb7fa262 100644 --- a/tools/server/webui/src/lib/services/models.ts +++ b/tools/server/webui/src/lib/services/models.ts @@ -7,7 +7,7 @@ import { getJsonHeaders } from '$lib/utils'; * * This service handles communication with model-related endpoints: * - `/v1/models` - OpenAI-compatible model list (MODEL + ROUTER mode) - * - `/models` - Router-specific model management (ROUTER mode only) + * - `/models/load`, `/models/unload` - Router-specific model management (ROUTER mode only) * * **Responsibilities:** * - List available models @@ -43,7 +43,7 @@ export class ModelsService { * Returns models with load status, paths, and other metadata */ static async listRouter(): Promise { - const response = await fetch(`${base}/models`, { + const response = await fetch(`${base}/v1/models`, { headers: getJsonHeaders() }); diff --git a/tools/server/webui/src/lib/stores/chat.svelte.ts b/tools/server/webui/src/lib/stores/chat.svelte.ts index 0c17b06bc1..4f78840a57 100644 --- a/tools/server/webui/src/lib/stores/chat.svelte.ts +++ b/tools/server/webui/src/lib/stores/chat.svelte.ts @@ -2,7 +2,11 @@ import { DatabaseService, ChatService } from '$lib/services'; import { conversationsStore } from '$lib/stores/conversations.svelte'; import { config } from '$lib/stores/settings.svelte'; import { contextSize, isRouterMode } from '$lib/stores/server.svelte'; -import { selectedModelName, modelsStore } from '$lib/stores/models.svelte'; +import { + selectedModelName, + modelsStore, + selectedModelContextSize +} from '$lib/stores/models.svelte'; import { normalizeModelName, filterByLeafNodeId, @@ -58,7 +62,11 @@ class ChatStore { activeProcessingState = $state(null); currentResponse = $state(''); - errorDialogState = $state<{ type: 'timeout' | 'server'; message: string } | null>(null); + errorDialogState = $state<{ + type: 'timeout' | 'server'; + message: string; + contextInfo?: { n_prompt_tokens: number; n_ctx: number }; + } | null>(null); isLoading = $state(false); chatLoadingStates = new SvelteMap(); chatStreamingStates = new SvelteMap(); @@ -257,6 +265,13 @@ class ChatStore { return activeState.contextTotal; } + if (isRouterMode()) { + const modelContextSize = selectedModelContextSize(); + if (modelContextSize && modelContextSize > 0) { + return modelContextSize; + } + } + const propsContextSize = contextSize(); if (propsContextSize && propsContextSize > 0) { return propsContextSize; @@ -335,8 +350,12 @@ class ChatStore { return error instanceof Error && (error.name === 'AbortError' || error instanceof DOMException); } - private showErrorDialog(type: 'timeout' | 'server', message: string): void { - this.errorDialogState = { type, message }; + private showErrorDialog( + type: 'timeout' | 'server', + message: string, + contextInfo?: { n_prompt_tokens: number; n_ctx: number } + ): void { + this.errorDialogState = { type, message, contextInfo }; } dismissErrorDialog(): void { @@ -347,6 +366,23 @@ class ChatStore { // Message Operations // ───────────────────────────────────────────────────────────────────────────── + /** + * Finds a message by ID and optionally validates its role. + * Returns message and index, or null if not found or role doesn't match. + */ + private getMessageByIdWithRole( + messageId: string, + expectedRole?: ChatRole + ): { message: DatabaseMessage; index: number } | null { + const index = conversationsStore.findMessageIndex(messageId); + if (index === -1) return null; + + const message = conversationsStore.activeMessages[index]; + if (expectedRole && message.role !== expectedRole) return null; + + return { message, index }; + } + async addMessage( role: ChatRole, content: string, @@ -433,6 +469,14 @@ class ChatStore { onError?: (error: Error) => void, modelOverride?: string | null ): Promise { + // Ensure model props are cached before streaming (for correct n_ctx in processing info) + if (isRouterMode()) { + const modelName = modelOverride || selectedModelName(); + if (modelName && !modelsStore.getModelProps(modelName)) { + await modelsStore.fetchModelProps(modelName); + } + } + let streamedContent = ''; let streamedReasoningContent = ''; let streamedToolCallContent = ''; @@ -508,7 +552,6 @@ class ChatStore { ) => { this.stopStreaming(); - // Build update data - only include model if not already persisted const updateData: Record = { content: finalContent || streamedContent, thinking: reasoningContent || streamedReasoningContent, @@ -520,7 +563,6 @@ class ChatStore { } await DatabaseService.updateMessage(assistantMessage.id, updateData); - // Update UI state - always include model and timings if available const idx = conversationsStore.findMessageIndex(assistantMessage.id); const uiUpdate: Partial = { content: updateData.content as string, @@ -543,22 +585,38 @@ class ChatStore { }, onError: (error: Error) => { this.stopStreaming(); + if (this.isAbortError(error)) { this.setChatLoading(assistantMessage.convId, false); this.clearChatStreaming(assistantMessage.convId); this.clearProcessingState(assistantMessage.convId); + return; } + console.error('Streaming error:', error); + this.setChatLoading(assistantMessage.convId, false); this.clearChatStreaming(assistantMessage.convId); this.clearProcessingState(assistantMessage.convId); + const idx = conversationsStore.findMessageIndex(assistantMessage.id); + if (idx !== -1) { const failedMessage = conversationsStore.removeMessageAtIndex(idx); if (failedMessage) DatabaseService.deleteMessage(failedMessage.id).catch(console.error); } - this.showErrorDialog(error.name === 'TimeoutError' ? 'timeout' : 'server', error.message); + + const contextInfo = ( + error as Error & { contextInfo?: { n_prompt_tokens: number; n_ctx: number } } + ).contextInfo; + + this.showErrorDialog( + error.name === 'TimeoutError' ? 'timeout' : 'server', + error.message, + contextInfo + ); + if (onError) onError(error); } }, @@ -585,13 +643,31 @@ class ChatStore { this.clearChatStreaming(currentConv.id); try { + if (isNewConversation) { + const rootId = await DatabaseService.createRootMessage(currentConv.id); + const currentConfig = config(); + const systemPrompt = currentConfig.systemMessage?.toString().trim(); + + if (systemPrompt) { + const systemMessage = await DatabaseService.createSystemMessage( + currentConv.id, + systemPrompt, + rootId + ); + + conversationsStore.addMessageToActive(systemMessage); + } + } + const userMessage = await this.addMessage('user', content, 'text', '-1', extras); if (!userMessage) throw new Error('Failed to add user message'); if (isNewConversation && content) await conversationsStore.updateConversationName(currentConv.id, content.trim()); const assistantMessage = await this.createAssistantMessage(userMessage.id); + if (!assistantMessage) throw new Error('Failed to create assistant message'); + conversationsStore.addMessageToActive(assistantMessage); await this.streamChatCompletion( conversationsStore.activeMessages.slice(0, -1), @@ -607,20 +683,35 @@ class ChatStore { if (!this.errorDialogState) { const dialogType = error instanceof Error && error.name === 'TimeoutError' ? 'timeout' : 'server'; - this.showErrorDialog(dialogType, error instanceof Error ? error.message : 'Unknown error'); + const contextInfo = ( + error as Error & { contextInfo?: { n_prompt_tokens: number; n_ctx: number } } + ).contextInfo; + + this.showErrorDialog( + dialogType, + error instanceof Error ? error.message : 'Unknown error', + contextInfo + ); } } } async stopGeneration(): Promise { const activeConv = conversationsStore.activeConversation; + if (!activeConv) return; - await this.savePartialResponseIfNeeded(activeConv.id); + + await this.stopGenerationForChat(activeConv.id); + } + + async stopGenerationForChat(convId: string): Promise { + await this.savePartialResponseIfNeeded(convId); + this.stopStreaming(); - this.abortRequest(activeConv.id); - this.setChatLoading(activeConv.id, false); - this.clearChatStreaming(activeConv.id); - this.clearProcessingState(activeConv.id); + this.abortRequest(convId); + this.setChatLoading(convId, false); + this.clearChatStreaming(convId); + this.clearProcessingState(convId); } /** @@ -655,17 +746,22 @@ class ChatStore { private async savePartialResponseIfNeeded(convId?: string): Promise { const conversationId = convId || conversationsStore.activeConversation?.id; + if (!conversationId) return; + const streamingState = this.chatStreamingStates.get(conversationId); + if (!streamingState || !streamingState.response.trim()) return; const messages = conversationId === conversationsStore.activeConversation?.id ? conversationsStore.activeMessages : await conversationsStore.getConversationMessages(conversationId); + if (!messages.length) return; const lastMessage = messages[messages.length - 1]; + if (lastMessage?.role === 'assistant') { try { const updateData: { content: string; thinking?: string; timings?: ChatMessageTimings } = { @@ -684,9 +780,13 @@ class ChatStore { : undefined }; } + await DatabaseService.updateMessage(lastMessage.id, updateData); + lastMessage.content = this.currentResponse; + if (updateData.thinking) lastMessage.thinking = updateData.thinking; + if (updateData.timings) lastMessage.timings = updateData.timings; } catch (error) { lastMessage.content = this.currentResponse; @@ -700,14 +800,12 @@ class ChatStore { if (!activeConv) return; if (this.isLoading) this.stopGeneration(); + const result = this.getMessageByIdWithRole(messageId, 'user'); + if (!result) return; + const { message: messageToUpdate, index: messageIndex } = result; + const originalContent = messageToUpdate.content; + try { - const messageIndex = conversationsStore.findMessageIndex(messageId); - if (messageIndex === -1) return; - - const messageToUpdate = conversationsStore.activeMessages[messageIndex]; - const originalContent = messageToUpdate.content; - if (messageToUpdate.role !== 'user') return; - const allMessages = await conversationsStore.getConversationMessages(activeConv.id); const rootMessage = allMessages.find((m) => m.type === 'root' && m.parent === null); const isFirstUserMessage = rootMessage && messageToUpdate.parent === rootMessage.id; @@ -724,7 +822,9 @@ class ChatStore { } const messagesToRemove = conversationsStore.activeMessages.slice(messageIndex + 1); + for (const message of messagesToRemove) await DatabaseService.deleteMessage(message.id); + conversationsStore.sliceActiveMessages(messageIndex + 1); conversationsStore.updateConversationTimestamp(); @@ -732,8 +832,11 @@ class ChatStore { this.clearChatStreaming(activeConv.id); const assistantMessage = await this.createAssistantMessage(); + if (!assistantMessage) throw new Error('Failed to create assistant message'); + conversationsStore.addMessageToActive(assistantMessage); + await conversationsStore.updateCurrentNode(assistantMessage.id); await this.streamChatCompletion( conversationsStore.activeMessages.slice(0, -1), @@ -758,12 +861,11 @@ class ChatStore { const activeConv = conversationsStore.activeConversation; if (!activeConv || this.isLoading) return; - try { - const messageIndex = conversationsStore.findMessageIndex(messageId); - if (messageIndex === -1) return; - const messageToRegenerate = conversationsStore.activeMessages[messageIndex]; - if (messageToRegenerate.role !== 'assistant') return; + const result = this.getMessageByIdWithRole(messageId, 'assistant'); + if (!result) return; + const { index: messageIndex } = result; + try { const messagesToRemove = conversationsStore.activeMessages.slice(messageIndex); for (const message of messagesToRemove) await DatabaseService.deleteMessage(message.id); conversationsStore.sliceActiveMessages(messageIndex); @@ -832,6 +934,7 @@ class ChatStore { const siblings = allMessages.filter( (m) => m.parent === messageToDelete.parent && m.id !== messageId ); + if (siblings.length > 0) { const latestSibling = siblings.reduce((latest, sibling) => sibling.timestamp > latest.timestamp ? sibling : latest @@ -845,6 +948,7 @@ class ChatStore { } await DatabaseService.deleteMessageCascading(activeConv.id, messageId); await conversationsStore.refreshActiveMessages(); + conversationsStore.updateConversationTimestamp(); } catch (error) { console.error('Failed to delete message:', error); @@ -862,12 +966,12 @@ class ChatStore { ): Promise { const activeConv = conversationsStore.activeConversation; if (!activeConv || this.isLoading) return; - try { - const idx = conversationsStore.findMessageIndex(messageId); - if (idx === -1) return; - const msg = conversationsStore.activeMessages[idx]; - if (msg.role !== 'assistant') return; + const result = this.getMessageByIdWithRole(messageId, 'assistant'); + if (!result) return; + const { message: msg, index: idx } = result; + + try { if (shouldBranch) { const newMessage = await DatabaseService.createMessageBranch( { @@ -902,12 +1006,12 @@ class ChatStore { async editUserMessagePreserveResponses(messageId: string, newContent: string): Promise { const activeConv = conversationsStore.activeConversation; if (!activeConv) return; - try { - const idx = conversationsStore.findMessageIndex(messageId); - if (idx === -1) return; - const msg = conversationsStore.activeMessages[idx]; - if (msg.role !== 'user') return; + const result = this.getMessageByIdWithRole(messageId, 'user'); + if (!result) return; + const { message: msg, index: idx } = result; + + try { await DatabaseService.updateMessage(messageId, { content: newContent, timestamp: Date.now() @@ -916,6 +1020,7 @@ class ChatStore { const allMessages = await conversationsStore.getConversationMessages(activeConv.id); const rootMessage = allMessages.find((m) => m.type === 'root' && m.parent === null); + if (rootMessage && msg.parent === rootMessage.id && newContent.trim()) { await conversationsStore.updateConversationTitleWithConfirmation( activeConv.id, @@ -932,15 +1037,22 @@ class ChatStore { async editMessageWithBranching(messageId: string, newContent: string): Promise { const activeConv = conversationsStore.activeConversation; if (!activeConv || this.isLoading) return; - try { - const idx = conversationsStore.findMessageIndex(messageId); - if (idx === -1) return; - const msg = conversationsStore.activeMessages[idx]; - if (msg.role !== 'user') return; + let result = this.getMessageByIdWithRole(messageId, 'user'); + + if (!result) { + result = this.getMessageByIdWithRole(messageId, 'system'); + } + + if (!result) return; + const { message: msg } = result; + + try { const allMessages = await conversationsStore.getConversationMessages(activeConv.id); const rootMessage = allMessages.find((m) => m.type === 'root' && m.parent === null); - const isFirstUserMessage = rootMessage && msg.parent === rootMessage.id; + const isFirstUserMessage = + msg.role === 'user' && rootMessage && msg.parent === rootMessage.id; + const parentId = msg.parent || rootMessage?.id; if (!parentId) return; @@ -970,7 +1082,10 @@ class ChatStore { ); } await conversationsStore.refreshActiveMessages(); - await this.generateResponseForMessage(newMessage.id); + + if (msg.role === 'user') { + await this.generateResponseForMessage(newMessage.id); + } } catch (error) { console.error('Failed to edit message with branching:', error); } @@ -1034,7 +1149,9 @@ class ChatStore { private async generateResponseForMessage(userMessageId: string): Promise { const activeConv = conversationsStore.activeConversation; + if (!activeConv) return; + this.errorDialogState = null; this.setChatLoading(activeConv.id, true); this.clearChatStreaming(activeConv.id); @@ -1071,26 +1188,30 @@ class ChatStore { async continueAssistantMessage(messageId: string): Promise { const activeConv = conversationsStore.activeConversation; if (!activeConv || this.isLoading) return; - try { - const idx = conversationsStore.findMessageIndex(messageId); - if (idx === -1) return; - const msg = conversationsStore.activeMessages[idx]; - if (msg.role !== 'assistant') return; - if (this.isChatLoading(activeConv.id)) return; + const result = this.getMessageByIdWithRole(messageId, 'assistant'); + if (!result) return; + const { message: msg, index: idx } = result; + + if (this.isChatLoading(activeConv.id)) return; + + try { this.errorDialogState = null; this.setChatLoading(activeConv.id, true); this.clearChatStreaming(activeConv.id); const allMessages = await conversationsStore.getConversationMessages(activeConv.id); const dbMessage = allMessages.find((m) => m.id === messageId); + if (!dbMessage) { this.setChatLoading(activeConv.id, false); + return; } const originalContent = dbMessage.content; const originalThinking = dbMessage.thinking || ''; + const conversationContext = conversationsStore.activeMessages.slice(0, idx); const contextWithContinue = [ ...conversationContext, @@ -1107,6 +1228,7 @@ class ChatStore { contextWithContinue, { ...this.getApiOptions(), + onChunk: (chunk: string) => { hasReceivedContent = true; appendedContent += chunk; @@ -1114,6 +1236,7 @@ class ChatStore { this.setChatStreaming(msg.convId, fullContent, msg.id); conversationsStore.updateMessageAtIndex(idx, { content: fullContent }); }, + onReasoningChunk: (reasoningChunk: string) => { hasReceivedContent = true; appendedThinking += reasoningChunk; @@ -1121,6 +1244,7 @@ class ChatStore { thinking: originalThinking + appendedThinking }); }, + onTimings: (timings: ChatMessageTimings, promptProgress?: ChatMessagePromptProgress) => { const tokensPerSecond = timings?.predicted_ms && timings?.predicted_n @@ -1137,6 +1261,7 @@ class ChatStore { msg.convId ); }, + onComplete: async ( finalContent?: string, reasoningContent?: string, @@ -1161,6 +1286,7 @@ class ChatStore { this.clearChatStreaming(msg.convId); this.clearProcessingState(msg.convId); }, + onError: async (error: Error) => { if (this.isAbortError(error)) { if (hasReceivedContent && appendedContent) { diff --git a/tools/server/webui/src/lib/stores/conversations.svelte.ts b/tools/server/webui/src/lib/stores/conversations.svelte.ts index 44ef36d6ee..f766561971 100644 --- a/tools/server/webui/src/lib/stores/conversations.svelte.ts +++ b/tools/server/webui/src/lib/stores/conversations.svelte.ts @@ -519,6 +519,19 @@ class ConversationsStore { return await DatabaseService.getConversationMessages(convId); } + /** + * Imports conversations from provided data (without file picker) + * @param data - Array of conversation data with messages + * @returns Import result with counts + */ + async importConversationsData( + data: ExportedConversations + ): Promise<{ imported: number; skipped: number }> { + const result = await DatabaseService.importConversations(data); + await this.loadConversations(); + return result; + } + /** * Adds a message to the active messages array * Used by chatStore when creating new messages diff --git a/tools/server/webui/src/lib/stores/models.svelte.ts b/tools/server/webui/src/lib/stores/models.svelte.ts index 2e834af5a0..29416c2fe5 100644 --- a/tools/server/webui/src/lib/stores/models.svelte.ts +++ b/tools/server/webui/src/lib/stores/models.svelte.ts @@ -158,6 +158,22 @@ class ModelsStore { return this.modelPropsCache.get(modelId) ?? null; } + /** + * Get context size (n_ctx) for a specific model from cached props + */ + getModelContextSize(modelId: string): number | null { + const props = this.modelPropsCache.get(modelId); + return props?.default_generation_settings?.n_ctx ?? null; + } + + /** + * Get context size for the currently selected model or null if no model is selected + */ + get selectedModelContextSize(): number | null { + if (!this.selectedModelName) return null; + return this.getModelContextSize(this.selectedModelName); + } + /** * Check if props are being fetched for a model */ @@ -579,3 +595,4 @@ export const loadedModelIds = () => modelsStore.loadedModelIds; export const loadingModelIds = () => modelsStore.loadingModelIds; export const propsCacheVersion = () => modelsStore.propsCacheVersion; export const singleModelName = () => modelsStore.singleModelName; +export const selectedModelContextSize = () => modelsStore.selectedModelContextSize; diff --git a/tools/server/webui/src/lib/stores/settings.svelte.ts b/tools/server/webui/src/lib/stores/settings.svelte.ts index 5140995eea..2b7d8db102 100644 --- a/tools/server/webui/src/lib/stores/settings.svelte.ts +++ b/tools/server/webui/src/lib/stores/settings.svelte.ts @@ -370,6 +370,10 @@ class SettingsStore { return { ...this.config }; } + canSyncParameter(key: string): boolean { + return ParameterSyncService.canSyncParameter(key); + } + /** * Get parameter information including source for a specific parameter */ diff --git a/tools/server/webui/src/lib/types/chat.d.ts b/tools/server/webui/src/lib/types/chat.d.ts index 0eafb80cbf..0e706b72b6 100644 --- a/tools/server/webui/src/lib/types/chat.d.ts +++ b/tools/server/webui/src/lib/types/chat.d.ts @@ -1,4 +1,4 @@ -export type ChatMessageType = 'root' | 'text' | 'think'; +export type ChatMessageType = 'root' | 'text' | 'think' | 'system'; export type ChatRole = 'user' | 'assistant' | 'system'; export interface ChatUploadedFile { diff --git a/tools/server/webui/src/lib/utils/file-type.ts b/tools/server/webui/src/lib/utils/file-type.ts index f096b463d4..ff7ed6b0c9 100644 --- a/tools/server/webui/src/lib/utils/file-type.ts +++ b/tools/server/webui/src/lib/utils/file-type.ts @@ -77,6 +77,13 @@ export function getFileTypeCategory(mimeType: string): FileTypeCategory | null { case MimeTypeText.SVELTE: case MimeTypeText.LATEX: case MimeTypeText.BIBTEX: + case MimeTypeText.CUDA: + case MimeTypeText.CPP_HDR: + case MimeTypeText.CSHARP: + case MimeTypeText.HASKELL: + case MimeTypeText.PROPERTIES: + case MimeTypeText.TEX: + case MimeTypeText.TEX_APP: return FileTypeCategory.TEXT; default: @@ -144,6 +151,12 @@ export function getFileTypeCategoryByExtension(filename: string): FileTypeCatego case FileExtensionText.SVELTE: case FileExtensionText.TEX: case FileExtensionText.BIB: + case FileExtensionText.COMP: + case FileExtensionText.CU: + case FileExtensionText.CUH: + case FileExtensionText.HPP: + case FileExtensionText.HS: + case FileExtensionText.PROPERTIES: return FileTypeCategory.TEXT; default: diff --git a/vendor/cpp-httplib/CMakeLists.txt b/vendor/cpp-httplib/CMakeLists.txt index 8e1cd9a9da..369502d7ae 100644 --- a/vendor/cpp-httplib/CMakeLists.txt +++ b/vendor/cpp-httplib/CMakeLists.txt @@ -144,4 +144,7 @@ if (CPPHTTPLIB_OPENSSL_SUPPORT) find_library(SECURITY_FRAMEWORK Security REQUIRED) target_link_libraries(${TARGET} PUBLIC ${CORE_FOUNDATION_FRAMEWORK} ${SECURITY_FRAMEWORK}) endif() + if (WIN32 AND NOT MSVC) + target_link_libraries(${TARGET} PUBLIC crypt32) + endif() endif()