From a68f31edd71cc39141113f05f7133a3e9ece8c61 Mon Sep 17 00:00:00 2001 From: ddh0 Date: Mon, 15 Sep 2025 02:54:57 -0500 Subject: [PATCH 01/52] fix KLD percentile output (#15999) In `llama-perplexity`, when using `--kl-divergence`, the KL divergence statistics output mistakenly displays the 99th percentile twice. This change fixes that and correctly displays the 90th percentile as originally intended (presumably). --- tools/perplexity/perplexity.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tools/perplexity/perplexity.cpp b/tools/perplexity/perplexity.cpp index 80cbb095da..c9fd082db9 100644 --- a/tools/perplexity/perplexity.cpp +++ b/tools/perplexity/perplexity.cpp @@ -1931,7 +1931,7 @@ static void kl_divergence(llama_context * ctx, const common_params & params) { LOG("Maximum KLD: %10.6f\n", kld_values.back()); LOG("99.9%% KLD: %10.6f\n", percentile(kld_values, 0.999f)); LOG("99.0%% KLD: %10.6f\n", percentile(kld_values, 0.990f)); - LOG("99.0%% KLD: %10.6f\n", percentile(kld_values, 0.990f)); + LOG("90.0%% KLD: %10.6f\n", percentile(kld_values, 0.900f)); LOG("Median KLD: %10.6f\n", kld_median); LOG("10.0%% KLD: %10.6f\n", percentile(kld_values, 0.100f)); LOG(" 5.0%% KLD: %10.6f\n", percentile(kld_values, 0.050f)); From 106220562aca42b6738b8f51acfce0db1b8a2fb6 Mon Sep 17 00:00:00 2001 From: Aman Gupta Date: Mon, 15 Sep 2025 17:35:11 +0800 Subject: [PATCH 02/52] CUDA: some micro-optimizations in mmf.cuh for mul_mat_id (#15926) --- ggml/src/ggml-cuda/mmf.cuh | 58 +++++++++++++++----------------------- 1 file changed, 23 insertions(+), 35 deletions(-) diff --git a/ggml/src/ggml-cuda/mmf.cuh b/ggml/src/ggml-cuda/mmf.cuh index bf724bc57b..61e3bf3015 100644 --- a/ggml/src/ggml-cuda/mmf.cuh +++ b/ggml/src/ggml-cuda/mmf.cuh @@ -57,31 +57,33 @@ static __global__ void mul_mat_f( T * tile_xy = (T *) compute_base + threadIdx.y*(tile_A::I * tile_k_padded); if constexpr (has_ids) { - __shared__ int has_any; - if (threadIdx.y == 0) { - int local_has_any = 0; - for (int j = threadIdx.x; j < cols_per_block; j += warp_size) { - int slot = -1; - for (int k = 0; k < nchannels_dst; ++k) { - const int idv = ids[j*stride_row_id + k*stride_col_id]; - if (idv == expert_idx) { - slot = k; - break; - } - } - if (j < cols_per_block) { - local_has_any |= (slot >= 0); - slot_map[j] = slot; + int found = 0; + + for (int j0 = 0; j0 < cols_per_block; j0 += nwarps) { + const int j = j0 + threadIdx.y; + const int32_t * __restrict__ id_row = ids + j*stride_row_id; + + if (threadIdx.x == 0) { + slot_map[j] = -1; + } + + for (int k = threadIdx.x; k < nchannels_dst; k += warp_size) { + int match = id_row[k*stride_col_id] == expert_idx; + + if (match) { + slot_map[j] = k; + found = 1; + break; } } - has_any = warp_reduce_any(local_has_any); } - __syncthreads(); - if (has_any == 0) { + + if (!__syncthreads_or(found)) { return; } } + for (int col = threadIdx.y*warp_size + threadIdx.x; col < ncols; col += nwarps*warp_size) { tile_A A[ntA][warp_size / tile_A::J]; #pragma unroll @@ -106,14 +108,7 @@ static __global__ void mul_mat_f( if constexpr (!has_ids) { tile_xy[j0*tile_k_padded + threadIdx.x] = j < cols_per_block ? y[j*stride_col_y + col] : 0.0f; } else { - float val = 0.0f; - if (j < cols_per_block) { - const int slot = slot_map[j]; - if (slot >= 0) { - val = y[slot*stride_channel_y + j*stride_col_y + col]; - } - } - tile_xy[j0*tile_k_padded + threadIdx.x] = val; + tile_xy[j0*tile_k_padded + threadIdx.x] = j < cols_per_block ? y[slot_map[j]*stride_channel_y + j*stride_col_y + col] : 0.0f; } } } else if constexpr (std::is_same_v || std::is_same_v) { @@ -125,14 +120,7 @@ static __global__ void mul_mat_f( const float2 tmp = j < cols_per_block ? y2[j*stride_col_y + col] : make_float2(0.0f, 0.0f); tile_xy[j0*tile_k_padded + threadIdx.x] = {tmp.x, tmp.y}; } else { - float2 tmp = make_float2(0.0f, 0.0f); - if (j < cols_per_block) { - const int slot = slot_map[j]; - if (slot >= 0) { - const float2 * y2_slot = (const float2 *)(y + slot*stride_channel_y); - tmp = y2_slot[j*stride_col_y + col]; - } - } + float2 tmp = j < cols_per_block && slot_map[j] >= 0 ? *(const float2*) &y[slot_map[j]*stride_channel_y + 2*(j*stride_col_y + col)] : make_float2(0.0f, 0.0f); tile_xy[j0*tile_k_padded + threadIdx.x] = {tmp.x, tmp.y}; } } @@ -221,7 +209,7 @@ static inline void mul_mat_f_switch_ids( const dim3 & block_nums, const dim3 & block_dims, const int nbytes_shared_total, cudaStream_t stream) { if (ids) { mul_mat_f<<>> - (x, y, ids, dst, ncols_x, nchannels_dst, stride_row, stride_col_y, stride_col_dst, + (x, y, ids, dst, ncols_x, nchannels_dst, stride_row, stride_col_y, stride_col_dst, stride_col_id, stride_row_id, channel_ratio, stride_channel_x, stride_channel_y, stride_channel_dst, sample_ratio, stride_sample_x, stride_sample_y, stride_sample_dst); } else { From 28c39da7c645185ade5436767929d7ec33006033 Mon Sep 17 00:00:00 2001 From: Nikolay Popov <131475237+npopov-vst@users.noreply.github.com> Date: Mon, 15 Sep 2025 13:08:30 +0300 Subject: [PATCH 03/52] llama-run: Fix model download on Windows (#15988) * llama-run: Fix model download on Windows * fix SSL error (SSL peer certificate or SSH remote key was not OK) * fix program crash on std::filesystem::rename * llama-run: create a separate method to utilize RAII * llama-run: handle rename exception --- tools/run/run.cpp | 72 +++++++++++++++++++++++++++++++---------------- 1 file changed, 47 insertions(+), 25 deletions(-) diff --git a/tools/run/run.cpp b/tools/run/run.cpp index 6fe728c685..772d66c921 100644 --- a/tools/run/run.cpp +++ b/tools/run/run.cpp @@ -407,39 +407,22 @@ class HttpClient { } std::string output_file_partial; - curl = curl_easy_init(); - if (!curl) { - return 1; - } - progress_data data; - File out; if (!output_file.empty()) { output_file_partial = output_file + ".partial"; - if (!out.open(output_file_partial, "ab")) { - printe("Failed to open file for writing\n"); - - return 1; - } - - if (out.lock()) { - printe("Failed to exclusively lock file\n"); - - return 1; - } } - set_write_options(response_str, out); - data.file_size = set_resume_point(output_file_partial); - set_progress_options(progress, data); - set_headers(headers); - CURLcode res = perform(url); - if (res != CURLE_OK){ - printe("Fetching resource '%s' failed: %s\n", url.c_str(), curl_easy_strerror(res)); + if (download(url, headers, output_file_partial, progress, response_str)) { return 1; } + if (!output_file.empty()) { - std::filesystem::rename(output_file_partial, output_file); + try { + std::filesystem::rename(output_file_partial, output_file); + } catch (const std::filesystem::filesystem_error & e) { + printe("Failed to rename '%s' to '%s': %s\n", output_file_partial.c_str(), output_file.c_str(), e.what()); + return 1; + } } return 0; @@ -459,6 +442,42 @@ class HttpClient { CURL * curl = nullptr; struct curl_slist * chunk = nullptr; + int download(const std::string & url, const std::vector & headers, const std::string & output_file, + const bool progress, std::string * response_str = nullptr) { + curl = curl_easy_init(); + if (!curl) { + return 1; + } + + progress_data data; + File out; + if (!output_file.empty()) { + if (!out.open(output_file, "ab")) { + printe("Failed to open file for writing\n"); + + return 1; + } + + if (out.lock()) { + printe("Failed to exclusively lock file\n"); + + return 1; + } + } + + set_write_options(response_str, out); + data.file_size = set_resume_point(output_file); + set_progress_options(progress, data); + set_headers(headers); + CURLcode res = perform(url); + if (res != CURLE_OK){ + printe("Fetching resource '%s' failed: %s\n", url.c_str(), curl_easy_strerror(res)); + return 1; + } + + return 0; + } + void set_write_options(std::string * response_str, const File & out) { if (response_str) { curl_easy_setopt(curl, CURLOPT_WRITEFUNCTION, capture_data); @@ -507,6 +526,9 @@ class HttpClient { curl_easy_setopt(curl, CURLOPT_FOLLOWLOCATION, 1L); curl_easy_setopt(curl, CURLOPT_DEFAULT_PROTOCOL, "https"); curl_easy_setopt(curl, CURLOPT_FAILONERROR, 1L); +#ifdef _WIN32 + curl_easy_setopt(curl, CURLOPT_SSL_OPTIONS, CURLSSLOPT_NATIVE_CA); +#endif return curl_easy_perform(curl); } From b907255f4bd169b0dc7dca9553b4c54af5170865 Mon Sep 17 00:00:00 2001 From: yael-works <106673277+yael-works@users.noreply.github.com> Date: Mon, 15 Sep 2025 19:51:35 +0300 Subject: [PATCH 04/52] SYCL: Add COUNT_EQUAL operator support (#15991) * SYCL: Add COUNT_EQUAL operator support (rebased on master) * SYCL: remove duplicate op_count_equal definition * tests: remove test_count_equal_typed and use test_count_equal for all cases * tests: keep only I32 case for COUNT_EQUAL as suggested * tests: keep only I32 case for COUNT_EQUAL as requested --- ggml/src/ggml-sycl/binbcast.cpp | 9 +++++++++ ggml/src/ggml-sycl/binbcast.hpp | 6 ++++++ ggml/src/ggml-sycl/ggml-sycl.cpp | 4 ++++ 3 files changed, 19 insertions(+) diff --git a/ggml/src/ggml-sycl/binbcast.cpp b/ggml/src/ggml-sycl/binbcast.cpp index 0a3883ae1e..e0a1de0f32 100644 --- a/ggml/src/ggml-sycl/binbcast.cpp +++ b/ggml/src/ggml-sycl/binbcast.cpp @@ -303,6 +303,10 @@ inline void ggml_sycl_op_sub(ggml_backend_sycl_context & ctx, ggml_tensor *dst) ggml_sycl_op_bin_bcast>(ctx, dst->src[0], dst->src[1], dst); } +inline void ggml_sycl_op_count_equal(ggml_backend_sycl_context & ctx, ggml_tensor * dst) { + ggml_sycl_op_bin_bcast>(ctx, dst->src[0], dst->src[1], dst); +} + inline void ggml_sycl_op_mul(ggml_backend_sycl_context & ctx, ggml_tensor *dst) { ggml_sycl_op_bin_bcast>(ctx, dst->src[0], dst->src[1], dst); @@ -328,6 +332,11 @@ void ggml_sycl_sub(ggml_backend_sycl_context & ctx, ggml_tensor * dst) { ggml_sycl_op_sub(ctx, dst); } +void ggml_sycl_count_equal(ggml_backend_sycl_context & ctx, ggml_tensor * dst) { + scope_op_debug_print scope_dbg_print(__func__, dst, /*num_src=*/2); + ggml_sycl_op_count_equal(ctx, dst); +} + void ggml_sycl_mul(ggml_backend_sycl_context & ctx, ggml_tensor * dst) { scope_op_debug_print scope_dbg_print(__func__, dst, /*num_src=*/2); ggml_sycl_op_mul(ctx, dst); diff --git a/ggml/src/ggml-sycl/binbcast.hpp b/ggml/src/ggml-sycl/binbcast.hpp index 9cce0f053a..34c4064f52 100644 --- a/ggml/src/ggml-sycl/binbcast.hpp +++ b/ggml/src/ggml-sycl/binbcast.hpp @@ -16,6 +16,12 @@ static __dpct_inline__ float op_sub(const float a, const float b) { return a - b; } +static __dpct_inline__ float op_count_equal(const float a, const float b) { + return (a == b) ? 1.0f : 0.0f; +} + +void ggml_sycl_count_equal(ggml_backend_sycl_context & ctx, ggml_tensor * dst); + static __dpct_inline__ float op_mul(const float a, const float b) { return a * b; } diff --git a/ggml/src/ggml-sycl/ggml-sycl.cpp b/ggml/src/ggml-sycl/ggml-sycl.cpp index e06ec613fc..9404e3ff4a 100644 --- a/ggml/src/ggml-sycl/ggml-sycl.cpp +++ b/ggml/src/ggml-sycl/ggml-sycl.cpp @@ -3577,6 +3577,9 @@ static bool ggml_sycl_compute_forward(ggml_backend_sycl_context & ctx, struct gg case GGML_OP_SUB: ggml_sycl_sub(ctx, dst); break; + case GGML_OP_COUNT_EQUAL: + ggml_sycl_count_equal(ctx, dst); + break; case GGML_OP_ACC: ggml_sycl_acc(ctx, dst); break; @@ -4356,6 +4359,7 @@ static bool ggml_backend_sycl_device_supports_op(ggml_backend_dev_t dev, const g case GGML_OP_ADD: case GGML_OP_ADD1: case GGML_OP_SUB: + case GGML_OP_COUNT_EQUAL: case GGML_OP_MUL: case GGML_OP_DIV: case GGML_OP_REPEAT: From 10d197409bd9537ff302ad09966fe406882fef9d Mon Sep 17 00:00:00 2001 From: Diego Devesa Date: Mon, 15 Sep 2025 14:38:42 -0700 Subject: [PATCH 05/52] releases : switch to rocWMMA develop branch, add gfx1151 (#15992) * releases : switch to rocWMMA develop branch, add gfx1151 * remove unused variable ROCM_VERSION --- .github/workflows/release.yml | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml index e959209ab2..f461456edf 100644 --- a/.github/workflows/release.yml +++ b/.github/workflows/release.yml @@ -530,15 +530,13 @@ jobs: runs-on: windows-2022 env: - # The ROCm version must correspond to the version used in the HIP SDK. - ROCM_VERSION: "6.4.2" HIPSDK_INSTALLER_VERSION: "25.Q3" strategy: matrix: include: - name: "radeon" - gpu_targets: "gfx1200;gfx1201;gfx1100;gfx1101;gfx1102;gfx1030;gfx1031;gfx1032" + gpu_targets: "gfx1151;gfx1200;gfx1201;gfx1100;gfx1101;gfx1102;gfx1030;gfx1031;gfx1032" steps: - name: Clone @@ -548,7 +546,7 @@ jobs: - name: Clone rocWMMA repository id: clone_rocwmma run: | - git clone https://github.com/rocm/rocwmma --branch rocm-${{ env.ROCM_VERSION }} --depth 1 + git clone https://github.com/rocm/rocwmma --branch develop --depth 1 - name: Cache ROCm Installation id: cache-rocm From dc381aa9a6dc45f00673471d34b8bddd30e77570 Mon Sep 17 00:00:00 2001 From: Diego Devesa Date: Mon, 15 Sep 2025 14:38:52 -0700 Subject: [PATCH 06/52] docker : enable rocWMMA in ROCm images, add gfx1151 (#15997) --- .devops/rocm.Dockerfile | 19 ++++++++++++------- 1 file changed, 12 insertions(+), 7 deletions(-) diff --git a/.devops/rocm.Dockerfile b/.devops/rocm.Dockerfile index 221077197d..106c62b4dc 100644 --- a/.devops/rocm.Dockerfile +++ b/.devops/rocm.Dockerfile @@ -17,14 +17,11 @@ FROM ${BASE_ROCM_DEV_CONTAINER} AS build # gfx906 is deprecated #check https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.4.1/reference/system-requirements.html -ARG ROCM_DOCKER_ARCH='gfx803,gfx900,gfx906,gfx908,gfx90a,gfx942,gfx1010,gfx1030,gfx1032,gfx1100,gfx1101,gfx1102,gfx1200,gfx1201' -#ARG ROCM_DOCKER_ARCH=gfx1100 +ARG ROCM_DOCKER_ARCH='gfx803;gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1010;gfx1030;gfx1032;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201;gfx1151' +#ARG ROCM_DOCKER_ARCH='gfx1151' -# Set ROCm architectured +# Set ROCm architectures ENV AMDGPU_TARGETS=${ROCM_DOCKER_ARCH} -# Enable ROCm -# ENV CC=/opt/rocm/llvm/bin/clang -# ENV CXX=/opt/rocm/llvm/bin/clang++ RUN apt-get update \ && apt-get install -y \ @@ -39,8 +36,16 @@ WORKDIR /app COPY . . +RUN git clone https://github.com/rocm/rocwmma --branch develop --depth 1 + RUN HIPCXX="$(hipconfig -l)/clang" HIP_PATH="$(hipconfig -R)" \ - cmake -S . -B build -DGGML_HIP=ON -DAMDGPU_TARGETS=$ROCM_DOCKER_ARCH -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DCMAKE_BUILD_TYPE=Release -DLLAMA_BUILD_TESTS=OFF \ + cmake -S . -B build \ + -DGGML_HIP=ON \ + -DGGML_HIP_ROCWMMA_FATTN=ON \ + -DCMAKE_HIP_FLAGS="-I$(pwd)/rocwmma/library/include/" \ + -DAMDGPU_TARGETS="$ROCM_DOCKER_ARCH" \ + -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON \ + -DCMAKE_BUILD_TYPE=Release -DLLAMA_BUILD_TESTS=OFF \ && cmake --build build --config Release -j$(nproc) RUN mkdir -p /app/lib \ From 3d4053f77f0f78ee2b791088c02af653ebee42dd Mon Sep 17 00:00:00 2001 From: Jake Karnes Date: Mon, 15 Sep 2025 16:28:31 -0600 Subject: [PATCH 07/52] CUDA: fix im2col_3d to respect non-contiguous inputs (views) (#15956) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * fix im2col_3d to respect non-contiguous inputs (views) The CUDA 3D im2col kernel computed source addresses assuming compact layout (products of dims), ignoring nb[] strides. This patch switches im2col_3d source indexing to use true strides derived from src1->nb[] (in elements), mirroring the approach used in the 2D CUDA im2col path. Destination indexing is unchanged. * use ggml_element_size() for src strides Co-authored-by: Johannes Gäßler --------- Co-authored-by: Johannes Gäßler --- ggml/src/ggml-cuda/im2col.cu | 31 ++++++++++++++++++++++++++----- 1 file changed, 26 insertions(+), 5 deletions(-) diff --git a/ggml/src/ggml-cuda/im2col.cu b/ggml/src/ggml-cuda/im2col.cu index 7737d6a5d5..56dc054574 100644 --- a/ggml/src/ggml-cuda/im2col.cu +++ b/ggml/src/ggml-cuda/im2col.cu @@ -122,11 +122,14 @@ static __global__ void im2col_3d_kernel( int64_t OH_OW, int64_t KD_KH_KW, int64_t ID_IH_IW, int64_t KH_KW, int64_t IH_IW, int64_t IC_ID_IH_IW, int64_t IC_KD_KH_KW, int64_t OW_KD_KH_KW, int64_t OD_OH_OW_IC_KD_KH_KW, int64_t OH_OW_IC_KD_KH_KW, int64_t OW_IC_KD_KH_KW, int64_t N_OD_OH, int64_t OD_OH, + int64_t stride_q, int64_t stride_z, int64_t stride_y, int64_t stride_x, int s0, int s1, int s2, int p0, int p1, int p2, int d0, int d1, int d2) { const int64_t i = threadIdx.x + blockIdx.x * blockDim.x; if (i >= IC_KD_KH_KW) { return; } + GGML_UNUSED(N); GGML_UNUSED(OC); GGML_UNUSED(OH_OW); GGML_UNUSED(OD); GGML_UNUSED(OW); GGML_UNUSED(KD); GGML_UNUSED(KH); + GGML_UNUSED(ID_IH_IW); GGML_UNUSED(IH_IW); GGML_UNUSED(IC_ID_IH_IW); GGML_UNUSED(OW_KD_KH_KW); const int64_t iic = i / KD_KH_KW; const int64_t ikd = (i - iic * KD_KH_KW) / KH_KW; @@ -148,7 +151,7 @@ static __global__ void im2col_3d_kernel( if (iih < 0 || iih >= IH || iiw < 0 || iiw >= IW || iid < 0 || iid >= ID) { dst[offset_dst] = 0.0f; } else { - const int64_t offset_src = in*IC_ID_IH_IW + iic*ID_IH_IW + iid*IH_IW + iih*IW + iiw; + const int64_t offset_src = ((in * IC + iic) * stride_q) + (iid * stride_z) + (iih * stride_y) + (iiw * stride_x); dst[offset_dst] = src[offset_src]; } } @@ -159,6 +162,7 @@ template static void im2col_3d_cuda(const float * src, T* dst, int64_t N, int64_t IC, int64_t ID, int64_t IH, int64_t IW, int64_t OC, int64_t KD, int64_t KH, int64_t KW, int64_t OD, int64_t OH, int64_t OW, + int64_t stride_q, int64_t stride_z, int64_t stride_y, int64_t stride_x, int s0, int s1, int s2, int p0, int p1, int p2, int d0, int d1, int d2, cudaStream_t stream) { const int64_t OH_OW = OH*OW; const int64_t KD_KH_KW = KD*KH*KW; @@ -179,23 +183,30 @@ static void im2col_3d_cuda(const float * src, T* dst, OH_OW, KD_KH_KW, ID_IH_IW, KH_KW, IH_IW, IC_ID_IH_IW, IC_KD_KH_KW, OW_KD_KH_KW, OD_OH_OW_IC_KD_KH_KW, OH_OW_IC_KD_KH_KW, OW_IC_KD_KH_KW, N_OD_OH, OD_OH, + stride_q, stride_z, stride_y, stride_x, s0, s1, s2, p0, p1, p2, d0, d1, d2); } static void im2col_3d_cuda_f16(const float * src, half * dst, int64_t N, int64_t IC, int64_t ID, int64_t IH, int64_t IW, int64_t OC, int64_t KD, int64_t KH, int64_t KW, int64_t OD, int64_t OH, int64_t OW, + int64_t stride_q, int64_t stride_z, int64_t stride_y, int64_t stride_x, int s0, int s1, int s2, int p0, int p1, int p2, int d0, int d1, int d2, cudaStream_t stream) { - im2col_3d_cuda(src, dst, N, IC, ID, IH, IW, OC, KD, KH, KW, OD, OH, OW, s0, s1, s2, p0, p1, p2, d0, d1, d2, stream); + im2col_3d_cuda(src, dst, N, IC, ID, IH, IW, OC, KD, KH, KW, OD, OH, OW, + stride_q, stride_z, stride_y, stride_x, + s0, s1, s2, p0, p1, p2, d0, d1, d2, stream); } static void im2col_3d_cuda_f32(const float * src, float * dst, int64_t N, int64_t IC, int64_t ID, int64_t IH, int64_t IW, int64_t OC, int64_t KD, int64_t KH, int64_t KW, int64_t OD, int64_t OH, int64_t OW, + int64_t stride_q, int64_t stride_z, int64_t stride_y, int64_t stride_x, int s0, int s1, int s2, int p0, int p1, int p2, int d0, int d1, int d2, cudaStream_t stream) { - im2col_3d_cuda(src, dst, N, IC, ID, IH, IW, OC, KD, KH, KW, OD, OH, OW, s0, s1, s2, p0, p1, p2, d0, d1, d2, stream); + im2col_3d_cuda(src, dst, N, IC, ID, IH, IW, OC, KD, KH, KW, OD, OH, OW, + stride_q, stride_z, stride_y, stride_x, + s0, s1, s2, p0, p1, p2, d0, d1, d2, stream); } void ggml_cuda_op_im2col_3d(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { @@ -235,9 +246,19 @@ void ggml_cuda_op_im2col_3d(ggml_backend_cuda_context & ctx, ggml_tensor * dst) const int64_t OH = ne2; const int64_t OW = ne1; + const size_t es = ggml_element_size(src1); + const int64_t stride_x = src1->nb[0] / es; + const int64_t stride_y = src1->nb[1] / es; + const int64_t stride_z = src1->nb[2] / es; + const int64_t stride_q = src1->nb[3] / es; + if(dst->type == GGML_TYPE_F16) { - im2col_3d_cuda_f16(src1_d, (half *) dst_d, N, IC, ID, IH, IW, OC, KD, KH, KW, OD, OH, OW, s0, s1, s2, p0, p1, p2, d0, d1, d2, stream); + im2col_3d_cuda_f16(src1_d, (half *) dst_d, N, IC, ID, IH, IW, OC, KD, KH, KW, OD, OH, OW, + stride_q, stride_z, stride_y, stride_x, + s0, s1, s2, p0, p1, p2, d0, d1, d2, stream); } else { - im2col_3d_cuda_f32(src1_d, (float *) dst_d, N, IC, ID, IH, IW, OC, KD, KH, KW, OD, OH, OW, s0, s1, s2, p0, p1, p2, d0, d1, d2, stream); + im2col_3d_cuda_f32(src1_d, (float *) dst_d, N, IC, ID, IH, IW, OC, KD, KH, KW, OD, OH, OW, + stride_q, stride_z, stride_y, stride_x, + s0, s1, s2, p0, p1, p2, d0, d1, d2, stream); } } From 6d758839ff741d4966ca92b7f801b7a8b5b96364 Mon Sep 17 00:00:00 2001 From: Aman Gupta Date: Tue, 16 Sep 2025 10:38:28 +0800 Subject: [PATCH 08/52] Add LLaDA-7b-MoE diffusion model (#16003) --- common/arg.cpp | 2 +- convert_hf_to_gguf.py | 73 +++++++++++ convert_hf_to_gguf_update.py | 1 + examples/diffusion/diffusion-cli.cpp | 24 ++-- gguf-py/gguf/constants.py | 19 +++ src/llama-arch.cpp | 22 ++++ src/llama-arch.h | 1 + src/llama-model.cpp | 179 +++++++++++++++++++++++++++ src/llama-vocab.cpp | 3 +- 9 files changed, 315 insertions(+), 9 deletions(-) diff --git a/common/arg.cpp b/common/arg.cpp index c15008fe79..19189d8f9f 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -1704,7 +1704,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex [](common_params & params, const std::string & value) { params.system_prompt = value; } - ).set_examples({LLAMA_EXAMPLE_MAIN})); + ).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_DIFFUSION})); add_opt(common_arg( {"--no-perf"}, string_format("disable internal libllama performance timings (default: %s)", params.no_perf ? "true" : "false"), diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py index 855789f1ba..5a21ba2110 100755 --- a/convert_hf_to_gguf.py +++ b/convert_hf_to_gguf.py @@ -888,6 +888,9 @@ class TextModel(ModelBase): if chkhsh == "a1e163ecab2e718a4c829d1148b6e86824ec36163bb71941c3dca9cd5ac25756": # ref: https://huggingface.co/JetBrains/Mellum-4b-base res = "mellum" + if chkhsh == "9b1be57e70d20d9501b2b3186e792d81181ae36ada3903c26f9fea418cf87206": + # ref: https://huggingface.co/inclusionAI/LLaDA-MoE-7B-A1B-Base + res = "llada-moe" if res is None: logger.warning("\n") @@ -8239,6 +8242,76 @@ class HunYuanMoEModel(TextModel): raise ValueError(f"Unprocessed experts: {experts}") +@ModelBase.register("LLaDAMoEModel", "LLaDAMoEModelLM") +class LLaDAMoEModel(TextModel): + model_arch = gguf.MODEL_ARCH.LLADA_MOE + + def set_gguf_parameters(self): + super().set_gguf_parameters() + if (n_experts := self.hparams.get("num_experts")) is not None: + self.gguf_writer.add_expert_count(n_experts) + + if (expert_intermediate_size := self.hparams.get("expert_intermediate_size")) is not None: + self.gguf_writer.add_expert_feed_forward_length(expert_intermediate_size) + + # number of experts used per token (top-k) + if (n_experts_used := self.hparams.get("num_experts_per_tok")) is not None: + self.gguf_writer.add_expert_used_count(n_experts_used) + + self.gguf_writer.add_mask_token_id(156895) + self.gguf_writer.add_causal_attention(False) + self.gguf_writer.add_diffusion_shift_logits(False) + + _experts: list[dict[str, Tensor]] | None = None + + # Copied from: Qwen2MoeModel + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + # process the experts separately + if name.find("experts") != -1: + n_experts = self.hparams["num_experts"] + assert bid is not None + + if self._experts is None: + self._experts = [{} for _ in range(self.block_count)] + + self._experts[bid][name] = data_torch + + if len(self._experts[bid]) >= n_experts * 3: + tensors: list[tuple[str, Tensor]] = [] + + # merge the experts into a single 3d tensor + for w_name in ["down_proj", "gate_proj", "up_proj"]: + datas: list[Tensor] = [] + + for xid in range(n_experts): + ename = f"model.layers.{bid}.mlp.experts.{xid}.{w_name}.weight" + datas.append(self._experts[bid][ename]) + del self._experts[bid][ename] + + data_torch = torch.stack(datas, dim=0) + + merged_name = f"model.layers.{bid}.mlp.experts.{w_name}.weight" + + new_name = self.map_tensor_name(merged_name) + + tensors.append((new_name, data_torch)) + return tensors + else: + return [] + + return [(self.map_tensor_name(name), data_torch)] + + # Copied from: Qwen2MoeModel + def prepare_tensors(self): + super().prepare_tensors() + + if self._experts is not None: + # flatten `list[dict[str, Tensor]]` into `list[str]` + experts = [k for d in self._experts for k in d.keys()] + if len(experts) > 0: + raise ValueError(f"Unprocessed experts: {experts}") + + @ModelBase.register("HunYuanDenseV1ForCausalLM") class HunYuanModel(TextModel): model_arch = gguf.MODEL_ARCH.HUNYUAN_DENSE diff --git a/convert_hf_to_gguf_update.py b/convert_hf_to_gguf_update.py index eb8fdfa7e1..21bb4a9f3e 100755 --- a/convert_hf_to_gguf_update.py +++ b/convert_hf_to_gguf_update.py @@ -139,6 +139,7 @@ models = [ {"name": "lfm2", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/LiquidAI/LFM2-Tokenizer"}, {"name": "exaone4", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/LGAI-EXAONE/EXAONE-4.0-32B", }, {"name": "mellum", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/JetBrains/Mellum-4b-base", }, + {"name": "llada-moe", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/inclusionAI/LLaDA-MoE-7B-A1B-Base", }, ] # some models are known to be broken upstream, so we will skip them as exceptions diff --git a/examples/diffusion/diffusion-cli.cpp b/examples/diffusion/diffusion-cli.cpp index abf7fb3573..273942a165 100644 --- a/examples/diffusion/diffusion-cli.cpp +++ b/examples/diffusion/diffusion-cli.cpp @@ -510,19 +510,27 @@ static void diffusion_generate(llama_context * ctx, n_generated = params.max_length; } -static std::string format_input_text(const std::string & prompt, bool use_chat_template, llama_model * model) { +static std::string format_input_text(const std::string & prompt, const std::string & system_prompt, bool use_chat_template, llama_model * model) { if (!use_chat_template) { return prompt; } auto chat_templates = common_chat_templates_init(model, ""); - common_chat_templates_inputs inputs; - common_chat_msg user_msg; - user_msg.role = "user"; - user_msg.content = prompt; - inputs.add_generation_prompt = true; + common_chat_msg system_msg; + + if (!system_prompt.empty()) { + system_msg.role = "system"; + system_msg.content = system_prompt; + inputs.messages.push_back(system_msg); + } + + common_chat_msg user_msg; + user_msg.role = "user"; + user_msg.content = prompt; + inputs.messages.push_back(user_msg); + inputs.add_generation_prompt = true; auto result = common_chat_templates_apply(chat_templates.get(), inputs); @@ -579,7 +587,8 @@ int main(int argc, char ** argv) { llama_set_n_threads(ctx, params.cpuparams.n_threads, params.cpuparams_batch.n_threads); const llama_vocab * vocab = llama_model_get_vocab(model); - std::string formatted_prompt = format_input_text(params.prompt, params.enable_chat_template, model); + + std::string formatted_prompt = format_input_text(params.prompt, params.system_prompt, params.enable_chat_template, model); std::vector input_tokens = common_tokenize(vocab, formatted_prompt, @@ -596,6 +605,7 @@ int main(int argc, char ** argv) { } llama_token mask_token_id = llama_vocab_mask(vocab); + GGML_ASSERT(mask_token_id != LLAMA_TOKEN_NULL); bool visual_mode = params.diffusion.visual_mode; diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py index c7edef919b..7e16cbcbde 100644 --- a/gguf-py/gguf/constants.py +++ b/gguf-py/gguf/constants.py @@ -399,6 +399,7 @@ class MODEL_ARCH(IntEnum): DREAM = auto() SMALLTHINKER = auto() LLADA = auto() + LLADA_MOE = auto() SEED_OSS = auto() @@ -735,6 +736,7 @@ MODEL_ARCH_NAMES: dict[MODEL_ARCH, str] = { MODEL_ARCH.DREAM: "dream", MODEL_ARCH.SMALLTHINKER: "smallthinker", MODEL_ARCH.LLADA: "llada", + MODEL_ARCH.LLADA_MOE: "llada-moe", MODEL_ARCH.SEED_OSS: "seed_oss", } @@ -2693,6 +2695,23 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = { MODEL_TENSOR.FFN_DOWN_EXP, MODEL_TENSOR.FFN_UP_EXP, ], + MODEL_ARCH.LLADA_MOE: [ + MODEL_TENSOR.TOKEN_EMBD, + MODEL_TENSOR.OUTPUT_NORM, + MODEL_TENSOR.OUTPUT, + MODEL_TENSOR.ATTN_OUT, + MODEL_TENSOR.ATTN_Q, + MODEL_TENSOR.ATTN_K, + MODEL_TENSOR.ATTN_V, + MODEL_TENSOR.ATTN_NORM, + MODEL_TENSOR.ATTN_Q_NORM, + MODEL_TENSOR.ATTN_K_NORM, + MODEL_TENSOR.FFN_NORM, + MODEL_TENSOR.FFN_GATE_INP, + MODEL_TENSOR.FFN_GATE_EXP, + MODEL_TENSOR.FFN_UP_EXP, + MODEL_TENSOR.FFN_DOWN_EXP, + ], # TODO } diff --git a/src/llama-arch.cpp b/src/llama-arch.cpp index 3122331d8e..a4d2973ada 100644 --- a/src/llama-arch.cpp +++ b/src/llama-arch.cpp @@ -96,6 +96,7 @@ static const std::map LLM_ARCH_NAMES = { { LLM_ARCH_DREAM, "dream" }, { LLM_ARCH_SMALLTHINKER, "smallthinker" }, { LLM_ARCH_LLADA, "llada" }, + { LLM_ARCH_LLADA_MOE, "llada-moe" }, { LLM_ARCH_SEED_OSS, "seed_oss" }, { LLM_ARCH_UNKNOWN, "(unknown)" }, }; @@ -2147,6 +2148,26 @@ static const std::map> LLM_TENSOR_N { LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" }, }, }, + { + LLM_ARCH_LLADA_MOE, + { + { LLM_TENSOR_TOKEN_EMBD, "token_embd" }, + { LLM_TENSOR_OUTPUT_NORM, "output_norm" }, + { LLM_TENSOR_OUTPUT, "output" }, + { LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" }, + { LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" }, + { LLM_TENSOR_ATTN_Q_NORM, "blk.%d.attn_q_norm" }, + { LLM_TENSOR_ATTN_K, "blk.%d.attn_k" }, + { LLM_TENSOR_ATTN_K_NORM, "blk.%d.attn_k_norm" }, + { LLM_TENSOR_ATTN_V, "blk.%d.attn_v" }, + { LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" }, + { LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" }, + { LLM_TENSOR_FFN_GATE_INP, "blk.%d.ffn_gate_inp" }, + { LLM_TENSOR_FFN_GATE_EXPS, "blk.%d.ffn_gate_exps" }, + { LLM_TENSOR_FFN_DOWN_EXPS, "blk.%d.ffn_down_exps" }, + { LLM_TENSOR_FFN_UP_EXPS, "blk.%d.ffn_up_exps" }, + }, + }, { LLM_ARCH_SEED_OSS, { @@ -2427,6 +2448,7 @@ bool llm_arch_is_diffusion(const llm_arch & arch) { switch (arch) { case LLM_ARCH_DREAM: case LLM_ARCH_LLADA: + case LLM_ARCH_LLADA_MOE: return true; default: return false; diff --git a/src/llama-arch.h b/src/llama-arch.h index a4ac28b525..d181ce6784 100644 --- a/src/llama-arch.h +++ b/src/llama-arch.h @@ -100,6 +100,7 @@ enum llm_arch { LLM_ARCH_DREAM, LLM_ARCH_SMALLTHINKER, LLM_ARCH_LLADA, + LLM_ARCH_LLADA_MOE, LLM_ARCH_SEED_OSS, LLM_ARCH_UNKNOWN, }; diff --git a/src/llama-model.cpp b/src/llama-model.cpp index 4864ed8e72..731e87383b 100644 --- a/src/llama-model.cpp +++ b/src/llama-model.cpp @@ -936,6 +936,18 @@ void llama_model::load_hparams(llama_model_loader & ml) { hparams.causal_attn = false; } break; + case LLM_ARCH_LLADA_MOE: + { + ml.get_key(LLM_KV_EXPERT_FEED_FORWARD_LENGTH, hparams.n_ff_exp, false); + + ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps); + // diffusion language model uses non-causal attention + hparams.causal_attn = false; + switch (hparams.n_layer) { + case 16: type = LLM_TYPE_A1_7B; break; + default: type = LLM_TYPE_UNKNOWN; + } + } break; case LLM_ARCH_QWEN2MOE: { ml.get_key(LLM_KV_EXPERT_FEED_FORWARD_LENGTH, hparams.n_ff_exp, false); @@ -2387,6 +2399,40 @@ bool llama_model::load_tensors(llama_model_loader & ml) { } } break; + case LLM_ARCH_LLADA_MOE: + { + tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0); + + // output + output_norm = create_tensor(tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd}, 0); + output = create_tensor(tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, 0); + + GGML_ASSERT(n_expert > 0 && "n_expert must be > 0 for llada-moe"); + GGML_ASSERT(n_expert_used > 0 && "n_expert_used must be > 0 for llada-moe"); + + for (int i = 0; i < n_layer; ++i) { + auto & layer = layers[i]; + + layer.attn_norm = create_tensor(tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd}, 0); + + layer.wq = create_tensor(tn(LLM_TENSOR_ATTN_Q, "weight", i), {n_embd, n_embd}, 0); + layer.wk = create_tensor(tn(LLM_TENSOR_ATTN_K, "weight", i), {n_embd, n_embd_gqa}, 0); + layer.wv = create_tensor(tn(LLM_TENSOR_ATTN_V, "weight", i), {n_embd, n_embd_gqa}, 0); + layer.wo = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd}, 0); + layer.attn_q_norm = create_tensor(tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {n_embd_head_k}, 0); + layer.attn_k_norm = create_tensor(tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {n_embd_head_k}, 0); + + layer.ffn_norm = create_tensor(tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, 0); + + layer.ffn_gate_inp = create_tensor(tn(LLM_TENSOR_FFN_GATE_INP, "weight", i), {n_embd, n_expert}, 0); + + const int64_t n_ff_exp = hparams.n_ff_exp ? hparams.n_ff_exp : n_ff / n_expert_used; + + layer.ffn_gate_exps = create_tensor(tn(LLM_TENSOR_FFN_GATE_EXPS, "weight", i), { n_embd, n_ff_exp, n_expert}, 0); + layer.ffn_down_exps = create_tensor(tn(LLM_TENSOR_FFN_DOWN_EXPS, "weight", i), {n_ff_exp, n_embd, n_expert}, 0); + layer.ffn_up_exps = create_tensor(tn(LLM_TENSOR_FFN_UP_EXPS, "weight", i), { n_embd, n_ff_exp, n_expert}, 0); + } + } break; case LLM_ARCH_LLAMA4: { tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0); @@ -12444,6 +12490,132 @@ struct llm_build_olmoe : public llm_graph_context { } }; +struct llm_build_llada_moe : public llm_graph_context { + llm_build_llada_moe(const llama_model & model, const llm_graph_params & params) : llm_graph_context(params) { + const int64_t n_embd_head = hparams.n_embd_head_v; + + GGML_ASSERT(n_embd_head == hparams.n_embd_head_k); + GGML_ASSERT(n_embd_head == hparams.n_rot); + + ggml_tensor * cur; + ggml_tensor * inpL; + + inpL = build_inp_embd(model.tok_embd); + + // inp_pos - contains the positions + ggml_tensor * inp_pos = build_inp_pos(); + + auto * inp_attn = build_attn_inp_no_cache(); + + ggml_tensor * inp_out_ids = build_inp_out_ids(); + + for (int il = 0; il < n_layer; ++il) { + ggml_tensor * inpSA = inpL; + + // norm + cur = build_norm(inpL, + model.layers[il].attn_norm, NULL, + LLM_NORM_RMS, il); + cb(cur, "attn_norm", il); + + // self_attention + { + // compute Q and K and RoPE them + ggml_tensor * Qcur = build_lora_mm(model.layers[il].wq, cur); + cb(Qcur, "Qcur", il); + + ggml_tensor * Kcur = build_lora_mm(model.layers[il].wk, cur); + cb(Kcur, "Kcur", il); + + ggml_tensor * Vcur = build_lora_mm(model.layers[il].wv, cur); + cb(Vcur, "Vcur", il); + + Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens); + Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens); + Vcur = ggml_reshape_3d(ctx0, Vcur, n_embd_head, n_head_kv, n_tokens); + + Qcur = build_norm(Qcur, model.layers[il].attn_q_norm, NULL, LLM_NORM_RMS, il); + cb(Qcur, "Qcur_normed", il); + + Kcur = build_norm(Kcur, model.layers[il].attn_k_norm, NULL, LLM_NORM_RMS, il); + cb(Kcur, "Kcur_normed", il); + + Qcur = ggml_rope_ext( + ctx0, Qcur, inp_pos, nullptr, + n_rot, rope_type, n_ctx_orig, freq_base, freq_scale, + ext_factor, attn_factor, beta_fast, beta_slow + ); + + Kcur = ggml_rope_ext( + ctx0, Kcur, inp_pos, nullptr, + n_rot, rope_type, n_ctx_orig, freq_base, freq_scale, + ext_factor, attn_factor, beta_fast, beta_slow + ); + + cb(Qcur, "Qcur", il); + cb(Kcur, "Kcur", il); + cb(Vcur, "Vcur", il); + + cur = build_attn(inp_attn, + model.layers[il].wo, NULL, + Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, 1.0f/sqrtf(float(n_embd_head)), il); + } + + if (il == n_layer - 1 && inp_out_ids) { + cur = ggml_get_rows(ctx0, cur, inp_out_ids); + inpSA = ggml_get_rows(ctx0, inpSA, inp_out_ids); + } + + ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpSA); + cb(ffn_inp, "ffn_inp", il); + + // MoE branch + cur = build_norm(ffn_inp, + model.layers[il].ffn_norm, NULL, + LLM_NORM_RMS, il); + cb(cur, "ffn_norm", il); + + cur = build_moe_ffn(cur, + model.layers[il].ffn_gate_inp, + model.layers[il].ffn_up_exps, + model.layers[il].ffn_gate_exps, + model.layers[il].ffn_down_exps, + nullptr, + n_expert, n_expert_used, + LLM_FFN_SILU, false, + false, 0.0, + LLAMA_EXPERT_GATING_FUNC_TYPE_SOFTMAX, + il); + cb(cur, "ffn_moe_out", il); + + cur = ggml_add(ctx0, cur, ffn_inp); + + cur = build_cvec(cur, il); + cb(cur, "l_out", il); + + // input for next layer + inpL = cur; + } + + cur = inpL; + + cur = build_norm(cur, + model.output_norm, NULL, + LLM_NORM_RMS, -1); + + cb(cur, "result_norm", -1); + res->t_embd = cur; + + // lm_head + cur = build_lora_mm(model.output, cur); + + cb(cur, "result_output", -1); + res->t_logits = cur; + + ggml_build_forward_expand(gf, cur); + } +}; + struct llm_build_openelm : public llm_graph_context { llm_build_openelm(const llama_model & model, const llm_graph_params & params) : llm_graph_context(params) { const int64_t n_embd_head = hparams.n_embd_head_v; @@ -18636,6 +18808,7 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params, //case LLM_ARCH_GEMMA_EMBEDDING: // TODO: disabled until the cacheless SWA logic is fixed [TAG_NO_CACHE_ISWA] case LLM_ARCH_DREAM: case LLM_ARCH_LLADA: + case LLM_ARCH_LLADA_MOE: { res = nullptr; } break; @@ -18841,6 +19014,11 @@ ggml_cgraph * llama_model::build_graph(const llm_graph_params & params) const { llm = std::make_unique(*this, params); } break; + case LLM_ARCH_LLADA_MOE: + { + llm = std::make_unique(*this, params); + } + break; case LLM_ARCH_QWEN2VL: { llm = std::make_unique(*this, params); @@ -19307,6 +19485,7 @@ llama_rope_type llama_model_rope_type(const llama_model * model) { case LLM_ARCH_QWEN2MOE: case LLM_ARCH_QWEN3: case LLM_ARCH_QWEN3MOE: + case LLM_ARCH_LLADA_MOE: case LLM_ARCH_OLMO2: case LLM_ARCH_OLMOE: case LLM_ARCH_PHI2: diff --git a/src/llama-vocab.cpp b/src/llama-vocab.cpp index b551253afb..8cb36661a0 100644 --- a/src/llama-vocab.cpp +++ b/src/llama-vocab.cpp @@ -1962,7 +1962,8 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) { pre_type = LLAMA_VOCAB_PRE_TYPE_TRILLION; clean_spaces = false; } else if ( - tokenizer_pre == "bailingmoe") { + tokenizer_pre == "bailingmoe" || + tokenizer_pre == "llada-moe") { pre_type = LLAMA_VOCAB_PRE_TYPE_BAILINGMOE; clean_spaces = false; } else if ( From 07808ebb07e2b1aa19032705e332679ddf967614 Mon Sep 17 00:00:00 2001 From: Yuri Khrustalev Date: Mon, 15 Sep 2025 22:54:44 -0400 Subject: [PATCH 09/52] cmake : Do not install tools on iOS targets (#15903) --- CMakeLists.txt | 7 +++++++ tools/batched-bench/CMakeLists.txt | 5 ++++- tools/cvector-generator/CMakeLists.txt | 5 ++++- tools/export-lora/CMakeLists.txt | 5 ++++- tools/gguf-split/CMakeLists.txt | 5 ++++- tools/imatrix/CMakeLists.txt | 5 ++++- tools/llama-bench/CMakeLists.txt | 5 ++++- tools/main/CMakeLists.txt | 5 ++++- tools/mtmd/CMakeLists.txt | 2 +- tools/perplexity/CMakeLists.txt | 5 ++++- tools/quantize/CMakeLists.txt | 5 ++++- tools/run/CMakeLists.txt | 4 +++- tools/tokenize/CMakeLists.txt | 4 +++- tools/tts/CMakeLists.txt | 5 ++++- 14 files changed, 54 insertions(+), 13 deletions(-) diff --git a/CMakeLists.txt b/CMakeLists.txt index 36a2078e4c..4720e1f1a2 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -58,6 +58,12 @@ if (MSVC) add_compile_options("$<$:/bigobj>") endif() +if (CMAKE_SYSTEM_NAME STREQUAL "iOS") + set(LLAMA_TOOLS_INSTALL_DEFAULT OFF) +else() + set(LLAMA_TOOLS_INSTALL_DEFAULT ${LLAMA_STANDALONE}) +endif() + # # option list # @@ -82,6 +88,7 @@ option(LLAMA_BUILD_TESTS "llama: build tests" ${LLAMA_STANDALONE}) option(LLAMA_BUILD_TOOLS "llama: build tools" ${LLAMA_STANDALONE}) option(LLAMA_BUILD_EXAMPLES "llama: build examples" ${LLAMA_STANDALONE}) option(LLAMA_BUILD_SERVER "llama: build server example" ${LLAMA_STANDALONE}) +option(LLAMA_TOOLS_INSTALL "llama: install tools" ${LLAMA_TOOLS_INSTALL_DEFAULT}) # 3rd party libs option(LLAMA_CURL "llama: use libcurl to download model from an URL" ON) diff --git a/tools/batched-bench/CMakeLists.txt b/tools/batched-bench/CMakeLists.txt index 68ad707f32..4a46b57a52 100644 --- a/tools/batched-bench/CMakeLists.txt +++ b/tools/batched-bench/CMakeLists.txt @@ -1,5 +1,8 @@ set(TARGET llama-batched-bench) add_executable(${TARGET} batched-bench.cpp) -install(TARGETS ${TARGET} RUNTIME) target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT}) target_compile_features(${TARGET} PRIVATE cxx_std_17) + +if(LLAMA_TOOLS_INSTALL) + install(TARGETS ${TARGET} RUNTIME) +endif() diff --git a/tools/cvector-generator/CMakeLists.txt b/tools/cvector-generator/CMakeLists.txt index 49ad9561c8..baeb4d00c1 100644 --- a/tools/cvector-generator/CMakeLists.txt +++ b/tools/cvector-generator/CMakeLists.txt @@ -1,5 +1,8 @@ set(TARGET llama-cvector-generator) add_executable(${TARGET} cvector-generator.cpp pca.hpp) -install(TARGETS ${TARGET} RUNTIME) target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT}) target_compile_features(${TARGET} PRIVATE cxx_std_17) + +if(LLAMA_TOOLS_INSTALL) + install(TARGETS ${TARGET} RUNTIME) +endif() diff --git a/tools/export-lora/CMakeLists.txt b/tools/export-lora/CMakeLists.txt index 310455787a..cddfa77f02 100644 --- a/tools/export-lora/CMakeLists.txt +++ b/tools/export-lora/CMakeLists.txt @@ -1,5 +1,8 @@ set(TARGET llama-export-lora) add_executable(${TARGET} export-lora.cpp) -install(TARGETS ${TARGET} RUNTIME) target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT}) target_compile_features(${TARGET} PRIVATE cxx_std_17) + +if(LLAMA_TOOLS_INSTALL) + install(TARGETS ${TARGET} RUNTIME) +endif() diff --git a/tools/gguf-split/CMakeLists.txt b/tools/gguf-split/CMakeLists.txt index c407e2f0af..9b2125087c 100644 --- a/tools/gguf-split/CMakeLists.txt +++ b/tools/gguf-split/CMakeLists.txt @@ -1,5 +1,8 @@ set(TARGET llama-gguf-split) add_executable(${TARGET} gguf-split.cpp) -install(TARGETS ${TARGET} RUNTIME) target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT}) target_compile_features(${TARGET} PRIVATE cxx_std_17) + +if(LLAMA_TOOLS_INSTALL) + install(TARGETS ${TARGET} RUNTIME) +endif() diff --git a/tools/imatrix/CMakeLists.txt b/tools/imatrix/CMakeLists.txt index 412696c47c..22f2fe5fdb 100644 --- a/tools/imatrix/CMakeLists.txt +++ b/tools/imatrix/CMakeLists.txt @@ -1,5 +1,8 @@ set(TARGET llama-imatrix) add_executable(${TARGET} imatrix.cpp) -install(TARGETS ${TARGET} RUNTIME) target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT}) target_compile_features(${TARGET} PRIVATE cxx_std_17) + +if(LLAMA_TOOLS_INSTALL) + install(TARGETS ${TARGET} RUNTIME) +endif() diff --git a/tools/llama-bench/CMakeLists.txt b/tools/llama-bench/CMakeLists.txt index 17e3b9b87b..b8543a9692 100644 --- a/tools/llama-bench/CMakeLists.txt +++ b/tools/llama-bench/CMakeLists.txt @@ -1,5 +1,8 @@ set(TARGET llama-bench) add_executable(${TARGET} llama-bench.cpp) -install(TARGETS ${TARGET} RUNTIME) target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT}) target_compile_features(${TARGET} PRIVATE cxx_std_17) + +if(LLAMA_TOOLS_INSTALL) + install(TARGETS ${TARGET} RUNTIME) +endif() diff --git a/tools/main/CMakeLists.txt b/tools/main/CMakeLists.txt index af3d9150f8..8f8e9d444c 100644 --- a/tools/main/CMakeLists.txt +++ b/tools/main/CMakeLists.txt @@ -1,5 +1,8 @@ set(TARGET llama-cli) add_executable(${TARGET} main.cpp) -install(TARGETS ${TARGET} RUNTIME) target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT}) target_compile_features(${TARGET} PRIVATE cxx_std_17) + +if(LLAMA_TOOLS_INSTALL) + install(TARGETS ${TARGET} RUNTIME) +endif() diff --git a/tools/mtmd/CMakeLists.txt b/tools/mtmd/CMakeLists.txt index 0979488560..2381012a0d 100644 --- a/tools/mtmd/CMakeLists.txt +++ b/tools/mtmd/CMakeLists.txt @@ -55,7 +55,7 @@ add_executable(llama-qwen2vl-cli deprecation-warning.cpp) set(TARGET llama-mtmd-cli) add_executable (${TARGET} mtmd-cli.cpp) set_target_properties (${TARGET} PROPERTIES OUTPUT_NAME llama-mtmd-cli) -if(NOT CMAKE_SYSTEM_NAME STREQUAL "iOS") +if(LLAMA_TOOLS_INSTALL) install(TARGETS ${TARGET} RUNTIME) endif() target_link_libraries (${TARGET} PRIVATE common mtmd Threads::Threads) diff --git a/tools/perplexity/CMakeLists.txt b/tools/perplexity/CMakeLists.txt index 3e68640933..12b28b2be4 100644 --- a/tools/perplexity/CMakeLists.txt +++ b/tools/perplexity/CMakeLists.txt @@ -1,5 +1,8 @@ set(TARGET llama-perplexity) add_executable(${TARGET} perplexity.cpp) -install(TARGETS ${TARGET} RUNTIME) target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT}) target_compile_features(${TARGET} PRIVATE cxx_std_17) + +if(LLAMA_TOOLS_INSTALL) + install(TARGETS ${TARGET} RUNTIME) +endif() diff --git a/tools/quantize/CMakeLists.txt b/tools/quantize/CMakeLists.txt index 47e5cbe30c..bd9ddbd67d 100644 --- a/tools/quantize/CMakeLists.txt +++ b/tools/quantize/CMakeLists.txt @@ -1,6 +1,9 @@ set(TARGET llama-quantize) add_executable(${TARGET} quantize.cpp) -install(TARGETS ${TARGET} RUNTIME) target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT}) target_include_directories(${TARGET} PRIVATE ../../common) target_compile_features(${TARGET} PRIVATE cxx_std_17) + +if(LLAMA_TOOLS_INSTALL) + install(TARGETS ${TARGET} RUNTIME) +endif() diff --git a/tools/run/CMakeLists.txt b/tools/run/CMakeLists.txt index d018959698..e52294ccc0 100644 --- a/tools/run/CMakeLists.txt +++ b/tools/run/CMakeLists.txt @@ -10,6 +10,8 @@ if (LLAMA_CURL) set(LLAMA_RUN_EXTRA_LIBS ${LLAMA_RUN_EXTRA_LIBS} ${CURL_LIBRARIES}) endif () -install(TARGETS ${TARGET} RUNTIME) +if(LLAMA_TOOLS_INSTALL) + install(TARGETS ${TARGET} RUNTIME) +endif() target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT} ${LLAMA_RUN_EXTRA_LIBS}) target_compile_features(${TARGET} PRIVATE cxx_std_17) diff --git a/tools/tokenize/CMakeLists.txt b/tools/tokenize/CMakeLists.txt index 1690b53e5d..feed9a1062 100644 --- a/tools/tokenize/CMakeLists.txt +++ b/tools/tokenize/CMakeLists.txt @@ -1,5 +1,7 @@ set(TARGET llama-tokenize) add_executable(${TARGET} tokenize.cpp) -install(TARGETS ${TARGET} RUNTIME) +if(LLAMA_TOOLS_INSTALL) + install(TARGETS ${TARGET} RUNTIME) +endif() target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT}) target_compile_features(${TARGET} PRIVATE cxx_std_17) diff --git a/tools/tts/CMakeLists.txt b/tools/tts/CMakeLists.txt index c72bd814c3..76320d4c2d 100644 --- a/tools/tts/CMakeLists.txt +++ b/tools/tts/CMakeLists.txt @@ -1,5 +1,8 @@ set(TARGET llama-tts) add_executable(${TARGET} tts.cpp) -install(TARGETS ${TARGET} RUNTIME) target_link_libraries(${TARGET} PRIVATE llama common ${CMAKE_THREAD_LIBS_INIT}) target_compile_features(${TARGET} PRIVATE cxx_std_17) + +if(LLAMA_TOOLS_INSTALL) + install(TARGETS ${TARGET} RUNTIME) +endif() From 51abc96bdc52ba8cd6ad78dcf12ed9a041d7b442 Mon Sep 17 00:00:00 2001 From: Daniel Bevenius Date: Tue, 16 Sep 2025 05:57:16 +0200 Subject: [PATCH 10/52] ci : update macos-latest* jobs to use macos-latest (#15938) * ci : update macos-latest* jobs to use macos-latest This commit updates the jobs that are named macos-latest* to use the macos-latest label instead explicit versions. The motivation for this is that there is currently a mixuture of versions in this workflow and there are jobs that are failing because they require a newer version. Refs: https://github.com/ggml-org/llama.cpp/actions/runs/17644792595/job/50140010907#step:5:1759 * ci : add xcodebuild -downloadPlatform iOS command --- .github/workflows/build.yml | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 1bd35627da..9a668bf8dd 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -56,7 +56,7 @@ env: jobs: macOS-latest-cmake-arm64: - runs-on: macos-14 + runs-on: macos-latest steps: - name: Clone @@ -97,7 +97,7 @@ jobs: ctest -L 'main|curl' --verbose --timeout 900 macOS-latest-cmake-x64: - runs-on: macos-13 + runs-on: macos-latest steps: - name: Clone @@ -138,7 +138,7 @@ jobs: ctest -L main --verbose --timeout 900 macOS-latest-cmake-arm64-webgpu: - runs-on: macos-14 + runs-on: latest steps: - name: Clone @@ -1171,7 +1171,9 @@ jobs: ./build-xcframework.sh - name: Build Xcode project - run: xcodebuild -project examples/llama.swiftui/llama.swiftui.xcodeproj -scheme llama.swiftui -sdk iphoneos CODE_SIGNING_REQUIRED=NO CODE_SIGN_IDENTITY= -destination 'generic/platform=iOS' FRAMEWORK_FOLDER_PATH=./build-ios build + run: | + xcodebuild -downloadPlatform iOS + xcodebuild -project examples/llama.swiftui/llama.swiftui.xcodeproj -scheme llama.swiftui -sdk iphoneos CODE_SIGNING_REQUIRED=NO CODE_SIGN_IDENTITY= -destination 'generic/platform=iOS' FRAMEWORK_FOLDER_PATH=./build-ios build android-build: runs-on: ubuntu-latest From f1fbffb5c0b34b2a68febb7da3fd0f8333f1ed4c Mon Sep 17 00:00:00 2001 From: Bowen Han Date: Mon, 15 Sep 2025 23:59:19 -0700 Subject: [PATCH 11/52] fix: apply clang-format to CUDA macros (#16017) clang-format previously broke long CUDA macros (e.g. __launch_bounds__) into unreadable line breaks inside template declarations, such as: template __launch_bounds__(nwarps*ggml_cuda_get_physical_warp_size(), 1) This change adjusts formatting rules so that CUDA macros remain consistent and aligned with the surrounding template syntax. --- .clang-format | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/.clang-format b/.clang-format index 117e6986f6..742723fc8f 100644 --- a/.clang-format +++ b/.clang-format @@ -22,6 +22,13 @@ AllowShortIfStatementsOnASingleLine: Never AllowShortLambdasOnASingleLine: Inline AllowShortLoopsOnASingleLine: false AlwaysBreakBeforeMultilineStrings: true +# Treat CUDA keywords/attributes as "attribute macros" and avoid breaking lines inside them +AttributeMacros: + - __host__ + - __device__ + - __global__ + - __forceinline__ + - __launch_bounds__ BinPackArguments: true BinPackParameters: false # OnePerLine BitFieldColonSpacing: Both From 76888d202ed2b835ae19ea9f9db6baf39e419297 Mon Sep 17 00:00:00 2001 From: Daniel Bevenius Date: Tue, 16 Sep 2025 13:41:38 +0200 Subject: [PATCH 12/52] ci : upload xcframework artifact from ios-xcode-build job (#16010) This commit updates the github workflows build.yml file to include steps for uploading and downloading the xcframework artifact. The macos-latest-swift job now depends on the ios-xcode-build job and downloads the xcframework artifact produced by it. The motivation for this changes is that it takes a long time to build the xcframework and we are currently doing this twice in the workflow. With this change, we only build it once and reuse the artifact. --- .github/workflows/build.yml | 19 ++++++++++++++----- 1 file changed, 14 insertions(+), 5 deletions(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 9a668bf8dd..7f2dccde0c 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -711,6 +711,7 @@ jobs: macOS-latest-swift: runs-on: macos-latest + needs: ios-xcode-build strategy: matrix: @@ -727,6 +728,12 @@ jobs: key: macOS-latest-swift evict-old-files: 1d + - name: Download xcframework artifact + uses: actions/download-artifact@v4 + with: + name: llama-xcframework + path: build-apple/llama.xcframework/ + - name: Dependencies id: depends continue-on-error: true @@ -748,11 +755,6 @@ jobs: -DCMAKE_OSX_ARCHITECTURES="arm64;x86_64" cmake --build build --config Release -j $(sysctl -n hw.logicalcpu) - - name: xcodebuild for swift package - id: xcodebuild - run: | - ./build-xcframework.sh - windows-msys2: runs-on: windows-2025 @@ -1170,6 +1172,13 @@ jobs: run: | ./build-xcframework.sh + - name: Upload xcframework artifact + uses: actions/upload-artifact@v4 + with: + name: llama-xcframework + path: build-apple/llama.xcframework/ + retention-days: 1 + - name: Build Xcode project run: | xcodebuild -downloadPlatform iOS From 3913f8730ec6d6245480affc30ae3049107956f4 Mon Sep 17 00:00:00 2001 From: Daniel Bevenius Date: Tue, 16 Sep 2025 15:25:57 +0200 Subject: [PATCH 13/52] ggml : fix padding in timestep embedding kernels (#15932) * ggml : remove adding extra dim timestep embedding This commit updates the ggml_timestep_embedding function to no longer add an extra dimension when the specified dimension is odd. The motivation for this change is that this introduces an unnecessary dimension when the dimension is odd, which caused an issue in the kernels which were not expecting this extra dimension and it resulted in uninitialized memory for the second to last dimension. * ggml-cuda : fix padding in timestep embedding kernel This commit removes the zeroing out of the last dimension now that we are not adding the extra padding dimension. * ggml-metal : fix padding in timestep embedding kernel This commit fixes the zero padding for odd dimensions in the timestep embedding kernel * ggml-opencl : fix padding in timestep embedding kernel This commit fixes the zero padding for odd dimensions in the timestep embedding kernel. * ggml-sycl : fix padding in timestep embedding kernel This commit fixes the zero padding for odd dimensions in the timestep embedding kernel. * ggml-vulkan : fix padding in timestep embedding kernel This commit fixes the zero padding for odd dimensions in the timestep embedding kernel. * ggml-cpu : fix padding in timestep embedding function This commit removes the zeroing out of the last dimension now that we are not adding the extra padding dimension. --- ggml/src/ggml-cpu/ops.cpp | 1 - ggml/src/ggml-cuda/tsembd.cu | 6 +++--- ggml/src/ggml-metal/ggml-metal.metal | 2 +- ggml/src/ggml-opencl/kernels/tsembd.cl | 4 ++-- ggml/src/ggml-sycl/tsembd.cpp | 7 ++++--- .../src/ggml-vulkan/vulkan-shaders/timestep_embedding.comp | 7 ++++--- ggml/src/ggml.c | 6 +----- 7 files changed, 15 insertions(+), 18 deletions(-) diff --git a/ggml/src/ggml-cpu/ops.cpp b/ggml/src/ggml-cpu/ops.cpp index 212e52ef6a..c4824d145a 100644 --- a/ggml/src/ggml-cpu/ops.cpp +++ b/ggml/src/ggml-cpu/ops.cpp @@ -8599,7 +8599,6 @@ static void ggml_compute_forward_timestep_embedding_f32( } if (dim % 2 != 0 && ith == 0) { embed_data[2 * half] = 0.f; - embed_data[dim] = 0.f; } } } diff --git a/ggml/src/ggml-cuda/tsembd.cu b/ggml/src/ggml-cuda/tsembd.cu index 153ddbcda9..b91a26fc80 100644 --- a/ggml/src/ggml-cuda/tsembd.cu +++ b/ggml/src/ggml-cuda/tsembd.cu @@ -7,11 +7,11 @@ static __global__ void timestep_embedding_f32(const float * timesteps, float * d int j = threadIdx.x + blockIdx.x * blockDim.x; float * embed_data = (float *)((char *)dst + i*nb1); - if (dim % 2 != 0 && j == ((dim + 1) / 2)) { - embed_data[dim] = 0.f; + int half = dim / 2; + if (dim % 2 != 0 && j == half) { + embed_data[2 * half] = 0.f; } - int half = dim / 2; if (j >= half) { return; } diff --git a/ggml/src/ggml-metal/ggml-metal.metal b/ggml/src/ggml-metal/ggml-metal.metal index 4314c9cc93..5057e264f6 100644 --- a/ggml/src/ggml-metal/ggml-metal.metal +++ b/ggml/src/ggml-metal/ggml-metal.metal @@ -4167,7 +4167,7 @@ kernel void kernel_timestep_embedding_f32( } if (args.dim % 2 != 0 && tpitg.x == 0) { - embed_data[args.dim] = 0.f; + embed_data[2 * half_] = 0.f; } } diff --git a/ggml/src/ggml-opencl/kernels/tsembd.cl b/ggml/src/ggml-opencl/kernels/tsembd.cl index 4b1107f70b..21444bd958 100644 --- a/ggml/src/ggml-opencl/kernels/tsembd.cl +++ b/ggml/src/ggml-opencl/kernels/tsembd.cl @@ -26,8 +26,8 @@ kernel void kernel_timestep_embedding( local_half_dim = logical_dim / 2; local_embed_data_ptr = (global float *)((global char *)local_dst_output_base_ptr + local_i * dst_nb1_bytes); - if (logical_dim % 2 != 0 && local_j == ((logical_dim + 1) / 2)) { - local_embed_data_ptr[logical_dim] = 0.0f; + if (logical_dim % 2 != 0 && local_j == local_half_dim) { + local_embed_data_ptr[2 * local_half_dim] = 0.0f; } if (local_j >= local_half_dim) { diff --git a/ggml/src/ggml-sycl/tsembd.cpp b/ggml/src/ggml-sycl/tsembd.cpp index f6ca626ea7..f2003794d3 100644 --- a/ggml/src/ggml-sycl/tsembd.cpp +++ b/ggml/src/ggml-sycl/tsembd.cpp @@ -21,11 +21,12 @@ static void timestep_embedding_f32( int j = item_ct1.get_local_id(2) + item_ct1.get_group(2) * item_ct1.get_local_range(2); float * embed_data = (float *)((char *)dst + i*nb1); - if (dim % 2 != 0 && j == ((dim + 1) / 2)) { - embed_data[dim] = 0.f; + int half = dim / 2; + + if (dim % 2 != 0 && j == half) { + embed_data[2 * half] = 0.f; } - int half = dim / 2; if (j >= half) { return; } diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/timestep_embedding.comp b/ggml/src/ggml-vulkan/vulkan-shaders/timestep_embedding.comp index 79e065a931..ce8e09442d 100644 --- a/ggml/src/ggml-vulkan/vulkan-shaders/timestep_embedding.comp +++ b/ggml/src/ggml-vulkan/vulkan-shaders/timestep_embedding.comp @@ -24,11 +24,12 @@ void main() { const uint j = gl_GlobalInvocationID.x; const uint d_offset = i * p.nb1; - if (p.dim % 2 != 0 && j == ((p.dim + 1) / 2)) { - data_d[d_offset + p.dim] = 0.f; + const uint half_dim = p.dim / 2; + + if (p.dim % 2 != 0 && j == half_dim) { + data_d[d_offset + 2 * half_dim] = 0.f; } - const uint half_dim = p.dim / 2; if (j >= half_dim) { return; } diff --git a/ggml/src/ggml.c b/ggml/src/ggml.c index 50dc1aa24f..3584827dca 100644 --- a/ggml/src/ggml.c +++ b/ggml/src/ggml.c @@ -4923,12 +4923,8 @@ struct ggml_tensor * ggml_timestep_embedding( struct ggml_tensor * timesteps, int dim, int max_period) { - int actual_dim = dim; - if (dim % 2 != 0) { - actual_dim = dim + 1; - } - struct ggml_tensor * result = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, actual_dim, timesteps->ne[0]); + struct ggml_tensor * result = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, dim, timesteps->ne[0]); ggml_set_op_params_i32(result, 0, dim); ggml_set_op_params_i32(result, 1, max_period); From 77475530b8bbea3bf578632507e1284cdfe2c8c0 Mon Sep 17 00:00:00 2001 From: Daniel Bevenius Date: Tue, 16 Sep 2025 15:27:52 +0200 Subject: [PATCH 14/52] ci : use macos-latest for arm64 webgpu build (#16029) This commit updates the runs-on field for the macOS arm64 webgpu build job to use macos-latest instead of just latest. The motivation for this is that this job can wait for a runner to pick up the job for a very long time, sometimes over 7 hours. This is an attempt to see if this change can help reduce the wait time. Refs: https://github.com/ggml-org/llama.cpp/actions/runs/17754163447/job/50454257570?pr=16004 --- .github/workflows/build.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 7f2dccde0c..0a00c85b73 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -138,7 +138,7 @@ jobs: ctest -L main --verbose --timeout 900 macOS-latest-cmake-arm64-webgpu: - runs-on: latest + runs-on: macos-latest steps: - name: Clone From 8ff206097c2bf3ca1c7aa95f9d6db779fc7bdd68 Mon Sep 17 00:00:00 2001 From: jacekpoplawski <67507230+jacekpoplawski@users.noreply.github.com> Date: Tue, 16 Sep 2025 16:17:08 +0200 Subject: [PATCH 15/52] llama-bench: add --n-cpu-moe support (#15952) * llama-bench: add --n-cpu-moe support Support --n-cpu-moe in llama-bench the same way it is supported by llama-server. --- common/arg.cpp | 8 +-- common/common.h | 14 +++++ tools/llama-bench/llama-bench.cpp | 87 +++++++++++++++++++++++++------ 3 files changed, 90 insertions(+), 19 deletions(-) diff --git a/common/arg.cpp b/common/arg.cpp index 19189d8f9f..9fd8858e82 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -2548,7 +2548,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex {"--cpu-moe", "-cmoe"}, "keep all Mixture of Experts (MoE) weights in the CPU", [](common_params & params) { - params.tensor_buft_overrides.push_back({"\\.ffn_(up|down|gate)_exps", ggml_backend_cpu_buffer_type()}); + params.tensor_buft_overrides.push_back(llm_ffn_exps_cpu_override()); } ).set_env("LLAMA_ARG_CPU_MOE")); add_opt(common_arg( @@ -2561,7 +2561,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex for (int i = 0; i < value; ++i) { // keep strings alive and avoid leaking memory by storing them in a static vector static std::list buft_overrides; - buft_overrides.push_back(string_format("blk\\.%d\\.ffn_(up|down|gate)_exps", i)); + buft_overrides.push_back(llm_ffn_exps_block_regex(i)); params.tensor_buft_overrides.push_back({buft_overrides.back().c_str(), ggml_backend_cpu_buffer_type()}); } } @@ -2570,7 +2570,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex {"--cpu-moe-draft", "-cmoed"}, "keep all Mixture of Experts (MoE) weights in the CPU for the draft model", [](common_params & params) { - params.speculative.tensor_buft_overrides.push_back({"\\.ffn_(up|down|gate)_exps", ggml_backend_cpu_buffer_type()}); + params.speculative.tensor_buft_overrides.push_back(llm_ffn_exps_cpu_override()); } ).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_CPU_MOE_DRAFT")); add_opt(common_arg( @@ -2582,7 +2582,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex } for (int i = 0; i < value; ++i) { static std::list buft_overrides_draft; - buft_overrides_draft.push_back(string_format("blk\\.%d\\.ffn_(up|down|gate)_exps", i)); + buft_overrides_draft.push_back(llm_ffn_exps_block_regex(i)); params.speculative.tensor_buft_overrides.push_back({buft_overrides_draft.back().c_str(), ggml_backend_cpu_buffer_type()}); } } diff --git a/common/common.h b/common/common.h index 5063d73f96..83d44dbaa7 100644 --- a/common/common.h +++ b/common/common.h @@ -734,6 +734,20 @@ const char * const LLM_KV_SPLIT_TENSORS_COUNT = "split.tensors.count"; } +// +// MoE utils +// + +const char * const LLM_FFN_EXPS_REGEX = "\\.ffn_(up|down|gate)_exps"; + +static std::string llm_ffn_exps_block_regex(int idx) { + return string_format("blk\\.%d%s", idx, LLM_FFN_EXPS_REGEX); +} + +static llama_model_tensor_buft_override llm_ffn_exps_cpu_override() { + return { LLM_FFN_EXPS_REGEX, ggml_backend_cpu_buffer_type() }; +} + // // training utils // diff --git a/tools/llama-bench/llama-bench.cpp b/tools/llama-bench/llama-bench.cpp index 95f662a297..ad47bf144f 100644 --- a/tools/llama-bench/llama-bench.cpp +++ b/tools/llama-bench/llama-bench.cpp @@ -250,6 +250,7 @@ struct cmd_params { std::vector cpu_strict; std::vector poll; std::vector n_gpu_layers; + std::vector n_cpu_moe; std::vector rpc_servers; std::vector split_mode; std::vector main_gpu; @@ -286,6 +287,7 @@ static const cmd_params cmd_params_defaults = { /* cpu_strict */ { false }, /* poll */ { 50 }, /* n_gpu_layers */ { 99 }, + /* n_cpu_moe */ { 0 }, /* rpc_servers */ { "" }, /* split_mode */ { LLAMA_SPLIT_MODE_LAYER }, /* main_gpu */ { 0 }, @@ -353,6 +355,8 @@ static void print_usage(int /* argc */, char ** argv) { printf(" --poll <0...100> (default: %s)\n", join(cmd_params_defaults.poll, ",").c_str()); printf(" -ngl, --n-gpu-layers (default: %s)\n", join(cmd_params_defaults.n_gpu_layers, ",").c_str()); + printf(" -ncmoe, --n-cpu-moe (default: %s)\n", + join(cmd_params_defaults.n_cpu_moe, ",").c_str()); if (llama_supports_rpc()) { printf(" -rpc, --rpc (default: %s)\n", join(cmd_params_defaults.rpc_servers, ",").c_str()); @@ -564,6 +568,13 @@ static cmd_params parse_cmd_params(int argc, char ** argv) { } auto p = parse_int_range(argv[i]); params.n_gpu_layers.insert(params.n_gpu_layers.end(), p.begin(), p.end()); + } else if (arg == "-ncmoe" || arg == "--n-cpu-moe") { + if (++i >= argc) { + invalid_param = true; + break; + } + auto p = parse_int_range(argv[i]); + params.n_cpu_moe.insert(params.n_cpu_moe.end(), p.begin(), p.end()); } else if (llama_supports_rpc() && (arg == "-rpc" || arg == "--rpc")) { if (++i >= argc) { invalid_param = true; @@ -841,6 +852,9 @@ static cmd_params parse_cmd_params(int argc, char ** argv) { if (params.n_gpu_layers.empty()) { params.n_gpu_layers = cmd_params_defaults.n_gpu_layers; } + if (params.n_cpu_moe.empty()) { + params.n_cpu_moe = cmd_params_defaults.n_cpu_moe; + } if (params.rpc_servers.empty()) { params.rpc_servers = cmd_params_defaults.rpc_servers; } @@ -901,6 +915,7 @@ struct cmd_params_instance { bool cpu_strict; int poll; int n_gpu_layers; + int n_cpu_moe; std::string rpc_servers_str; llama_split_mode split_mode; int main_gpu; @@ -973,20 +988,50 @@ struct cmd_params_instance { mparams.tensor_split = tensor_split.data(); mparams.use_mmap = use_mmap; - if (tensor_buft_overrides.empty()) { - mparams.tensor_buft_overrides = nullptr; + if (n_cpu_moe <= 0) { + if (tensor_buft_overrides.empty()) { + mparams.tensor_buft_overrides = nullptr; + } else { + GGML_ASSERT(tensor_buft_overrides.back().pattern == nullptr && + "Tensor buffer overrides not terminated with empty pattern"); + mparams.tensor_buft_overrides = tensor_buft_overrides.data(); + } } else { - GGML_ASSERT(tensor_buft_overrides.back().pattern == nullptr && "Tensor buffer overrides not terminated with empty pattern"); - mparams.tensor_buft_overrides = tensor_buft_overrides.data(); + static std::vector merged; + static std::vector patterns; + + merged.clear(); + patterns.clear(); + + auto first = tensor_buft_overrides.begin(); + auto last = tensor_buft_overrides.end(); + if (first != last && (last - 1)->pattern == nullptr) { + --last; + } + merged.insert(merged.end(), first, last); + + patterns.reserve((size_t) n_cpu_moe); + merged.reserve(merged.size() + (size_t) n_cpu_moe + 1); + + for (int i = 0; i < n_cpu_moe; ++i) { + patterns.push_back(llm_ffn_exps_block_regex(i)); + merged.push_back({ patterns.back().c_str(), + ggml_backend_cpu_buffer_type() }); + } + + merged.push_back({ nullptr, nullptr }); + + mparams.tensor_buft_overrides = merged.data(); } return mparams; } bool equal_mparams(const cmd_params_instance & other) const { - return model == other.model && n_gpu_layers == other.n_gpu_layers && rpc_servers_str == other.rpc_servers_str && - split_mode == other.split_mode && main_gpu == other.main_gpu && use_mmap == other.use_mmap && - tensor_split == other.tensor_split && vec_tensor_buft_override_equal(tensor_buft_overrides, other.tensor_buft_overrides); + return model == other.model && n_gpu_layers == other.n_gpu_layers && n_cpu_moe == other.n_cpu_moe && + rpc_servers_str == other.rpc_servers_str && split_mode == other.split_mode && + main_gpu == other.main_gpu && use_mmap == other.use_mmap && tensor_split == other.tensor_split && + vec_tensor_buft_override_equal(tensor_buft_overrides, other.tensor_buft_overrides); } llama_context_params to_llama_cparams() const { @@ -1014,6 +1059,7 @@ static std::vector get_cmd_params_instances(const cmd_param // clang-format off for (const auto & m : params.model) for (const auto & nl : params.n_gpu_layers) + for (const auto & ncmoe : params.n_cpu_moe) for (const auto & rpc : params.rpc_servers) for (const auto & sm : params.split_mode) for (const auto & mg : params.main_gpu) @@ -1051,6 +1097,7 @@ static std::vector get_cmd_params_instances(const cmd_param /* .cpu_strict = */ cs, /* .poll = */ pl, /* .n_gpu_layers = */ nl, + /* .n_cpu_moe = */ ncmoe, /* .rpc_servers = */ rpc, /* .split_mode = */ sm, /* .main_gpu = */ mg, @@ -1083,6 +1130,7 @@ static std::vector get_cmd_params_instances(const cmd_param /* .cpu_strict = */ cs, /* .poll = */ pl, /* .n_gpu_layers = */ nl, + /* .n_cpu_moe = */ ncmoe, /* .rpc_servers = */ rpc, /* .split_mode = */ sm, /* .main_gpu = */ mg, @@ -1115,6 +1163,7 @@ static std::vector get_cmd_params_instances(const cmd_param /* .cpu_strict = */ cs, /* .poll = */ pl, /* .n_gpu_layers = */ nl, + /* .n_cpu_moe = */ ncmoe, /* .rpc_servers = */ rpc, /* .split_mode = */ sm, /* .main_gpu = */ mg, @@ -1152,6 +1201,7 @@ struct test { ggml_type type_k; ggml_type type_v; int n_gpu_layers; + int n_cpu_moe; llama_split_mode split_mode; int main_gpu; bool no_kv_offload; @@ -1186,6 +1236,7 @@ struct test { type_k = inst.type_k; type_v = inst.type_v; n_gpu_layers = inst.n_gpu_layers; + n_cpu_moe = inst.n_cpu_moe; split_mode = inst.split_mode; main_gpu = inst.main_gpu; no_kv_offload = inst.no_kv_offload; @@ -1236,12 +1287,14 @@ struct test { static const std::vector & get_fields() { static const std::vector fields = { - "build_commit", "build_number", "cpu_info", "gpu_info", "backends", "model_filename", - "model_type", "model_size", "model_n_params", "n_batch", "n_ubatch", "n_threads", - "cpu_mask", "cpu_strict", "poll", "type_k", "type_v", "n_gpu_layers", - "split_mode", "main_gpu", "no_kv_offload", "flash_attn", "tensor_split", "tensor_buft_overrides", - "use_mmap", "embeddings", "no_op_offload", "n_prompt", "n_gen", "n_depth", "test_time", - "avg_ns", "stddev_ns", "avg_ts", "stddev_ts", + "build_commit", "build_number", "cpu_info", "gpu_info", "backends", + "model_filename", "model_type", "model_size", "model_n_params", "n_batch", + "n_ubatch", "n_threads", "cpu_mask", "cpu_strict", "poll", + "type_k", "type_v", "n_gpu_layers", "n_cpu_moe", "split_mode", + "main_gpu", "no_kv_offload", "flash_attn", "tensor_split", "tensor_buft_overrides", + "use_mmap", "embeddings", "no_op_offload", "n_prompt", "n_gen", + "n_depth", "test_time", "avg_ns", "stddev_ns", "avg_ts", + "stddev_ts" }; return fields; } @@ -1251,8 +1304,8 @@ struct test { static field_type get_field_type(const std::string & field) { if (field == "build_number" || field == "n_batch" || field == "n_ubatch" || field == "n_threads" || field == "poll" || field == "model_size" || field == "model_n_params" || field == "n_gpu_layers" || - field == "main_gpu" || field == "n_prompt" || field == "n_gen" || field == "n_depth" || - field == "avg_ns" || field == "stddev_ns" || field == "no_op_offload") { + field == "main_gpu" || field == "n_prompt" || field == "n_gen" || field == "n_depth" || field == "avg_ns" || + field == "stddev_ns" || field == "no_op_offload" || field == "n_cpu_moe") { return INT; } if (field == "f16_kv" || field == "no_kv_offload" || field == "cpu_strict" || field == "flash_attn" || @@ -1320,6 +1373,7 @@ struct test { ggml_type_name(type_k), ggml_type_name(type_v), std::to_string(n_gpu_layers), + std::to_string(n_cpu_moe), split_mode_str(split_mode), std::to_string(main_gpu), std::to_string(no_kv_offload), @@ -1568,6 +1622,9 @@ struct markdown_printer : public printer { if (!is_cpu_backend) { fields.emplace_back("n_gpu_layers"); } + if (params.n_cpu_moe.size() > 1) { + fields.emplace_back("n_cpu_moe"); + } if (params.n_threads.size() > 1 || params.n_threads != cmd_params_defaults.n_threads || is_cpu_backend) { fields.emplace_back("n_threads"); } From d5fabe3682de515fd09d6c981f7a0d1b75614455 Mon Sep 17 00:00:00 2001 From: Chenguang Li <757486878@qq.com> Date: Wed, 17 Sep 2025 14:33:08 +0800 Subject: [PATCH 16/52] CANN: Optimize ggml_cann_set_device (#15935) * CANN: Fix ggml_cann_set_device to avoid redundant device switches - Added a check to skip aclrtSetDevice if the current device is already set. - Prevents unnecessary context switches while keeping thread/device consistency. * CANN: add device default id --- ggml/src/ggml-cann/common.h | 5 ++++- ggml/src/ggml-cann/ggml-cann.cpp | 12 ++++++------ 2 files changed, 10 insertions(+), 7 deletions(-) diff --git a/ggml/src/ggml-cann/common.h b/ggml/src/ggml-cann/common.h index c5fce8dc91..b707b84359 100755 --- a/ggml/src/ggml-cann/common.h +++ b/ggml/src/ggml-cann/common.h @@ -526,7 +526,10 @@ struct ggml_backend_cann_context { */ aclrtStream stream(int stream) { if (streams[stream] == nullptr) { - ggml_cann_set_device(device); + // If the device is not set here, destroying the stream later may cause a mismatch + // between the thread contexts where the stream was created and destroyed. + // However, I printed the device_id, thread_id, and stream, and they are all consistent. + ACL_CHECK(aclrtSetDevice(device)); ACL_CHECK(aclrtCreateStream(&streams[stream])); } return streams[stream]; diff --git a/ggml/src/ggml-cann/ggml-cann.cpp b/ggml/src/ggml-cann/ggml-cann.cpp index 19a18a281d..56d82b4af3 100755 --- a/ggml/src/ggml-cann/ggml-cann.cpp +++ b/ggml/src/ggml-cann/ggml-cann.cpp @@ -75,13 +75,12 @@ * @param device The device ID to set. */ void ggml_cann_set_device(const int32_t device) { - // TODO: uncomment these lines after empty context has fixed. - // int current_device; - // ACL_CHECK(aclrtGetDevice(¤t_device)); + int current_device = -1; + aclrtGetDevice(¤t_device); - // if (device == current_device) { - // return; - // } + if (device == current_device) { + return; + } ACL_CHECK(aclrtSetDevice(device)); } @@ -1729,6 +1728,7 @@ static bool ggml_cann_compute_forward(ggml_backend_cann_context& ctx, ggml_cann_get_rows(ctx, dst); break; case GGML_OP_SET_ROWS: + std::cout << "lcg GGML_OP_SET_ROWS"<< std::endl; ggml_cann_set_rows(ctx, dst); break; case GGML_OP_DUP: From 85286f354813056f6c835046c0acfa3bf6ba9432 Mon Sep 17 00:00:00 2001 From: Shane A Date: Wed, 17 Sep 2025 00:01:58 -0700 Subject: [PATCH 17/52] model : add OLMo3 support (#16015) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * Add HF to gguf conversion logic for Olmo3 * Add Olmo3 implementation * Update rope comment * Fix indentation Co-authored-by: Sigbjørn Skjæret * Apply suggestion from @CISC Co-authored-by: Sigbjørn Skjæret --------- Co-authored-by: Sigbjørn Skjæret --- convert_hf_to_gguf.py | 25 +++++++++++++++++++++++ src/llama-model.cpp | 47 +++++++++++++++++++++++++++++++++++++++---- 2 files changed, 68 insertions(+), 4 deletions(-) diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py index 5a21ba2110..ce83f24695 100755 --- a/convert_hf_to_gguf.py +++ b/convert_hf_to_gguf.py @@ -6009,9 +6009,34 @@ class SeedOssModel(TextModel): @ModelBase.register("Olmo2ForCausalLM") +@ModelBase.register("Olmo3ForCausalLM") class Olmo2Model(TextModel): model_arch = gguf.MODEL_ARCH.OLMO2 + def set_gguf_parameters(self): + super().set_gguf_parameters() + + rope_scaling = self.hparams.get("rope_scaling") or {} + if rope_scaling.get("rope_type", rope_scaling.get("type")) == "yarn" and "factor" in rope_scaling: + self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.YARN) + self.gguf_writer.add_rope_scaling_factor(rope_scaling["factor"]) + self.gguf_writer.add_rope_scaling_attn_factors(rope_scaling["attention_factor"]) + self.gguf_writer.add_rope_scaling_orig_ctx_len(rope_scaling["original_max_position_embeddings"]) + + if "sliding_window" in self.hparams: + self.gguf_writer.add_sliding_window(self.hparams["sliding_window"]) + + sliding_window_pattern = [] + if "layer_types" in self.hparams: + sliding_window_pattern = [t == "sliding_attention" for t in self.hparams["layer_types"]] + else: + # Olmo2 does not use sliding window attention. + # Olmo3 defaults to using sliding window for all layers except every 4th. + for i in range(self.hparams["num_hidden_layers"]): + sliding_window_pattern.append((i + 1) % 4 != 0) + + self.gguf_writer.add_sliding_window_pattern(sliding_window_pattern) + @ModelBase.register("OlmoeForCausalLM") class OlmoeModel(TextModel): diff --git a/src/llama-model.cpp b/src/llama-model.cpp index 731e87383b..2be807a6a9 100644 --- a/src/llama-model.cpp +++ b/src/llama-model.cpp @@ -1350,6 +1350,14 @@ void llama_model::load_hparams(llama_model_loader & ml) { { ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps); + const bool found_swa = ml.get_key(LLM_KV_ATTENTION_SLIDING_WINDOW, hparams.n_swa, false); + if (found_swa && hparams.n_swa > 0) { + hparams.swa_type = LLAMA_SWA_TYPE_STANDARD; + hparams.set_swa_pattern(4); + } else { + hparams.swa_type = LLAMA_SWA_TYPE_NONE; + } + switch (hparams.n_layer) { case 16: type = LLM_TYPE_1B; break; case 32: type = LLM_TYPE_7B; break; @@ -12233,6 +12241,7 @@ struct llm_build_olmo : public llm_graph_context { } }; +template struct llm_build_olmo2 : public llm_graph_context { llm_build_olmo2(const llama_model & model, const llm_graph_params & params) : llm_graph_context(params) { const int64_t n_embd_head = hparams.n_embd_head_v; @@ -12248,7 +12257,14 @@ struct llm_build_olmo2 : public llm_graph_context { // inp_pos - contains the positions ggml_tensor * inp_pos = build_inp_pos(); - auto * inp_attn = build_attn_inp_kv(); + using inp_attn_type = std::conditional_t; + inp_attn_type * inp_attn = nullptr; + + if constexpr (iswa) { + inp_attn = build_attn_inp_kv_iswa(); + } else { + inp_attn = build_attn_inp_kv(); + } ggml_tensor * inp_out_ids = build_inp_out_ids(); @@ -12281,17 +12297,36 @@ struct llm_build_olmo2 : public llm_graph_context { Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens); Vcur = ggml_reshape_3d(ctx0, Vcur, n_embd_head, n_head_kv, n_tokens); - Qcur = ggml_rope_ext( + const bool is_swa = hparams.is_swa(il); + + if (is_swa) { + // For sliding window layers, Olmo3 use regular rope with no yarn rope scaling. + // This is achieved here by setting freq_scale and attn_factor to 1. + // We also set ext_factor to 0 to avoid a few unnecessary computations. + Qcur = ggml_rope_ext( + ctx0, Qcur, inp_pos, nullptr, + n_rot, rope_type, n_ctx_orig, freq_base, 1.0, + 0.0, 1.0, beta_fast, beta_slow + ); + + Kcur = ggml_rope_ext( + ctx0, Kcur, inp_pos, nullptr, + n_rot, rope_type, n_ctx_orig, freq_base, 1.0, + 0.0, 1.0, beta_fast, beta_slow + ); + } else { + Qcur = ggml_rope_ext( ctx0, Qcur, inp_pos, nullptr, n_rot, rope_type, n_ctx_orig, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow ); - Kcur = ggml_rope_ext( + Kcur = ggml_rope_ext( ctx0, Kcur, inp_pos, nullptr, n_rot, rope_type, n_ctx_orig, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow ); + } cb(Qcur, "Qcur", il); cb(Kcur, "Kcur", il); @@ -19131,7 +19166,11 @@ ggml_cgraph * llama_model::build_graph(const llm_graph_params & params) const { } break; case LLM_ARCH_OLMO2: { - llm = std::make_unique(*this, params); + if (hparams.swa_type == LLAMA_SWA_TYPE_STANDARD) { + llm = std::make_unique>(*this, params); + } else { + llm = std::make_unique>(*this, params); + } } break; case LLM_ARCH_OLMOE: { From 1cbd80f8cf80a817715b1ccc5680fe2a3c5172c8 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jie=20Fu=20=28=E5=82=85=E6=9D=B0=29?= Date: Wed, 17 Sep 2025 15:29:00 +0800 Subject: [PATCH 18/52] examples : support encoder-decoder models in the simple example (#16002) Signed-off-by: Jie Fu --- examples/simple/simple.cpp | 14 ++++++++++++++ 1 file changed, 14 insertions(+) diff --git a/examples/simple/simple.cpp b/examples/simple/simple.cpp index 633b87e584..d09771d104 100644 --- a/examples/simple/simple.cpp +++ b/examples/simple/simple.cpp @@ -145,6 +145,20 @@ int main(int argc, char ** argv) { llama_batch batch = llama_batch_get_one(prompt_tokens.data(), prompt_tokens.size()); + if (llama_model_has_encoder(model)) { + if (llama_encode(ctx, batch)) { + fprintf(stderr, "%s : failed to eval\n", __func__); + return 1; + } + + llama_token decoder_start_token_id = llama_model_decoder_start_token(model); + if (decoder_start_token_id == LLAMA_TOKEN_NULL) { + decoder_start_token_id = llama_vocab_bos(vocab); + } + + batch = llama_batch_get_one(&decoder_start_token_id, 1); + } + // main loop const auto t_main_start = ggml_time_us(); From 745cbcf2fe1eb88f8db615ac622f0b944d924ad6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jie=20Fu=20=28=E5=82=85=E6=9D=B0=29?= Date: Wed, 17 Sep 2025 15:30:55 +0800 Subject: [PATCH 19/52] llama-quant : fix the verification of attention layers for encoder-decoder models (#16023) Signed-off-by: Jie Fu --- src/llama-quant.cpp | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/llama-quant.cpp b/src/llama-quant.cpp index c93e8065a8..97228b2a69 100644 --- a/src/llama-quant.cpp +++ b/src/llama-quant.cpp @@ -725,7 +725,9 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std:: // attention layers have a non-zero number of kv heads int32_t n_attn_layer = 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)) { - n_attn_layer *= 3; + // now n_attn_layer is the number of attention layers in the encoder + // for each decoder block, there are 2 attention layers + n_attn_layer += 2 * model.hparams.dec_n_layer; } GGML_ASSERT((qs.n_attention_wv == n_attn_layer - pruned_attention_w) && "n_attention_wv is unexpected"); } From a91d035b901e8a9edf810f63d130ee49adf27be2 Mon Sep 17 00:00:00 2001 From: Daniel Bevenius Date: Wed, 17 Sep 2025 09:34:09 +0200 Subject: [PATCH 20/52] ci : revert back to macos-13 for macOS-latest-cmake-x64 (#16040) This commit reverts the change of the runs-on parameter for the macOS-latest-cmake-x64 job back to macos-13 that was make in Commit 51abc96bdc52ba8cd6ad78dcf12ed9a041d7b442 ("ci : update macos-latest* jobs to use macos-latest (#15938)"). The motivation for this is that using macos-latest will cause an ARM based runner to be used, and not an x64 based runner. Refs: https://github.com/ggml-org/llama.cpp/pull/15938#issuecomment-3300805127 --- .github/workflows/build.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 0a00c85b73..ff42b19f1d 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -97,7 +97,7 @@ jobs: ctest -L 'main|curl' --verbose --timeout 900 macOS-latest-cmake-x64: - runs-on: macos-latest + runs-on: macos-13 steps: - name: Clone From cb5bb6cc05119c24e7711ca2956cd0e6d409d396 Mon Sep 17 00:00:00 2001 From: Eve <139727413+netrunnereve@users.noreply.github.com> Date: Wed, 17 Sep 2025 07:35:37 +0000 Subject: [PATCH 21/52] vulkan: automatically remove unsupported devices (#15976) * remove unsupported vulkan devices * make this happen during selection instead * pass by reference --- ggml/src/ggml-vulkan/ggml-vulkan.cpp | 18 ++++++++++++++++-- 1 file changed, 16 insertions(+), 2 deletions(-) diff --git a/ggml/src/ggml-vulkan/ggml-vulkan.cpp b/ggml/src/ggml-vulkan/ggml-vulkan.cpp index 60a99dc78b..1f1136382e 100644 --- a/ggml/src/ggml-vulkan/ggml-vulkan.cpp +++ b/ggml/src/ggml-vulkan/ggml-vulkan.cpp @@ -4423,8 +4423,8 @@ static void ggml_vk_print_gpu_info(size_t idx) { static bool ggml_vk_instance_validation_ext_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); static void ggml_vk_instance_init() { if (vk_instance_initialized) { @@ -4540,7 +4540,7 @@ static void ggml_vk_instance_init() { new_driver.pNext = &new_id; devices[i].getProperties2(&new_props); - if (new_props.properties.deviceType == vk::PhysicalDeviceType::eDiscreteGpu || new_props.properties.deviceType == vk::PhysicalDeviceType::eIntegratedGpu) { + if ((new_props.properties.deviceType == vk::PhysicalDeviceType::eDiscreteGpu || new_props.properties.deviceType == vk::PhysicalDeviceType::eIntegratedGpu) && ggml_vk_device_is_supported(devices[i])) { // Check if there are two physical devices corresponding to the same GPU auto old_device = std::find_if( vk_instance.device_indices.begin(), @@ -12738,6 +12738,20 @@ static bool ggml_vk_instance_debug_utils_ext_available( UNUSED(instance_extensions); } +static bool ggml_vk_device_is_supported(const vk::PhysicalDevice & vkdev) { + VkPhysicalDeviceFeatures2 device_features2; + device_features2.sType = VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_FEATURES_2; + + VkPhysicalDeviceVulkan11Features vk11_features; + vk11_features.pNext = nullptr; + vk11_features.sType = VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_VULKAN_1_1_FEATURES; + device_features2.pNext = &vk11_features; + + vkGetPhysicalDeviceFeatures2(vkdev, &device_features2); + + return vk11_features.storageBuffer16BitAccess; +} + static bool ggml_vk_khr_cooperative_matrix_support(const vk::PhysicalDeviceProperties& props, const vk::PhysicalDeviceDriverProperties& driver_props, vk_device_architecture arch) { switch (props.vendorID) { case VK_VENDOR_ID_INTEL: From cd08fc3ecc0264b4414b68af3874a6c689ed60c1 Mon Sep 17 00:00:00 2001 From: David Ribeiro Alves Date: Wed, 17 Sep 2025 01:08:02 -0700 Subject: [PATCH 22/52] common : Fix corrupted memory error on json grammar initialization (#16038) Initalizing RESERVED_NAME in is_reserved_name() is not thread safe and leads to corrupted memory when used from multiple threads as can be seen in the asan trace below. This fixes the initialization to make it thread-safe. #0 0x000100abd018 in std::__1::pair, std::__1::allocator>, void*>*>, bool> std::__1::__hash_table, std::__1::allocator>, std::__1::hash, std::__1::allocator>>, std::__1::equal_to, std::__1::allocator>>, std::__1::allocator, std::__1::allocator>>>::__emplace_unique_key_args, std::__1::allocator>, std::__1::basic_string, std::__1::allocator> const&>(std::__1::basic_string, std::__1::allocator> const&, std::__1::basic_string, std::__1::allocator> const&) __hash_table:1565 #1 0x000100ab0320 in SchemaConverter::visit(nlohmann::json_abi_v3_12_0::basic_json, std::__1::allocator>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector>, void> const&, std::__1::basic_string, std::__1::allocator> const&) json-schema-to-grammar.cpp:802 #2 0x000100aafc48 in std::__1::__function::__func const&, common_grammar_options const&)::$_2, std::__1::allocator const&, common_grammar_options const&)::$_2>, std::__1::basic_string, std::__1::allocator> (std::__1::basic_string, std::__1::allocator> const&, nlohmann::json_abi_v3_12_0::basic_json, std::__1::allocator>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector>, void> const&)>::operator()(std::__1::basic_string, std::__1::allocator> const&, nlohmann::json_abi_v3_12_0::basic_json, std::__1::allocator>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector>, void> const&) function.h:319 #3 0x000100a2c938 in std::__1::__function::__func, std::__1::allocator>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector>, void> const&), std::__1::allocator, std::__1::allocator>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector>, void> const&)>, void (nlohmann::json_abi_v3_12_0::basic_json, std::__1::allocator>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector>, void> const&)>::operator()(nlohmann::json_abi_v3_12_0::basic_json, std::__1::allocator>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector>, void> const&) function.h:319 #4 0x000100a139f8 in foreach_function(nlohmann::json_abi_v3_12_0::basic_json, std::__1::allocator>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector>, void> const&, std::__1::function, std::__1::allocator>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector>, void> const&)> const&) chat.cpp:762 #5 0x000100a2a7f4 in std::__1::__function::__func, void (common_grammar_builder const&)>::operator()(common_grammar_builder const&) function.h:319 #6 0x000100aa98f4 in build_grammar(std::__1::function const&, common_grammar_options const&) json-schema-to-grammar.cpp:982 #7 0x0001009c9314 in common_chat_params_init_llama_3_x(minja::chat_template const&, templates_params const&, bool) chat.cpp:1110 #8 0x0001009b8afc in common_chat_templates_apply_jinja(common_chat_templates const*, common_chat_templates_inputs const&) chat.cpp:1992 #9 0x0001009b533c in common_chat_templates_apply(common_chat_templates const*, common_chat_templates_inputs const&) chat.cpp:2074 #10 0x000100810120 in llamacpp_apply_chat_template+0x724 (predict_oai-98384e17fb94e863:arm64+0x100090120) ... ==45482==Register values: x[0] = 0x00006020004147f8 x[1] = 0x00006080000013c8 x[2] = 0x0000000000000000 x[3] = 0x0000604006289738 x[4] = 0x0000000000000002 x[5] = 0x0000000000000001 x[6] = 0x04034000004b4000 x[7] = 0x0000000000000001 x[8] = 0xbebebebebebebebe x[9] = 0x17d7d7d7d7d7d7d7 x[10] = 0x00000c04000828ff x[11] = 0x0000000000000001 x[12] = 0x000000002018d383 x[13] = 0x0000000000000000 x[14] = 0xfa0000000000fafa x[15] = 0x000010700001ffff x[16] = 0x000000019dc012c0 x[17] = 0x00000001021284f8 x[18] = 0x0000000000000000 x[19] = 0x00000001700acdc0 x[20] = 0x0000000000000002 x[21] = 0x000000002018d384 x[22] = 0x16dd16fd2e731151 x[23] = 0x0000007000020000 x[24] = 0x0000000100c69c08 x[25] = 0x0000000100c69c20 x[26] = 0x00006080000013c7 x[27] = 0x0000000100c69c00 x[28] = 0x00000001700acd60 fp = 0x00000001700aceb0 lr = 0x0000000100abce30 sp = 0x00000001700acd60 AddressSanitizer can not provide additional info. SUMMARY: AddressSanitizer: SEGV __hash_table:1565 in std::__1::pair, std::__1::allocator>, void*>*>, bool> std::__1::__hash_table, std::__1::allocator>, std::__1::hash, std::__1::allocator>>, std::__1::equal_to, std::__1::allocator>>, std::__1::allocator, std::__1::allocator>>>::__emplace_unique_key_args, std::__1::allocator>, std::__1::basic_string, std::__1::allocator> const&>(std::__1::basic_string, std::__1::allocator> const&, std::__1::basic_string, std::__1::allocator> const&) Thread T5 created by T0 here: #0 0x0001020b99d4 in pthread_create+0x5c (libclang_rt.asan_osx_dynamic.dylib:arm64e+0x359d4) #1 0x000100873910 in std::sys::pal::unix::thread::Thread::new::h77254fdd87a28e05+0x118 (predict_oai-98384e17fb94e863:arm64+0x1000f3910) #2 0x0001007c7a1c in test::run_test::haeb3c2bcd5ed6cf6+0x76c (predict_oai-98384e17fb94e863:arm64+0x100047a1c) #3 0x0001007aedb0 in test::console::run_tests_console::he9d142d704f3a986+0x149c (predict_oai-98384e17fb94e863:arm64+0x10002edb0) #4 0x0001007c5758 in test::test_main::hf86a5e20735245b9+0x118 (predict_oai-98384e17fb94e863:arm64+0x100045758) #5 0x0001007c5da0 in test::test_main_static::h61ee9c8fd30abca0+0x54 (predict_oai-98384e17fb94e863:arm64+0x100045da0) ... ==45482==ABORTING --- common/json-schema-to-grammar.cpp | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/common/json-schema-to-grammar.cpp b/common/json-schema-to-grammar.cpp index 182c787544..db1f0b23dd 100644 --- a/common/json-schema-to-grammar.cpp +++ b/common/json-schema-to-grammar.cpp @@ -257,12 +257,13 @@ std::unordered_map STRING_FORMAT_RULES = { }; static bool is_reserved_name(const std::string & name) { - static std::unordered_set RESERVED_NAMES; - if (RESERVED_NAMES.empty()) { - RESERVED_NAMES.insert("root"); - for (const auto &p : PRIMITIVE_RULES) RESERVED_NAMES.insert(p.first); - for (const auto &p : STRING_FORMAT_RULES) RESERVED_NAMES.insert(p.first); - } + static const std::unordered_set RESERVED_NAMES = [] { + std::unordered_set s; + s.insert("root"); + for (const auto & p : PRIMITIVE_RULES) s.insert(p.first); + for (const auto & p : STRING_FORMAT_RULES) s.insert(p.first); + return s; + }(); return RESERVED_NAMES.find(name) != RESERVED_NAMES.end(); } From c959b676be29e93f8dbc3bd6056ceba812a9eb72 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Johannes=20G=C3=A4=C3=9Fler?= Date: Wed, 17 Sep 2025 15:32:42 +0200 Subject: [PATCH 23/52] CUDA: fix FA occupancy, optimize tile kernel (#15982) --- ggml/src/ggml-cuda/common.cuh | 16 + ggml/src/ggml-cuda/fattn-common.cuh | 13 +- ggml/src/ggml-cuda/fattn-tile.cu | 551 ++++++++++++++++------------ ggml/src/ggml-cuda/vendors/hip.h | 34 +- 4 files changed, 361 insertions(+), 253 deletions(-) diff --git a/ggml/src/ggml-cuda/common.cuh b/ggml/src/ggml-cuda/common.cuh index b0feea3623..045c6d3006 100644 --- a/ggml/src/ggml-cuda/common.cuh +++ b/ggml/src/ggml-cuda/common.cuh @@ -75,6 +75,8 @@ #define GGML_CUDA_CC_IS_RDNA4(cc) (cc >= GGML_CUDA_CC_RDNA4) #define GGML_CUDA_CC_IS_GCN(cc) (cc > GGML_CUDA_CC_OFFSET_AMD && cc < GGML_CUDA_CC_CDNA1) #define GGML_CUDA_CC_IS_CDNA(cc) (cc >= GGML_CUDA_CC_CDNA1 && cc < GGML_CUDA_CC_RDNA1) +#define GGML_CUDA_CC_IS_CDNA1(cc) (cc >= GGML_CUDA_CC_CDNA1 && cc < GGML_CUDA_CC_CDNA2) +#define GGML_CUDA_CC_IS_CDNA2(cc) (cc >= GGML_CUDA_CC_CDNA2 && cc < GGML_CUDA_CC_CDNA3) #define GGML_CUDA_CC_IS_CDNA3(cc) (cc >= GGML_CUDA_CC_CDNA3 && cc < GGML_CUDA_CC_RDNA1) // Moore Threads @@ -325,6 +327,20 @@ static constexpr __device__ int ggml_cuda_get_physical_warp_size() { #endif // defined(GGML_USE_HIP) && (defined(__GFX9__) || defined(__GFX8__)) } +// Maximum number of bytes that can be copied in a single instruction. +static constexpr __device__ int ggml_cuda_get_max_cpy_bytes() { +#ifdef GGML_USE_HIP + return 16; +#else +#if __CUDA_ARCH__ >= GGML_CUDA_CC_VOLTA + return 16; +#else + return 8; +#endif // __CUDA_ARCH__ >= GGML_CUDA_CC_VOLTA +#endif // GGML_USE_HIP +} + + [[noreturn]] static __device__ void no_device_code( const char * file_name, const int line, const char * function_name, const int arch, const char * arch_list) { diff --git a/ggml/src/ggml-cuda/fattn-common.cuh b/ggml/src/ggml-cuda/fattn-common.cuh index b69f57d659..142a3a88d1 100644 --- a/ggml/src/ggml-cuda/fattn-common.cuh +++ b/ggml/src/ggml-cuda/fattn-common.cuh @@ -647,9 +647,7 @@ static __global__ void flash_attn_stream_k_fixup( } template // D == head size -#if !defined(GGML_USE_HIP) __launch_bounds__(D, 1) -#endif // !(defined(GGML_USE_HIP) static __global__ void flash_attn_combine_results( const float * __restrict__ VKQ_parts, const float2 * __restrict__ VKQ_meta, @@ -692,10 +690,7 @@ static __global__ void flash_attn_combine_results( float VKQ_numerator = 0.0f; float VKQ_denominator = 0.0f; for (int l = 0; l < parallel_blocks; ++l) { - const float diff = meta[l].x - kqmax; - float KQ_max_scale = expf(diff); - const uint32_t ftz_mask = 0xFFFFFFFF * (diff > SOFTMAX_FTZ_THRESHOLD); - *((uint32_t *) &KQ_max_scale) &= ftz_mask; + const float KQ_max_scale = expf(meta[l].x - kqmax); VKQ_numerator += KQ_max_scale * VKQ_parts[l*D + tid]; VKQ_denominator += KQ_max_scale * meta[l].y; @@ -836,11 +831,10 @@ void launch_fattn( CUDA_CHECK(cudaGetLastError()); } - int parallel_blocks = 1; - const dim3 block_dim(warp_size, nwarps, 1); int max_blocks_per_sm = 1; // Max. number of active blocks limited by occupancy. CUDA_CHECK(cudaOccupancyMaxActiveBlocksPerMultiprocessor(&max_blocks_per_sm, fattn_kernel, block_dim.x * block_dim.y * block_dim.z, nbytes_shared)); + int parallel_blocks = max_blocks_per_sm; dim3 blocks_num; if (stream_k) { @@ -862,9 +856,6 @@ void launch_fattn( GGML_ASSERT(K->ne[1] % KQ_row_granularity == 0); const int ntiles_KQ = K->ne[1] / KQ_row_granularity; // Max. number of parallel blocks limited by tensor size. - // parallel_blocks should be at least large enough to achieve max. occupancy for a single wave: - parallel_blocks = std::max((nsm * max_blocks_per_sm) / ntiles_total, 1); - // parallel_blocks must not be larger than what the tensor size allows: parallel_blocks = std::min(parallel_blocks, ntiles_KQ); diff --git a/ggml/src/ggml-cuda/fattn-tile.cu b/ggml/src/ggml-cuda/fattn-tile.cu index c6a399ce5d..a2d9951ea5 100644 --- a/ggml/src/ggml-cuda/fattn-tile.cu +++ b/ggml/src/ggml-cuda/fattn-tile.cu @@ -2,20 +2,30 @@ #include "fattn-common.cuh" #include "fattn-tile.cuh" -#define FATTN_TILE_NTHREADS 256 +// kq_stride == number of KQ rows to process per iteration +// kq_nbatch == number of K columns to load in parallel for KQ calculation static int fattn_tile_get_kq_stride_host(const int D, const int ncols, const int cc, const int warp_size) { if (GGML_CUDA_CC_IS_AMD(cc)) { + if (GGML_CUDA_CC_IS_RDNA(cc)) { + switch (D) { + case 64: + return 128; + case 128: + case 256: + return ncols <= 16 ? 128 : 64; + default: + GGML_ABORT("fatal error"); + return -1; + } + } switch (D) { case 64: - return 64; + return ncols == 32 ? 128 : 64; case 128: + return ncols == 32 ? 64 : 32; case 256: - if (GGML_CUDA_CC_IS_GCN(cc) || GGML_CUDA_CC_IS_CDNA(cc)) { - return ncols <= 16 ? 64 : 32; - } else { - return 64; - } + return 32; default: GGML_ABORT("fatal error"); return -1; @@ -49,24 +59,28 @@ static int fattn_tile_get_kq_stride_host(const int D, const int ncols, const int static constexpr __device__ int fattn_tile_get_kq_stride_device(int D, int ncols, int warp_size) { #ifdef GGML_USE_HIP +#ifdef RDNA switch (D) { case 64: - return 64; + return 128; case 128: -#if defined(GCN) || defined(CDNA) - return ncols <= 16 ? 64 : 32; -#else - return 64; -#endif // defined(GCN) || defined(CDNA) case 256: -#if defined(GCN) || defined(CDNA) - return ncols <= 16 ? 64 : 32; -#else - return 64; -#endif // defined(GCN) || defined(CDNA) + return ncols <= 16 ? 128 : 64; default: return -1; } +#else + switch (D) { + case 64: + return ncols == 32 ? 128 : 64; + case 128: + return ncols == 32 ? 64 : 32; + case 256: + return 32; + default: + return -1; + } +#endif // RDNA #else #ifdef FAST_FP16_AVAILABLE switch (D) { @@ -100,17 +114,8 @@ static constexpr __device__ int fattn_tile_get_kq_nbatch_device(int D, int ncols case 64: return 64; case 128: -#if defined(GCN) || defined(CDNA) - return ncols <= 16 ? 64 : 128; -#else - return 64; -#endif // defined(GCN) || defined(CDNA) case 256: -#if defined(GCN) || defined(CDNA) - return ncols <= 16 ? 64 : 128; -#else - return ncols <= 16 ? 64 : 256; -#endif // defined(GCN) || defined(CDNA) + return 128; default: return -1; } @@ -120,9 +125,8 @@ static constexpr __device__ int fattn_tile_get_kq_nbatch_device(int D, int ncols case 64: return 64; case 128: - return ncols <= 16 ? 128 : 64; case 256: - return ncols <= 16 ? 64 : 128; + return 128; default: return -1; } @@ -142,12 +146,27 @@ static constexpr __device__ int fattn_tile_get_kq_nbatch_device(int D, int ncols GGML_UNUSED_VARS(ncols, warp_size); } -template // D == head size -#ifdef GGML_USE_HIP -__launch_bounds__(FATTN_TILE_NTHREADS, 1) +static int fattn_tile_get_nthreads_host(const int cc, const int ncols) { + return 256; + GGML_UNUSED_VARS(cc, ncols); +} + +static constexpr __device__ int fattn_tile_get_nthreads_device(int ncols) { + return 256; + GGML_UNUSED(ncols); +} + +static constexpr __device__ int fattn_tile_get_occupancy_device(int ncols) { +#ifdef RDNA + return 3; #else -__launch_bounds__(FATTN_TILE_NTHREADS, 2) -#endif // GGML_USE_HIP + return ncols <= 16 ? 3 : 2; +#endif // RDNA + GGML_UNUSED(ncols); +} + +template // D == head size +__launch_bounds__(fattn_tile_get_nthreads_device(ncols), fattn_tile_get_occupancy_device(ncols)) static __global__ void flash_attn_tile( const char * __restrict__ Q, const char * __restrict__ K, @@ -193,7 +212,7 @@ static __global__ void flash_attn_tile( } constexpr int warp_size = 32; - constexpr int nwarps = FATTN_TILE_NTHREADS / warp_size; + constexpr int nwarps = fattn_tile_get_nthreads_device(ncols) / warp_size; constexpr int kq_stride = fattn_tile_get_kq_stride_device(D, ncols, warp_size); static_assert(kq_stride % warp_size == 0, "kq_stride not divisable by warp_size."); constexpr int kq_nbatch = fattn_tile_get_kq_nbatch_device(D, ncols, warp_size); @@ -206,90 +225,126 @@ static __global__ void flash_attn_tile( const int sequence = blockIdx.z / ne02; const int head = blockIdx.z - sequence*ne02; const int gqa_ratio = ne02 / ne12; // With grouped query attention there are > 1 Q matrices per K, V matrix. - const float2 * Q_f2 = (const float2 *) (Q + nb03* sequence + nb02* head + nb01*ic0); - const half2 * K_h2 = (const half2 *) (K + nb13* sequence + nb12*(head / gqa_ratio)); - const half2 * V_h2 = (const half2 *) (V + nb13* sequence + nb12*(head / gqa_ratio)); // K and V have same shape - const half * maskh = (const half *) (mask + nb33*(sequence % ne33) + nb31*ic0); - const float * sinksf = (const float *) (sinks); + const float * Q_f = (const float *) (Q + nb03* sequence + nb02* head + nb01*ic0); + const half2 * K_h2 = (const half2 *) (K + nb13* sequence + nb12*(head / gqa_ratio)); + const half2 * V_h2 = (const half2 *) (V + nb13* sequence + nb12*(head / gqa_ratio)); // K and V have same shape + const half * maskh = (const half *) (mask + nb33*(sequence % ne33) + nb31*ic0); + const float * sinksf = (const float *) (sinks); const int stride_KV2 = nb11 / sizeof(half2); const float slope = get_alibi_slope(max_bias, head, n_head_log2, m0, m1); -#if defined(GGML_USE_HIP) - constexpr int cpy_nb = 16; -#else - constexpr int cpy_nb = 8; -#endif // defined(GGML_USE_HIP) && defined(GCN) + constexpr int cpy_nb = ggml_cuda_get_max_cpy_bytes(); constexpr int cpy_ne = cpy_nb / 4; - __shared__ float KQ[ncols][kq_stride]; + constexpr int cpw = ncols/nwarps; // cols per warp + + // softmax_iter_j == number of KQ columns for which to calculate softmax in parallel. + // KQ is originall 2D but uses a Z-shaped memory pattern for larger reads/writes. #ifdef FAST_FP16_AVAILABLE + constexpr int softmax_iter_j = cpw < 2*cpy_ne ? cpw : 2*cpy_ne; + + __shared__ half KQ[ncols/softmax_iter_j][kq_stride][softmax_iter_j]; __shared__ half2 Q_tmp[ncols][D/2]; - __shared__ half2 KV_tmp_h2[kq_stride * (kq_nbatch/2 + cpy_ne)]; // Padded to avoid memory bank conflicts. - half2 VKQ[ncols/nwarps][D/(2*warp_size)] = {{{0.0f, 0.0f}}}; + __shared__ half2 KV_tmp[kq_stride * (kq_nbatch/2 + cpy_ne)]; // Padded to avoid memory bank conflicts. + half2 VKQ[cpw][D/(2*warp_size)] = {{{0.0f, 0.0f}}}; #else + constexpr int softmax_iter_j = cpw < 1*cpy_ne ? cpw : 1*cpy_ne; + + __shared__ float KQ[ncols/softmax_iter_j][kq_stride][softmax_iter_j]; __shared__ float Q_tmp[ncols][D]; - __shared__ float KV_tmp_f[kq_stride * (kq_nbatch + cpy_ne)]; // Padded to avoid memory bank conflicts. - float2 * KV_tmp_f2 = (float2 *) KV_tmp_f; - float2 VKQ[ncols/nwarps][D/(2*warp_size)] = {{{0.0f, 0.0f}}}; + __shared__ float KV_tmp[kq_stride * (kq_nbatch + cpy_ne)]; // Padded to avoid memory bank conflicts. + float2 VKQ[cpw][D/(2*warp_size)] = {{{0.0f, 0.0f}}}; #endif // FAST_FP16_AVAILABLE + static_assert(cpw % softmax_iter_j == 0, "bad softmax_iter_j"); - - float kqmax[ncols/nwarps]; + float KQ_max[cpw]; #pragma unroll for (int j0 = 0; j0 < ncols; j0 += nwarps) { - kqmax[j0/nwarps] = -FLT_MAX/2.0f; + KQ_max[j0/nwarps] = -FLT_MAX/2.0f; } - float kqsum[ncols/nwarps] = {0.0f}; + float KQ_sum[cpw] = {0.0f}; + + // Load Q data, convert to FP16 if fast. +#pragma unroll + for (int j0 = 0; j0 < cpw; ++j0) { + const int j = j0 + threadIdx.y*cpw; + + constexpr int cpy_ne_D = cpy_ne < D/warp_size ? cpy_ne : D/warp_size; #pragma unroll - for (int j0 = 0; j0 < ncols; j0 += nwarps) { - const int j = j0 + threadIdx.y; + for (int i0 = 0; i0 < D; i0 += warp_size*cpy_ne_D) { + float tmp_f[cpy_ne_D] = {0.0f}; + if (ic0 + j < ne01) { + ggml_cuda_memcpy_1(tmp_f, &Q_f[j*(nb01/sizeof(float)) + i0 + threadIdx.x*cpy_ne_D]); + } #pragma unroll - for (int i0 = 0; i0 < D/2; i0 += warp_size) { - const float2 tmp = ic0 + j < ne01 ? Q_f2[j*(nb01/sizeof(float2)) + i0 + threadIdx.x] : make_float2(0.0f, 0.0f); + for (int i1 = 0; i1 < cpy_ne_D; ++i1) { + tmp_f[i1] *= scale; + } + #ifdef FAST_FP16_AVAILABLE - Q_tmp[j][i0 + threadIdx.x] = make_half2(tmp.x * scale, tmp.y * scale); + half2 tmp_h2[cpy_ne_D/2]; +#pragma unroll + for (int i1 = 0; i1 < cpy_ne_D; i1 += 2) { + tmp_h2[i1/2] = make_half2(tmp_f[i1 + 0], tmp_f[i1 + 1]); + } + ggml_cuda_memcpy_1(&Q_tmp[j][i0/2 + threadIdx.x*(cpy_ne_D/2)], tmp_h2); #else - Q_tmp[j][2*i0 + threadIdx.x] = tmp.x * scale; - Q_tmp[j][2*i0 + warp_size + threadIdx.x] = tmp.y * scale; + ggml_cuda_memcpy_1 (&Q_tmp[j][i0 + threadIdx.x* cpy_ne_D], tmp_f); #endif // FAST_FP16_AVAILABLE } } __syncthreads(); + // Main loop over KV cache: const int k_VKQ_max = KV_max ? KV_max[sequence*gridDim.x + blockIdx.x] : ne11; for (int k_VKQ_0 = blockIdx.y*kq_stride; k_VKQ_0 < k_VKQ_max; k_VKQ_0 += gridDim.y*kq_stride) { // Calculate KQ tile and keep track of new maximum KQ values: - float kqmax_new[ncols/nwarps]; + float KQ_max_new[cpw]; #pragma unroll - for (int j = 0; j < ncols/nwarps; ++j) { - kqmax_new[j] = kqmax[j]; + for (int j = 0; j < cpw; ++j) { + KQ_max_new[j] = KQ_max[j]; } - float sum[kq_stride/warp_size][ncols/nwarps] = {{0.0f}}; + float KQ_acc[kq_stride/warp_size][cpw] = {{0.0f}}; // Accumulators for KQ matrix multiplication. + // KQ = K @ Q matrix multiplication: #pragma unroll for (int k_KQ_0 = 0; k_KQ_0 < D; k_KQ_0 += kq_nbatch) { #pragma unroll for (int i_KQ_0 = 0; i_KQ_0 < kq_stride; i_KQ_0 += nwarps) { const int i_KQ = i_KQ_0 + threadIdx.y; -#pragma unroll - for (int k_KQ_1 = 0; k_KQ_1 < kq_nbatch/2; k_KQ_1 += warp_size) { - const half2 tmp_h2 = K_h2[int64_t(k_VKQ_0 + i_KQ)*stride_KV2 + k_KQ_0/2 + k_KQ_1 + threadIdx.x]; #ifdef FAST_FP16_AVAILABLE - KV_tmp_h2[i_KQ*(kq_nbatch/2 + cpy_ne) + k_KQ_1 + threadIdx.x] = tmp_h2; -#else - const float2 tmp_f2 = __half22float2(tmp_h2); - KV_tmp_f[i_KQ*(kq_nbatch + cpy_ne) + 2*k_KQ_1 + threadIdx.x] = tmp_f2.x; - KV_tmp_f[i_KQ*(kq_nbatch + cpy_ne) + 2*k_KQ_1 + warp_size + threadIdx.x] = tmp_f2.y; -#endif // FAST_FP16_AVAILABLE + constexpr int cpy_ne_kqnb = cpy_ne < kq_nbatch/(2*warp_size) ? cpy_ne : kq_nbatch/(2*warp_size); +#pragma unroll + for (int k_KQ_1 = 0; k_KQ_1 < kq_nbatch/2; k_KQ_1 += warp_size*cpy_ne_kqnb) { + ggml_cuda_memcpy_1( + &KV_tmp[i_KQ*(kq_nbatch/2 + cpy_ne) + k_KQ_1 + threadIdx.x*cpy_ne_kqnb], + &K_h2[int64_t(k_VKQ_0 + i_KQ)*stride_KV2 + k_KQ_0/2 + k_KQ_1 + threadIdx.x*cpy_ne_kqnb]); } +#else + constexpr int cpy_ne_kqnb = cpy_ne < kq_nbatch/warp_size ? cpy_ne : kq_nbatch/warp_size; +#pragma unroll + for (int k_KQ_1 = 0; k_KQ_1 < kq_nbatch; k_KQ_1 += warp_size*cpy_ne_kqnb) { + half2 tmp_h2[cpy_ne_kqnb/2]; + ggml_cuda_memcpy_1( + tmp_h2, &K_h2[int64_t(k_VKQ_0 + i_KQ)*stride_KV2 + k_KQ_0/2 + k_KQ_1/2 + threadIdx.x*(cpy_ne_kqnb/2)]); + + float2 tmp_f2[cpy_ne_kqnb/2]; +#pragma unroll + for (int k_KQ_2 = 0; k_KQ_2 < cpy_ne_kqnb/2; ++k_KQ_2) { + tmp_f2[k_KQ_2] = __half22float2(tmp_h2[k_KQ_2]); + } + ggml_cuda_memcpy_1( + &KV_tmp[i_KQ*(kq_nbatch + cpy_ne) + k_KQ_1 + threadIdx.x*cpy_ne_kqnb], tmp_f2); + } +#endif // FAST_FP16_AVAILABLE } __syncthreads(); @@ -298,12 +353,12 @@ static __global__ void flash_attn_tile( #pragma unroll for (int k_KQ_1 = 0; k_KQ_1 < kq_nbatch/2; k_KQ_1 += cpy_ne) { half2 K_k[kq_stride/warp_size][cpy_ne]; - half2 Q_k[ncols/nwarps][cpy_ne]; + half2 Q_k[cpw][cpy_ne]; #else #pragma unroll for (int k_KQ_1 = 0; k_KQ_1 < kq_nbatch; k_KQ_1 += cpy_ne) { float K_k[kq_stride/warp_size][cpy_ne]; - float Q_k[ncols/nwarps][cpy_ne]; + float Q_k[cpw][cpy_ne]; #endif // FAST_FP16_AVAILABLE #pragma unroll @@ -311,29 +366,29 @@ static __global__ void flash_attn_tile( const int i_KQ = i_KQ_0 + threadIdx.x; #ifdef FAST_FP16_AVAILABLE - ggml_cuda_memcpy_1(&K_k[i_KQ_0/warp_size], &KV_tmp_h2[i_KQ*(kq_nbatch/2 + cpy_ne) + k_KQ_1]); + ggml_cuda_memcpy_1(&K_k[i_KQ_0/warp_size], &KV_tmp[i_KQ*(kq_nbatch/2 + cpy_ne) + k_KQ_1]); #else - ggml_cuda_memcpy_1(&K_k[i_KQ_0/warp_size], &KV_tmp_f [i_KQ*(kq_nbatch + cpy_ne) + k_KQ_1]); + ggml_cuda_memcpy_1(&K_k[i_KQ_0/warp_size], &KV_tmp[i_KQ*(kq_nbatch + cpy_ne) + k_KQ_1]); #endif // FAST_FP16_AVAILABLE } #pragma unroll - for (int j_KQ_0 = 0; j_KQ_0 < ncols; j_KQ_0 += nwarps) { - const int j_KQ = j_KQ_0 + threadIdx.y; + for (int j_KQ_0 = 0; j_KQ_0 < cpw; ++j_KQ_0) { + const int j_KQ = j_KQ_0 + threadIdx.y*cpw; #ifdef FAST_FP16_AVAILABLE - ggml_cuda_memcpy_1(&Q_k[j_KQ_0/nwarps], &Q_tmp[j_KQ][k_KQ_0/2 + k_KQ_1]); + ggml_cuda_memcpy_1(&Q_k[j_KQ_0], &Q_tmp[j_KQ][k_KQ_0/2 + k_KQ_1]); #else - ggml_cuda_memcpy_1(&Q_k[j_KQ_0/nwarps], &Q_tmp[j_KQ][k_KQ_0 + k_KQ_1]); + ggml_cuda_memcpy_1(&Q_k[j_KQ_0], &Q_tmp[j_KQ][k_KQ_0 + k_KQ_1]); #endif // FAST_FP16_AVAILABLE } #pragma unroll for (int i_KQ_0 = 0; i_KQ_0 < kq_stride; i_KQ_0 += warp_size) { #pragma unroll - for (int j_KQ_0 = 0; j_KQ_0 < ncols; j_KQ_0 += nwarps) { + for (int j_KQ_0 = 0; j_KQ_0 < cpw; ++j_KQ_0) { #pragma unroll for (int k = 0; k < cpy_ne; ++k) { - ggml_cuda_mad(sum[i_KQ_0/warp_size][j_KQ_0/nwarps], K_k[i_KQ_0/warp_size][k], Q_k[j_KQ_0/nwarps][k]); + ggml_cuda_mad(KQ_acc[i_KQ_0/warp_size][j_KQ_0], K_k[i_KQ_0/warp_size][k], Q_k[j_KQ_0][k]); } } } @@ -344,104 +399,77 @@ static __global__ void flash_attn_tile( } } + // Apply logit softcap, mask, update KQ_max: #pragma unroll for (int i_KQ_0 = 0; i_KQ_0 < kq_stride; i_KQ_0 += warp_size) { const int i_KQ = i_KQ_0 + threadIdx.x; #pragma unroll - for (int j_KQ_0 = 0; j_KQ_0 < ncols; j_KQ_0 += nwarps) { - const int j_KQ = j_KQ_0 + threadIdx.y; + for (int j_KQ_0 = 0; j_KQ_0 < cpw; ++j_KQ_0) { + const int j_KQ = j_KQ_0 + threadIdx.y*cpw; if (use_logit_softcap) { - sum[i_KQ_0/warp_size][j_KQ_0/nwarps] = logit_softcap * tanhf(sum[i_KQ_0/warp_size][j_KQ_0/nwarps]); + KQ_acc[i_KQ_0/warp_size][j_KQ_0] = logit_softcap * tanhf(KQ_acc[i_KQ_0/warp_size][j_KQ_0]); } - sum[i_KQ_0/warp_size][j_KQ_0/nwarps] += mask ? slope*__half2float(maskh[j_KQ*ne11 + k_VKQ_0 + i_KQ]) : 0.0f; + KQ_acc[i_KQ_0/warp_size][j_KQ_0] += mask ? slope*__half2float(maskh[j_KQ*ne11 + k_VKQ_0 + i_KQ]) : 0.0f; - kqmax_new[j_KQ_0/nwarps] = fmaxf(kqmax_new[j_KQ_0/nwarps], sum[i_KQ_0/warp_size][j_KQ_0/nwarps]); - - KQ[j_KQ][i_KQ] = sum[i_KQ_0/warp_size][j_KQ_0/nwarps]; + KQ_max_new[j_KQ_0] = fmaxf(KQ_max_new[j_KQ_0], KQ_acc[i_KQ_0/warp_size][j_KQ_0]); } } __syncthreads(); + // Calculate KQ softmax, write to shared KQ buffer, re-scale VKQ accumulators: #pragma unroll - for (int j0 = 0; j0 < ncols; j0 += nwarps) { - const int j = j0 + threadIdx.y; - - kqmax_new[j0/nwarps] = warp_reduce_max(kqmax_new[j0/nwarps]); - const float KQ_max_scale = expf(kqmax[j0/nwarps] - kqmax_new[j0/nwarps]); - kqmax[j0/nwarps] = kqmax_new[j0/nwarps]; - - float kqsum_add = 0.0f; - if (kq_stride % (4*warp_size) == 0 && cpy_ne % 4 == 0) { -#pragma unroll - for (int i0 = 0; i0 < kq_stride; i0 += 4*warp_size) { - const int i = i0 + 4*threadIdx.x; - - float4 val = *(const float4 *) &KQ[j][i]; - val.x = expf(val.x - kqmax[j0/nwarps]); - val.y = expf(val.y - kqmax[j0/nwarps]); - val.z = expf(val.z - kqmax[j0/nwarps]); - val.w = expf(val.w - kqmax[j0/nwarps]); - kqsum_add += val.x + val.y + val.z + val.w; - + for (int j0 = 0; j0 < cpw; j0 += softmax_iter_j) { #ifdef FAST_FP16_AVAILABLE - const half2 tmp[2] = {make_half2(val.x, val.y), make_half2(val.z, val.w)}; - ggml_cuda_memcpy_1(&KQ[j][i/2], &tmp); + half tmp[kq_stride/warp_size][softmax_iter_j]; #else - ggml_cuda_memcpy_1(&KQ[j][i], &val); + float tmp[kq_stride/warp_size][softmax_iter_j]; #endif // FAST_FP16_AVAILABLE - } - } else if (kq_stride % (2*warp_size) == 0 && cpy_ne % 2 == 0) { -#pragma unroll - for (int i0 = 0; i0 < kq_stride; i0 += 2*warp_size) { - const int i = i0 + 2*threadIdx.x; - float2 val = *(const float2 *) &KQ[j][i]; - val.x = expf(val.x - kqmax[j0/nwarps]); - val.y = expf(val.y - kqmax[j0/nwarps]); - kqsum_add += val.x + val.y; -#ifdef FAST_FP16_AVAILABLE - const half2 tmp = make_half2(val.x, val.y); - ggml_cuda_memcpy_1(&KQ[j][i/2], &tmp); -#else - ggml_cuda_memcpy_1(&KQ[j][i], &val); -#endif // FAST_FP16_AVAILABLE - } - } else { +#pragma unroll + for (int j1 = 0; j1 < softmax_iter_j; ++j1) { + KQ_max_new[j0+j1] = warp_reduce_max(KQ_max_new[j0+j1]); + const float KQ_max_scale = expf(KQ_max[j0+j1] - KQ_max_new[j0+j1]); + KQ_max[j0+j1] = KQ_max_new[j0+j1]; + + float KQ_sum_add = 0.0f; +#pragma unroll for (int i0 = 0; i0 < kq_stride; i0 += warp_size) { - const int i = i0 + threadIdx.x; - - const float diff = KQ[j][i] - kqmax[j0/nwarps]; - const float val = expf(diff); - kqsum_add += val; -#ifdef FAST_FP16_AVAILABLE - ((half *) KQ[j])[i] = val; -#else - KQ[j][i] = val; -#endif // FAST_FP16_AVAILABLE + const float val = expf(KQ_acc[i0/warp_size][j0+j1] - KQ_max[j0+j1]); + KQ_sum_add += val; + tmp[i0/warp_size][j1] = val; } - } - kqsum[j0/nwarps] = kqsum[j0/nwarps]*KQ_max_scale + kqsum_add; + KQ_sum[j0+j1] = KQ_sum[j0+j1]*KQ_max_scale + KQ_sum_add; #ifdef FAST_FP16_AVAILABLE - const half2 KQ_max_scale_h2 = make_half2(KQ_max_scale, KQ_max_scale); + const half2 KQ_max_scale_h2 = make_half2(KQ_max_scale, KQ_max_scale); #pragma unroll - for (int i0 = 0; i0 < D/2; i0 += warp_size) { - VKQ[j0/nwarps][i0/warp_size] *= KQ_max_scale_h2; - } + for (int i0 = 0; i0 < D/2; i0 += warp_size) { + VKQ[j0+j1][i0/warp_size] *= KQ_max_scale_h2; + } #else #pragma unroll - for (int i0 = 0; i0 < D/2; i0 += warp_size) { - VKQ[j0/nwarps][i0/warp_size].x *= KQ_max_scale; - VKQ[j0/nwarps][i0/warp_size].y *= KQ_max_scale; - } + for (int i0 = 0; i0 < D/2; i0 += warp_size) { + VKQ[j0+j1][i0/warp_size].x *= KQ_max_scale; + VKQ[j0+j1][i0/warp_size].y *= KQ_max_scale; + } #endif // FAST_FP16_AVAILABLE + } + +#pragma unroll + for (int i0 = 0; i0 < kq_stride; i0 += warp_size) { + const int i = i0 + threadIdx.x; + + ggml_cuda_memcpy_1( + KQ[j0/softmax_iter_j + threadIdx.y*(cpw/softmax_iter_j)][i], tmp[i0/warp_size]); + } } - constexpr int V_cols_per_iter = kq_stride*kq_nbatch / D; + // VKQ = V @ KQ matrix multiplication: + constexpr int V_cols_per_iter = kq_stride*kq_nbatch / D; // Number of V columns that fit in SRAM for K. static_assert(kq_stride % V_cols_per_iter == 0, "bad V_cols_per_iter"); #pragma unroll for (int k0 = 0; k0 < kq_stride; k0 += V_cols_per_iter) { @@ -449,65 +477,96 @@ static __global__ void flash_attn_tile( for (int k1 = 0; k1 < V_cols_per_iter; k1 += nwarps) { const int k_tile = k1 + threadIdx.y; -#pragma unroll - for (int i0 = 0; i0 < D/2; i0 += warp_size) { - const int i = i0 + threadIdx.x; - - const half2 tmp = V_h2[int64_t(k_VKQ_0 + k0 + k_tile)*stride_KV2 + i]; #ifdef FAST_FP16_AVAILABLE - KV_tmp_h2[k_tile*(D/2) + i] = tmp; -#else - KV_tmp_f2[k_tile*(D/2) + i] = __half22float2(tmp); -#endif // FAST_FP16_AVAILABLE + constexpr int cpy_ne_D = cpy_ne < D/(2*warp_size) ? cpy_ne : D/(2*warp_size); +#pragma unroll + for (int i0 = 0; i0 < D/2; i0 += warp_size*cpy_ne_D) { + ggml_cuda_memcpy_1( + &KV_tmp[k_tile*(D/2) + i0 + threadIdx.x*cpy_ne_D], + &V_h2[int64_t(k_VKQ_0 + k0 + k_tile)*stride_KV2 + i0 + threadIdx.x*cpy_ne_D]); } +#else + constexpr int cpy_ne_D = cpy_ne < D/warp_size ? cpy_ne : D/warp_size; +#pragma unroll + for (int i0 = 0; i0 < D; i0 += warp_size*cpy_ne_D) { + half2 tmp_h2[cpy_ne_D/2]; + ggml_cuda_memcpy_1( + tmp_h2, &V_h2[int64_t(k_VKQ_0 + k0 + k_tile)*stride_KV2 + i0/2 + threadIdx.x*(cpy_ne_D/2)]); + + float2 tmp_f2[cpy_ne_D/2]; +#pragma unroll + for (int i1 = 0; i1 < cpy_ne_D/2; ++i1) { + tmp_f2[i1] = __half22float2(tmp_h2[i1]); + } + ggml_cuda_memcpy_1( + &KV_tmp[k_tile*D + i0 + threadIdx.x*cpy_ne_D], tmp_f2); + } +#endif // FAST_FP16_AVAILABLE } __syncthreads(); +#ifdef FAST_FP16_AVAILABLE #pragma unroll for (int k1 = 0; k1 < V_cols_per_iter; ++k1) { -#ifdef FAST_FP16_AVAILABLE half2 V_k[(D/2)/warp_size]; - half2 KQ_k[ncols/nwarps]; -#else - float2 V_k[(D/2)/warp_size]; - float KQ_k[ncols/nwarps]; -#endif // FAST_FP16_AVAILABLE + half2 KQ_k[cpw]; + constexpr int cpy_ne_D = cpy_ne/2 < (D/2)/warp_size ? cpy_ne/2 : (D/2)/warp_size; #pragma unroll - for (int i0 = 0; i0 < D/2; i0 += warp_size) { - const int i = i0 + threadIdx.x; - -#ifdef FAST_FP16_AVAILABLE - V_k[i0/warp_size] = KV_tmp_h2[k1*(D/2) + i]; -#else - V_k[i0/warp_size] = KV_tmp_f2[k1*(D/2) + i]; -#endif // FAST_FP16_AVAILABLE + for (int i0 = 0; i0 < D/2; i0 += warp_size*cpy_ne_D) { + ggml_cuda_memcpy_1(&V_k[i0/warp_size], &KV_tmp[k1*(D/2) + i0 + threadIdx.x*cpy_ne_D]); } #pragma unroll - for (int j0 = 0; j0 < ncols; j0 += nwarps) { - const int j = j0 + threadIdx.y; + for (int j0 = 0; j0 < cpw; j0 += softmax_iter_j) { + const int j = j0/softmax_iter_j + threadIdx.y*(cpw/softmax_iter_j); -#ifdef FAST_FP16_AVAILABLE - KQ_k[j0/nwarps] = __half2half2(((const half *)KQ[j])[k0 + k1]); -#else - KQ_k[j0/nwarps] = KQ[j][k0 + k1]; -#endif // FAST_FP16_AVAILABLE + half tmp[softmax_iter_j]; + ggml_cuda_memcpy_1( + &tmp, KQ[j][k0 + k1]); +#pragma unroll + for (int j1 = 0; j1 < softmax_iter_j; ++j1) { + KQ_k[j0+j1] = __half2half2(tmp[j1]); + } } #pragma unroll for (int i0 = 0; i0 < D/2; i0 += warp_size) { #pragma unroll - for (int j0 = 0; j0 < ncols; j0 += nwarps) { -#ifdef FAST_FP16_AVAILABLE - VKQ[j0/nwarps][i0/warp_size] += V_k[i0/warp_size] *KQ_k[j0/nwarps]; -#else - VKQ[j0/nwarps][i0/warp_size].x += V_k[i0/warp_size].x*KQ_k[j0/nwarps]; - VKQ[j0/nwarps][i0/warp_size].y += V_k[i0/warp_size].y*KQ_k[j0/nwarps]; -#endif // FAST_FP16_AVAILABLE + for (int j0 = 0; j0 < cpw; ++j0) { + VKQ[j0][i0/warp_size] += V_k[i0/warp_size]*KQ_k[j0]; } } } +#else +#pragma unroll + for (int k1 = 0; k1 < V_cols_per_iter; ++k1) { + float2 V_k[(D/2)/warp_size]; + float KQ_k[cpw]; + + constexpr int cpy_ne_D = cpy_ne < D/warp_size ? cpy_ne : D/warp_size; +#pragma unroll + for (int i0 = 0; i0 < D; i0 += warp_size*cpy_ne_D) { + ggml_cuda_memcpy_1(&V_k[i0/(2*warp_size)], &KV_tmp[k1*D + i0 + threadIdx.x*cpy_ne_D]); + } +#pragma unroll + for (int j0 = 0; j0 < cpw; j0 += softmax_iter_j) { + const int j = j0/softmax_iter_j + threadIdx.y*(cpw/softmax_iter_j); + + ggml_cuda_memcpy_1( + &KQ_k[j0], KQ[j][k0 + k1]); + } + +#pragma unroll + for (int i0 = 0; i0 < D/2; i0 += warp_size) { +#pragma unroll + for (int j0 = 0; j0 < cpw; ++j0) { + VKQ[j0][i0/warp_size].x += V_k[i0/warp_size].x*KQ_k[j0]; + VKQ[j0][i0/warp_size].y += V_k[i0/warp_size].y*KQ_k[j0]; + } + } + } +#endif // FAST_FP16_AVAILABLE __syncthreads(); } @@ -519,69 +578,92 @@ static __global__ void flash_attn_tile( const float sink = sinksf[head]; #pragma unroll - for (int j0 = 0; j0 < ncols; j0 += nwarps) { - float kqmax_new_j = fmaxf(kqmax[j0/nwarps], sink); - kqmax_new_j = warp_reduce_max(kqmax_new_j); + for (int j0 = 0; j0 < cpw; ++j0) { + float KQ_max_new_j = fmaxf(KQ_max[j0], sink); + KQ_max_new_j = warp_reduce_max(KQ_max_new_j); - const float KQ_max_scale = expf(kqmax[j0/nwarps] - kqmax_new_j); - kqmax[j0/nwarps] = kqmax_new_j; + const float KQ_max_scale = expf(KQ_max[j0] - KQ_max_new_j); + KQ_max[j0] = KQ_max_new_j; - const float val = expf(sink - kqmax[j0/nwarps]); - kqsum[j0/nwarps] = kqsum[j0/nwarps] * KQ_max_scale; + const float val = expf(sink - KQ_max[j0]); + KQ_sum[j0] = KQ_sum[j0] * KQ_max_scale; if (threadIdx.x == 0) { - kqsum[j0/nwarps] += val; + KQ_sum[j0] += val; } #ifdef FAST_FP16_AVAILABLE const half2 KQ_max_scale_h2 = make_half2(KQ_max_scale, KQ_max_scale); #pragma unroll for (int i0 = 0; i0 < D/2; i0 += warp_size) { - VKQ[j0/nwarps][i0/warp_size] *= KQ_max_scale_h2; + VKQ[j0][i0/warp_size] *= KQ_max_scale_h2; } #else #pragma unroll for (int i0 = 0; i0 < D/2; i0 += warp_size) { - VKQ[j0/nwarps][i0/warp_size].x *= KQ_max_scale; - VKQ[j0/nwarps][i0/warp_size].y *= KQ_max_scale; + VKQ[j0][i0/warp_size].x *= KQ_max_scale; + VKQ[j0][i0/warp_size].y *= KQ_max_scale; } #endif // FAST_FP16_AVAILABLE } } - float2 * dst2 = (float2 *) dst; - #pragma unroll - for (int j_VKQ_0 = 0; j_VKQ_0 < ncols; j_VKQ_0 += nwarps) { - const int j_VKQ = j_VKQ_0 + threadIdx.y; + for (int j_VKQ_0 = 0; j_VKQ_0 < cpw; ++j_VKQ_0) { + KQ_sum[j_VKQ_0] = warp_reduce_sum(KQ_sum[j_VKQ_0]); + } + if (gridDim.y == 1) { +#pragma unroll + for (int j_VKQ_0 = 0; j_VKQ_0 < cpw; ++j_VKQ_0) { +#ifdef FAST_FP16_AVAILABLE + const half2 KQ_sum_j_inv = make_half2(1.0f/KQ_sum[j_VKQ_0], 1.0f/KQ_sum[j_VKQ_0]); +#pragma unroll + for (int i = 0; i < (D/2)/warp_size; ++i) { + VKQ[j_VKQ_0][i] *= KQ_sum_j_inv; + } +#else + const float KQ_sum_j_inv = 1.0f/KQ_sum[j_VKQ_0]; +#pragma unroll + for (int i = 0; i < (D/2)/warp_size; ++i) { + VKQ[j_VKQ_0][i].x *= KQ_sum_j_inv; + VKQ[j_VKQ_0][i].y *= KQ_sum_j_inv; + } +#endif // FAST_FP16_AVAILABLE + } + } + + // Write back results: +#pragma unroll + for (int j_VKQ_0 = 0; j_VKQ_0 < cpw; ++j_VKQ_0) { + const int j_VKQ = j_VKQ_0 + threadIdx.y*cpw; if (ic0 + j_VKQ >= ne01) { return; } - float kqsum_j = kqsum[j_VKQ_0/nwarps]; - kqsum_j = warp_reduce_sum(kqsum_j); - const int j_dst_unrolled = ((sequence*ne01 + ic0 + j_VKQ)*ne02 + head)*gridDim.y + blockIdx.y; -#pragma unroll - for (int i00 = 0; i00 < D/2; i00 += warp_size) { - const int i0 = i00 + threadIdx.x; - #ifdef FAST_FP16_AVAILABLE - float2 dst_val = __half22float2(VKQ[j_VKQ_0/nwarps][i0/warp_size]); + constexpr int cpy_ne_D = cpy_ne/2 < (D/2)/warp_size ? cpy_ne/2 : (D/2)/warp_size; +#pragma unroll + for (int i0 = 0; i0 < D/2; i0 += warp_size*cpy_ne_D) { + float2 tmp[cpy_ne_D]; +#pragma unroll + for (int i1 = 0; i1 < cpy_ne_D; ++i1) { + tmp[i1] = __half22float2(VKQ[j_VKQ_0][i0/warp_size + i1]); + } + ggml_cuda_memcpy_1(&dst[j_dst_unrolled*D + 2*i0 + threadIdx.x*(2*cpy_ne_D)], tmp); + } #else - float2 dst_val = VKQ[j_VKQ_0/nwarps][i0/warp_size]; + constexpr int cpy_ne_D = cpy_ne < D/warp_size ? cpy_ne : D/warp_size; +#pragma unroll + for (int i0 = 0; i0 < D; i0 += warp_size*cpy_ne_D) { + ggml_cuda_memcpy_1( + &dst[j_dst_unrolled*D + i0 + threadIdx.x*cpy_ne_D], &VKQ[j_VKQ_0][i0/(2*warp_size)]); + } #endif // FAST_FP16_AVAILABLE - if (gridDim.y == 1) { - dst_val.x /= kqsum_j; - dst_val.y /= kqsum_j; - } - dst2[j_dst_unrolled*(D/2) + i0] = dst_val; - } - if (gridDim.y != 1 && threadIdx.x == 0) { - dst_meta[j_dst_unrolled] = make_float2(kqmax[j_VKQ_0/nwarps], kqsum_j); + dst_meta[j_dst_unrolled] = make_float2(KQ_max[j_VKQ_0], KQ_sum[j_VKQ_0]); } } #else @@ -602,15 +684,29 @@ template static void launch_fattn_tile_switch_ncols(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { const ggml_tensor * Q = dst->src[0]; - const int id = ggml_cuda_get_device(); - const int cc = ggml_cuda_info().devices[id].cc; - const int warp_size = 32; - const int nwarps = FATTN_TILE_NTHREADS / warp_size; + const int id = ggml_cuda_get_device(); + const int cc = ggml_cuda_info().devices[id].cc; + const int warp_size = 32; constexpr size_t nbytes_shared = 0; +#ifdef GGML_USE_HIP + if constexpr (D <= 128) { + if (Q->ne[1] > 32) { + constexpr int cols_per_block = 64; + const int nwarps = fattn_tile_get_nthreads_host(cc, cols_per_block) / warp_size; + fattn_kernel_t fattn_kernel = flash_attn_tile; + const int kq_stride = fattn_tile_get_kq_stride_host(D, cols_per_block, cc, warp_size); + launch_fattn + (ctx, dst, fattn_kernel, nwarps, nbytes_shared, kq_stride, true, true, false, warp_size); + return; + } + } +#endif // GGML_USE_HIP + if (Q->ne[1] > 16) { constexpr int cols_per_block = 32; + const int nwarps = fattn_tile_get_nthreads_host(cc, cols_per_block) / warp_size; fattn_kernel_t fattn_kernel = flash_attn_tile; const int kq_stride = fattn_tile_get_kq_stride_host(D, cols_per_block, cc, warp_size); launch_fattn @@ -619,6 +715,7 @@ static void launch_fattn_tile_switch_ncols(ggml_backend_cuda_context & ctx, ggml } constexpr int cols_per_block = 16; + const int nwarps = fattn_tile_get_nthreads_host(cc, cols_per_block) / warp_size; fattn_kernel_t fattn_kernel = flash_attn_tile; const int kq_stride = fattn_tile_get_kq_stride_host(D, cols_per_block, cc, warp_size); launch_fattn diff --git a/ggml/src/ggml-cuda/vendors/hip.h b/ggml/src/ggml-cuda/vendors/hip.h index 12bbee4556..37386afcd4 100644 --- a/ggml/src/ggml-cuda/vendors/hip.h +++ b/ggml/src/ggml-cuda/vendors/hip.h @@ -158,41 +158,41 @@ #define __CUDA_ARCH__ 1300 -#if defined(__gfx803__) || defined(__gfx900__) || defined(__gfx906__) -#define GCN -#endif - #if defined(__gfx900__) || defined(__gfx906__) #define GCN5 -#endif +#endif // defined(__gfx900__) || defined(__gfx906__) #if defined(__gfx803__) #define GCN4 -#endif +#endif // defined(__gfx803__) -#if defined(__gfx908__) || defined(__gfx90a__) || defined(__gfx942__) -#define CDNA // For the entire family -#endif +#if defined(GCN5) || defined(GCN4) +#define GCN +#endif // defined(GCN5) || defined(GCN4) #if defined(__gfx942__) #define CDNA3 -#endif +#endif // defined(__gfx942__) #if defined(__gfx90a__) #define CDNA2 -#endif +#endif // defined(__gfx90a__) #if defined(__gfx908__) #define CDNA1 -#endif +#endif // defined(__gfx908__) + +#if defined(CDNA3) || defined(CDNA2) || defined(CDNA1) +#define CDNA // For the entire family +#endif // defined(CDNA3) || defined(CDNA2) || defined(CDNA1) #if defined(__GFX12__) #define RDNA4 -#endif +#endif // defined(__GFX12__) #if defined(__GFX11__) #define RDNA3 -#endif +#endif // defined(__GFX11__) #if defined(__gfx1030__) || defined(__gfx1031__) || defined(__gfx1032__) || defined(__gfx1033__) || \ defined(__gfx1034__) || defined(__gfx1035__) || defined(__gfx1036__) || defined(__gfx1037__) @@ -201,7 +201,11 @@ #if defined(__gfx1010__) || defined(__gfx1012__) #define RDNA1 -#endif +#endif // defined(__gfx1010__) || defined(__gfx1012__) + +#if defined(RDNA4) || defined(RDNA3) || defined(RDNA2) || defined(RDNA1) +#define RDNA // For the entire family +#endif // defined(RDNA4) || defined(RDNA3) || defined(RDNA2) || defined(RDNA1) #ifndef __has_builtin #define __has_builtin(x) 0 From 8f8f2274ee3601fecf6e2d57b52f701c81bede21 Mon Sep 17 00:00:00 2001 From: Xuan-Son Nguyen Date: Thu, 18 Sep 2025 00:18:21 +0700 Subject: [PATCH 24/52] convert : add Llama4ForCausalLM (#16042) * convert : add Llama4ForCausalLM * handle swa * half working version * fix use_kq_norm * fix use_kq_norm --- convert_hf_to_gguf.py | 9 +++++++- src/llama-hparams.h | 2 +- src/llama-model.cpp | 48 ++++++++++++++++++++++++++++++++++--------- src/llama-model.h | 3 +++ 4 files changed, 50 insertions(+), 12 deletions(-) diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py index ce83f24695..7ddec48ad7 100755 --- a/convert_hf_to_gguf.py +++ b/convert_hf_to_gguf.py @@ -2393,7 +2393,10 @@ class SmolVLMModel(MmprojModel): return [] # skip other tensors -@ModelBase.register("Llama4ForConditionalGeneration") +@ModelBase.register( + "Llama4ForConditionalGeneration", + "Llama4ForCausalLM", +) class Llama4Model(LlamaModel): model_arch = gguf.MODEL_ARCH.LLAMA4 undo_permute = False @@ -2411,6 +2414,10 @@ class Llama4Model(LlamaModel): super().set_gguf_parameters() self.gguf_writer.add_interleave_moe_layer_step(self.hparams["interleave_moe_layer_step"]) self.gguf_writer.add_expert_feed_forward_length(self.hparams["intermediate_size_moe"]) + if "layer_types" in self.hparams: + if all(lt == "full_attention" for lt in self.hparams["layer_types"]): + # all layers are full attention (for MobileLLM), disable swa + self.gguf_writer.add_sliding_window(0) def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None): if name.startswith("language_model."): diff --git a/src/llama-hparams.h b/src/llama-hparams.h index 116d728e8c..202cbbd1b2 100644 --- a/src/llama-hparams.h +++ b/src/llama-hparams.h @@ -149,7 +149,7 @@ struct llama_hparams { bool causal_attn = true; bool use_alibi = false; bool attn_soft_cap = false; - bool use_kq_norm = true; + bool use_kq_norm = false; // for Classifiers uint32_t n_cls_out = 1; diff --git a/src/llama-model.cpp b/src/llama-model.cpp index 2be807a6a9..981e57083c 100644 --- a/src/llama-model.cpp +++ b/src/llama-model.cpp @@ -36,6 +36,7 @@ const char * llm_type_name(llm_type type) { case LLM_TYPE_80M: return "80M"; case LLM_TYPE_109M: return "109M"; case LLM_TYPE_137M: return "137M"; + case LLM_TYPE_140M: return "140M"; case LLM_TYPE_160M: return "160M"; case LLM_TYPE_190M: return "190M"; case LLM_TYPE_220M: return "220M"; @@ -44,6 +45,7 @@ const char * llm_type_name(llm_type type) { case LLM_TYPE_270M: return "270M"; case LLM_TYPE_335M: return "335M"; case LLM_TYPE_350M: return "350M"; + case LLM_TYPE_360M: return "360M"; case LLM_TYPE_410M: return "410M"; case LLM_TYPE_450M: return "450M"; case LLM_TYPE_475M: return "475M"; @@ -51,6 +53,7 @@ const char * llm_type_name(llm_type type) { case LLM_TYPE_700M: return "700M"; case LLM_TYPE_770M: return "770M"; case LLM_TYPE_780M: return "780M"; + case LLM_TYPE_950M: return "950M"; case LLM_TYPE_0_3B: return "0.3B"; case LLM_TYPE_0_5B: return "0.5B"; case LLM_TYPE_0_6B: return "0.6B"; @@ -622,19 +625,32 @@ void llama_model::load_hparams(llama_model_loader & ml) { ml.get_key(LLM_KV_EXPERT_FEED_FORWARD_LENGTH, hparams.n_ff_exp); ml.get_key(LLM_KV_INTERLEAVE_MOE_LAYER_STEP, hparams.n_moe_layer_step); - hparams.swa_type = LLAMA_SWA_TYPE_CHUNKED; - hparams.n_swa = 8192; // should this be a gguf kv? currently it's the same for Scout and Maverick - hparams.set_swa_pattern(4); // pattern: 3 chunked - 1 full + const bool found_swa = ml.get_key(LLM_KV_ATTENTION_SLIDING_WINDOW, hparams.n_swa, false); + if (found_swa && hparams.n_swa == 0) { + hparams.swa_type = LLAMA_SWA_TYPE_NONE; + hparams.n_no_rope_layer_step = hparams.n_layer; // always use rope + } else { + hparams.swa_type = LLAMA_SWA_TYPE_CHUNKED; + hparams.n_swa = 8192; + hparams.set_swa_pattern(4); // pattern: 3 chunked - 1 full + } switch (hparams.n_expert) { + case 0: { + // MobileLLM (no MoE) + switch (hparams.n_embd) { + case 2048: type = LLM_TYPE_140M; break; + case 4096: type = LLM_TYPE_360M; break; + case 6144: type = LLM_TYPE_950M; break; + default: type = LLM_TYPE_UNKNOWN; + } + } break; case 16: type = LLM_TYPE_17B_16E; break; case 128: type = LLM_TYPE_17B_128E; break; default: type = LLM_TYPE_UNKNOWN; } - if (type == LLM_TYPE_17B_128E) { - hparams.use_kq_norm = false; - } + hparams.use_kq_norm = type != LLM_TYPE_17B_128E; } break; case LLM_ARCH_ARCEE: { @@ -2454,9 +2470,8 @@ bool llama_model::load_tensors(llama_model_loader & ml) { output = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, TENSOR_DUPLICATED); } - GGML_ASSERT(hparams.n_moe_layer_step > 0 && "Llama 4 requires n_moe_layer_step > 0"); for (int i = 0; i < n_layer; ++i) { - bool is_moe_layer = (i + 1) % hparams.n_moe_layer_step == 0; + bool is_moe_layer = hparams.n_moe_layer_step > 0 && (i + 1) % hparams.n_moe_layer_step == 0; auto & layer = layers[i]; @@ -6328,6 +6343,14 @@ struct llm_build_llama : public llm_graph_context { cb(Kcur, "Kcur", il); cb(Vcur, "Vcur", il); + if (hparams.use_kq_norm) { + // Llama4TextL2Norm + Qcur = ggml_rms_norm(ctx0, Qcur, hparams.f_norm_rms_eps); + Kcur = ggml_rms_norm(ctx0, Kcur, hparams.f_norm_rms_eps); + cb(Qcur, "Qcur_normed", il); + cb(Kcur, "Kcur_normed", il); + } + cur = build_attn(inp_attn, model.layers[il].wo, model.layers[il].bo, Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, kq_scale, il); @@ -6435,7 +6458,8 @@ struct llm_build_llama_iswa : public llm_graph_context { for (int il = 0; il < n_layer; ++il) { ggml_tensor * inpSA = inpL; - const bool use_rope = (il + 1) % hparams.n_no_rope_layer_step != 0; + const bool use_rope = hparams.n_no_rope_layer_step > 0 && + (il + 1) % hparams.n_no_rope_layer_step != 0; // norm cur = build_norm(inpL, @@ -18981,7 +19005,11 @@ ggml_cgraph * llama_model::build_graph(const llm_graph_params & params) const { } break; case LLM_ARCH_LLAMA4: { - llm = std::make_unique(*this, params); + if (hparams.swa_type == LLAMA_SWA_TYPE_NONE) { + llm = std::make_unique(*this, params); + } else { + llm = std::make_unique(*this, params); + } } break; case LLM_ARCH_DECI: { diff --git a/src/llama-model.h b/src/llama-model.h index 10b1767f27..b1981978e3 100644 --- a/src/llama-model.h +++ b/src/llama-model.h @@ -28,6 +28,7 @@ enum llm_type { LLM_TYPE_80M, LLM_TYPE_109M, LLM_TYPE_137M, + LLM_TYPE_140M, LLM_TYPE_160M, LLM_TYPE_190M, LLM_TYPE_220M, @@ -36,6 +37,7 @@ enum llm_type { LLM_TYPE_270M, LLM_TYPE_335M, LLM_TYPE_350M, + LLM_TYPE_360M, LLM_TYPE_410M, LLM_TYPE_450M, LLM_TYPE_475M, @@ -43,6 +45,7 @@ enum llm_type { LLM_TYPE_700M, LLM_TYPE_770M, LLM_TYPE_780M, + LLM_TYPE_950M, LLM_TYPE_0_3B, LLM_TYPE_0_5B, LLM_TYPE_0_6B, From a7a98e0fffed794396b3fbad4dcdbbc184963645 Mon Sep 17 00:00:00 2001 From: Aleksander Grygier Date: Wed, 17 Sep 2025 19:29:13 +0200 Subject: [PATCH 25/52] SvelteKit-based WebUI (#14839) --- .editorconfig | 8 + .github/workflows/server.yml | 229 +- .gitignore | 4 + .windsurf/rules/css-architecture.md | 7 + .windsurf/rules/sveltekit-architecture.md | 48 + 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tools/server/webui/src/stories/ChatMessage.stories.svelte create mode 100644 tools/server/webui/src/stories/ChatSettingsDialog.stories.svelte create mode 100644 tools/server/webui/src/stories/ChatSidebar.stories.svelte create mode 100644 tools/server/webui/src/stories/Introduction.mdx create mode 100644 tools/server/webui/src/stories/MarkdownContent.stories.svelte create mode 100644 tools/server/webui/src/stories/fixtures/ai-tutorial.ts create mode 100644 tools/server/webui/src/stories/fixtures/api-docs.ts create mode 100644 tools/server/webui/src/stories/fixtures/assets/1.jpg create mode 100644 tools/server/webui/src/stories/fixtures/assets/beautiful-flowers-lotus.webp create mode 100644 tools/server/webui/src/stories/fixtures/assets/example.pdf create mode 100644 tools/server/webui/src/stories/fixtures/assets/hf-logo.svg create mode 100644 tools/server/webui/src/stories/fixtures/blog-post.ts create mode 100644 tools/server/webui/src/stories/fixtures/data-analysis.ts create mode 100644 tools/server/webui/src/stories/fixtures/empty.ts create mode 100644 tools/server/webui/src/stories/fixtures/math-formulas.ts create mode 100644 tools/server/webui/src/stories/fixtures/readme.ts create mode 100644 tools/server/webui/src/stories/fixtures/storybook-mocks.ts delete mode 100644 tools/server/webui/src/utils/app.context.tsx delete mode 100644 tools/server/webui/src/utils/common.tsx delete mode 100644 tools/server/webui/src/utils/llama-vscode.ts delete mode 100644 tools/server/webui/src/utils/misc.ts delete mode 100644 tools/server/webui/src/utils/storage.ts delete mode 100644 tools/server/webui/src/utils/types.ts delete mode 100644 tools/server/webui/src/vite-env.d.ts create mode 100644 tools/server/webui/static/favicon.svg create mode 100644 tools/server/webui/static/loading.html create mode 100644 tools/server/webui/svelte.config.js delete mode 100644 tools/server/webui/tailwind.config.js delete mode 100644 tools/server/webui/tsconfig.app.json delete mode 100644 tools/server/webui/tsconfig.node.json create mode 100644 tools/server/webui/vitest-setup-client.ts diff --git a/.editorconfig b/.editorconfig index c90b171f55..0722ac73c8 100644 --- a/.editorconfig +++ b/.editorconfig @@ -52,3 +52,11 @@ insert_final_newline = unset [vendor/miniaudio/miniaudio.h] trim_trailing_whitespace = unset insert_final_newline = unset + +[tools/server/webui/**] +indent_style = unset +indent_size = unset +end_of_line = unset +charset = unset +trim_trailing_whitespace = unset +insert_final_newline = unset diff --git a/.github/workflows/server.yml b/.github/workflows/server.yml index f6da488576..1ea1300c2e 100644 --- a/.github/workflows/server.yml +++ b/.github/workflows/server.yml @@ -76,51 +76,206 @@ jobs: run: | pip install -r tools/server/tests/requirements.txt - # Setup nodejs (to be used for verifying bundled index.html) - - uses: actions/setup-node@v4 + webui-setup: + name: WebUI Setup + runs-on: ubuntu-latest + steps: + - name: Checkout code + uses: actions/checkout@v4 with: - node-version: '22.11.0' + fetch-depth: 0 + ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }} - - name: WebUI - Install dependencies - id: webui_lint + - name: Setup Node.js + uses: actions/setup-node@v4 + with: + node-version: "22" + cache: "npm" + cache-dependency-path: "tools/server/webui/package-lock.json" + + - name: Cache node_modules + uses: actions/cache@v4 + id: cache-node-modules + with: + path: tools/server/webui/node_modules + key: ${{ runner.os }}-node-modules-${{ hashFiles('tools/server/webui/package-lock.json') }} + restore-keys: | + ${{ runner.os }}-node-modules- + + - name: Install dependencies + if: steps.cache-node-modules.outputs.cache-hit != 'true' + run: npm ci + working-directory: tools/server/webui + + webui-check: + needs: webui-setup + name: WebUI Check + runs-on: ubuntu-latest + steps: + - name: Checkout code + uses: actions/checkout@v4 + with: + fetch-depth: 0 + ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }} + + - name: Setup Node.js + uses: actions/setup-node@v4 + with: + node-version: "22" + + - name: Restore node_modules cache + uses: actions/cache@v4 + with: + path: tools/server/webui/node_modules + key: ${{ runner.os }}-node-modules-${{ hashFiles('tools/server/webui/package-lock.json') }} + restore-keys: | + ${{ runner.os }}-node-modules- + + - name: Run type checking + run: npm run check + working-directory: tools/server/webui + + - name: Run linting + run: npm run lint + working-directory: tools/server/webui + + webui-build: + needs: webui-check + name: WebUI Build + runs-on: ubuntu-latest + steps: + - name: Checkout code + uses: actions/checkout@v4 + with: + fetch-depth: 0 + ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }} + + - name: Setup Node.js + uses: actions/setup-node@v4 + with: + node-version: "22" + + - name: Restore node_modules cache + uses: actions/cache@v4 + with: + path: tools/server/webui/node_modules + key: ${{ runner.os }}-node-modules-${{ hashFiles('tools/server/webui/package-lock.json') }} + restore-keys: | + ${{ runner.os }}-node-modules- + + - name: Build application + run: npm run build + working-directory: tools/server/webui + + webui-tests: + needs: webui-build + name: Run WebUI tests + permissions: + contents: read + + runs-on: ubuntu-latest + + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Setup Node.js + uses: actions/setup-node@v4 + with: + node-version: "22" + + - name: Restore node_modules cache + uses: actions/cache@v4 + with: + path: tools/server/webui/node_modules + key: ${{ runner.os }}-node-modules-${{ hashFiles('tools/server/webui/package-lock.json') }} + restore-keys: | + ${{ runner.os }}-node-modules- + + - name: Install Playwright browsers + run: npx playwright install --with-deps + working-directory: tools/server/webui + + - name: Build Storybook + run: npm run build-storybook + working-directory: tools/server/webui + + - name: Run Client tests + run: npm run test:client + working-directory: tools/server/webui + + - name: Run Server tests + run: npm run test:server + working-directory: tools/server/webui + + - name: Run UI tests + run: npm run test:ui + working-directory: tools/server/webui + + - name: Run E2E tests + run: npm run test:e2e + working-directory: tools/server/webui + + server-build: + needs: [webui-tests] + runs-on: ubuntu-latest + + strategy: + matrix: + sanitizer: [ADDRESS, UNDEFINED] # THREAD is broken + build_type: [RelWithDebInfo] + include: + - build_type: Release + sanitizer: "" + fail-fast: false # While -DLLAMA_SANITIZE_THREAD=ON is broken + + steps: + - name: Dependencies + id: depends run: | - cd tools/server/webui - npm ci + sudo apt-get update + sudo apt-get -y install \ + build-essential \ + xxd \ + git \ + cmake \ + curl \ + wget \ + language-pack-en \ + libcurl4-openssl-dev - - name: WebUI - Check code format - id: webui_format + - name: Clone + id: checkout + uses: actions/checkout@v4 + with: + fetch-depth: 0 + ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }} + + - name: Python setup + id: setup_python + uses: actions/setup-python@v5 + with: + python-version: '3.11' + + - name: Tests dependencies + id: test_dependencies run: | - git config --global --add safe.directory $(realpath .) - cd tools/server/webui - git status + pip install -r tools/server/tests/requirements.txt - npm run format - git status - modified_files="$(git status -s)" - echo "Modified files: ${modified_files}" - if [ -n "${modified_files}" ]; then - echo "Files do not follow coding style. To fix: npm run format" - echo "${modified_files}" - exit 1 - fi + - name: Setup Node.js for WebUI + uses: actions/setup-node@v4 + with: + node-version: "22" + cache: "npm" + cache-dependency-path: "tools/server/webui/package-lock.json" - - name: Verify bundled index.html - id: verify_server_index_html - run: | - git config --global --add safe.directory $(realpath .) - cd tools/server/webui - git status + - name: Install WebUI dependencies + run: npm ci + working-directory: tools/server/webui - npm run build - git status - modified_files="$(git status -s)" - echo "Modified files: ${modified_files}" - if [ -n "${modified_files}" ]; then - echo "Repository is dirty or server/webui is not built as expected" - echo "Hint: You may need to follow Web UI build guide in server/README.md" - echo "${modified_files}" - exit 1 - fi + - name: Build WebUI + run: npm run build + working-directory: tools/server/webui - name: Build (no OpenMP) id: cmake_build_no_openmp diff --git a/.gitignore b/.gitignore index 595831accb..e1ecdb7a81 100644 --- a/.gitignore +++ b/.gitignore @@ -148,3 +148,7 @@ poetry.toml /run-vim.sh /run-chat.sh .ccache/ + +# Code Workspace +*.code-workspace + diff --git a/.windsurf/rules/css-architecture.md b/.windsurf/rules/css-architecture.md new file mode 100644 index 0000000000..10a183585c --- /dev/null +++ b/.windsurf/rules/css-architecture.md @@ -0,0 +1,7 @@ +--- +trigger: manual +--- + +#### Tailwind & CSS + +- We are using Tailwind v4 which uses oklch colors so we now want to refer to the CSS vars directly, without wrapping it with any color function like `hsla/hsl`, `rgba` etc. diff --git a/.windsurf/rules/sveltekit-architecture.md b/.windsurf/rules/sveltekit-architecture.md new file mode 100644 index 0000000000..c2c0aa07ce --- /dev/null +++ b/.windsurf/rules/sveltekit-architecture.md @@ -0,0 +1,48 @@ +--- +trigger: manual +--- + +# Coding rules + +## Svelte & SvelteKit + +### Services vs Stores Separation Pattern + +#### `lib/services/` - Pure Business Logic + +- **Purpose**: Stateless business logic and external communication +- **Contains**: + - API calls to external services (ApiService) + - Pure business logic functions (ChatService, etc.) +- **Rules**: + - NO Svelte runes ($state, $derived, $effect) + - NO reactive state management + - Pure functions and classes only + - Can import types but not stores + - Focus on "how" - implementation details + +#### `lib/stores/` - Reactive State Management + +- **Purpose**: Svelte-specific reactive state with runes +- **Contains**: + - Reactive state classes with $state, $derived, $effect + - Database operations (DatabaseStore) + - UI-focused state management + - Store orchestration logic +- **Rules**: + - USE Svelte runes for reactivity + - Import and use services for business logic + - NO direct database operations + - NO direct API calls (use services) + - Focus on "what" - reactive state for UI + +#### Enforcement + +- Services should be testable without Svelte +- Stores should leverage Svelte's reactivity system +- Clear separation: services handle data, stores handle state +- Services can be reused across multiple stores + +#### Misc + +- Always use `let` for $derived state variables diff --git a/.windsurf/rules/tests.md b/.windsurf/rules/tests.md new file mode 100644 index 0000000000..e388fa9544 --- /dev/null +++ b/.windsurf/rules/tests.md @@ -0,0 +1,9 @@ +--- +trigger: manual +--- + +# Automated Tests + +## General rules + +- NEVER include any test code in the production code - we should always have it in a separate dedicated files diff --git a/.windsurf/rules/typescript-architecture.md b/.windsurf/rules/typescript-architecture.md new file mode 100644 index 0000000000..a61ff6b98f --- /dev/null +++ b/.windsurf/rules/typescript-architecture.md @@ -0,0 +1,7 @@ +--- +trigger: manual +--- + +## TypeScript + +- Add JSDocs for functions diff --git a/tools/server/public/index.html.gz b/tools/server/public/index.html.gz index 0e3e1f9834a7f22c5c3bc4445914f20cc1c6579d..909fa1cceb81d4030c5a11b475304ba206a8d95b 100644 GIT binary patch literal 842295 zcmV($K;yq3iwFP!000020PKBxcN;g7@83J0g5x>4YdIv%ryle;XB5kEG!x3>SRO}? za&lT^i)@LnWs{ajUER-qe^q!i(2ahOl4p|Hne19@pin3j3WWktDE#@4mC7GVrPE;$ zmhgXGDGVlqkzcwD@Xy6E81+lj%hFgOUyj)Dj-XiFEqtU7~@F)J< zTloFb#fl4v(zE%r=Z7JcI+~Uy(?!Ye2MYiI0awxw=6-K6S`ozQv^4gv{Zen}O$L5g zF3tT*e_mQl8R3(U{zd7-@sm=B0>N}r3MQQX(66<;Zard&|kcKvRqtN_MeoVbJi%BT%+>Q z%O^o^I(bqWf{>R_`rg9p1Y>XDKMy|-zP=rgUR-#gzuPMR{ri)~r`5Mj@8gd(@2D1Z zuRb)6gKt|GA8(hvbuI9||FPCPntuMF*>Cn&?Phn?{@fe)K6kGUZ@RAz*8OoWIDRu6 zc^~`JepG(;3BP-dlhvn>|5)}K!_WO!_0gxR>)NOBUxV(e`t{lPyWoe@!Of?S?-p;5 z4sT9^TI=oUyVcv%>znSIe<1%XIR5_A?9)&ER~OB}!SU7Mp!@1@b#i((uxXsNF5Zlm zUKXvV*X_6O4+Pxmc<^aF3NJw4#rR

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zoJa9kG?|DeBI$k2ez#NSd#}!;IN%jOiO2WtRr9qvQnYVgVAgsGRZX4ctAOYs&BXgl0K~&0pkiC7 z3BPmy@E$xO=RZwY)hgUX1$ML+AA~HARFoLeU0xKJ(|vADTkhn8hFZmr`C@|%m)3OJ zS`h06li+X~F9Eb#GKZagYhgIZ--dn@fGqpsWOZ>abCi2n~F&-^h& zhL_%pU_GW@KW=x~f1$hDqhPf;0l7#ht37-d$GKO={nqf2wwlaU(2|K4`?wAp4Umi+ z#kTQM`uuT$mRw9Y+g5IEf(+5RPn0T_Jc@4e(blXv#ghLFQNvA6pR1d{OfQF8PV5Hp zw%ifoz_(7>dH8@vPwO9WDU+w`Gae%;)GAg}Ma?a5O_l)&N95{8UcLeRdVK7o+FL_H zT}?#bQG@}qi3;SgbkV|N8C|!+>rQJ-T<~VC);nKAAyJ#Y@I)cnjH6pm=Mcdi5F6-! zV|x9_y8K$>-q2&9GoV_0_ATqB-nf(J&F5R{>o4dLvqnBYFUe{{1e+w?pX0;vZ1m3b z|M+synarf+{!o>!ydj z;jC*$0qcf?E=wnGG%#e;D2a!ywkU)^L2%*?<6}_K`GbNS{H1jHPrbd&mVSDfhc@o5 znJ6WE$MJpEA9U-4j4P%ay@gg2`2sjFyWecFO)u>?v*V7R#k*8nc755-$ox?o%xp0I zs67HWd^>Vmz4sx}9uRIYI2xjalMmS#$k%DtwgFluCk+25dl+be7&Fp9AuzGo&}w+= zDY5z(TQiM=r7r*LSRux@e;geA>$u--J*X>5EEilp*uM_!hkt*OXx}g2{&mc~Ce}10 Rk{bNu{{T73m*zuWLjVJyM4$iw diff --git a/tools/server/server.cpp b/tools/server/server.cpp index 519704fad7..5e5698e672 100644 --- a/tools/server/server.cpp +++ b/tools/server/server.cpp @@ -5261,6 +5261,42 @@ int main(int argc, char ** argv) { svr->Get (params.api_prefix + "/slots", handle_slots); svr->Post(params.api_prefix + "/slots/:id_slot", handle_slots_action); + // SPA fallback route - serve index.html for any route that doesn't match API endpoints + // This enables client-side routing for dynamic routes like /chat/[id] + if (params.webui && params.public_path.empty()) { + // Only add fallback when using embedded static files + svr->Get(".*", [](const httplib::Request & req, httplib::Response & res) { + // Skip API routes - they should have been handled above + if (req.path.find("/v1/") != std::string::npos || + req.path.find("/health") != std::string::npos || + req.path.find("/metrics") != std::string::npos || + req.path.find("/props") != std::string::npos || + req.path.find("/models") != std::string::npos || + req.path.find("/api/tags") != std::string::npos || + req.path.find("/completions") != std::string::npos || + req.path.find("/chat/completions") != std::string::npos || + req.path.find("/embeddings") != std::string::npos || + req.path.find("/tokenize") != std::string::npos || + req.path.find("/detokenize") != std::string::npos || + req.path.find("/lora-adapters") != std::string::npos || + req.path.find("/slots") != std::string::npos) { + return false; // Let other handlers process API routes + } + + // Serve index.html for all other routes (SPA fallback) + if (req.get_header_value("Accept-Encoding").find("gzip") == std::string::npos) { + res.set_content("Error: gzip is not supported by this browser", "text/plain"); + } else { + res.set_header("Content-Encoding", "gzip"); + // COEP and COOP headers, required by pyodide (python interpreter) + res.set_header("Cross-Origin-Embedder-Policy", "require-corp"); + res.set_header("Cross-Origin-Opener-Policy", "same-origin"); + res.set_content(reinterpret_cast(index_html_gz), index_html_gz_len, "text/html; charset=utf-8"); + } + return false; + }); + } + // // Start the server // diff --git a/tools/server/tests/unit/test_basic.py b/tools/server/tests/unit/test_basic.py index 58ade52be6..829af2ebe7 100644 --- a/tools/server/tests/unit/test_basic.py +++ b/tools/server/tests/unit/test_basic.py @@ -92,7 +92,7 @@ def test_no_webui(): url = f"http://{server.server_host}:{server.server_port}" res = requests.get(url) assert res.status_code == 200 - assert "" in res.text + assert "" in res.text server.stop() # with --no-webui diff --git a/tools/server/webui/.gitignore b/tools/server/webui/.gitignore index a547bf36d8..cc54bb717f 100644 --- a/tools/server/webui/.gitignore +++ b/tools/server/webui/.gitignore @@ -1,24 +1,27 @@ -# Logs -logs -*.log -npm-debug.log* -yarn-debug.log* -yarn-error.log* -pnpm-debug.log* -lerna-debug.log* - +test-results node_modules -dist -dist-ssr -*.local -# Editor directories and files -.vscode/* -!.vscode/extensions.json -.idea +# Output +.output +.vercel +.netlify +.wrangler +/.svelte-kit +/build + +# OS .DS_Store -*.suo -*.ntvs* -*.njsproj -*.sln -*.sw? +Thumbs.db + +# Env +.env +.env.* +!.env.example +!.env.test + +# Vite +vite.config.js.timestamp-* +vite.config.ts.timestamp-* + +*storybook.log +storybook-static diff --git a/tools/server/webui/.npmrc b/tools/server/webui/.npmrc new file mode 100644 index 0000000000..b6f27f1359 --- /dev/null +++ b/tools/server/webui/.npmrc @@ -0,0 +1 @@ +engine-strict=true diff --git a/tools/server/webui/.prettierignore b/tools/server/webui/.prettierignore index c0cb165b37..7d74fe2468 100644 --- a/tools/server/webui/.prettierignore +++ b/tools/server/webui/.prettierignore @@ -1,10 +1,9 @@ -**/.vscode -**/.github -**/.git -**/.svn -**/.hg -**/node_modules -**/dist -**/build +# Package Managers +package-lock.json +pnpm-lock.yaml +yarn.lock +bun.lock +bun.lockb -*.config.js +# Miscellaneous +/static/ diff --git a/tools/server/webui/.prettierrc b/tools/server/webui/.prettierrc new file mode 100644 index 0000000000..8103a0b5d2 --- /dev/null +++ b/tools/server/webui/.prettierrc @@ -0,0 +1,16 @@ +{ + "useTabs": true, + "singleQuote": true, + "trailingComma": "none", + "printWidth": 100, + "plugins": ["prettier-plugin-svelte", "prettier-plugin-tailwindcss"], + "overrides": [ + { + "files": "*.svelte", + "options": { + "parser": "svelte" + } + } + ], + "tailwindStylesheet": "./src/app.css" +} diff --git a/tools/server/webui/.storybook/ModeWatcherDecorator.svelte b/tools/server/webui/.storybook/ModeWatcherDecorator.svelte new file mode 100644 index 0000000000..8bded8b3f1 --- /dev/null +++ b/tools/server/webui/.storybook/ModeWatcherDecorator.svelte @@ -0,0 +1,36 @@ + + + + +{#if children} + {@const Component = children} + + +{/if} diff --git a/tools/server/webui/.storybook/TooltipProviderDecorator.svelte b/tools/server/webui/.storybook/TooltipProviderDecorator.svelte new file mode 100644 index 0000000000..9aad1eaa4a --- /dev/null +++ b/tools/server/webui/.storybook/TooltipProviderDecorator.svelte @@ -0,0 +1,13 @@ + + + + {@render children()} + diff --git a/tools/server/webui/.storybook/main.ts b/tools/server/webui/.storybook/main.ts new file mode 100644 index 0000000000..7145bcb7eb --- /dev/null +++ b/tools/server/webui/.storybook/main.ts @@ -0,0 +1,17 @@ +import type { StorybookConfig } from '@storybook/sveltekit'; + +const config: StorybookConfig = { + stories: ['../src/**/*.mdx', '../src/**/*.stories.@(js|ts|svelte)'], + addons: [ + '@storybook/addon-svelte-csf', + '@chromatic-com/storybook', + '@storybook/addon-docs', + '@storybook/addon-a11y', + '@storybook/addon-vitest' + ], + framework: { + name: '@storybook/sveltekit', + options: {} + } +}; +export default config; diff --git a/tools/server/webui/.storybook/preview.ts b/tools/server/webui/.storybook/preview.ts new file mode 100644 index 0000000000..fb91386af4 --- /dev/null +++ b/tools/server/webui/.storybook/preview.ts @@ -0,0 +1,34 @@ +import type { Preview } from '@storybook/sveltekit'; +import '../src/app.css'; +import ModeWatcherDecorator from './ModeWatcherDecorator.svelte'; +import TooltipProviderDecorator from './TooltipProviderDecorator.svelte'; + +const preview: Preview = { + parameters: { + controls: { + matchers: { + color: /(background|color)$/i, + date: /Date$/i + } + }, + backgrounds: { + disable: true + } + }, + decorators: [ + (story) => ({ + Component: ModeWatcherDecorator, + props: { + children: story + } + }), + (story) => ({ + Component: TooltipProviderDecorator, + props: { + children: story + } + }) + ] +}; + +export default preview; diff --git a/tools/server/webui/.storybook/vitest.setup.ts b/tools/server/webui/.storybook/vitest.setup.ts new file mode 100644 index 0000000000..e0c1753c84 --- /dev/null +++ b/tools/server/webui/.storybook/vitest.setup.ts @@ -0,0 +1,11 @@ +import { setProjectAnnotations } from '@storybook/sveltekit'; +import * as previewAnnotations from './preview'; +import { beforeAll } from 'vitest'; + +const project = setProjectAnnotations([previewAnnotations]); + +beforeAll(async () => { + if (project.beforeAll) { + await project.beforeAll(); + } +}); diff --git a/tools/server/webui/README.md b/tools/server/webui/README.md new file mode 100644 index 0000000000..9d16f34d86 --- /dev/null +++ b/tools/server/webui/README.md @@ -0,0 +1,66 @@ +# llama.cpp Web UI + +A modern, feature-rich web interface for llama.cpp built with SvelteKit. This UI provides an intuitive chat interface with advanced file handling, conversation management, and comprehensive model interaction capabilities. + +## Features + +- **Modern Chat Interface** - Clean, responsive design with dark/light mode +- **File Attachments** - Support for images, text files, PDFs, and audio with rich previews and drag-and-drop support +- **Conversation Management** - Create, edit, branch, and search conversations +- **Advanced Markdown** - Code highlighting, math formulas (KaTeX), and content blocks +- **Reasoning Content** - Support for models with thinking blocks +- **Keyboard Shortcuts** - Keyboard navigation (Shift+Ctrl/Cmd+O for new chat, Shift+Ctrl/Cmdt+E for edit conversation, Shift+Ctrl/Cmdt+D for delete conversation, Ctrl/Cmd+K for search, Ctrl/Cmd+V for paste, Ctrl/Cmd+B for opening/collapsing sidebar) +- **Request Tracking** - Monitor processing with slots endpoint integration +- **UI Testing** - Storybook component library with automated tests + +## Development + +Install dependencies: + +```bash +npm install +``` + +Start the development server + Storybook: + +```bash +npm run dev +``` + +This will start both the SvelteKit dev server and Storybook on port 6006. + +## Building + +Create a production build: + +```bash +npm run build +``` + +The build outputs static files to `../public` directory for deployment with llama.cpp server. + +## Testing + +Run the test suite: + +```bash +# E2E tests +npm run test:e2e + +# Unit tests +npm run test:unit + +# UI tests +npm run test:ui + +# All tests +npm run test +``` + +## Architecture + +- **Framework**: SvelteKit with Svelte 5 runes +- **Components**: ShadCN UI + bits-ui design system +- **Database**: IndexedDB with Dexie for local storage +- **Build**: Static adapter for deployment with llama.cpp server +- **Testing**: Playwright (E2E) + Vitest (unit) + Storybook (components) diff --git a/tools/server/webui/components.json b/tools/server/webui/components.json new file mode 100644 index 0000000000..224bd70acf --- /dev/null +++ b/tools/server/webui/components.json @@ -0,0 +1,16 @@ +{ + "$schema": "https://shadcn-svelte.com/schema.json", + "tailwind": { + "css": "src/app.css", + "baseColor": "neutral" + }, + "aliases": { + "components": "$lib/components", + "utils": "$lib/components/ui/utils", + "ui": "$lib/components/ui", + "hooks": "$lib/hooks", + "lib": "$lib" + }, + "typescript": true, + "registry": "https://shadcn-svelte.com/registry" +} diff --git a/tools/server/webui/e2e/demo.test.ts b/tools/server/webui/e2e/demo.test.ts new file mode 100644 index 0000000000..9985ce113e --- /dev/null +++ b/tools/server/webui/e2e/demo.test.ts @@ -0,0 +1,6 @@ +import { expect, test } from '@playwright/test'; + +test('home page has expected h1', async ({ page }) => { + await page.goto('/'); + await expect(page.locator('h1')).toBeVisible(); +}); diff --git a/tools/server/webui/eslint.config.js b/tools/server/webui/eslint.config.js index 7c0d39b89b..5baea57f33 100644 --- a/tools/server/webui/eslint.config.js +++ b/tools/server/webui/eslint.config.js @@ -1,26 +1,49 @@ -import js from '@eslint/js' -import globals from 'globals' -import reactHooks from 'eslint-plugin-react-hooks' -import reactRefresh from 'eslint-plugin-react-refresh' -import tseslint from 'typescript-eslint' +// For more info, see https://github.com/storybookjs/eslint-plugin-storybook#configuration-flat-config-format +import storybook from 'eslint-plugin-storybook'; -export default tseslint.config( - { ignores: ['dist'] }, - { - extends: [js.configs.recommended, ...tseslint.configs.recommended], - files: ['**/*.{ts,tsx}'], - languageOptions: { - ecmaVersion: 2020, - globals: globals.browser, - }, - plugins: { - 'react-hooks': reactHooks, - 'react-refresh': reactRefresh, - }, - rules: { - ...reactHooks.configs.recommended.rules, - 'react-refresh/only-export-components': 'off', - '@typescript-eslint/no-unused-vars': 'off', - }, - }, -) +import prettier from 'eslint-config-prettier'; +import { includeIgnoreFile } from '@eslint/compat'; +import js from '@eslint/js'; +import svelte from 'eslint-plugin-svelte'; +import globals from 'globals'; +import { fileURLToPath } from 'node:url'; +import ts from 'typescript-eslint'; +import svelteConfig from './svelte.config.js'; + +const gitignorePath = fileURLToPath(new URL('./.gitignore', import.meta.url)); + +export default ts.config( + includeIgnoreFile(gitignorePath), + js.configs.recommended, + ...ts.configs.recommended, + ...svelte.configs.recommended, + prettier, + ...svelte.configs.prettier, + { + languageOptions: { + globals: { ...globals.browser, ...globals.node } + }, + rules: { + // typescript-eslint strongly recommend that you do not use the no-undef lint rule on TypeScript projects. + // see: https://typescript-eslint.io/troubleshooting/faqs/eslint/#i-get-errors-from-the-no-undef-rule-about-global-variables-not-being-defined-even-though-there-are-no-typescript-errors + 'no-undef': 'off', + 'svelte/no-at-html-tags': 'off' + } + }, + { + files: ['**/*.svelte', '**/*.svelte.ts', '**/*.svelte.js'], + languageOptions: { + parserOptions: { + projectService: true, + extraFileExtensions: ['.svelte'], + parser: ts.parser, + svelteConfig + } + } + }, + { + // Exclude Storybook files from main ESLint rules + ignores: ['.storybook/**/*'] + }, + storybook.configs['flat/recommended'] +); diff --git a/tools/server/webui/index.html b/tools/server/webui/index.html deleted file mode 100644 index 471f46b3ad..0000000000 --- a/tools/server/webui/index.html +++ /dev/null @@ -1,16 +0,0 @@ - - - - - - - 🦙 llama.cpp - chat - - -

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b/tools/server/webui/package.json index 8076840324..30c7cd15c6 100644 --- a/tools/server/webui/package.json +++ b/tools/server/webui/package.json @@ -1,66 +1,90 @@ { - "name": "webui", - "private": true, - "version": "0.0.0", - "type": "module", - "scripts": { - "dev": "vite", - "build": "npm run format && tsc -b && vite build", - "format": "eslint . && prettier --write .", - "lint": "eslint .", - "preview": "vite preview" - }, - "dependencies": { - "@heroicons/react": "^2.2.0", - "@sec-ant/readable-stream": "^0.6.0", - "@tailwindcss/postcss": "^4.1.1", - "@tailwindcss/vite": "^4.1.1", - "@vscode/markdown-it-katex": "^1.1.1", - "autoprefixer": "^10.4.20", - "daisyui": "^5.0.12", - "dexie": "^4.0.11", - "highlight.js": "^11.10.0", - "katex": "^0.16.15", - "pdfjs-dist": "^5.2.133", - "postcss": "^8.4.49", - "react": "^18.3.1", - "react-dom": "^18.3.1", - "react-dropzone": "^14.3.8", - "react-hot-toast": "^2.5.2", - "react-markdown": "^9.0.3", - "react-router": "^7.1.5", - "rehype-highlight": "^7.0.2", - "rehype-katex": "^7.0.1", - "remark-breaks": "^4.0.0", - "remark-gfm": "^4.0.0", - "remark-math": "^6.0.0", - "tailwindcss": "^4.1.1", - "textlinestream": "^1.1.1", - "vite-plugin-singlefile": "^2.0.3" - }, - "devDependencies": { - "@eslint/js": "^9.17.0", - "@types/markdown-it": "^14.1.2", - "@types/node": "^22.13.1", - "@types/react": "^18.3.18", - "@types/react-dom": "^18.3.5", - "@vitejs/plugin-react": "^4.3.4", - "eslint": "^9.17.0", - "eslint-plugin-react-hooks": "^5.0.0", - "eslint-plugin-react-refresh": "^0.4.16", - "fflate": "^0.8.2", - "globals": "^15.14.0", - "prettier": "^3.4.2", - "sass-embedded": "^1.83.4", - "typescript": "~5.6.2", - "typescript-eslint": "^8.18.2", - "vite": "^6.0.5" - }, - "prettier": { - "trailingComma": "es5", - "tabWidth": 2, - "semi": true, - "singleQuote": true, - "bracketSameLine": false - } + "name": "webui", + "private": true, + "version": "1.0.0", + "type": "module", + "scripts": { + "dev": "vite dev --host 0.0.0.0 & storybook dev -p 6006 --ci", + "build": "vite build && ./scripts/post-build.sh", + "preview": "vite preview", + "prepare": "svelte-kit sync || echo ''", + "check": "svelte-kit sync && svelte-check --tsconfig ./tsconfig.json", + "check:watch": "svelte-kit sync && svelte-check --tsconfig ./tsconfig.json --watch", + "reset": "rm -rf .svelte-kit node_modules", + "format": "prettier --write .", + "lint": "prettier --check . && eslint .", + "test": "npm run test:ui -- --run && npm run test:client -- --run && npm run test:server -- --run && npm run test:e2e", + "test:e2e": "playwright test", + "test:client": "vitest --project=client", + "test:server": "vitest --project=server", + "test:ui": "vitest --project=ui", + "test:unit": "vitest", + "storybook": "storybook dev -p 6006", + "build-storybook": "storybook build" + }, + "devDependencies": { + "@chromatic-com/storybook": "^4.0.1", + "@eslint/compat": "^1.2.5", + "@eslint/js": "^9.18.0", + "@internationalized/date": "^3.8.2", + "@lucide/svelte": "^0.515.0", + "@playwright/test": "^1.49.1", + "@storybook/addon-a11y": "^9.0.17", + "@storybook/addon-docs": "^9.0.17", + "@storybook/addon-svelte-csf": "^5.0.7", + "@storybook/addon-vitest": "^9.0.17", + "@storybook/sveltekit": "^9.0.17", + "@sveltejs/adapter-static": "^3.0.8", + "@sveltejs/kit": "^2.22.0", + "@sveltejs/vite-plugin-svelte": "^6.0.0", + "@tailwindcss/forms": "^0.5.9", + "@tailwindcss/typography": "^0.5.15", + "@tailwindcss/vite": "^4.0.0", + "@types/node": "^22", + "@vitest/browser": "^3.2.3", + "bits-ui": "^2.8.11", + "clsx": "^2.1.1", + "dexie": "^4.0.11", + "eslint": "^9.18.0", + "eslint-config-prettier": "^10.0.1", + "eslint-plugin-storybook": "^9.0.17", + "eslint-plugin-svelte": "^3.0.0", + "fflate": "^0.8.2", + "globals": "^16.0.0", + "mdsvex": "^0.12.3", + "playwright": "^1.53.0", + "prettier": "^3.4.2", + "prettier-plugin-svelte": "^3.3.3", + "prettier-plugin-tailwindcss": "^0.6.11", + "rehype-katex": "^7.0.1", + "remark-math": "^6.0.0", + "storybook": "^9.0.17", + "svelte": "^5.0.0", + "svelte-check": "^4.0.0", + "tailwind-merge": "^3.3.1", + "tailwind-variants": "^1.0.0", + "tailwindcss": "^4.0.0", + "tw-animate-css": "^1.3.5", + "typescript": "^5.0.0", + "typescript-eslint": "^8.20.0", + "uuid": "^13.0.0", + "vite": "^7.0.4", + "vite-plugin-devtools-json": "^0.2.0", + "vitest": "^3.2.3", + "vitest-browser-svelte": "^0.1.0" + }, + "dependencies": { + "highlight.js": "^11.11.1", + "mode-watcher": "^1.1.0", + "pdfjs-dist": "^5.4.54", + "rehype-highlight": "^7.0.2", + "rehype-stringify": "^10.0.1", + "remark": "^15.0.1", + "remark-breaks": "^4.0.0", + "remark-gfm": "^4.0.1", + "remark-html": "^16.0.1", + "remark-rehype": "^11.1.2", + "svelte-sonner": "^1.0.5", + "unist-util-visit": "^5.0.0" + } } diff --git a/tools/server/webui/playwright.config.ts b/tools/server/webui/playwright.config.ts new file mode 100644 index 0000000000..90ca19b09f --- /dev/null +++ b/tools/server/webui/playwright.config.ts @@ -0,0 +1,9 @@ +import { defineConfig } from '@playwright/test'; + +export default defineConfig({ + webServer: { + command: 'npm run build && npx http-server ../public -p 8181', + port: 8181 + }, + testDir: 'e2e' +}); diff --git a/tools/server/webui/postcss.config.js b/tools/server/webui/postcss.config.js deleted file mode 100644 index fb05b5692b..0000000000 --- a/tools/server/webui/postcss.config.js +++ /dev/null @@ -1,5 +0,0 @@ -export default { - plugins: { - "@tailwindcss/postcss": {}, - }, -} diff --git a/tools/server/webui/public/demo-conversation.json b/tools/server/webui/public/demo-conversation.json deleted file mode 100644 index 338b4aea59..0000000000 --- a/tools/server/webui/public/demo-conversation.json +++ /dev/null @@ -1,33 +0,0 @@ -{ - "demo": true, - "id": "conv-1734086746930", - "lastModified": 1734087548943, - "messages": [ - { - "id": 1734086764521, - "role": "user", - "content": "this is a demo conversation, used in dev mode" - }, - { - "id": 1734087548327, - "role": "assistant", - "content": "This is the formula:\n\n$\\frac{e^{x_i}}{\\sum_{j=1}^{n}e^{x_j}}$\n\nGiven an input vector \\(\\mathbf{x} = [x_1, x_2, \\ldots, x_n]\\)\n\n\\[\ny_i = \\frac{e^{x_i}}{\\sum_{j=1}^n e^{x_j}}\n\\]\n\n$2x + y = z$\n\nCode block latex:\n```latex\n\\frac{e^{x_i}}{\\sum_{j=1}^{n}e^{x_j}}\n```\n\nTest dollar sign: $1234 $4567\n\nInvalid latex syntax: $E = mc^$ and $$E = mc^$$", - "timings": { - "prompt_n": 1, - "prompt_ms": 28.923, - "predicted_n": 25, - "predicted_ms": 573.016 - } - }, - { - "id": 1734087548328, - "role": "user", - "content": "this is a demo conversation, used in dev mode" - }, - { - "id": 1734087548329, - "role": "assistant", - "content": "Code block:\n```js\nconsole.log('hello world')\n```\n```sh\nls -la /dev\n```" - } - ] -} diff --git a/tools/server/webui/scripts/install-git-hooks.sh b/tools/server/webui/scripts/install-git-hooks.sh new file mode 100755 index 0000000000..740075e281 --- /dev/null +++ b/tools/server/webui/scripts/install-git-hooks.sh @@ -0,0 +1,123 @@ +#!/bin/bash + +# Script to install pre-commit and post-commit hooks for webui +# Pre-commit: formats code and builds, stashes unstaged changes +# Post-commit: automatically unstashes changes + +REPO_ROOT=$(git rev-parse --show-toplevel) +PRE_COMMIT_HOOK="$REPO_ROOT/.git/hooks/pre-commit" +POST_COMMIT_HOOK="$REPO_ROOT/.git/hooks/post-commit" + +echo "Installing pre-commit and post-commit hooks for webui..." + +# Create the pre-commit hook +cat > "$PRE_COMMIT_HOOK" << 'EOF' +#!/bin/bash + +# Check if there are any changes in the webui directory +if git diff --cached --name-only | grep -q "^tools/server/webui/"; then + echo "Formatting webui code..." + + # Change to webui directory and run format + cd tools/server/webui + + # Check if npm is available and package.json exists + if [ ! -f "package.json" ]; then + echo "Error: package.json not found in tools/server/webui" + exit 1 + fi + + # Stash any unstaged changes to avoid conflicts during format/build + echo "Stashing unstaged changes..." + git stash push --keep-index --include-untracked -m "Pre-commit hook: stashed unstaged changes" + STASH_CREATED=$? + + # Run the format command + npm run format + + # Check if format command succeeded + if [ $? -ne 0 ]; then + echo "Error: npm run format failed" + if [ $STASH_CREATED -eq 0 ]; then + echo "You can restore your unstaged changes with: git stash pop" + fi + exit 1 + fi + + # Run the check command + npm run check + + # Check if check command succeeded + if [ $? -ne 0 ]; then + echo "Error: npm run check failed" + if [ $STASH_CREATED -eq 0 ]; then + echo "You can restore your unstaged changes with: git stash pop" + fi + exit 1 + fi + + # Run the build command + npm run build + + # Check if build command succeeded + if [ $? -ne 0 ]; then + echo "Error: npm run build failed" + if [ $STASH_CREATED -eq 0 ]; then + echo "You can restore your unstaged changes with: git stash pop" + fi + exit 1 + fi + + # Go back to repo root to add build output + cd ../../.. + + # Add the build output to staging area + git add tools/server/public/index.html.gz + + if [ $STASH_CREATED -eq 0 ]; then + echo "✅ Build completed. Your unstaged changes have been stashed." + echo "They will be automatically restored after the commit." + # Create a marker file to indicate stash was created by pre-commit hook + touch .git/WEBUI_STASH_MARKER + fi + + echo "Webui code formatted successfully" +fi + +exit 0 +EOF + +# Create the post-commit hook +cat > "$POST_COMMIT_HOOK" << 'EOF' +#!/bin/bash + +# Check if we have a stash marker from the pre-commit hook +if [ -f .git/WEBUI_STASH_MARKER ]; then + echo "Restoring your unstaged changes..." + git stash pop + rm -f .git/WEBUI_STASH_MARKER + echo "✅ Your unstaged changes have been restored." +fi + +exit 0 +EOF + +# Make both hooks executable +chmod +x "$PRE_COMMIT_HOOK" +chmod +x "$POST_COMMIT_HOOK" + +if [ $? -eq 0 ]; then + echo "✅ Pre-commit and post-commit hooks installed successfully!" + echo " Pre-commit: $PRE_COMMIT_HOOK" + echo " Post-commit: $POST_COMMIT_HOOK" + echo "" + echo "The hooks will automatically:" + echo " • Format and build webui code before commits" + echo " • Stash unstaged changes during the process" + echo " • Restore your unstaged changes after the commit" + echo "" + echo "To test the hooks, make a change to a file in the webui directory and commit it." +else + echo "❌ Failed to make hooks executable" + exit 1 +fi diff --git a/tools/server/webui/scripts/post-build.sh b/tools/server/webui/scripts/post-build.sh new file mode 100755 index 0000000000..ae5c1f30be --- /dev/null +++ b/tools/server/webui/scripts/post-build.sh @@ -0,0 +1,3 @@ +rm -rf ../public/_app; +rm ../public/favicon.svg; +rm ../public/index.html; \ No newline at end of file diff --git a/tools/server/webui/src/App.tsx b/tools/server/webui/src/App.tsx deleted file mode 100644 index 8dfcf49075..0000000000 --- a/tools/server/webui/src/App.tsx +++ /dev/null @@ -1,52 +0,0 @@ -import { HashRouter, Outlet, Route, Routes } from 'react-router'; -import Header from './components/Header'; -import Sidebar from './components/Sidebar'; -import { AppContextProvider, useAppContext } from './utils/app.context'; -import ChatScreen from './components/ChatScreen'; -import SettingDialog from './components/SettingDialog'; -import { Toaster } from 'react-hot-toast'; -import { ModalProvider } from './components/ModalProvider'; - -function App() { - return ( - - -
- - - }> - } /> - } /> - - - -
- - - ); -} - -function AppLayout() { - const { showSettings, setShowSettings } = useAppContext(); - return ( - <> - -
-
- -
- { - setShowSettings(false)} - /> - } - - - ); -} - -export default App; diff --git a/tools/server/webui/src/Config.ts b/tools/server/webui/src/Config.ts deleted file mode 100644 index c03ac287f3..0000000000 --- a/tools/server/webui/src/Config.ts +++ /dev/null @@ -1,96 +0,0 @@ -import daisyuiThemes from 'daisyui/theme/object'; -import { isNumeric } from './utils/misc'; - -export const isDev = import.meta.env.MODE === 'development'; - -// constants -export const BASE_URL = new URL('.', document.baseURI).href - .toString() - .replace(/\/$/, ''); - -export const CONFIG_DEFAULT = { - // Note: in order not to introduce breaking changes, please keep the same data type (number, string, etc) if you want to change the default value. Do not use null or undefined for default value. - // Do not use nested objects, keep it single level. Prefix the key if you need to group them. - apiKey: '', - systemMessage: '', - showTokensPerSecond: false, - showThoughtInProgress: false, - excludeThoughtOnReq: true, - pasteLongTextToFileLen: 2500, - pdfAsImage: false, - // make sure these default values are in sync with `common.h` - samplers: 'edkypmxt', - temperature: 0.8, - dynatemp_range: 0.0, - dynatemp_exponent: 1.0, - top_k: 40, - top_p: 0.95, - min_p: 0.05, - xtc_probability: 0.0, - xtc_threshold: 0.1, - typical_p: 1.0, - repeat_last_n: 64, - repeat_penalty: 1.0, - presence_penalty: 0.0, - frequency_penalty: 0.0, - dry_multiplier: 0.0, - dry_base: 1.75, - dry_allowed_length: 2, - dry_penalty_last_n: -1, - max_tokens: -1, - custom: '', // custom json-stringified object - // experimental features - pyIntepreterEnabled: false, -}; -export const CONFIG_INFO: Record = { - 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.', - pasteLongTextToFileLen: - 'On pasting long text, it will be converted to a file. You can control the file length by setting the value of this parameter. Value 0 means disable.', - samplers: - 'The order at which samplers are applied, in simplified way. Default is "dkypmxt": dry->top_k->typ_p->top_p->min_p->xtc->temperature', - temperature: - 'Controls the randomness of the generated text by affecting the probability distribution of the output tokens. Higher = more random, lower = more focused.', - dynatemp_range: - 'Addon for the temperature sampler. The added value to the range of dynamic temperature, which adjusts probabilities by entropy of tokens.', - dynatemp_exponent: - 'Addon for the temperature sampler. Smoothes out the probability redistribution based on the most probable token.', - top_k: 'Keeps only k top tokens.', - top_p: - 'Limits tokens to those that together have a cumulative probability of at least p', - min_p: - 'Limits tokens based on the minimum probability for a token to be considered, relative to the probability of the most likely token.', - xtc_probability: - 'XTC sampler cuts out top tokens; this parameter controls the chance of cutting tokens at all. 0 disables XTC.', - xtc_threshold: - 'XTC sampler cuts out top tokens; this parameter controls the token probability that is required to cut that token.', - typical_p: - 'Sorts and limits tokens based on the difference between log-probability and entropy.', - repeat_last_n: 'Last n tokens to consider for penalizing repetition', - repeat_penalty: - 'Controls the repetition of token sequences in the generated text', - presence_penalty: - 'Limits tokens based on whether they appear in the output or not.', - frequency_penalty: - 'Limits tokens based on how often they appear in the output.', - dry_multiplier: - 'DRY sampling reduces repetition in generated text even across long contexts. This parameter sets the DRY sampling multiplier.', - dry_base: - 'DRY sampling reduces repetition in generated text even across long contexts. This parameter sets the DRY sampling base value.', - dry_allowed_length: - 'DRY sampling reduces repetition in generated text even across long contexts. This parameter sets the allowed length for DRY sampling.', - dry_penalty_last_n: - 'DRY sampling reduces repetition in generated text even across long contexts. This parameter sets DRY penalty for the last n tokens.', - max_tokens: 'The maximum number of token per output.', - custom: '', // custom json-stringified object -}; -// config keys having numeric value (i.e. temperature, top_k, top_p, etc) -export const CONFIG_NUMERIC_KEYS = Object.entries(CONFIG_DEFAULT) - .filter((e) => isNumeric(e[1])) - .map((e) => e[0]); -// list of themes supported by daisyui -export const THEMES = ['light', 'dark'] - // make sure light & dark are always at the beginning - .concat( - Object.keys(daisyuiThemes).filter((t) => t !== 'light' && t !== 'dark') - ); diff --git a/tools/server/webui/src/app.css b/tools/server/webui/src/app.css new file mode 100644 index 0000000000..d05a422f02 --- /dev/null +++ b/tools/server/webui/src/app.css @@ -0,0 +1,123 @@ +@import 'tailwindcss'; + +@import 'tw-animate-css'; + +@custom-variant dark (&:is(.dark *)); + +:root { + --radius: 0.625rem; + --background: oklch(1 0 0); + --foreground: oklch(0.145 0 0); + --card: oklch(1 0 0); + --card-foreground: oklch(0.145 0 0); + --popover: oklch(1 0 0); + --popover-foreground: oklch(0.145 0 0); + --primary: oklch(0.205 0 0); + --primary-foreground: oklch(0.985 0 0); + --secondary: oklch(0.97 0 0); + --secondary-foreground: oklch(0.205 0 0); + --muted: oklch(0.97 0 0); + --muted-foreground: oklch(0.556 0 0); + --accent: oklch(0.97 0 0); + --accent-foreground: oklch(0.205 0 0); + --destructive: oklch(0.577 0.245 27.325); + --border: oklch(0.875 0 0); + --input: oklch(0.92 0 0); + --ring: oklch(0.708 0 0); + --chart-1: oklch(0.646 0.222 41.116); + --chart-2: oklch(0.6 0.118 184.704); + --chart-3: oklch(0.398 0.07 227.392); + --chart-4: oklch(0.828 0.189 84.429); + --chart-5: oklch(0.769 0.188 70.08); + --sidebar: oklch(0.985 0 0); + --sidebar-foreground: oklch(0.145 0 0); + --sidebar-primary: oklch(0.205 0 0); + --sidebar-primary-foreground: oklch(0.985 0 0); + --sidebar-accent: oklch(0.97 0 0); + --sidebar-accent-foreground: oklch(0.205 0 0); + --sidebar-border: oklch(0.922 0 0); + --sidebar-ring: oklch(0.708 0 0); + --code-background: oklch(0.225 0 0); + --code-foreground: oklch(0.875 0 0); +} + +.dark { + --background: oklch(0.16 0 0); + --foreground: oklch(0.985 0 0); + --card: oklch(0.205 0 0); + --card-foreground: oklch(0.985 0 0); + --popover: oklch(0.205 0 0); + --popover-foreground: oklch(0.985 0 0); + --primary: oklch(0.922 0 0); + --primary-foreground: oklch(0.205 0 0); + --secondary: oklch(0.269 0 0); + --secondary-foreground: oklch(0.985 0 0); + --muted: oklch(0.269 0 0); + --muted-foreground: oklch(0.708 0 0); + --accent: oklch(0.269 0 0); + --accent-foreground: oklch(0.985 0 0); + --destructive: oklch(0.704 0.191 22.216); + --border: oklch(1 0 0 / 30%); + --input: oklch(1 0 0 / 30%); + --ring: oklch(0.556 0 0); + --chart-1: oklch(0.488 0.243 264.376); + --chart-2: oklch(0.696 0.17 162.48); + --chart-3: oklch(0.769 0.188 70.08); + --chart-4: oklch(0.627 0.265 303.9); + --chart-5: oklch(0.645 0.246 16.439); + --sidebar: oklch(0.205 0 0); + --sidebar-foreground: oklch(0.985 0 0); + --sidebar-primary: oklch(0.488 0.243 264.376); + --sidebar-primary-foreground: oklch(0.985 0 0); + --sidebar-accent: oklch(0.269 0 0); + --sidebar-accent-foreground: oklch(0.985 0 0); + --sidebar-border: oklch(1 0 0 / 10%); + --sidebar-ring: oklch(0.556 0 0); +} + +@theme inline { + --radius-sm: calc(var(--radius) - 4px); + --radius-md: calc(var(--radius) - 2px); + --radius-lg: var(--radius); + --radius-xl: calc(var(--radius) + 4px); + --color-background: var(--background); + --color-foreground: var(--foreground); + --color-card: var(--card); + --color-card-foreground: var(--card-foreground); + --color-popover: var(--popover); + --color-popover-foreground: var(--popover-foreground); + --color-primary: var(--primary); + --color-primary-foreground: var(--primary-foreground); + --color-secondary: var(--secondary); + --color-secondary-foreground: var(--secondary-foreground); + --color-muted: var(--muted); + --color-muted-foreground: var(--muted-foreground); + --color-accent: var(--accent); + --color-accent-foreground: var(--accent-foreground); + --color-destructive: var(--destructive); + --color-border: var(--border); + --color-input: var(--input); + --color-ring: var(--ring); + --color-chart-1: var(--chart-1); + --color-chart-2: var(--chart-2); + --color-chart-3: var(--chart-3); + --color-chart-4: var(--chart-4); + --color-chart-5: var(--chart-5); + --color-sidebar: var(--sidebar); + --color-sidebar-foreground: var(--sidebar-foreground); + --color-sidebar-primary: var(--sidebar-primary); + --color-sidebar-primary-foreground: var(--sidebar-primary-foreground); + --color-sidebar-accent: var(--sidebar-accent); + --color-sidebar-accent-foreground: var(--sidebar-accent-foreground); + --color-sidebar-border: var(--sidebar-border); + --color-sidebar-ring: var(--sidebar-ring); +} + +@layer base { + * { + @apply border-border outline-ring/50; + } + body { + @apply bg-background text-foreground; + } +} diff --git a/tools/server/webui/src/app.d.ts b/tools/server/webui/src/app.d.ts new file mode 100644 index 0000000000..e9bb140939 --- /dev/null +++ b/tools/server/webui/src/app.d.ts @@ -0,0 +1,81 @@ +// See https://svelte.dev/docs/kit/types#app.d.ts +// for information about these interfaces + +// Import chat types from dedicated module + +import type { + ApiChatCompletionRequest, + ApiChatCompletionResponse, + ApiChatCompletionStreamChunk, + ApiChatMessageData, + ApiChatMessageContentPart, + ApiContextSizeError, + ApiErrorResponse, + ApiLlamaCppServerProps, + ApiProcessingState +} from '$lib/types/api'; + +import type { + ChatMessageType, + ChatRole, + ChatUploadedFile, + ChatMessageSiblingInfo, + ChatMessagePromptProgress, + ChatMessageTimings +} from '$lib/types/chat'; + +import type { + DatabaseConversation, + DatabaseMessage, + DatabaseMessageExtra, + DatabaseMessageExtraAudioFile, + DatabaseMessageExtraImageFile, + DatabaseMessageExtraTextFile, + DatabaseMessageExtraPdfFile +} from '$lib/types/database'; + +import type { + SettingsConfigValue, + SettingsFieldConfig, + SettingsConfigType +} from '$lib/types/settings'; + +declare global { + // namespace App { + // interface Error {} + // interface Locals {} + // interface PageData {} + // interface PageState {} + // interface Platform {} + // } + + export { + ApiChatCompletionRequest, + ApiChatCompletionResponse, + ApiChatCompletionStreamChunk, + ApiChatMessageData, + ApiChatMessageContentPart, + ApiContextSizeError, + ApiErrorResponse, + ApiLlamaCppServerProps, + ApiProcessingState, + ChatMessageData, + ChatMessagePromptProgress, + ChatMessageSiblingInfo, + ChatMessageTimings, + ChatMessageType, + ChatRole, + ChatUploadedFile, + DatabaseConversation, + DatabaseMessage, + DatabaseMessageExtra, + DatabaseMessageExtraAudioFile, + DatabaseMessageExtraImageFile, + DatabaseMessageExtraTextFile, + DatabaseMessageExtraPdfFile, + SettingsConfigValue, + SettingsFieldConfig, + SettingsConfigType, + SettingsChatServiceOptions + }; +} diff --git a/tools/server/webui/src/app.html b/tools/server/webui/src/app.html new file mode 100644 index 0000000000..1391f88488 --- /dev/null +++ b/tools/server/webui/src/app.html @@ -0,0 +1,12 @@ + + + + + + + %sveltekit.head% + + +
%sveltekit.body%
+ + diff --git a/tools/server/webui/src/components/CanvasPyInterpreter.tsx b/tools/server/webui/src/components/CanvasPyInterpreter.tsx deleted file mode 100644 index c2707fe20f..0000000000 --- a/tools/server/webui/src/components/CanvasPyInterpreter.tsx +++ /dev/null @@ -1,195 +0,0 @@ -import { useEffect, useState } from 'react'; -import { useAppContext } from '../utils/app.context'; -import { OpenInNewTab, XCloseButton } from '../utils/common'; -import { CanvasType } from '../utils/types'; -import { PlayIcon, StopIcon } from '@heroicons/react/24/outline'; -import StorageUtils from '../utils/storage'; - -const canInterrupt = typeof SharedArrayBuffer === 'function'; - -// adapted from https://pyodide.org/en/stable/usage/webworker.html -const WORKER_CODE = ` -importScripts("https://cdn.jsdelivr.net/pyodide/v0.27.2/full/pyodide.js"); - -let stdOutAndErr = []; - -let pyodideReadyPromise = loadPyodide({ - stdout: (data) => stdOutAndErr.push(data), - stderr: (data) => stdOutAndErr.push(data), -}); - -let alreadySetBuff = false; - -self.onmessage = async (event) => { - stdOutAndErr = []; - - // make sure loading is done - const pyodide = await pyodideReadyPromise; - const { id, python, context, interruptBuffer } = event.data; - - if (interruptBuffer && !alreadySetBuff) { - pyodide.setInterruptBuffer(interruptBuffer); - alreadySetBuff = true; - } - - // Now load any packages we need, run the code, and send the result back. - await pyodide.loadPackagesFromImports(python); - - // make a Python dictionary with the data from content - const dict = pyodide.globals.get("dict"); - const globals = dict(Object.entries(context)); - try { - self.postMessage({ id, running: true }); - // Execute the python code in this context - const result = pyodide.runPython(python, { globals }); - self.postMessage({ result, id, stdOutAndErr }); - } catch (error) { - self.postMessage({ error: error.message, id }); - } - interruptBuffer[0] = 0; -}; -`; - -let worker: Worker; -const interruptBuffer = canInterrupt - ? new Uint8Array(new SharedArrayBuffer(1)) - : null; - -const startWorker = () => { - if (!worker) { - worker = new Worker( - URL.createObjectURL(new Blob([WORKER_CODE], { type: 'text/javascript' })) - ); - } -}; - -if (StorageUtils.getConfig().pyIntepreterEnabled) { - startWorker(); -} - -const runCodeInWorker = ( - pyCode: string, - callbackRunning: () => void -): { - donePromise: Promise; - interrupt: () => void; -} => { - startWorker(); - const id = Math.random() * 1e8; - const context = {}; - if (interruptBuffer) { - interruptBuffer[0] = 0; - } - - const donePromise = new Promise((resolve) => { - worker.onmessage = (event) => { - const { error, stdOutAndErr, running } = event.data; - if (id !== event.data.id) return; - if (running) { - callbackRunning(); - return; - } else if (error) { - resolve(error.toString()); - } else { - resolve(stdOutAndErr.join('\n')); - } - }; - worker.postMessage({ id, python: pyCode, context, interruptBuffer }); - }); - - const interrupt = () => { - console.log('Interrupting...'); - console.trace(); - if (interruptBuffer) { - interruptBuffer[0] = 2; - } - }; - - return { donePromise, interrupt }; -}; - -export default function CanvasPyInterpreter() { - const { canvasData, setCanvasData } = useAppContext(); - - const [code, setCode] = useState(canvasData?.content ?? ''); // copy to avoid direct mutation - const [running, setRunning] = useState(false); - const [output, setOutput] = useState(''); - const [interruptFn, setInterruptFn] = useState<() => void>(); - const [showStopBtn, setShowStopBtn] = useState(false); - - const runCode = async (pycode: string) => { - interruptFn?.(); - setRunning(true); - setOutput('Loading Pyodide...'); - const { donePromise, interrupt } = runCodeInWorker(pycode, () => { - setOutput('Running...'); - setShowStopBtn(canInterrupt); - }); - setInterruptFn(() => interrupt); - const out = await donePromise; - setOutput(out); - setRunning(false); - setShowStopBtn(false); - }; - - // run code on mount - useEffect(() => { - setCode(canvasData?.content ?? ''); - runCode(canvasData?.content ?? ''); - // eslint-disable-next-line react-hooks/exhaustive-deps - }, [canvasData?.content]); - - if (canvasData?.type !== CanvasType.PY_INTERPRETER) { - return null; - } - - return ( -
-
-
- Python Interpreter - setCanvasData(null)} - /> -
-
- -
-
- - {showStopBtn && ( - - )} - - - Report a bug - - -
- -
-
-
-
- ); -} diff --git a/tools/server/webui/src/components/ChatInputExtraContextItem.tsx b/tools/server/webui/src/components/ChatInputExtraContextItem.tsx deleted file mode 100644 index 2d4179ea47..0000000000 --- a/tools/server/webui/src/components/ChatInputExtraContextItem.tsx +++ /dev/null @@ -1,135 +0,0 @@ -import { - DocumentTextIcon, - SpeakerWaveIcon, - XMarkIcon, -} from '@heroicons/react/24/outline'; -import { MessageExtra } from '../utils/types'; -import { useState } from 'react'; -import { classNames } from '../utils/misc'; - -export default function ChatInputExtraContextItem({ - items, - removeItem, - clickToShow, -}: { - items?: MessageExtra[]; - removeItem?: (index: number) => void; - clickToShow?: boolean; -}) { - const [show, setShow] = useState(-1); - const showingItem = show >= 0 ? items?.[show] : undefined; - - if (!items) return null; - - return ( -
- {items.map((item, i) => ( -
clickToShow && setShow(i)} - tabIndex={0} - aria-description={ - clickToShow ? `Click to show: ${item.name}` : undefined - } - role={clickToShow ? 'button' : 'menuitem'} - > - {removeItem && ( -
- -
- )} - -
- {item.type === 'imageFile' ? ( - <> - {`Preview - - ) : ( - <> -
- {item.type === 'audioFile' ? ( - - ) : ( - - )} -
- -
- {item.name ?? 'Extra content'} -
- - )} -
-
- ))} - - {showingItem && ( - -
-
- {showingItem.name ?? 'Extra content'} - -
- {showingItem.type === 'imageFile' ? ( - {`Preview - ) : showingItem.type === 'audioFile' ? ( - - ) : ( -
- 
-                  {showingItem.content}
-
-
- )} -
-
setShow(-1)}>
- - )} -
- ); -} diff --git a/tools/server/webui/src/components/ChatMessage.tsx b/tools/server/webui/src/components/ChatMessage.tsx deleted file mode 100644 index a1a7d152f9..0000000000 --- a/tools/server/webui/src/components/ChatMessage.tsx +++ /dev/null @@ -1,320 +0,0 @@ -import { useMemo, useState } from 'react'; -import { useAppContext } from '../utils/app.context'; -import { Message, PendingMessage } from '../utils/types'; -import { classNames } from '../utils/misc'; -import MarkdownDisplay, { CopyButton } from './MarkdownDisplay'; -import { - ArrowPathIcon, - ChevronLeftIcon, - ChevronRightIcon, - PencilSquareIcon, -} from '@heroicons/react/24/outline'; -import ChatInputExtraContextItem from './ChatInputExtraContextItem'; -import { BtnWithTooltips } from '../utils/common'; - -interface SplitMessage { - content: PendingMessage['content']; - thought?: string; - isThinking?: boolean; -} - -export default function ChatMessage({ - msg, - siblingLeafNodeIds, - siblingCurrIdx, - id, - onRegenerateMessage, - onEditMessage, - onChangeSibling, - isPending, -}: { - msg: Message | PendingMessage; - siblingLeafNodeIds: Message['id'][]; - siblingCurrIdx: number; - id?: string; - onRegenerateMessage(msg: Message): void; - onEditMessage(msg: Message, content: string): void; - onChangeSibling(sibling: Message['id']): void; - isPending?: boolean; -}) { - const { viewingChat, config } = useAppContext(); - const [editingContent, setEditingContent] = useState(null); - const timings = useMemo( - () => - msg.timings - ? { - ...msg.timings, - prompt_per_second: - (msg.timings.prompt_n / msg.timings.prompt_ms) * 1000, - predicted_per_second: - (msg.timings.predicted_n / msg.timings.predicted_ms) * 1000, - } - : null, - [msg.timings] - ); - const nextSibling = siblingLeafNodeIds[siblingCurrIdx + 1]; - const prevSibling = siblingLeafNodeIds[siblingCurrIdx - 1]; - - // for reasoning model, we split the message into content and thought - // TODO: implement this as remark/rehype plugin in the future - const { content, thought, isThinking }: SplitMessage = useMemo(() => { - if (msg.content === null || msg.role !== 'assistant') { - return { content: msg.content }; - } - const REGEX_THINK_OPEN = /|<\|channel\|>analysis<\|message\|>/; - const REGEX_THINK_CLOSE = /<\/think>|<\|end\|>/; - let actualContent = ''; - let thought = ''; - let isThinking = false; - let thinkSplit = msg.content.split(REGEX_THINK_OPEN, 2); - actualContent += thinkSplit[0]; - while (thinkSplit[1] !== undefined) { - // tag found - thinkSplit = thinkSplit[1].split(REGEX_THINK_CLOSE, 2); - thought += thinkSplit[0]; - isThinking = true; - if (thinkSplit[1] !== undefined) { - // closing tag found - isThinking = false; - thinkSplit = thinkSplit[1].split(REGEX_THINK_OPEN, 2); - actualContent += thinkSplit[0]; - } - } - return { content: actualContent, thought, isThinking }; - }, [msg]); - - if (!viewingChat) return null; - - const isUser = msg.role === 'user'; - - return ( -
-
- {msg.extra && msg.extra.length > 0 && ( - - )} - -
- {/* textarea for editing message */} - {editingContent !== null && ( - <> - -
- - - - )} - {/* not editing content, render message */} - {editingContent === null && ( - <> - {content === null ? ( - <> - {/* show loading dots for pending message */} - - - ) : ( - <> - {/* render message as markdown */} -
- {thought && ( - - )} - - -
- - )} - {/* render timings if enabled */} - {timings && config.showTokensPerSecond && ( -
-
- Speed: {timings.predicted_per_second.toFixed(1)} t/s -
-
- Prompt -
- Tokens: {timings.prompt_n} -
- Time: {timings.prompt_ms} ms -
- Speed: {timings.prompt_per_second.toFixed(1)} t/s -
- Generation -
- Tokens: {timings.predicted_n} -
- Time: {timings.predicted_ms} ms -
- Speed: {timings.predicted_per_second.toFixed(1)} t/s -
-
-
- )} - - )} -
-
- - {/* actions for each message */} - {msg.content !== null && ( -
- {siblingLeafNodeIds && siblingLeafNodeIds.length > 1 && ( -
- - - {siblingCurrIdx + 1} / {siblingLeafNodeIds.length} - - -
- )} - {/* user message */} - {msg.role === 'user' && ( - setEditingContent(msg.content)} - disabled={msg.content === null} - tooltipsContent="Edit message" - > - - - )} - {/* assistant message */} - {msg.role === 'assistant' && ( - <> - {!isPending && ( - { - if (msg.content !== null) { - onRegenerateMessage(msg as Message); - } - }} - disabled={msg.content === null} - tooltipsContent="Regenerate response" - > - - - )} - - )} - -
- )} -
- ); -} - -function ThoughtProcess({ - isThinking, - content, - open, -}: { - isThinking: boolean; - content: string; - open: boolean; -}) { - return ( -
- -
-
- {isThinking ? ( - - - Thinking - - ) : ( - <>Thought Process - )} -
-
-
-
- -
-
-
- ); -} diff --git a/tools/server/webui/src/components/ChatScreen.tsx b/tools/server/webui/src/components/ChatScreen.tsx deleted file mode 100644 index c1a6691445..0000000000 --- a/tools/server/webui/src/components/ChatScreen.tsx +++ /dev/null @@ -1,459 +0,0 @@ -import { ClipboardEvent, useEffect, useMemo, useRef, useState } from 'react'; -import { CallbackGeneratedChunk, useAppContext } from '../utils/app.context'; -import ChatMessage from './ChatMessage'; -import { CanvasType, Message, PendingMessage } from '../utils/types'; -import { classNames, cleanCurrentUrl } from '../utils/misc'; -import CanvasPyInterpreter from './CanvasPyInterpreter'; -import StorageUtils from '../utils/storage'; -import { useVSCodeContext } from '../utils/llama-vscode'; -import { useChatTextarea, ChatTextareaApi } from './useChatTextarea.ts'; -import { - ArrowUpIcon, - StopIcon, - PaperClipIcon, -} from '@heroicons/react/24/solid'; -import { - ChatExtraContextApi, - useChatExtraContext, -} from './useChatExtraContext.tsx'; -import Dropzone from 'react-dropzone'; -import toast from 'react-hot-toast'; -import ChatInputExtraContextItem from './ChatInputExtraContextItem.tsx'; -import { scrollToBottom, useChatScroll } from './useChatScroll.tsx'; - -/** - * A message display is a message node with additional information for rendering. - * For example, siblings of the message node are stored as their last node (aka leaf node). - */ -export interface MessageDisplay { - msg: Message | PendingMessage; - siblingLeafNodeIds: Message['id'][]; - siblingCurrIdx: number; - isPending?: boolean; -} - -/** - * If the current URL contains "?m=...", prefill the message input with the value. - * If the current URL contains "?q=...", prefill and SEND the message. - */ -const prefilledMsg = { - content() { - const url = new URL(window.location.href); - return url.searchParams.get('m') ?? url.searchParams.get('q') ?? ''; - }, - shouldSend() { - const url = new URL(window.location.href); - return url.searchParams.has('q'); - }, - clear() { - cleanCurrentUrl(['m', 'q']); - }, -}; - -function getListMessageDisplay( - msgs: Readonly, - leafNodeId: Message['id'] -): MessageDisplay[] { - const currNodes = StorageUtils.filterByLeafNodeId(msgs, leafNodeId, true); - const res: MessageDisplay[] = []; - const nodeMap = new Map(); - for (const msg of msgs) { - nodeMap.set(msg.id, msg); - } - // find leaf node from a message node - const findLeafNode = (msgId: Message['id']): Message['id'] => { - let currNode: Message | undefined = nodeMap.get(msgId); - while (currNode) { - if (currNode.children.length === 0) break; - currNode = nodeMap.get(currNode.children.at(-1) ?? -1); - } - return currNode?.id ?? -1; - }; - // traverse the current nodes - for (const msg of currNodes) { - const parentNode = nodeMap.get(msg.parent ?? -1); - if (!parentNode) continue; - const siblings = parentNode.children; - if (msg.type !== 'root') { - res.push({ - msg, - siblingLeafNodeIds: siblings.map(findLeafNode), - siblingCurrIdx: siblings.indexOf(msg.id), - }); - } - } - return res; -} - -export default function ChatScreen() { - const { - viewingChat, - sendMessage, - isGenerating, - stopGenerating, - pendingMessages, - canvasData, - replaceMessageAndGenerate, - } = useAppContext(); - - const textarea: ChatTextareaApi = useChatTextarea(prefilledMsg.content()); - const extraContext = useChatExtraContext(); - useVSCodeContext(textarea, extraContext); - - const msgListRef = useRef(null); - useChatScroll(msgListRef); - - // keep track of leaf node for rendering - const [currNodeId, setCurrNodeId] = useState(-1); - const messages: MessageDisplay[] = useMemo(() => { - if (!viewingChat) return []; - else return getListMessageDisplay(viewingChat.messages, currNodeId); - }, [currNodeId, viewingChat]); - - const currConvId = viewingChat?.conv.id ?? null; - const pendingMsg: PendingMessage | undefined = - pendingMessages[currConvId ?? '']; - - useEffect(() => { - // reset to latest node when conversation changes - setCurrNodeId(-1); - // scroll to bottom when conversation changes - scrollToBottom(false, 1); - }, [currConvId]); - - const onChunk: CallbackGeneratedChunk = (currLeafNodeId?: Message['id']) => { - if (currLeafNodeId) { - setCurrNodeId(currLeafNodeId); - } - // useChatScroll will handle the auto scroll - }; - - const sendNewMessage = async () => { - const lastInpMsg = textarea.value(); - if (lastInpMsg.trim().length === 0 || isGenerating(currConvId ?? '')) { - toast.error('Please enter a message'); - return; - } - textarea.setValue(''); - scrollToBottom(false); - setCurrNodeId(-1); - // get the last message node - const lastMsgNodeId = messages.at(-1)?.msg.id ?? null; - if ( - !(await sendMessage( - currConvId, - lastMsgNodeId, - lastInpMsg, - extraContext.items, - onChunk - )) - ) { - // restore the input message if failed - textarea.setValue(lastInpMsg); - } - // OK - extraContext.clearItems(); - }; - - // for vscode context - textarea.refOnSubmit.current = sendNewMessage; - - const handleEditMessage = async (msg: Message, content: string) => { - if (!viewingChat) return; - setCurrNodeId(msg.id); - scrollToBottom(false); - await replaceMessageAndGenerate( - viewingChat.conv.id, - msg.parent, - content, - msg.extra, - onChunk - ); - setCurrNodeId(-1); - scrollToBottom(false); - }; - - const handleRegenerateMessage = async (msg: Message) => { - if (!viewingChat) return; - setCurrNodeId(msg.parent); - scrollToBottom(false); - await replaceMessageAndGenerate( - viewingChat.conv.id, - msg.parent, - null, - msg.extra, - onChunk - ); - setCurrNodeId(-1); - scrollToBottom(false); - }; - - const hasCanvas = !!canvasData; - - useEffect(() => { - if (prefilledMsg.shouldSend()) { - // send the prefilled message if needed - sendNewMessage(); - } else { - // otherwise, focus on the input - textarea.focus(); - } - prefilledMsg.clear(); - // no need to keep track of sendNewMessage - // eslint-disable-next-line react-hooks/exhaustive-deps - }, [textarea.ref]); - - // due to some timing issues of StorageUtils.appendMsg(), we need to make sure the pendingMsg is not duplicated upon rendering (i.e. appears once in the saved conversation and once in the pendingMsg) - const pendingMsgDisplay: MessageDisplay[] = - pendingMsg && messages.at(-1)?.msg.id !== pendingMsg.id - ? [ - { - msg: pendingMsg, - siblingLeafNodeIds: [], - siblingCurrIdx: 0, - isPending: true, - }, - ] - : []; - - return ( -
-
- {/* chat messages */} -
-
- {/* placeholder to shift the message to the bottom */} - {viewingChat ? ( - '' - ) : ( - <> -
Send a message to start
- - - )} -
- {[...messages, ...pendingMsgDisplay].map((msg) => ( - - ))} -
- - {/* chat input */} - stopGenerating(currConvId ?? '')} - isGenerating={isGenerating(currConvId ?? '')} - /> -
-
- {canvasData?.type === CanvasType.PY_INTERPRETER && ( - - )} -
-
- ); -} - -function ServerInfo() { - const { serverProps } = useAppContext(); - const modalities = []; - if (serverProps?.modalities?.audio) { - modalities.push('audio'); - } - if (serverProps?.modalities?.vision) { - modalities.push('vision'); - } - return ( -
-
- Server Info -

- Model: {serverProps?.model_path?.split(/(\\|\/)/).pop()} -
- Build: {serverProps?.build_info} -
- {modalities.length > 0 ? ( - <> - Supported modalities: {modalities.join(', ')} - - ) : ( - '' - )} -

-
-
- ); -} - -function ChatInput({ - textarea, - extraContext, - onSend, - onStop, - isGenerating, -}: { - textarea: ChatTextareaApi; - extraContext: ChatExtraContextApi; - onSend: () => void; - onStop: () => void; - isGenerating: boolean; -}) { - const { config } = useAppContext(); - const [isDrag, setIsDrag] = useState(false); - - return ( -
- { - setIsDrag(false); - extraContext.onFileAdded(files); - }} - onDragEnter={() => setIsDrag(true)} - onDragLeave={() => setIsDrag(false)} - multiple={true} - > - {({ getRootProps, getInputProps }) => ( -
) => { - const text = e.clipboardData.getData('text/plain'); - if ( - text.length > 0 && - config.pasteLongTextToFileLen > 0 && - text.length > config.pasteLongTextToFileLen - ) { - // if the text is too long, we will convert it to a file - extraContext.addItems([ - { - type: 'context', - name: 'Pasted Content', - content: text, - }, - ]); - e.preventDefault(); - return; - } - - // if a file is pasted, we will handle it here - const files = Array.from(e.clipboardData.items) - .filter((item) => item.kind === 'file') - .map((item) => item.getAsFile()) - .filter((file) => file !== null); - - if (files.length > 0) { - e.preventDefault(); - extraContext.onFileAdded(files); - } - }} - {...getRootProps()} - > - {!isGenerating && ( - - )} - -
- - - {/* buttons area */} -
- - - {isGenerating ? ( - - ) : ( - - )} -
-
-
- )} - -
- ); -} diff --git a/tools/server/webui/src/components/Header.tsx b/tools/server/webui/src/components/Header.tsx deleted file mode 100644 index ccddc21dda..0000000000 --- a/tools/server/webui/src/components/Header.tsx +++ /dev/null @@ -1,92 +0,0 @@ -import { useEffect, useState } from 'react'; -import StorageUtils from '../utils/storage'; -import { useAppContext } from '../utils/app.context'; -import { classNames } from '../utils/misc'; -import daisyuiThemes from 'daisyui/theme/object'; -import { THEMES } from '../Config'; -import { - Cog8ToothIcon, - MoonIcon, - Bars3Icon, -} from '@heroicons/react/24/outline'; - -export default function Header() { - const [selectedTheme, setSelectedTheme] = useState(StorageUtils.getTheme()); - const { setShowSettings } = useAppContext(); - - const setTheme = (theme: string) => { - StorageUtils.setTheme(theme); - setSelectedTheme(theme); - }; - - useEffect(() => { - document.body.setAttribute('data-theme', selectedTheme); - document.body.setAttribute( - 'data-color-scheme', - daisyuiThemes[selectedTheme]?.['color-scheme'] ?? 'auto' - ); - }, [selectedTheme]); - - return ( -
- {/* open sidebar button */} - - -
llama.cpp
- - {/* action buttons (top right) */} -
-
setShowSettings(true)} - > - -
- - {/* theme controller is copied from https://daisyui.com/components/theme-controller/ */} -
-
-
- -
-
    -
  • - -
    • - {THEMES.map((theme) => ( -
  • - e.target.checked && setTheme(theme)} - /> -
    • - ))} -
-
-
-
-
- ); -} diff --git a/tools/server/webui/src/components/MarkdownDisplay.tsx b/tools/server/webui/src/components/MarkdownDisplay.tsx deleted file mode 100644 index 380dbc570a..0000000000 --- a/tools/server/webui/src/components/MarkdownDisplay.tsx +++ /dev/null @@ -1,317 +0,0 @@ -import React, { useMemo, useState } from 'react'; -import Markdown, { ExtraProps } from 'react-markdown'; -import remarkGfm from 'remark-gfm'; -import rehypeHightlight from 'rehype-highlight'; -import rehypeKatex from 'rehype-katex'; -import remarkMath from 'remark-math'; -import remarkBreaks from 'remark-breaks'; -import 'katex/dist/katex.min.css'; -import { classNames, copyStr } from '../utils/misc'; -import { ElementContent, Root } from 'hast'; -import { visit } from 'unist-util-visit'; -import { useAppContext } from '../utils/app.context'; -import { CanvasType } from '../utils/types'; -import { BtnWithTooltips } from '../utils/common'; -import { DocumentDuplicateIcon, PlayIcon } from '@heroicons/react/24/outline'; - -export default function MarkdownDisplay({ - content, - isGenerating, -}: { - content: string; - isGenerating?: boolean; -}) { - const preprocessedContent = useMemo( - () => preprocessLaTeX(content), - [content] - ); - return ( - ( - - ), - // note: do not use "pre", "p" or other basic html elements here, it will cause the node to re-render when the message is being generated (this should be a bug with react-markdown, not sure how to fix it) - }} - > - {preprocessedContent} - - ); -} - -const CodeBlockButtons: React.ElementType< - React.ClassAttributes & - React.HTMLAttributes & - ExtraProps & { origContent: string; isGenerating?: boolean } -> = ({ node, origContent, isGenerating }) => { - const { config } = useAppContext(); - const startOffset = node?.position?.start.offset ?? 0; - const endOffset = node?.position?.end.offset ?? 0; - - const copiedContent = useMemo( - () => - origContent - .substring(startOffset, endOffset) - .replace(/^```[^\n]+\n/g, '') - .replace(/```$/g, ''), - [origContent, startOffset, endOffset] - ); - - const codeLanguage = useMemo( - () => - origContent - .substring(startOffset, startOffset + 10) - .match(/^```([^\n]+)\n/)?.[1] ?? '', - [origContent, startOffset] - ); - - const canRunCode = - !isGenerating && - config.pyIntepreterEnabled && - codeLanguage.startsWith('py'); - - return ( -
- - {canRunCode && ( - - )} -
- ); -}; - -export const CopyButton = ({ - content, - className, -}: { - content: string; - className?: string; -}) => { - const [copied, setCopied] = useState(false); - return ( - { - copyStr(content); - setCopied(true); - }} - onMouseLeave={() => setCopied(false)} - tooltipsContent={copied ? 'Copied!' : 'Copy'} - > - - - ); -}; - -export const RunPyCodeButton = ({ - content, - className, -}: { - content: string; - className?: string; -}) => { - const { setCanvasData } = useAppContext(); - return ( - <> - - setCanvasData({ - type: CanvasType.PY_INTERPRETER, - content, - }) - } - tooltipsContent="Run code" - > - - - - ); -}; - -/** - * This injects the "button" element before each "pre" element. - * The actual button will be replaced with a react component in the MarkdownDisplay. - * We don't replace "pre" node directly because it will cause the node to re-render, which causes this bug: https://github.com/ggerganov/llama.cpp/issues/9608 - */ -function rehypeCustomCopyButton() { - return function (tree: Root) { - visit(tree, 'element', function (node) { - if (node.tagName === 'pre' && !node.properties.visited) { - const preNode = { ...node }; - // replace current node - preNode.properties.visited = 'true'; - node.tagName = 'div'; - node.properties = {}; - // add node for button - const btnNode: ElementContent = { - type: 'element', - tagName: 'button', - properties: {}, - children: [], - position: node.position, - }; - node.children = [btnNode, preNode]; - } - }); - }; -} - -/** - * The part below is copied and adapted from: - * https://github.com/danny-avila/LibreChat/blob/main/client/src/utils/latex.ts - * (MIT License) - */ - -// Regex to check if the processed content contains any potential LaTeX patterns -const containsLatexRegex = - /\\\(.*?\\\)|\\\[.*?\\\]|\$.*?\$|\\begin\{equation\}.*?\\end\{equation\}/; - -// Regex for inline and block LaTeX expressions -const inlineLatex = new RegExp(/\\\((.+?)\\\)/, 'g'); -const blockLatex = new RegExp(/\\\[(.*?[^\\])\\\]/, 'gs'); - -// Function to restore code blocks -const restoreCodeBlocks = (content: string, codeBlocks: string[]) => { - return content.replace( - /<>/g, - (_, index) => codeBlocks[index] - ); -}; - -// Regex to identify code blocks and inline code -const codeBlockRegex = /(```[\s\S]*?```|`.*?`)/g; - -export const processLaTeX = (_content: string) => { - let content = _content; - // Temporarily replace code blocks and inline code with placeholders - const codeBlocks: string[] = []; - let index = 0; - content = content.replace(codeBlockRegex, (match) => { - codeBlocks[index] = match; - return `<>`; - }); - - // Escape dollar signs followed by a digit or space and digit - let processedContent = content.replace(/(\$)(?=\s?\d)/g, '\\$'); - - // If no LaTeX patterns are found, restore code blocks and return the processed content - if (!containsLatexRegex.test(processedContent)) { - return restoreCodeBlocks(processedContent, codeBlocks); - } - - // Convert LaTeX expressions to a markdown compatible format - processedContent = processedContent - .replace(inlineLatex, (_: string, equation: string) => `$${equation}$`) // Convert inline LaTeX - .replace(blockLatex, (_: string, equation: string) => `$$${equation}$$`); // Convert block LaTeX - - // Restore code blocks - return restoreCodeBlocks(processedContent, codeBlocks); -}; - -/** - * Preprocesses LaTeX content by replacing delimiters and escaping certain characters. - * - * @param content The input string containing LaTeX expressions. - * @returns The processed string with replaced delimiters and escaped characters. - */ -export function preprocessLaTeX(content: string): string { - // Step 1: Protect code blocks - const codeBlocks: string[] = []; - content = content.replace(/(```[\s\S]*?```|`[^`\n]+`)/g, (_, code) => { - codeBlocks.push(code); - return `<>`; - }); - - // Step 2: Protect existing LaTeX expressions - const latexExpressions: string[] = []; - - // Protect block math ($$...$$), \[...\], and \(...\) as before. - content = content.replace( - /(\$\$[\s\S]*?\$\$|\\\[[\s\S]*?\\\]|\\\(.*?\\\))/g, - (match) => { - latexExpressions.push(match); - return `<>`; - } - ); - - // Protect inline math ($...$) only if it does NOT match a currency pattern. - // We assume a currency pattern is one where the inner content is purely numeric (with optional decimals). - content = content.replace(/\$([^$]+)\$/g, (match, inner) => { - if (/^\s*\d+(?:\.\d+)?\s*$/.test(inner)) { - // This looks like a currency value (e.g. "$123" or "$12.34"), - // so don't protect it. - return match; - } else { - // Otherwise, treat it as a LaTeX expression. - latexExpressions.push(match); - return `<>`; - } - }); - - // Step 3: Escape dollar signs that are likely currency indicators. - // (Now that inline math is protected, this will only escape dollars not already protected) - content = content.replace(/\$(?=\d)/g, '\\$'); - - // Step 4: Restore LaTeX expressions - content = content.replace( - /<>/g, - (_, index) => latexExpressions[parseInt(index)] - ); - - // Step 5: Restore code blocks - content = content.replace( - /<>/g, - (_, index) => codeBlocks[parseInt(index)] - ); - - // Step 6: Apply additional escaping functions - content = escapeBrackets(content); - content = escapeMhchem(content); - - return content; -} - -export function escapeBrackets(text: string): string { - const pattern = - /(```[\S\s]*?```|`.*?`)|\\\[([\S\s]*?[^\\])\\]|\\\((.*?)\\\)/g; - return text.replace( - pattern, - ( - match: string, - codeBlock: string | undefined, - squareBracket: string | undefined, - roundBracket: string | undefined - ): string => { - if (codeBlock != null) { - return codeBlock; - } else if (squareBracket != null) { - return `$$${squareBracket}$$`; - } else if (roundBracket != null) { - return `$${roundBracket}$`; - } - return match; - } - ); -} - -export function escapeMhchem(text: string) { - return text.replaceAll('$\\ce{', '$\\\\ce{').replaceAll('$\\pu{', '$\\\\pu{'); -} diff --git a/tools/server/webui/src/components/ModalProvider.tsx b/tools/server/webui/src/components/ModalProvider.tsx deleted file mode 100644 index f2ebf8e0a7..0000000000 --- a/tools/server/webui/src/components/ModalProvider.tsx +++ /dev/null @@ -1,151 +0,0 @@ -import React, { createContext, useState, useContext } from 'react'; - -type ModalContextType = { - showConfirm: (message: string) => Promise; - showPrompt: ( - message: string, - defaultValue?: string - ) => Promise; - showAlert: (message: string) => Promise; -}; -const ModalContext = createContext(null!); - -interface ModalState { - isOpen: boolean; - message: string; - defaultValue?: string; - resolve: ((value: T) => void) | null; -} - -export function ModalProvider({ children }: { children: React.ReactNode }) { - const [confirmState, setConfirmState] = useState>({ - isOpen: false, - message: '', - resolve: null, - }); - const [promptState, setPromptState] = useState< - ModalState - >({ isOpen: false, message: '', resolve: null }); - const [alertState, setAlertState] = useState>({ - isOpen: false, - message: '', - resolve: null, - }); - const inputRef = React.useRef(null); - - const showConfirm = (message: string): Promise => { - return new Promise((resolve) => { - setConfirmState({ isOpen: true, message, resolve }); - }); - }; - - const showPrompt = ( - message: string, - defaultValue?: string - ): Promise => { - return new Promise((resolve) => { - setPromptState({ isOpen: true, message, defaultValue, resolve }); - }); - }; - - const showAlert = (message: string): Promise => { - return new Promise((resolve) => { - setAlertState({ isOpen: true, message, resolve }); - }); - }; - - const handleConfirm = (result: boolean) => { - confirmState.resolve?.(result); - setConfirmState({ isOpen: false, message: '', resolve: null }); - }; - - const handlePrompt = (result?: string) => { - promptState.resolve?.(result); - setPromptState({ isOpen: false, message: '', resolve: null }); - }; - - const handleAlertClose = () => { - alertState.resolve?.(); - setAlertState({ isOpen: false, message: '', resolve: null }); - }; - - return ( - - {children} - - {/* Confirm Modal */} - {confirmState.isOpen && ( - -
-

{confirmState.message}

-
- - -
-
- - )} - - {/* Prompt Modal */} - {promptState.isOpen && ( - -
-

{promptState.message}

- { - if (e.key === 'Enter') { - handlePrompt((e.target as HTMLInputElement).value); - } - }} - /> -
- - -
-
- - )} - - {/* Alert Modal */} - {alertState.isOpen && ( - -
-

{alertState.message}

-
- -
-
- - )} - - ); -} - -export function useModals() { - const context = useContext(ModalContext); - if (!context) throw new Error('useModals must be used within ModalProvider'); - return context; -} diff --git a/tools/server/webui/src/components/SettingDialog.tsx b/tools/server/webui/src/components/SettingDialog.tsx deleted file mode 100644 index 45a8d73b00..0000000000 --- a/tools/server/webui/src/components/SettingDialog.tsx +++ /dev/null @@ -1,553 +0,0 @@ -import { useState } from 'react'; -import { useAppContext } from '../utils/app.context'; -import { CONFIG_DEFAULT, CONFIG_INFO } from '../Config'; -import { isDev } from '../Config'; -import StorageUtils from '../utils/storage'; -import { classNames, isBoolean, isNumeric, isString } from '../utils/misc'; -import { - BeakerIcon, - ChatBubbleOvalLeftEllipsisIcon, - Cog6ToothIcon, - FunnelIcon, - HandRaisedIcon, - SquaresPlusIcon, -} from '@heroicons/react/24/outline'; -import { OpenInNewTab } from '../utils/common'; -import { useModals } from './ModalProvider'; - -type SettKey = keyof typeof CONFIG_DEFAULT; - -const BASIC_KEYS: SettKey[] = [ - 'temperature', - 'top_k', - 'top_p', - 'min_p', - 'max_tokens', -]; -const SAMPLER_KEYS: SettKey[] = [ - 'dynatemp_range', - 'dynatemp_exponent', - 'typical_p', - 'xtc_probability', - 'xtc_threshold', -]; -const PENALTY_KEYS: SettKey[] = [ - 'repeat_last_n', - 'repeat_penalty', - 'presence_penalty', - 'frequency_penalty', - 'dry_multiplier', - 'dry_base', - 'dry_allowed_length', - 'dry_penalty_last_n', -]; - -enum SettingInputType { - SHORT_INPUT, - LONG_INPUT, - CHECKBOX, - CUSTOM, -} - -interface SettingFieldInput { - type: Exclude; - label: string | React.ReactElement; - help?: string | React.ReactElement; - key: SettKey; -} - -interface SettingFieldCustom { - type: SettingInputType.CUSTOM; - key: SettKey; - component: - | string - | React.FC<{ - value: string | boolean | number; - onChange: (value: string) => void; - }>; -} - -interface SettingSection { - title: React.ReactElement; - fields: (SettingFieldInput | SettingFieldCustom)[]; -} - -const ICON_CLASSNAME = 'w-4 h-4 mr-1 inline'; - -const SETTING_SECTIONS: SettingSection[] = [ - { - title: ( - <> - - General - - ), - fields: [ - { - type: SettingInputType.SHORT_INPUT, - label: 'API Key', - key: 'apiKey', - }, - { - type: SettingInputType.LONG_INPUT, - label: 'System Message (will be disabled if left empty)', - key: 'systemMessage', - }, - ...BASIC_KEYS.map( - (key) => - ({ - type: SettingInputType.SHORT_INPUT, - label: key, - key, - }) as SettingFieldInput - ), - { - type: SettingInputType.SHORT_INPUT, - label: 'Paste length to file', - key: 'pasteLongTextToFileLen', - }, - { - type: SettingInputType.CHECKBOX, - label: 'Parse PDF as image instead of text', - key: 'pdfAsImage', - }, - ], - }, - { - title: ( - <> - - Samplers - - ), - fields: [ - { - type: SettingInputType.SHORT_INPUT, - label: 'Samplers queue', - key: 'samplers', - }, - ...SAMPLER_KEYS.map( - (key) => - ({ - type: SettingInputType.SHORT_INPUT, - label: key, - key, - }) as SettingFieldInput - ), - ], - }, - { - title: ( - <> - - Penalties - - ), - fields: PENALTY_KEYS.map((key) => ({ - type: SettingInputType.SHORT_INPUT, - label: key, - key, - })), - }, - { - title: ( - <> - - Reasoning - - ), - fields: [ - { - type: SettingInputType.CHECKBOX, - label: 'Expand thought process by default when generating messages', - key: 'showThoughtInProgress', - }, - { - type: SettingInputType.CHECKBOX, - label: - 'Exclude thought process when sending requests to API (Recommended for DeepSeek-R1)', - key: 'excludeThoughtOnReq', - }, - ], - }, - { - title: ( - <> - - Advanced - - ), - fields: [ - { - type: SettingInputType.CUSTOM, - key: 'custom', // dummy key, won't be used - component: () => { - const debugImportDemoConv = async () => { - const res = await fetch('/demo-conversation.json'); - const demoConv = await res.json(); - StorageUtils.remove(demoConv.id); - for (const msg of demoConv.messages) { - StorageUtils.appendMsg(demoConv.id, msg); - } - }; - return ( - - ); - }, - }, - { - type: SettingInputType.CHECKBOX, - label: 'Show tokens per second', - key: 'showTokensPerSecond', - }, - { - type: SettingInputType.LONG_INPUT, - label: ( - <> - Custom JSON config (For more info, refer to{' '} - - server documentation - - ) - - ), - key: 'custom', - }, - ], - }, - { - title: ( - <> - - Experimental - - ), - fields: [ - { - type: SettingInputType.CUSTOM, - key: 'custom', // dummy key, won't be used - component: () => ( - <> -

- Experimental features are not guaranteed to work correctly. -
-
- If you encounter any problems, create a{' '} - - Bug (misc.) - {' '} - report on Github. Please also specify webui/experimental on - the report title and include screenshots. -
-
- Some features may require packages downloaded from CDN, so they - need internet connection. -

- - ), - }, - { - type: SettingInputType.CHECKBOX, - label: ( - <> - Enable Python interpreter -
- - This feature uses{' '} - pyodide, - downloaded from CDN. To use this feature, ask the LLM to generate - Python code inside a Markdown code block. You will see a "Run" - button on the code block, near the "Copy" button. - - - ), - key: 'pyIntepreterEnabled', - }, - ], - }, -]; - -export default function SettingDialog({ - show, - onClose, -}: { - show: boolean; - onClose: () => void; -}) { - const { config, saveConfig } = useAppContext(); - const [sectionIdx, setSectionIdx] = useState(0); - - // clone the config object to prevent direct mutation - const [localConfig, setLocalConfig] = useState( - JSON.parse(JSON.stringify(config)) - ); - const { showConfirm, showAlert } = useModals(); - - const resetConfig = async () => { - if (await showConfirm('Are you sure you want to reset all settings?')) { - setLocalConfig(CONFIG_DEFAULT); - } - }; - - const handleSave = async () => { - // copy the local config to prevent direct mutation - const newConfig: typeof CONFIG_DEFAULT = JSON.parse( - JSON.stringify(localConfig) - ); - // validate the config - for (const key in newConfig) { - const value = newConfig[key as SettKey]; - const mustBeBoolean = isBoolean(CONFIG_DEFAULT[key as SettKey]); - const mustBeString = isString(CONFIG_DEFAULT[key as SettKey]); - const mustBeNumeric = isNumeric(CONFIG_DEFAULT[key as SettKey]); - if (mustBeString) { - if (!isString(value)) { - await showAlert(`Value for ${key} must be string`); - return; - } - } else if (mustBeNumeric) { - const trimmedValue = value.toString().trim(); - const numVal = Number(trimmedValue); - if (isNaN(numVal) || !isNumeric(numVal) || trimmedValue.length === 0) { - await showAlert(`Value for ${key} must be numeric`); - return; - } - // force conversion to number - // @ts-expect-error this is safe - newConfig[key] = numVal; - } else if (mustBeBoolean) { - if (!isBoolean(value)) { - await showAlert(`Value for ${key} must be boolean`); - return; - } - } else { - console.error(`Unknown default type for key ${key}`); - } - } - if (isDev) console.log('Saving config', newConfig); - saveConfig(newConfig); - onClose(); - }; - - const onChange = (key: SettKey) => (value: string | boolean) => { - // note: we do not perform validation here, because we may get incomplete value as user is still typing it - setLocalConfig({ ...localConfig, [key]: value }); - }; - - return ( - -
-

Settings

-
- {/* Left panel, showing sections - Desktop version */} -
- {SETTING_SECTIONS.map((section, idx) => ( - - ))} -
- - {/* Left panel, showing sections - Mobile version */} - {/* This menu is skipped on a11y, otherwise it's repeated the desktop version */} -
-
- - {SETTING_SECTIONS[sectionIdx].title} - -
    - {SETTING_SECTIONS.map((section, idx) => ( -
    setSectionIdx(idx)} - dir="auto" - > - {section.title} -
    - ))} -
-
-
- - {/* Right panel, showing setting fields */} -
- {SETTING_SECTIONS[sectionIdx].fields.map((field, idx) => { - const key = `${sectionIdx}-${idx}`; - if (field.type === SettingInputType.SHORT_INPUT) { - return ( - - ); - } else if (field.type === SettingInputType.LONG_INPUT) { - return ( - - ); - } else if (field.type === SettingInputType.CHECKBOX) { - return ( - - ); - } else if (field.type === SettingInputType.CUSTOM) { - return ( -
- {typeof field.component === 'string' - ? field.component - : field.component({ - value: localConfig[field.key], - onChange: onChange(field.key), - })} -
- ); - } - })} - -

- Settings are saved in browser's localStorage -

-
-
- -
- - - -
-
- - ); -} - -function SettingsModalLongInput({ - configKey, - value, - onChange, - label, -}: { - configKey: SettKey; - value: string; - onChange: (value: string) => void; - label?: string; -}) { - return ( -
+
+ +
+ + +
+ + {#each currentSection.fields as field (field.key)} +
+ {#if field.type === 'input'} + + + (localConfig[field.key] = e.currentTarget.value)} + placeholder={`Default: ${SETTING_CONFIG_DEFAULT[field.key] || 'none'}`} + class="max-w-md" + /> + {#if field.help || SETTING_CONFIG_INFO[field.key]} +

+ {field.help || SETTING_CONFIG_INFO[field.key]} +

+ {/if} + {:else if field.type === 'textarea'} + + + diff --git a/tools/server/webui/src/lib/components/ui/tooltip/index.ts b/tools/server/webui/src/lib/components/ui/tooltip/index.ts new file mode 100644 index 0000000000..273d831e6e --- /dev/null +++ b/tools/server/webui/src/lib/components/ui/tooltip/index.ts @@ -0,0 +1,21 @@ +import { Tooltip as TooltipPrimitive } from 'bits-ui'; +import Trigger from './tooltip-trigger.svelte'; +import Content from './tooltip-content.svelte'; + +const Root = TooltipPrimitive.Root; +const Provider = TooltipPrimitive.Provider; +const Portal = TooltipPrimitive.Portal; + +export { + Root, + Trigger, + Content, + Provider, + Portal, + // + Root as Tooltip, + Content as TooltipContent, + Trigger as TooltipTrigger, + Provider as TooltipProvider, + Portal as TooltipPortal +}; diff --git a/tools/server/webui/src/lib/components/ui/tooltip/tooltip-content.svelte b/tools/server/webui/src/lib/components/ui/tooltip/tooltip-content.svelte new file mode 100644 index 0000000000..72ea93a010 --- /dev/null +++ b/tools/server/webui/src/lib/components/ui/tooltip/tooltip-content.svelte @@ -0,0 +1,47 @@ + + + + + {@render children?.()} + + {#snippet child({ props })} +
+ {/snippet} + + + diff --git a/tools/server/webui/src/lib/components/ui/tooltip/tooltip-trigger.svelte b/tools/server/webui/src/lib/components/ui/tooltip/tooltip-trigger.svelte new file mode 100644 index 0000000000..5631d1b4c1 --- /dev/null +++ b/tools/server/webui/src/lib/components/ui/tooltip/tooltip-trigger.svelte @@ -0,0 +1,7 @@ + + + diff --git a/tools/server/webui/src/lib/components/ui/utils.ts b/tools/server/webui/src/lib/components/ui/utils.ts new file mode 100644 index 0000000000..f92bfcbb3f --- /dev/null +++ b/tools/server/webui/src/lib/components/ui/utils.ts @@ -0,0 +1,13 @@ +import { clsx, type ClassValue } from 'clsx'; +import { twMerge } from 'tailwind-merge'; + +export function cn(...inputs: ClassValue[]) { + return twMerge(clsx(inputs)); +} + +// eslint-disable-next-line @typescript-eslint/no-explicit-any +export type WithoutChild = T extends { child?: any } ? Omit : T; +// eslint-disable-next-line @typescript-eslint/no-explicit-any +export type WithoutChildren = T extends { children?: any } ? Omit : T; +export type WithoutChildrenOrChild = WithoutChildren>; +export type WithElementRef = T & { ref?: U | null }; diff --git a/tools/server/webui/src/lib/constants/auto-scroll.ts b/tools/server/webui/src/lib/constants/auto-scroll.ts new file mode 100644 index 0000000000..098f435d6c --- /dev/null +++ b/tools/server/webui/src/lib/constants/auto-scroll.ts @@ -0,0 +1,3 @@ +export const AUTO_SCROLL_INTERVAL = 100; +export const INITIAL_SCROLL_DELAY = 50; +export const AUTO_SCROLL_AT_BOTTOM_THRESHOLD = 10; diff --git a/tools/server/webui/src/lib/constants/debounce.ts b/tools/server/webui/src/lib/constants/debounce.ts new file mode 100644 index 0000000000..7394669f3a --- /dev/null +++ b/tools/server/webui/src/lib/constants/debounce.ts @@ -0,0 +1 @@ +export const SLOTS_DEBOUNCE_INTERVAL = 100; diff --git a/tools/server/webui/src/lib/constants/input-classes.ts b/tools/server/webui/src/lib/constants/input-classes.ts new file mode 100644 index 0000000000..a541cfc553 --- /dev/null +++ b/tools/server/webui/src/lib/constants/input-classes.ts @@ -0,0 +1,6 @@ +export const INPUT_CLASSES = ` + bg-muted/70 dark:bg-muted/85 + border border-border/30 focus-within:border-border dark:border-border/20 dark:focus-within:border-border + outline-none + text-foreground +`; diff --git a/tools/server/webui/src/lib/constants/max-bundle-size.ts b/tools/server/webui/src/lib/constants/max-bundle-size.ts new file mode 100644 index 0000000000..e04348febe --- /dev/null +++ b/tools/server/webui/src/lib/constants/max-bundle-size.ts @@ -0,0 +1 @@ +export const MAX_BUNDLE_SIZE = 2 * 1024 * 1024; diff --git a/tools/server/webui/src/lib/constants/processing-info.ts b/tools/server/webui/src/lib/constants/processing-info.ts new file mode 100644 index 0000000000..726439211b --- /dev/null +++ b/tools/server/webui/src/lib/constants/processing-info.ts @@ -0,0 +1 @@ +export const PROCESSING_INFO_TIMEOUT = 2000; diff --git a/tools/server/webui/src/lib/constants/settings-config.ts b/tools/server/webui/src/lib/constants/settings-config.ts new file mode 100644 index 0000000000..89eff7bdbd --- /dev/null +++ b/tools/server/webui/src/lib/constants/settings-config.ts @@ -0,0 +1,84 @@ +export const SETTING_CONFIG_DEFAULT: Record = { + // Note: in order not to introduce breaking changes, please keep the same data type (number, string, etc) if you want to change the default value. Do not use null or undefined for default value. + // Do not use nested objects, keep it single level. Prefix the key if you need to group them. + apiKey: '', + systemMessage: '', + theme: 'system', + showTokensPerSecond: false, + showThoughtInProgress: false, + keepStatsVisible: false, + askForTitleConfirmation: false, + pasteLongTextToFileLen: 2500, + pdfAsImage: false, + // make sure these default values are in sync with `common.h` + samplers: 'top_k;typ_p;top_p;min_p;temperature', + temperature: 0.8, + dynatemp_range: 0.0, + dynatemp_exponent: 1.0, + top_k: 40, + top_p: 0.95, + min_p: 0.05, + xtc_probability: 0.0, + xtc_threshold: 0.1, + typ_p: 1.0, + repeat_last_n: 64, + repeat_penalty: 1.0, + presence_penalty: 0.0, + frequency_penalty: 0.0, + dry_multiplier: 0.0, + dry_base: 1.75, + dry_allowed_length: 2, + dry_penalty_last_n: -1, + max_tokens: -1, + custom: '', // custom json-stringified object + // experimental features + pyInterpreterEnabled: false +}; + +export const SETTING_CONFIG_INFO: Record = { + 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.', + theme: + 'Choose the color theme for the interface. You can choose between System (follows your device settings), Light, or Dark.', + pasteLongTextToFileLen: + 'On pasting long text, it will be converted to a file. You can control the file length by setting the value of this parameter. Value 0 means disable.', + samplers: + 'The order at which samplers are applied, in simplified way. Default is "top_k;typ_p;top_p;min_p;temperature": top_k->typ_p->top_p->min_p->temperature', + temperature: + 'Controls the randomness of the generated text by affecting the probability distribution of the output tokens. Higher = more random, lower = more focused.', + dynatemp_range: + 'Addon for the temperature sampler. The added value to the range of dynamic temperature, which adjusts probabilities by entropy of tokens.', + dynatemp_exponent: + 'Addon for the temperature sampler. Smoothes out the probability redistribution based on the most probable token.', + top_k: 'Keeps only k top tokens.', + top_p: 'Limits tokens to those that together have a cumulative probability of at least p', + min_p: + 'Limits tokens based on the minimum probability for a token to be considered, relative to the probability of the most likely token.', + xtc_probability: + 'XTC sampler cuts out top tokens; this parameter controls the chance of cutting tokens at all. 0 disables XTC.', + xtc_threshold: + 'XTC sampler cuts out top tokens; this parameter controls the token probability that is required to cut that token.', + typ_p: 'Sorts and limits tokens based on the difference between log-probability and entropy.', + repeat_last_n: 'Last n tokens to consider for penalizing repetition', + repeat_penalty: 'Controls the repetition of token sequences in the generated text', + presence_penalty: 'Limits tokens based on whether they appear in the output or not.', + frequency_penalty: 'Limits tokens based on how often they appear in the output.', + dry_multiplier: + 'DRY sampling reduces repetition in generated text even across long contexts. This parameter sets the DRY sampling multiplier.', + dry_base: + 'DRY sampling reduces repetition in generated text even across long contexts. This parameter sets the DRY sampling base value.', + dry_allowed_length: + 'DRY sampling reduces repetition in generated text even across long contexts. This parameter sets the allowed length for DRY sampling.', + dry_penalty_last_n: + 'DRY sampling reduces repetition in generated text even across long contexts. This parameter sets DRY penalty for the last n tokens.', + max_tokens: 'The maximum number of token per output. Use -1 for infinite (no limit).', + custom: 'Custom JSON parameters to send to the API. Must be valid JSON format.', + showTokensPerSecond: 'Display generation speed in tokens per second during streaming.', + showThoughtInProgress: 'Expand thought process by default when generating messages.', + keepStatsVisible: 'Keep processing statistics visible after generation finishes.', + askForTitleConfirmation: + 'Ask for confirmation before automatically changing conversation title when editing the first message.', + pdfAsImage: 'Parse PDF as image instead of text (requires vision-capable model).', + pyInterpreterEnabled: + 'Enable Python interpreter using Pyodide. Allows running Python code in markdown code blocks.' +}; diff --git a/tools/server/webui/src/lib/constants/supported-file-types.ts b/tools/server/webui/src/lib/constants/supported-file-types.ts new file mode 100644 index 0000000000..f53b55c476 --- /dev/null +++ b/tools/server/webui/src/lib/constants/supported-file-types.ts @@ -0,0 +1,180 @@ +/** + * Comprehensive dictionary of all supported file types in webui + * Organized by category with TypeScript enums for better type safety + */ + +import { + FileExtensionAudio, + FileExtensionImage, + FileExtensionPdf, + FileExtensionText, + FileTypeAudio, + FileTypeImage, + FileTypePdf, + FileTypeText, + MimeTypeAudio, + MimeTypeImage, + MimeTypeApplication, + MimeTypeText +} from '$lib/enums/files'; + +// File type configuration using enums +export const AUDIO_FILE_TYPES = { + [FileTypeAudio.MP3]: { + extensions: [FileExtensionAudio.MP3], + mimeTypes: [MimeTypeAudio.MP3_MPEG, MimeTypeAudio.MP3] + }, + [FileTypeAudio.WAV]: { + extensions: [FileExtensionAudio.WAV], + mimeTypes: [MimeTypeAudio.WAV] + } +} as const; + +export const IMAGE_FILE_TYPES = { + [FileTypeImage.JPEG]: { + extensions: [FileExtensionImage.JPG, FileExtensionImage.JPEG], + mimeTypes: [MimeTypeImage.JPEG] + }, + [FileTypeImage.PNG]: { + extensions: [FileExtensionImage.PNG], + mimeTypes: [MimeTypeImage.PNG] + }, + [FileTypeImage.GIF]: { + extensions: [FileExtensionImage.GIF], + mimeTypes: [MimeTypeImage.GIF] + }, + [FileTypeImage.WEBP]: { + extensions: [FileExtensionImage.WEBP], + mimeTypes: [MimeTypeImage.WEBP] + }, + [FileTypeImage.SVG]: { + extensions: [FileExtensionImage.SVG], + mimeTypes: [MimeTypeImage.SVG] + } +} as const; + +export const PDF_FILE_TYPES = { + [FileTypePdf.PDF]: { + extensions: [FileExtensionPdf.PDF], + mimeTypes: [MimeTypeApplication.PDF] + } +} as const; + +export const TEXT_FILE_TYPES = { + [FileTypeText.PLAIN_TEXT]: { + extensions: [FileExtensionText.TXT], + mimeTypes: [MimeTypeText.PLAIN] + }, + [FileTypeText.MARKDOWN]: { + extensions: [FileExtensionText.MD], + mimeTypes: [MimeTypeText.MARKDOWN] + }, + [FileTypeText.JAVASCRIPT]: { + extensions: [FileExtensionText.JS], + mimeTypes: [MimeTypeText.JAVASCRIPT, MimeTypeText.JAVASCRIPT_APP] + }, + [FileTypeText.TYPESCRIPT]: { + extensions: [FileExtensionText.TS], + mimeTypes: [MimeTypeText.TYPESCRIPT] + }, + [FileTypeText.JSX]: { + extensions: [FileExtensionText.JSX], + mimeTypes: [MimeTypeText.JSX] + }, + [FileTypeText.TSX]: { + extensions: [FileExtensionText.TSX], + mimeTypes: [MimeTypeText.TSX] + }, + [FileTypeText.CSS]: { + extensions: [FileExtensionText.CSS], + mimeTypes: [MimeTypeText.CSS] + }, + [FileTypeText.HTML]: { + extensions: [FileExtensionText.HTML, FileExtensionText.HTM], + mimeTypes: [MimeTypeText.HTML] + }, + [FileTypeText.JSON]: { + extensions: [FileExtensionText.JSON], + mimeTypes: [MimeTypeText.JSON] + }, + [FileTypeText.XML]: { + extensions: [FileExtensionText.XML], + mimeTypes: [MimeTypeText.XML_TEXT, MimeTypeText.XML_APP] + }, + [FileTypeText.YAML]: { + extensions: [FileExtensionText.YAML, FileExtensionText.YML], + mimeTypes: [MimeTypeText.YAML_TEXT, MimeTypeText.YAML_APP] + }, + [FileTypeText.CSV]: { + extensions: [FileExtensionText.CSV], + mimeTypes: [MimeTypeText.CSV] + }, + [FileTypeText.LOG]: { + extensions: [FileExtensionText.LOG], + mimeTypes: [MimeTypeText.PLAIN] + }, + [FileTypeText.PYTHON]: { + extensions: [FileExtensionText.PY], + mimeTypes: [MimeTypeText.PYTHON] + }, + [FileTypeText.JAVA]: { + extensions: [FileExtensionText.JAVA], + mimeTypes: [MimeTypeText.JAVA] + }, + [FileTypeText.CPP]: { + extensions: [FileExtensionText.CPP, FileExtensionText.C, FileExtensionText.H], + mimeTypes: [MimeTypeText.CPP_SRC, MimeTypeText.C_SRC, MimeTypeText.C_HDR] + }, + [FileTypeText.PHP]: { + extensions: [FileExtensionText.PHP], + mimeTypes: [MimeTypeText.PHP] + }, + [FileTypeText.RUBY]: { + extensions: [FileExtensionText.RB], + mimeTypes: [MimeTypeText.RUBY] + }, + [FileTypeText.GO]: { + extensions: [FileExtensionText.GO], + mimeTypes: [MimeTypeText.GO] + }, + [FileTypeText.RUST]: { + extensions: [FileExtensionText.RS], + mimeTypes: [MimeTypeText.RUST] + }, + [FileTypeText.SHELL]: { + extensions: [FileExtensionText.SH, FileExtensionText.BAT], + mimeTypes: [MimeTypeText.SHELL, MimeTypeText.BAT] + }, + [FileTypeText.SQL]: { + extensions: [FileExtensionText.SQL], + mimeTypes: [MimeTypeText.SQL] + }, + [FileTypeText.R]: { + extensions: [FileExtensionText.R], + mimeTypes: [MimeTypeText.R] + }, + [FileTypeText.SCALA]: { + extensions: [FileExtensionText.SCALA], + mimeTypes: [MimeTypeText.SCALA] + }, + [FileTypeText.KOTLIN]: { + extensions: [FileExtensionText.KT], + mimeTypes: [MimeTypeText.KOTLIN] + }, + [FileTypeText.SWIFT]: { + extensions: [FileExtensionText.SWIFT], + mimeTypes: [MimeTypeText.SWIFT] + }, + [FileTypeText.DART]: { + extensions: [FileExtensionText.DART], + mimeTypes: [MimeTypeText.DART] + }, + [FileTypeText.VUE]: { + extensions: [FileExtensionText.VUE], + mimeTypes: [MimeTypeText.VUE] + }, + [FileTypeText.SVELTE]: { + extensions: [FileExtensionText.SVELTE], + mimeTypes: [MimeTypeText.SVELTE] + } +} as const; diff --git a/tools/server/webui/src/lib/constants/tooltip-config.ts b/tools/server/webui/src/lib/constants/tooltip-config.ts new file mode 100644 index 0000000000..3c30c8c072 --- /dev/null +++ b/tools/server/webui/src/lib/constants/tooltip-config.ts @@ -0,0 +1 @@ +export const TOOLTIP_DELAY_DURATION = 100; diff --git a/tools/server/webui/src/lib/constants/viewport.ts b/tools/server/webui/src/lib/constants/viewport.ts new file mode 100644 index 0000000000..26e202cfea --- /dev/null +++ b/tools/server/webui/src/lib/constants/viewport.ts @@ -0,0 +1 @@ +export const DEFAULT_MOBILE_BREAKPOINT = 768; diff --git a/tools/server/webui/src/lib/enums/files.ts b/tools/server/webui/src/lib/enums/files.ts new file mode 100644 index 0000000000..5aec9e7e9f --- /dev/null +++ b/tools/server/webui/src/lib/enums/files.ts @@ -0,0 +1,178 @@ +/** + * Comprehensive dictionary of all supported file types in webui + * Organized by category with TypeScript enums for better type safety + */ + +// File type category enum +export enum FileTypeCategory { + IMAGE = 'image', + AUDIO = 'audio', + PDF = 'pdf', + TEXT = 'text' +} + +// Specific file type enums for each category +export enum FileTypeImage { + JPEG = 'jpeg', + PNG = 'png', + GIF = 'gif', + WEBP = 'webp', + SVG = 'svg' +} + +export enum FileTypeAudio { + MP3 = 'mp3', + WAV = 'wav', + WEBM = 'webm' +} + +export enum FileTypePdf { + PDF = 'pdf' +} + +export enum FileTypeText { + PLAIN_TEXT = 'plainText', + MARKDOWN = 'markdown', + JAVASCRIPT = 'javascript', + TYPESCRIPT = 'typescript', + JSX = 'jsx', + TSX = 'tsx', + CSS = 'css', + HTML = 'html', + JSON = 'json', + XML = 'xml', + YAML = 'yaml', + CSV = 'csv', + LOG = 'log', + PYTHON = 'python', + JAVA = 'java', + CPP = 'cpp', + PHP = 'php', + RUBY = 'ruby', + GO = 'go', + RUST = 'rust', + SHELL = 'shell', + SQL = 'sql', + R = 'r', + SCALA = 'scala', + KOTLIN = 'kotlin', + SWIFT = 'swift', + DART = 'dart', + VUE = 'vue', + SVELTE = 'svelte' +} + +// File extension enums +export enum FileExtensionImage { + JPG = '.jpg', + JPEG = '.jpeg', + PNG = '.png', + GIF = '.gif', + WEBP = '.webp', + SVG = '.svg' +} + +export enum FileExtensionAudio { + MP3 = '.mp3', + WAV = '.wav' +} + +export enum FileExtensionPdf { + PDF = '.pdf' +} + +export enum FileExtensionText { + TXT = '.txt', + MD = '.md', + JS = '.js', + TS = '.ts', + JSX = '.jsx', + TSX = '.tsx', + CSS = '.css', + HTML = '.html', + HTM = '.htm', + JSON = '.json', + XML = '.xml', + YAML = '.yaml', + YML = '.yml', + CSV = '.csv', + LOG = '.log', + PY = '.py', + JAVA = '.java', + CPP = '.cpp', + C = '.c', + H = '.h', + PHP = '.php', + RB = '.rb', + GO = '.go', + RS = '.rs', + SH = '.sh', + BAT = '.bat', + SQL = '.sql', + R = '.r', + SCALA = '.scala', + KT = '.kt', + SWIFT = '.swift', + DART = '.dart', + VUE = '.vue', + SVELTE = '.svelte' +} + +// MIME type enums +export enum MimeTypeApplication { + PDF = 'application/pdf' +} + +export enum MimeTypeAudio { + MP3_MPEG = 'audio/mpeg', + MP3 = 'audio/mp3', + MP4 = 'audio/mp4', + WAV = 'audio/wav', + WEBM = 'audio/webm', + WEBM_OPUS = 'audio/webm;codecs=opus' +} + +export enum MimeTypeImage { + JPEG = 'image/jpeg', + PNG = 'image/png', + GIF = 'image/gif', + WEBP = 'image/webp', + SVG = 'image/svg+xml' +} + +export enum MimeTypeText { + PLAIN = 'text/plain', + MARKDOWN = 'text/markdown', + JAVASCRIPT = 'text/javascript', + JAVASCRIPT_APP = 'application/javascript', + TYPESCRIPT = 'text/typescript', + JSX = 'text/jsx', + TSX = 'text/tsx', + CSS = 'text/css', + HTML = 'text/html', + JSON = 'application/json', + XML_TEXT = 'text/xml', + XML_APP = 'application/xml', + YAML_TEXT = 'text/yaml', + YAML_APP = 'application/yaml', + CSV = 'text/csv', + PYTHON = 'text/x-python', + JAVA = 'text/x-java-source', + CPP_SRC = 'text/x-c++src', + C_SRC = 'text/x-csrc', + C_HDR = 'text/x-chdr', + PHP = 'text/x-php', + RUBY = 'text/x-ruby', + GO = 'text/x-go', + RUST = 'text/x-rust', + SHELL = 'text/x-shellscript', + BAT = 'application/x-bat', + SQL = 'text/x-sql', + R = 'text/x-r', + SCALA = 'text/x-scala', + KOTLIN = 'text/x-kotlin', + SWIFT = 'text/x-swift', + DART = 'text/x-dart', + VUE = 'text/x-vue', + SVELTE = 'text/x-svelte' +} diff --git a/tools/server/webui/src/lib/hooks/is-mobile.svelte.ts b/tools/server/webui/src/lib/hooks/is-mobile.svelte.ts new file mode 100644 index 0000000000..22c74f4a6f --- /dev/null +++ b/tools/server/webui/src/lib/hooks/is-mobile.svelte.ts @@ -0,0 +1,8 @@ +import { DEFAULT_MOBILE_BREAKPOINT } from '$lib/constants/viewport'; +import { MediaQuery } from 'svelte/reactivity'; + +export class IsMobile extends MediaQuery { + constructor(breakpoint: number = DEFAULT_MOBILE_BREAKPOINT) { + super(`max-width: ${breakpoint - 1}px`); + } +} diff --git a/tools/server/webui/src/lib/hooks/use-processing-state.svelte.ts b/tools/server/webui/src/lib/hooks/use-processing-state.svelte.ts new file mode 100644 index 0000000000..e8c3aa1ae8 --- /dev/null +++ b/tools/server/webui/src/lib/hooks/use-processing-state.svelte.ts @@ -0,0 +1,173 @@ +import { slotsService } from '$lib/services'; +import { config } from '$lib/stores/settings.svelte'; + +export interface UseProcessingStateReturn { + readonly processingState: ApiProcessingState | null; + getProcessingDetails(): string[]; + getProcessingMessage(): string; + shouldShowDetails(): boolean; + startMonitoring(): Promise; + stopMonitoring(): void; +} + +/** + * useProcessingState - Reactive processing state hook + * + * This hook provides reactive access to the processing state of the server. + * It subscribes to timing data updates from the slots service and provides + * formatted processing details for UI display. + * + * **Features:** + * - Real-time processing state monitoring + * - Context and output token tracking + * - Tokens per second calculation + * - Graceful degradation when slots endpoint unavailable + * - Automatic cleanup on component unmount + * + * @returns Hook interface with processing state and control methods + */ +export function useProcessingState(): UseProcessingStateReturn { + let isMonitoring = $state(false); + let processingState = $state(null); + let lastKnownState = $state(null); + let unsubscribe: (() => void) | null = null; + + async function startMonitoring(): Promise { + if (isMonitoring) return; + + isMonitoring = true; + + unsubscribe = slotsService.subscribe((state) => { + processingState = state; + if (state) { + lastKnownState = state; + } else { + lastKnownState = null; + } + }); + + try { + const currentState = await slotsService.getCurrentState(); + + if (currentState) { + processingState = currentState; + lastKnownState = currentState; + } + + if (slotsService.isStreaming()) { + slotsService.startStreaming(); + } + } catch (error) { + console.warn('Failed to start slots monitoring:', error); + // Continue without slots monitoring - graceful degradation + } + } + + function stopMonitoring(): void { + if (!isMonitoring) return; + + isMonitoring = false; + + // Only clear processing state if keepStatsVisible is disabled + // This preserves the last known state for display when stats should remain visible + const currentConfig = config(); + if (!currentConfig.keepStatsVisible) { + processingState = null; + } else if (lastKnownState) { + // Keep the last known state visible when keepStatsVisible is enabled + processingState = lastKnownState; + } + + if (unsubscribe) { + unsubscribe(); + unsubscribe = null; + } + } + + function getProcessingMessage(): string { + if (!processingState) { + return 'Processing...'; + } + + switch (processingState.status) { + case 'initializing': + return 'Initializing...'; + case 'preparing': + if (processingState.progressPercent !== undefined) { + return `Processing (${processingState.progressPercent}%)`; + } + return 'Preparing response...'; + case 'generating': + if (processingState.tokensDecoded > 0) { + return `Generating... (${processingState.tokensDecoded} tokens)`; + } + return 'Generating...'; + default: + return 'Processing...'; + } + } + + function getProcessingDetails(): string[] { + // Use current processing state or fall back to last known state + const stateToUse = processingState || lastKnownState; + if (!stateToUse) { + return []; + } + + const details: string[] = []; + const currentConfig = config(); // Get fresh config each time + + // Always show context info when we have valid data + if (stateToUse.contextUsed >= 0 && stateToUse.contextTotal > 0) { + const contextPercent = Math.round((stateToUse.contextUsed / stateToUse.contextTotal) * 100); + + details.push( + `Context: ${stateToUse.contextUsed}/${stateToUse.contextTotal} (${contextPercent}%)` + ); + } + + if (stateToUse.outputTokensUsed > 0) { + // Handle infinite max_tokens (-1) case + if (stateToUse.outputTokensMax <= 0) { + details.push(`Output: ${stateToUse.outputTokensUsed}/∞`); + } else { + const outputPercent = Math.round( + (stateToUse.outputTokensUsed / stateToUse.outputTokensMax) * 100 + ); + + details.push( + `Output: ${stateToUse.outputTokensUsed}/${stateToUse.outputTokensMax} (${outputPercent}%)` + ); + } + } + + if ( + currentConfig.showTokensPerSecond && + stateToUse.tokensPerSecond && + stateToUse.tokensPerSecond > 0 + ) { + details.push(`${stateToUse.tokensPerSecond.toFixed(1)} tokens/sec`); + } + + if (stateToUse.speculative) { + details.push('Speculative decoding enabled'); + } + + return details; + } + + function shouldShowDetails(): boolean { + return processingState !== null && processingState.status !== 'idle'; + } + + return { + get processingState() { + return processingState; + }, + getProcessingDetails, + getProcessingMessage, + shouldShowDetails, + startMonitoring, + stopMonitoring + }; +} diff --git a/tools/server/webui/src/lib/services/chat.ts b/tools/server/webui/src/lib/services/chat.ts new file mode 100644 index 0000000000..7133bbab81 --- /dev/null +++ b/tools/server/webui/src/lib/services/chat.ts @@ -0,0 +1,715 @@ +import { config } from '$lib/stores/settings.svelte'; +import { slotsService } from './slots'; +/** + * ChatService - Low-level API communication layer for llama.cpp server interactions + * + * This service handles direct communication with the llama.cpp server's chat completion API. + * It provides the network layer abstraction for AI model interactions while remaining + * stateless and focused purely on API communication. + * + * **Architecture & Relationship with ChatStore:** + * - **ChatService** (this class): Stateless API communication layer + * - Handles HTTP requests/responses with llama.cpp server + * - Manages streaming and non-streaming response parsing + * - Provides request abortion capabilities + * - Converts database messages to API format + * - Handles error translation and context detection + * + * - **ChatStore**: Stateful orchestration and UI state management + * - Uses ChatService for all AI model communication + * - Manages conversation state, message history, and UI reactivity + * - Coordinates with DatabaseStore for persistence + * - Handles complex workflows like branching and regeneration + * + * **Key Responsibilities:** + * - Message format conversion (DatabaseMessage → API format) + * - Streaming response handling with real-time callbacks + * - Reasoning content extraction and processing + * - File attachment processing (images, PDFs, audio, text) + * - Context error detection and reporting + * - Request lifecycle management (abort, cleanup) + */ +export class ChatService { + private abortController: AbortController | null = null; + + /** + * Sends a chat completion request to the llama.cpp server. + * Supports both streaming and non-streaming responses with comprehensive parameter configuration. + * Automatically converts database messages with attachments to the appropriate API format. + * + * @param messages - Array of chat messages to send to the API (supports both ApiChatMessageData and DatabaseMessage with attachments) + * @param options - Configuration options for the chat completion request. See `SettingsChatServiceOptions` type for details. + * @returns {Promise} that resolves to the complete response string (non-streaming) or void (streaming) + * @throws {Error} if the request fails or is aborted + */ + async sendMessage( + messages: ApiChatMessageData[] | (DatabaseMessage & { extra?: DatabaseMessageExtra[] })[], + options: SettingsChatServiceOptions = {} + ): Promise { + const { + stream, + onChunk, + onComplete, + onError, + // Generation parameters + temperature, + max_tokens, + // Sampling parameters + dynatemp_range, + dynatemp_exponent, + top_k, + top_p, + min_p, + xtc_probability, + xtc_threshold, + typ_p, + // Penalty parameters + repeat_last_n, + repeat_penalty, + presence_penalty, + frequency_penalty, + dry_multiplier, + dry_base, + dry_allowed_length, + dry_penalty_last_n, + // Other parameters + samplers, + custom, + timings_per_token + } = options; + + // Cancel any ongoing request and create a new abort controller + this.abort(); + this.abortController = new AbortController(); + + // Convert database messages with attachments to API format if needed + const normalizedMessages: ApiChatMessageData[] = messages + .map((msg) => { + // Check if this is a DatabaseMessage by checking for DatabaseMessage-specific fields + if ('id' in msg && 'convId' in msg && 'timestamp' in msg) { + // This is a DatabaseMessage, convert it + const dbMsg = msg as DatabaseMessage & { extra?: DatabaseMessageExtra[] }; + return ChatService.convertMessageToChatServiceData(dbMsg); + } else { + // This is already an ApiChatMessageData object + return msg as ApiChatMessageData; + } + }) + .filter((msg) => { + // Filter out empty system messages + if (msg.role === 'system') { + const content = typeof msg.content === 'string' ? msg.content : ''; + + return content.trim().length > 0; + } + + return true; + }); + + // Build base request body with system message injection + const processedMessages = this.injectSystemMessage(normalizedMessages); + + const requestBody: ApiChatCompletionRequest = { + messages: processedMessages.map((msg: ApiChatMessageData) => ({ + role: msg.role, + content: msg.content + })), + stream + }; + + requestBody.reasoning_format = 'auto'; + + if (temperature !== undefined) requestBody.temperature = temperature; + // Set max_tokens to -1 (infinite) if not provided or empty + requestBody.max_tokens = + max_tokens !== undefined && max_tokens !== null && max_tokens !== 0 ? max_tokens : -1; + + if (dynatemp_range !== undefined) requestBody.dynatemp_range = dynatemp_range; + if (dynatemp_exponent !== undefined) requestBody.dynatemp_exponent = dynatemp_exponent; + if (top_k !== undefined) requestBody.top_k = top_k; + if (top_p !== undefined) requestBody.top_p = top_p; + if (min_p !== undefined) requestBody.min_p = min_p; + if (xtc_probability !== undefined) requestBody.xtc_probability = xtc_probability; + if (xtc_threshold !== undefined) requestBody.xtc_threshold = xtc_threshold; + if (typ_p !== undefined) requestBody.typ_p = typ_p; + + if (repeat_last_n !== undefined) requestBody.repeat_last_n = repeat_last_n; + if (repeat_penalty !== undefined) requestBody.repeat_penalty = repeat_penalty; + if (presence_penalty !== undefined) requestBody.presence_penalty = presence_penalty; + if (frequency_penalty !== undefined) requestBody.frequency_penalty = frequency_penalty; + if (dry_multiplier !== undefined) requestBody.dry_multiplier = dry_multiplier; + if (dry_base !== undefined) requestBody.dry_base = dry_base; + if (dry_allowed_length !== undefined) requestBody.dry_allowed_length = dry_allowed_length; + if (dry_penalty_last_n !== undefined) requestBody.dry_penalty_last_n = dry_penalty_last_n; + + if (samplers !== undefined) { + requestBody.samplers = + typeof samplers === 'string' + ? samplers.split(';').filter((s: string) => s.trim()) + : samplers; + } + + if (timings_per_token !== undefined) requestBody.timings_per_token = timings_per_token; + + if (custom) { + try { + const customParams = typeof custom === 'string' ? JSON.parse(custom) : custom; + Object.assign(requestBody, customParams); + } catch (error) { + console.warn('Failed to parse custom parameters:', error); + } + } + + try { + const currentConfig = config(); + const apiKey = currentConfig.apiKey?.toString().trim(); + + const response = await fetch(`/v1/chat/completions`, { + method: 'POST', + headers: { + 'Content-Type': 'application/json', + ...(apiKey ? { Authorization: `Bearer ${apiKey}` } : {}) + }, + body: JSON.stringify(requestBody), + signal: this.abortController.signal + }); + + if (!response.ok) { + // Use the new parseErrorResponse method to handle structured errors + const error = await this.parseErrorResponse(response); + if (onError) { + onError(error); + } + throw error; + } + + if (stream) { + return this.handleStreamResponse( + response, + onChunk, + onComplete, + onError, + options.onReasoningChunk + ); + } else { + return this.handleNonStreamResponse(response, onComplete, onError); + } + } catch (error) { + if (error instanceof Error && error.name === 'AbortError') { + console.log('Chat completion request was aborted'); + return; + } + + let userFriendlyError: Error; + + if (error instanceof Error) { + if (error.name === 'TypeError' && error.message.includes('fetch')) { + userFriendlyError = new Error( + 'Unable to connect to server - please check if the server is running' + ); + } else if (error.message.includes('ECONNREFUSED')) { + userFriendlyError = new Error('Connection refused - server may be offline'); + } else if (error.message.includes('ETIMEDOUT')) { + userFriendlyError = new Error('Request timeout - server may be overloaded'); + } else { + userFriendlyError = error; + } + } else { + userFriendlyError = new Error('Unknown error occurred while sending message'); + } + + console.error('Error in sendMessage:', error); + if (onError) { + onError(userFriendlyError); + } + throw userFriendlyError; + } + } + + /** + * Handles streaming response from the chat completion API. + * Processes server-sent events and extracts content chunks from the stream. + * + * @param response - The fetch Response object containing the streaming data + * @param onChunk - Optional callback invoked for each content chunk received + * @param onComplete - Optional callback invoked when the stream is complete with full response + * @param onError - Optional callback invoked if an error occurs during streaming + * @param onReasoningChunk - Optional callback invoked for each reasoning content chunk + * @returns {Promise} Promise that resolves when streaming is complete + * @throws {Error} if the stream cannot be read or parsed + */ + private async handleStreamResponse( + response: Response, + onChunk?: (chunk: string) => void, + onComplete?: ( + response: string, + reasoningContent?: string, + timings?: ChatMessageTimings + ) => void, + onError?: (error: Error) => void, + onReasoningChunk?: (chunk: string) => void + ): Promise { + const reader = response.body?.getReader(); + + if (!reader) { + throw new Error('No response body'); + } + + const decoder = new TextDecoder(); + let fullResponse = ''; + let fullReasoningContent = ''; + let regularContent = ''; + let insideThinkTag = false; + let hasReceivedData = false; + let lastTimings: ChatMessageTimings | undefined; + + try { + while (true) { + const { done, value } = await reader.read(); + if (done) break; + + const chunk = decoder.decode(value, { stream: true }); + const lines = chunk.split('\n'); + + for (const line of lines) { + if (line.startsWith('data: ')) { + const data = line.slice(6); + if (data === '[DONE]') { + if (!hasReceivedData && fullResponse.length === 0) { + const contextError = new Error( + 'The request exceeds the available context size. Try increasing the context size or enable context shift.' + ); + contextError.name = 'ContextError'; + onError?.(contextError); + return; + } + + onComplete?.(regularContent, fullReasoningContent || undefined, lastTimings); + + return; + } + + try { + const parsed: ApiChatCompletionStreamChunk = JSON.parse(data); + + const content = parsed.choices[0]?.delta?.content; + const reasoningContent = parsed.choices[0]?.delta?.reasoning_content; + const timings = parsed.timings; + const promptProgress = parsed.prompt_progress; + + if (timings || promptProgress) { + this.updateProcessingState(timings, promptProgress); + + // Store the latest timing data + if (timings) { + lastTimings = timings; + } + } + + if (content) { + hasReceivedData = true; + fullResponse += content; + + // Track the regular content before processing this chunk + const regularContentBefore = regularContent; + + // Process content character by character to handle think tags + insideThinkTag = this.processContentForThinkTags( + content, + insideThinkTag, + () => { + // Think content is ignored - we don't include it in API requests + }, + (regularChunk) => { + regularContent += regularChunk; + } + ); + + const newRegularContent = regularContent.slice(regularContentBefore.length); + if (newRegularContent) { + onChunk?.(newRegularContent); + } + } + + if (reasoningContent) { + hasReceivedData = true; + fullReasoningContent += reasoningContent; + onReasoningChunk?.(reasoningContent); + } + } catch (e) { + console.error('Error parsing JSON chunk:', e); + } + } + } + } + + if (!hasReceivedData && fullResponse.length === 0) { + const contextError = new Error( + 'The request exceeds the available context size. Try increasing the context size or enable context shift.' + ); + contextError.name = 'ContextError'; + onError?.(contextError); + return; + } + } catch (error) { + const err = error instanceof Error ? error : new Error('Stream error'); + + onError?.(err); + + throw err; + } finally { + reader.releaseLock(); + } + } + + /** + * Handles non-streaming response from the chat completion API. + * Parses the JSON response and extracts the generated content. + * + * @param response - The fetch Response object containing the JSON data + * @param onComplete - Optional callback invoked when response is successfully parsed + * @param onError - Optional callback invoked if an error occurs during parsing + * @returns {Promise} Promise that resolves to the generated content string + * @throws {Error} if the response cannot be parsed or is malformed + */ + private async handleNonStreamResponse( + response: Response, + onComplete?: ( + response: string, + reasoningContent?: string, + timings?: ChatMessageTimings + ) => void, + onError?: (error: Error) => void + ): Promise { + try { + const responseText = await response.text(); + + if (!responseText.trim()) { + const contextError = new Error( + 'The request exceeds the available context size. Try increasing the context size or enable context shift.' + ); + contextError.name = 'ContextError'; + onError?.(contextError); + throw contextError; + } + + const data: ApiChatCompletionResponse = JSON.parse(responseText); + const content = data.choices[0]?.message?.content || ''; + const reasoningContent = data.choices[0]?.message?.reasoning_content; + + if (reasoningContent) { + console.log('Full reasoning content:', reasoningContent); + } + + if (!content.trim()) { + const contextError = new Error( + 'The request exceeds the available context size. Try increasing the context size or enable context shift.' + ); + contextError.name = 'ContextError'; + onError?.(contextError); + throw contextError; + } + + onComplete?.(content, reasoningContent); + + return content; + } catch (error) { + if (error instanceof Error && error.name === 'ContextError') { + throw error; + } + + const err = error instanceof Error ? error : new Error('Parse error'); + + onError?.(err); + + throw err; + } + } + + /** + * Converts a database message with attachments to API chat message format. + * Processes various attachment types (images, text files, PDFs) and formats them + * as content parts suitable for the chat completion API. + * + * @param message - Database message object with optional extra attachments + * @param message.content - The text content of the message + * @param message.role - The role of the message sender (user, assistant, system) + * @param message.extra - Optional array of message attachments (images, files, etc.) + * @returns {ApiChatMessageData} object formatted for the chat completion API + * @static + */ + static convertMessageToChatServiceData( + message: DatabaseMessage & { extra?: DatabaseMessageExtra[] } + ): ApiChatMessageData { + if (!message.extra || message.extra.length === 0) { + return { + role: message.role as 'user' | 'assistant' | 'system', + content: message.content + }; + } + + const contentParts: ApiChatMessageContentPart[] = []; + + if (message.content) { + contentParts.push({ + type: 'text', + text: message.content + }); + } + + const imageFiles = message.extra.filter( + (extra: DatabaseMessageExtra): extra is DatabaseMessageExtraImageFile => + extra.type === 'imageFile' + ); + + for (const image of imageFiles) { + contentParts.push({ + type: 'image_url', + image_url: { url: image.base64Url } + }); + } + + const textFiles = message.extra.filter( + (extra: DatabaseMessageExtra): extra is DatabaseMessageExtraTextFile => + extra.type === 'textFile' + ); + + for (const textFile of textFiles) { + contentParts.push({ + type: 'text', + text: `\n\n--- File: ${textFile.name} ---\n${textFile.content}` + }); + } + + const audioFiles = message.extra.filter( + (extra: DatabaseMessageExtra): extra is DatabaseMessageExtraAudioFile => + extra.type === 'audioFile' + ); + + for (const audio of audioFiles) { + contentParts.push({ + type: 'input_audio', + input_audio: { + data: audio.base64Data, + format: audio.mimeType.includes('wav') ? 'wav' : 'mp3' + } + }); + } + + const pdfFiles = message.extra.filter( + (extra: DatabaseMessageExtra): extra is DatabaseMessageExtraPdfFile => + extra.type === 'pdfFile' + ); + + for (const pdfFile of pdfFiles) { + if (pdfFile.processedAsImages && pdfFile.images) { + for (let i = 0; i < pdfFile.images.length; i++) { + contentParts.push({ + type: 'image_url', + image_url: { url: pdfFile.images[i] } + }); + } + } else { + contentParts.push({ + type: 'text', + text: `\n\n--- PDF File: ${pdfFile.name} ---\n${pdfFile.content}` + }); + } + } + + return { + role: message.role as 'user' | 'assistant' | 'system', + content: contentParts + }; + } + + /** + * Get server properties - static method for API compatibility + */ + static async getServerProps(): Promise { + try { + const currentConfig = config(); + const apiKey = currentConfig.apiKey?.toString().trim(); + + const response = await fetch(`/props`, { + headers: { + 'Content-Type': 'application/json', + ...(apiKey ? { Authorization: `Bearer ${apiKey}` } : {}) + } + }); + + 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; + } + } + + /** + * Processes content to separate thinking tags from regular content. + * Parses and tags to route content to appropriate handlers. + * + * @param content - The content string to process + * @param currentInsideThinkTag - Current state of whether we're inside a think tag + * @param addThinkContent - Callback to handle content inside think tags + * @param addRegularContent - Callback to handle regular content outside think tags + * @returns Boolean indicating if we're still inside a think tag after processing + * @private + */ + private processContentForThinkTags( + content: string, + currentInsideThinkTag: boolean, + addThinkContent: (chunk: string) => void, + addRegularContent: (chunk: string) => void + ): boolean { + let i = 0; + let insideThinkTag = currentInsideThinkTag; + + while (i < content.length) { + if (!insideThinkTag && content.substring(i, i + 7) === '') { + insideThinkTag = true; + i += 7; // Skip the tag + continue; + } + + if (insideThinkTag && content.substring(i, i + 8) === '') { + insideThinkTag = false; + i += 8; // Skip the tag + continue; + } + + if (insideThinkTag) { + addThinkContent(content[i]); + } else { + addRegularContent(content[i]); + } + + i++; + } + + return insideThinkTag; + } + + /** + * Aborts any ongoing chat completion request. + * Cancels the current request and cleans up the abort controller. + * + * @public + */ + public abort(): void { + if (this.abortController) { + this.abortController.abort(); + this.abortController = null; + } + } + + /** + * Injects a system message at the beginning of the conversation if configured in settings. + * Checks for existing system messages to avoid duplication and retrieves the system message + * from the current configuration settings. + * + * @param messages - Array of chat messages to process + * @returns Array of messages with system message injected at the beginning if configured + * @private + */ + private injectSystemMessage(messages: ApiChatMessageData[]): ApiChatMessageData[] { + const currentConfig = config(); + const systemMessage = currentConfig.systemMessage?.toString().trim(); + + if (!systemMessage) { + return messages; + } + + if (messages.length > 0 && messages[0].role === 'system') { + if (messages[0].content !== systemMessage) { + const updatedMessages = [...messages]; + updatedMessages[0] = { + role: 'system', + content: systemMessage + }; + return updatedMessages; + } + + return messages; + } + + const systemMsg: ApiChatMessageData = { + role: 'system', + content: systemMessage + }; + + 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 async parseErrorResponse(response: Response): Promise { + try { + const errorText = await response.text(); + const errorData: ApiErrorResponse = JSON.parse(errorText); + + if (errorData.error?.type === 'exceed_context_size_error') { + const contextError = errorData.error as ApiContextSizeError; + const error = new Error(contextError.message); + error.name = 'ContextError'; + // Attach structured context information + ( + error as Error & { + contextInfo?: { promptTokens: number; maxContext: number; estimatedTokens: number }; + } + ).contextInfo = { + promptTokens: contextError.n_prompt_tokens, + maxContext: contextError.n_ctx, + estimatedTokens: contextError.n_prompt_tokens + }; + return error; + } + + // Fallback for other error types + const message = errorData.error?.message || 'Unknown server error'; + return new Error(message); + } catch { + // If we can't parse the error response, return a generic error + return new Error(`Server error (${response.status}): ${response.statusText}`); + } + } + + /** + * Updates the processing state with timing information from the server response + * @param timings - Timing data from the API response + * @param promptProgress - Progress data from the API response + */ + private updateProcessingState( + timings?: ChatMessageTimings, + promptProgress?: ChatMessagePromptProgress + ): void { + // Calculate tokens per second from timing data + const tokensPerSecond = + timings?.predicted_ms && timings?.predicted_n + ? (timings.predicted_n / timings.predicted_ms) * 1000 + : 0; + + // Update slots service with timing data (async but don't wait) + slotsService + .updateFromTimingData({ + prompt_n: timings?.prompt_n || 0, + predicted_n: timings?.predicted_n || 0, + predicted_per_second: tokensPerSecond, + cache_n: timings?.cache_n || 0, + prompt_progress: promptProgress + }) + .catch((error) => { + console.warn('Failed to update processing state:', error); + }); + } +} + +export const chatService = new ChatService(); diff --git a/tools/server/webui/src/lib/services/context.ts b/tools/server/webui/src/lib/services/context.ts new file mode 100644 index 0000000000..d4af7508e7 --- /dev/null +++ b/tools/server/webui/src/lib/services/context.ts @@ -0,0 +1,102 @@ +import { slotsService } from './slots'; + +export interface ContextCheckResult { + wouldExceed: boolean; + currentUsage: number; + maxContext: number; + availableTokens: number; + reservedTokens: number; +} + +/** + * ContextService - Context window management and limit checking + * + * This service provides context window monitoring and limit checking using real-time + * server data from the slots service. It helps prevent context overflow by tracking + * current usage and calculating available space for new content. + * + * **Architecture & Relationships:** + * - **ContextService** (this class): Context limit monitoring + * - Uses SlotsService for real-time context usage data + * - Calculates available tokens with configurable reserves + * - Provides context limit checking and error messaging + * - Helps prevent context window overflow + * + * - **SlotsService**: Provides current context usage from server slots + * - **ChatStore**: Uses context checking before sending messages + * - **UI Components**: Display context usage warnings and limits + * + * **Key Features:** + * - **Real-time Context Checking**: Uses live server data for accuracy + * - **Token Reservation**: Reserves tokens for response generation + * - **Limit Detection**: Prevents context window overflow + * - **Usage Reporting**: Detailed context usage statistics + * - **Error Messaging**: User-friendly context limit messages + * - **Configurable Reserves**: Adjustable token reservation for responses + * + * **Context Management:** + * - Monitors current context usage from active slots + * - Calculates available space considering reserved tokens + * - Provides early warning before context limits are reached + * - Helps optimize conversation length and content + */ +export class ContextService { + private reserveTokens: number; + + constructor(reserveTokens = 512) { + this.reserveTokens = reserveTokens; + } + + /** + * Checks if the context limit would be exceeded + * + * @returns {Promise} Promise that resolves to the context check result or null if an error occurs + */ + async checkContextLimit(): Promise { + try { + const currentState = await slotsService.getCurrentState(); + + if (!currentState) { + return null; + } + + const maxContext = currentState.contextTotal; + const currentUsage = currentState.contextUsed; + const availableTokens = maxContext - currentUsage - this.reserveTokens; + const wouldExceed = availableTokens <= 0; + + return { + wouldExceed, + currentUsage, + maxContext, + availableTokens: Math.max(0, availableTokens), + reservedTokens: this.reserveTokens + }; + } catch (error) { + console.warn('Error checking context limit:', error); + return null; + } + } + + /** + * Returns a formatted error message for context limit exceeded + * + * @param {ContextCheckResult} result - Context check result + * @returns {string} Formatted error message + */ + getContextErrorMessage(result: ContextCheckResult): string { + const usagePercent = Math.round((result.currentUsage / result.maxContext) * 100); + return `Context window is nearly full. Current usage: ${result.currentUsage.toLocaleString()}/${result.maxContext.toLocaleString()} tokens (${usagePercent}%). Available space: ${result.availableTokens.toLocaleString()} tokens (${result.reservedTokens} reserved for response).`; + } + + /** + * Sets the number of tokens to reserve for response generation + * + * @param {number} tokens - Number of tokens to reserve + */ + setReserveTokens(tokens: number): void { + this.reserveTokens = tokens; + } +} + +export const contextService = new ContextService(); diff --git a/tools/server/webui/src/lib/services/index.ts b/tools/server/webui/src/lib/services/index.ts new file mode 100644 index 0000000000..e5a1173ff7 --- /dev/null +++ b/tools/server/webui/src/lib/services/index.ts @@ -0,0 +1,3 @@ +export { chatService } from './chat'; +export { contextService } from './context'; +export { slotsService } from './slots'; diff --git a/tools/server/webui/src/lib/services/slots.ts b/tools/server/webui/src/lib/services/slots.ts new file mode 100644 index 0000000000..b93a5a90e7 --- /dev/null +++ b/tools/server/webui/src/lib/services/slots.ts @@ -0,0 +1,254 @@ +import { config } from '$lib/stores/settings.svelte'; + +/** + * SlotsService - Real-time processing state monitoring and token rate calculation + * + * This service provides real-time information about generation progress, token rates, + * and context usage based on timing data from ChatService streaming responses. + * It manages streaming session tracking and provides accurate processing state updates. + * + * **Architecture & Relationships:** + * - **SlotsService** (this class): Processing state monitoring + * - Receives timing data from ChatService streaming responses + * - Calculates token generation rates and context usage + * - Manages streaming session lifecycle + * - Provides real-time updates to UI components + * + * - **ChatService**: Provides timing data from `/chat/completions` streaming + * - **UI Components**: Subscribe to processing state for progress indicators + * + * **Key Features:** + * - **Real-time Monitoring**: Live processing state during generation + * - **Token Rate Calculation**: Accurate tokens/second from timing data + * - **Context Tracking**: Current context usage and remaining capacity + * - **Streaming Lifecycle**: Start/stop tracking for streaming sessions + * - **Timing Data Processing**: Converts streaming timing data to structured state + * - **Error Handling**: Graceful handling when timing data is unavailable + * + * **Processing States:** + * - `idle`: No active processing + * - `generating`: Actively generating tokens + * + * **Token Rate Calculation:** + * Uses timing data from `/chat/completions` streaming response for accurate + * real-time token generation rate measurement. + */ +export class SlotsService { + private callbacks: Set<(state: ApiProcessingState | null) => void> = new Set(); + private isStreamingActive: boolean = false; + private lastKnownState: ApiProcessingState | null = null; + + /** + * Start streaming session tracking + */ + startStreaming(): void { + this.isStreamingActive = true; + } + + /** + * Stop streaming session tracking + */ + stopStreaming(): void { + this.isStreamingActive = false; + } + + /** + * Clear the current processing state + * Used when switching to a conversation without timing data + */ + clearState(): void { + this.lastKnownState = null; + + for (const callback of this.callbacks) { + try { + callback(null); + } catch (error) { + console.error('Error in clearState callback:', error); + } + } + } + + /** + * Check if currently in a streaming session + */ + isStreaming(): boolean { + return this.isStreamingActive; + } + + /** + * @deprecated Polling is no longer used - timing data comes from ChatService streaming response + * This method logs a warning if called to help identify outdated usage + */ + fetchAndNotify(): void { + console.warn( + 'SlotsService.fetchAndNotify() is deprecated - use timing data from ChatService instead' + ); + } + + subscribe(callback: (state: ApiProcessingState | null) => void): () => void { + this.callbacks.add(callback); + + if (this.lastKnownState) { + callback(this.lastKnownState); + } + + return () => { + this.callbacks.delete(callback); + }; + } + + /** + * Updates processing state with timing data from ChatService streaming response + */ + async updateFromTimingData(timingData: { + prompt_n: number; + predicted_n: number; + predicted_per_second: number; + cache_n: number; + prompt_progress?: ChatMessagePromptProgress; + }): Promise { + const processingState = await this.parseCompletionTimingData(timingData); + + // Only update if we successfully parsed the state + if (processingState === null) { + console.warn('Failed to parse timing data - skipping update'); + return; + } + + this.lastKnownState = processingState; + + for (const callback of this.callbacks) { + try { + callback(processingState); + } catch (error) { + console.error('Error in timing callback:', error); + } + } + } + + /** + * Gets context total from last known slots data or fetches from server + */ + private async getContextTotal(): Promise { + if (this.lastKnownState && this.lastKnownState.contextTotal > 0) { + return this.lastKnownState.contextTotal; + } + + try { + const currentConfig = config(); + const apiKey = currentConfig.apiKey?.toString().trim(); + + const response = await fetch('/slots', { + headers: { + ...(apiKey ? { Authorization: `Bearer ${apiKey}` } : {}) + } + }); + if (response.ok) { + const slotsData = await response.json(); + if (Array.isArray(slotsData) && slotsData.length > 0) { + const slot = slotsData[0]; + if (slot.n_ctx && slot.n_ctx > 0) { + return slot.n_ctx; + } + } + } + } catch (error) { + console.warn('Failed to fetch context total from /slots:', error); + } + + return 4096; + } + + private async parseCompletionTimingData( + timingData: Record + ): Promise { + const promptTokens = (timingData.prompt_n as number) || 0; + const predictedTokens = (timingData.predicted_n as number) || 0; + const tokensPerSecond = (timingData.predicted_per_second as number) || 0; + const cacheTokens = (timingData.cache_n as number) || 0; + const promptProgress = timingData.prompt_progress as + | { + total: number; + cache: number; + processed: number; + time_ms: number; + } + | undefined; + + const contextTotal = await this.getContextTotal(); + + if (contextTotal === null) { + console.warn('No context total available - cannot calculate processing state'); + return null; + } + + const currentConfig = config(); + const outputTokensMax = currentConfig.max_tokens || -1; + + const contextUsed = promptTokens + cacheTokens + predictedTokens; + const outputTokensUsed = predictedTokens; + + const progressPercent = promptProgress + ? Math.round((promptProgress.processed / promptProgress.total) * 100) + : undefined; + + return { + status: predictedTokens > 0 ? 'generating' : promptProgress ? 'preparing' : 'idle', + tokensDecoded: predictedTokens, + tokensRemaining: outputTokensMax - predictedTokens, + contextUsed, + contextTotal, + outputTokensUsed, + outputTokensMax, + hasNextToken: predictedTokens > 0, + tokensPerSecond, + temperature: currentConfig.temperature ?? 0.8, + topP: currentConfig.top_p ?? 0.95, + speculative: false, + progressPercent, + promptTokens, + cacheTokens + }; + } + + /** + * Get current processing state + * Returns the last known state from timing data, or null if no data available + */ + async getCurrentState(): Promise { + if (this.lastKnownState) { + return this.lastKnownState; + } + try { + // Import dynamically to avoid circular dependency + const { chatStore } = await import('$lib/stores/chat.svelte'); + const messages = chatStore.activeMessages; + + for (let i = messages.length - 1; i >= 0; i--) { + const message = messages[i]; + if (message.role === 'assistant' && message.timings) { + const restoredState = await this.parseCompletionTimingData({ + prompt_n: message.timings.prompt_n || 0, + predicted_n: message.timings.predicted_n || 0, + predicted_per_second: + message.timings.predicted_n && message.timings.predicted_ms + ? (message.timings.predicted_n / message.timings.predicted_ms) * 1000 + : 0, + cache_n: message.timings.cache_n || 0 + }); + + if (restoredState) { + this.lastKnownState = restoredState; + return restoredState; + } + } + } + } catch (error) { + console.warn('Failed to restore timing data from messages:', error); + } + + return null; + } +} + +export const slotsService = new SlotsService(); diff --git a/tools/server/webui/src/lib/stores/chat.svelte.ts b/tools/server/webui/src/lib/stores/chat.svelte.ts new file mode 100644 index 0000000000..ac5e986428 --- /dev/null +++ b/tools/server/webui/src/lib/stores/chat.svelte.ts @@ -0,0 +1,1394 @@ +import { DatabaseStore } from '$lib/stores/database'; +import { chatService, slotsService } from '$lib/services'; +import { serverStore } from '$lib/stores/server.svelte'; +import { config } from '$lib/stores/settings.svelte'; +import { filterByLeafNodeId, findLeafNode, findDescendantMessages } from '$lib/utils/branching'; +import { browser } from '$app/environment'; +import { goto } from '$app/navigation'; +import { extractPartialThinking } from '$lib/utils/thinking'; + +/** + * ChatStore - Central state management for chat conversations and AI interactions + * + * This store manages the complete chat experience including: + * - Conversation lifecycle (create, load, delete, update) + * - Message management with branching support for conversation trees + * - Real-time AI response streaming with reasoning content support + * - File attachment handling and processing + * - Context error management and recovery + * - Database persistence through DatabaseStore integration + * + * **Architecture & Relationships:** + * - **ChatService**: Handles low-level API communication with AI models + * - ChatStore orchestrates ChatService for streaming responses + * - ChatService provides abort capabilities and error handling + * - ChatStore manages the UI state while ChatService handles network layer + * + * - **DatabaseStore**: Provides persistent storage for conversations and messages + * - ChatStore uses DatabaseStore for all CRUD operations + * - Maintains referential integrity for conversation trees + * - Handles message branching and parent-child relationships + * + * - **SlotsService**: Monitors server resource usage during AI generation + * - ChatStore coordinates slots polling during streaming + * - Provides real-time feedback on server capacity + * + * **Key Features:** + * - Reactive state management using Svelte 5 runes ($state) + * - Conversation branching for exploring different response paths + * - Streaming AI responses with real-time content updates + * - File attachment support (images, PDFs, text files, audio) + * - Context window management with error recovery + * - Partial response saving when generation is interrupted + * - Message editing with automatic response regeneration + */ +class ChatStore { + activeConversation = $state(null); + activeMessages = $state([]); + conversations = $state([]); + currentResponse = $state(''); + isInitialized = $state(false); + isLoading = $state(false); + maxContextError = $state<{ message: string; estimatedTokens: number; maxContext: number } | null>( + null + ); + titleUpdateConfirmationCallback?: (currentTitle: string, newTitle: string) => Promise; + + constructor() { + if (browser) { + this.initialize(); + } + } + + /** + * Initializes the chat store by loading conversations from the database + * Sets up the initial state and loads existing conversations + */ + async initialize(): Promise { + try { + await this.loadConversations(); + + this.maxContextError = null; + + this.isInitialized = true; + } catch (error) { + console.error('Failed to initialize chat store:', error); + } + } + + /** + * Loads all conversations from the database + * Refreshes the conversations list from persistent storage + */ + async loadConversations(): Promise { + this.conversations = await DatabaseStore.getAllConversations(); + } + + /** + * Creates a new conversation and navigates to it + * @param name - Optional name for the conversation, defaults to timestamped name + * @returns The ID of the created conversation + */ + async createConversation(name?: string): Promise { + const conversationName = name || `Chat ${new Date().toLocaleString()}`; + const conversation = await DatabaseStore.createConversation(conversationName); + + this.conversations.unshift(conversation); + + this.activeConversation = conversation; + this.activeMessages = []; + + this.maxContextError = null; + + await goto(`/chat/${conversation.id}`); + + return conversation.id; + } + + /** + * Loads a specific conversation and its messages + * @param convId - The conversation ID to load + * @returns True if conversation was loaded successfully, false otherwise + */ + async loadConversation(convId: string): Promise { + try { + const conversation = await DatabaseStore.getConversation(convId); + + if (!conversation) { + return false; + } + + this.activeConversation = conversation; + + if (conversation.currNode) { + const allMessages = await DatabaseStore.getConversationMessages(convId); + this.activeMessages = filterByLeafNodeId( + allMessages, + conversation.currNode, + false + ) as DatabaseMessage[]; + } else { + // Load all messages for conversations without currNode (backward compatibility) + this.activeMessages = await DatabaseStore.getConversationMessages(convId); + } + + this.maxContextError = null; + + return true; + } catch (error) { + console.error('Failed to load conversation:', error); + + return false; + } + } + + /** + * Adds a new message to the active conversation + * @param role - The role of the message sender (user/assistant) + * @param content - The message content + * @param type - The message type, defaults to 'text' + * @param parent - Parent message ID, defaults to '-1' for auto-detection + * @param extras - Optional extra data (files, attachments, etc.) + * @returns The created message or null if failed + */ + async addMessage( + role: ChatRole, + content: string, + type: ChatMessageType = 'text', + parent: string = '-1', + extras?: DatabaseMessageExtra[] + ): Promise { + if (!this.activeConversation) { + console.error('No active conversation when trying to add message'); + return null; + } + + try { + let parentId: string | null = null; + + if (parent === '-1') { + if (this.activeMessages.length > 0) { + parentId = this.activeMessages[this.activeMessages.length - 1].id; + } else { + const allMessages = await DatabaseStore.getConversationMessages( + this.activeConversation.id + ); + const rootMessage = allMessages.find((m) => m.parent === null && m.type === 'root'); + + if (!rootMessage) { + const rootId = await DatabaseStore.createRootMessage(this.activeConversation.id); + parentId = rootId; + } else { + parentId = rootMessage.id; + } + } + } else { + parentId = parent; + } + + const message = await DatabaseStore.createMessageBranch( + { + convId: this.activeConversation.id, + role, + content, + type, + timestamp: Date.now(), + thinking: '', + children: [], + extra: extras + }, + parentId + ); + + this.activeMessages.push(message); + + await DatabaseStore.updateCurrentNode(this.activeConversation.id, message.id); + this.activeConversation.currNode = message.id; + + this.updateConversationTimestamp(); + + return message; + } catch (error) { + console.error('Failed to add message:', error); + return null; + } + } + + /** + * Gets API options from current configuration settings + * Converts settings store values to API-compatible format + * @returns API options object for chat completion requests + */ + private getApiOptions(): Record { + const currentConfig = config(); + const apiOptions: Record = { + stream: true, + timings_per_token: true + }; + + if (currentConfig.temperature !== undefined && currentConfig.temperature !== null) { + apiOptions.temperature = Number(currentConfig.temperature); + } + if (currentConfig.max_tokens !== undefined && currentConfig.max_tokens !== null) { + apiOptions.max_tokens = Number(currentConfig.max_tokens); + } + if (currentConfig.dynatemp_range !== undefined && currentConfig.dynatemp_range !== null) { + apiOptions.dynatemp_range = Number(currentConfig.dynatemp_range); + } + if (currentConfig.dynatemp_exponent !== undefined && currentConfig.dynatemp_exponent !== null) { + apiOptions.dynatemp_exponent = Number(currentConfig.dynatemp_exponent); + } + if (currentConfig.top_k !== undefined && currentConfig.top_k !== null) { + apiOptions.top_k = Number(currentConfig.top_k); + } + if (currentConfig.top_p !== undefined && currentConfig.top_p !== null) { + apiOptions.top_p = Number(currentConfig.top_p); + } + if (currentConfig.min_p !== undefined && currentConfig.min_p !== null) { + apiOptions.min_p = Number(currentConfig.min_p); + } + if (currentConfig.xtc_probability !== undefined && currentConfig.xtc_probability !== null) { + apiOptions.xtc_probability = Number(currentConfig.xtc_probability); + } + if (currentConfig.xtc_threshold !== undefined && currentConfig.xtc_threshold !== null) { + apiOptions.xtc_threshold = Number(currentConfig.xtc_threshold); + } + if (currentConfig.typ_p !== undefined && currentConfig.typ_p !== null) { + apiOptions.typ_p = Number(currentConfig.typ_p); + } + if (currentConfig.repeat_last_n !== undefined && currentConfig.repeat_last_n !== null) { + apiOptions.repeat_last_n = Number(currentConfig.repeat_last_n); + } + if (currentConfig.repeat_penalty !== undefined && currentConfig.repeat_penalty !== null) { + apiOptions.repeat_penalty = Number(currentConfig.repeat_penalty); + } + if (currentConfig.presence_penalty !== undefined && currentConfig.presence_penalty !== null) { + apiOptions.presence_penalty = Number(currentConfig.presence_penalty); + } + if (currentConfig.frequency_penalty !== undefined && currentConfig.frequency_penalty !== null) { + apiOptions.frequency_penalty = Number(currentConfig.frequency_penalty); + } + if (currentConfig.dry_multiplier !== undefined && currentConfig.dry_multiplier !== null) { + apiOptions.dry_multiplier = Number(currentConfig.dry_multiplier); + } + if (currentConfig.dry_base !== undefined && currentConfig.dry_base !== null) { + apiOptions.dry_base = Number(currentConfig.dry_base); + } + if ( + currentConfig.dry_allowed_length !== undefined && + currentConfig.dry_allowed_length !== null + ) { + apiOptions.dry_allowed_length = Number(currentConfig.dry_allowed_length); + } + if ( + currentConfig.dry_penalty_last_n !== undefined && + currentConfig.dry_penalty_last_n !== null + ) { + apiOptions.dry_penalty_last_n = Number(currentConfig.dry_penalty_last_n); + } + if (currentConfig.samplers) { + apiOptions.samplers = currentConfig.samplers; + } + if (currentConfig.custom) { + apiOptions.custom = currentConfig.custom; + } + + return apiOptions; + } + + /** + * Handles streaming chat completion with the AI model + * @param allMessages - All messages in the conversation + * @param assistantMessage - The assistant message to stream content into + * @param onComplete - Optional callback when streaming completes + * @param onError - Optional callback when an error occurs + */ + private async streamChatCompletion( + allMessages: DatabaseMessage[], + assistantMessage: DatabaseMessage, + onComplete?: (content: string) => Promise, + onError?: (error: Error) => void + ): Promise { + let streamedContent = ''; + + let streamedReasoningContent = ''; + + slotsService.startStreaming(); + + await chatService.sendMessage(allMessages, { + ...this.getApiOptions(), + + onChunk: (chunk: string) => { + streamedContent += chunk; + this.currentResponse = streamedContent; + + const partialThinking = extractPartialThinking(streamedContent); + const messageIndex = this.findMessageIndex(assistantMessage.id); + this.updateMessageAtIndex(messageIndex, { + content: partialThinking.remainingContent || streamedContent + }); + }, + + onReasoningChunk: (reasoningChunk: string) => { + streamedReasoningContent += reasoningChunk; + const messageIndex = this.findMessageIndex(assistantMessage.id); + this.updateMessageAtIndex(messageIndex, { thinking: streamedReasoningContent }); + }, + + onComplete: async ( + finalContent?: string, + reasoningContent?: string, + timings?: ChatMessageTimings + ) => { + slotsService.stopStreaming(); + + await DatabaseStore.updateMessage(assistantMessage.id, { + content: finalContent || streamedContent, + thinking: reasoningContent || streamedReasoningContent, + timings: timings + }); + + const messageIndex = this.findMessageIndex(assistantMessage.id); + + this.updateMessageAtIndex(messageIndex, { + timings: timings + }); + + await DatabaseStore.updateCurrentNode(this.activeConversation!.id, assistantMessage.id); + this.activeConversation!.currNode = assistantMessage.id; + + await this.refreshActiveMessages(); + + if (onComplete) { + await onComplete(streamedContent); + } + + this.isLoading = false; + this.currentResponse = ''; + }, + + onError: (error: Error) => { + slotsService.stopStreaming(); + + if (error.name === 'AbortError' || error instanceof DOMException) { + this.isLoading = false; + this.currentResponse = ''; + return; + } + + if (error.name === 'ContextError') { + console.warn('Context error detected:', error.message); + this.isLoading = false; + this.currentResponse = ''; + + const messageIndex = this.activeMessages.findIndex( + (m: DatabaseMessage) => m.id === assistantMessage.id + ); + + if (messageIndex !== -1) { + this.activeMessages.splice(messageIndex, 1); + DatabaseStore.deleteMessage(assistantMessage.id).catch(console.error); + } + + // Use structured context info from new exceed_context_size_error format if available + const contextInfo = ( + error as Error & { + contextInfo?: { promptTokens: number; maxContext: number; estimatedTokens: number }; + } + ).contextInfo; + let estimatedTokens = 0; + let maxContext = serverStore.serverProps?.default_generation_settings.n_ctx || 8192; + + if (contextInfo) { + // Use precise token counts from server response + estimatedTokens = contextInfo.promptTokens; + maxContext = contextInfo.maxContext; + } else { + // Fallback to estimation for older error format + try { + // Rough estimation: ~4 characters per token + const messageContent = JSON.stringify(messages); + estimatedTokens = Math.ceil(messageContent.length / 4); + } catch { + estimatedTokens = 0; + } + } + + this.maxContextError = { + message: error.message, + estimatedTokens, + maxContext + }; + + if (onError) { + onError(error); + } + return; + } + + console.error('Streaming error:', error); + this.isLoading = false; + this.currentResponse = ''; + + const messageIndex = this.activeMessages.findIndex( + (m: DatabaseMessage) => m.id === assistantMessage.id + ); + + if (messageIndex !== -1) { + this.activeMessages[messageIndex].content = `Error: ${error.message}`; + } + + if (onError) { + onError(error); + } + } + }); + } + + /** + * Checks if an error is an abort error (user cancelled operation) + * @param error - The error to check + * @returns True if the error is an abort error + */ + private isAbortError(error: unknown): boolean { + return error instanceof Error && (error.name === 'AbortError' || error instanceof DOMException); + } + + /** + * Finds the index of a message in the active messages array + * @param messageId - The message ID to find + * @returns The index of the message, or -1 if not found + */ + private findMessageIndex(messageId: string): number { + return this.activeMessages.findIndex((m) => m.id === messageId); + } + + /** + * Updates a message at a specific index with partial data + * @param index - The index of the message to update + * @param updates - Partial message data to update + */ + private updateMessageAtIndex(index: number, updates: Partial): void { + if (index !== -1) { + Object.assign(this.activeMessages[index], updates); + } + } + + /** + * Creates a new assistant message in the database + * @param parentId - Optional parent message ID, defaults to '-1' + * @returns The created assistant message or null if failed + */ + private async createAssistantMessage(parentId?: string): Promise { + if (!this.activeConversation) return null; + + return await DatabaseStore.createMessageBranch( + { + convId: this.activeConversation.id, + type: 'text', + role: 'assistant', + content: '', + timestamp: Date.now(), + thinking: '', + children: [] + }, + parentId || null + ); + } + + /** + * Updates conversation lastModified timestamp and moves it to top of list + * Ensures recently active conversations appear first in the sidebar + */ + private updateConversationTimestamp(): void { + if (!this.activeConversation) return; + + const chatIndex = this.conversations.findIndex((c) => c.id === this.activeConversation!.id); + + if (chatIndex !== -1) { + this.conversations[chatIndex].lastModified = Date.now(); + const updatedConv = this.conversations.splice(chatIndex, 1)[0]; + this.conversations.unshift(updatedConv); + } + } + + /** + * Sends a new message and generates AI response + * @param content - The message content to send + * @param extras - Optional extra data (files, attachments, etc.) + */ + async sendMessage(content: string, extras?: DatabaseMessageExtra[]): Promise { + if ((!content.trim() && (!extras || extras.length === 0)) || this.isLoading) return; + + let isNewConversation = false; + + if (!this.activeConversation) { + await this.createConversation(); + isNewConversation = true; + } + + if (!this.activeConversation) { + console.error('No active conversation available for sending message'); + return; + } + + this.isLoading = true; + this.currentResponse = ''; + + let userMessage: DatabaseMessage | null = null; + + try { + userMessage = await this.addMessage('user', content, 'text', '-1', extras); + + if (!userMessage) { + throw new Error('Failed to add user message'); + } + + // If this is a new conversation, update the title with the first user prompt + if (isNewConversation && content) { + const title = content.trim(); + await this.updateConversationName(this.activeConversation.id, title); + } + + const allMessages = await DatabaseStore.getConversationMessages(this.activeConversation.id); + const assistantMessage = await this.createAssistantMessage(userMessage.id); + + if (!assistantMessage) { + throw new Error('Failed to create assistant message'); + } + + this.activeMessages.push(assistantMessage); + // Don't update currNode until after streaming completes to maintain proper conversation path + + await this.streamChatCompletion(allMessages, assistantMessage, undefined, (error: Error) => { + if (error.name === 'ContextError' && userMessage) { + const userMessageIndex = this.findMessageIndex(userMessage.id); + if (userMessageIndex !== -1) { + this.activeMessages.splice(userMessageIndex, 1); + DatabaseStore.deleteMessage(userMessage.id).catch(console.error); + } + } + }); + } catch (error) { + if (this.isAbortError(error)) { + this.isLoading = false; + return; + } + + if (error instanceof Error && error.name === 'ContextError' && userMessage) { + const userMessageIndex = this.findMessageIndex(userMessage.id); + if (userMessageIndex !== -1) { + this.activeMessages.splice(userMessageIndex, 1); + DatabaseStore.deleteMessage(userMessage.id).catch(console.error); + } + } + + console.error('Failed to send message:', error); + this.isLoading = false; + } + } + + /** + * Stops the current message generation + * Aborts ongoing requests and saves partial response if available + */ + stopGeneration(): void { + slotsService.stopStreaming(); + chatService.abort(); + this.savePartialResponseIfNeeded(); + this.isLoading = false; + this.currentResponse = ''; + } + + /** + * Gracefully stops generation and saves partial response + */ + async gracefulStop(): Promise { + if (!this.isLoading) return; + + slotsService.stopStreaming(); + chatService.abort(); + await this.savePartialResponseIfNeeded(); + this.isLoading = false; + this.currentResponse = ''; + } + + /** + * Clears the max context error state + * Removes any displayed context limit warnings + */ + clearMaxContextError(): void { + this.maxContextError = null; + } + + /** + * Sets the max context error state + * @param error - The context error details or null to clear + */ + setMaxContextError( + error: { message: string; estimatedTokens: number; maxContext: number } | null + ): void { + this.maxContextError = error; + } + + /** + * Saves partial response if generation was interrupted + * Preserves user's partial content and timing data when generation is stopped early + */ + private async savePartialResponseIfNeeded(): Promise { + if (!this.currentResponse.trim() || !this.activeMessages.length) { + return; + } + + const lastMessage = this.activeMessages[this.activeMessages.length - 1]; + + if (lastMessage && lastMessage.role === 'assistant') { + try { + const partialThinking = extractPartialThinking(this.currentResponse); + + const updateData: { + content: string; + thinking?: string; + timings?: ChatMessageTimings; + } = { + content: partialThinking.remainingContent || this.currentResponse + }; + + if (partialThinking.thinking) { + updateData.thinking = partialThinking.thinking; + } + + const lastKnownState = await slotsService.getCurrentState(); + + if (lastKnownState) { + updateData.timings = { + prompt_n: lastKnownState.promptTokens || 0, + predicted_n: lastKnownState.tokensDecoded || 0, + cache_n: lastKnownState.cacheTokens || 0, + // We don't have ms data from the state, but we can estimate + predicted_ms: + lastKnownState.tokensPerSecond && lastKnownState.tokensDecoded + ? (lastKnownState.tokensDecoded / lastKnownState.tokensPerSecond) * 1000 + : undefined + }; + } + + await DatabaseStore.updateMessage(lastMessage.id, updateData); + + lastMessage.content = partialThinking.remainingContent || this.currentResponse; + if (updateData.timings) { + lastMessage.timings = updateData.timings; + } + } catch (error) { + lastMessage.content = this.currentResponse; + console.error('Failed to save partial response:', error); + } + } else { + console.error('Last message is not an assistant message'); + } + } + + /** + * Updates a user message and regenerates the assistant response + * @param messageId - The ID of the message to update + * @param newContent - The new content for the message + */ + async updateMessage(messageId: string, newContent: string): Promise { + if (!this.activeConversation) return; + + if (this.isLoading) { + this.stopGeneration(); + } + + try { + const messageIndex = this.findMessageIndex(messageId); + if (messageIndex === -1) { + console.error('Message not found for update'); + return; + } + + const messageToUpdate = this.activeMessages[messageIndex]; + const originalContent = messageToUpdate.content; + + if (messageToUpdate.role !== 'user') { + console.error('Only user messages can be edited'); + return; + } + + const allMessages = await DatabaseStore.getConversationMessages(this.activeConversation.id); + const rootMessage = allMessages.find((m) => m.type === 'root' && m.parent === null); + const isFirstUserMessage = + rootMessage && messageToUpdate.parent === rootMessage.id && messageToUpdate.role === 'user'; + + this.updateMessageAtIndex(messageIndex, { content: newContent }); + await DatabaseStore.updateMessage(messageId, { content: newContent }); + + // If this is the first user message, update the conversation title with confirmation if needed + if (isFirstUserMessage && newContent.trim()) { + await this.updateConversationTitleWithConfirmation( + this.activeConversation.id, + newContent.trim(), + this.titleUpdateConfirmationCallback + ); + } + + const messagesToRemove = this.activeMessages.slice(messageIndex + 1); + for (const message of messagesToRemove) { + await DatabaseStore.deleteMessage(message.id); + } + + this.activeMessages = this.activeMessages.slice(0, messageIndex + 1); + this.updateConversationTimestamp(); + + this.isLoading = true; + this.currentResponse = ''; + + try { + const assistantMessage = await this.createAssistantMessage(); + if (!assistantMessage) { + throw new Error('Failed to create assistant message'); + } + + this.activeMessages.push(assistantMessage); + await DatabaseStore.updateCurrentNode(this.activeConversation.id, assistantMessage.id); + this.activeConversation.currNode = assistantMessage.id; + + await this.streamChatCompletion( + this.activeMessages.slice(0, -1), + assistantMessage, + undefined, + () => { + const editedMessageIndex = this.findMessageIndex(messageId); + this.updateMessageAtIndex(editedMessageIndex, { content: originalContent }); + } + ); + } catch (regenerateError) { + console.error('Failed to regenerate response:', regenerateError); + this.isLoading = false; + + const messageIndex = this.findMessageIndex(messageId); + this.updateMessageAtIndex(messageIndex, { content: originalContent }); + } + } catch (error) { + if (this.isAbortError(error)) { + return; + } + + console.error('Failed to update message:', error); + } + } + + /** + * Regenerates an assistant message with a new response + * @param messageId - The ID of the assistant message to regenerate + */ + async regenerateMessage(messageId: string): Promise { + if (!this.activeConversation || this.isLoading) return; + + try { + const messageIndex = this.findMessageIndex(messageId); + if (messageIndex === -1) { + console.error('Message not found for regeneration'); + return; + } + + const messageToRegenerate = this.activeMessages[messageIndex]; + if (messageToRegenerate.role !== 'assistant') { + console.error('Only assistant messages can be regenerated'); + return; + } + + const messagesToRemove = this.activeMessages.slice(messageIndex); + for (const message of messagesToRemove) { + await DatabaseStore.deleteMessage(message.id); + } + + this.activeMessages = this.activeMessages.slice(0, messageIndex); + this.updateConversationTimestamp(); + + this.isLoading = true; + this.currentResponse = ''; + + try { + const allMessages = await DatabaseStore.getConversationMessages(this.activeConversation.id); + const assistantMessage = await this.createAssistantMessage(); + + if (!assistantMessage) { + throw new Error('Failed to create assistant message'); + } + + this.activeMessages.push(assistantMessage); + await DatabaseStore.updateCurrentNode(this.activeConversation.id, assistantMessage.id); + this.activeConversation.currNode = assistantMessage.id; + + await this.streamChatCompletion(allMessages, assistantMessage); + } catch (regenerateError) { + console.error('Failed to regenerate response:', regenerateError); + this.isLoading = false; + } + } catch (error) { + if (this.isAbortError(error)) return; + console.error('Failed to regenerate message:', error); + } + } + + /** + * Updates the name of a conversation + * @param convId - The conversation ID to update + * @param name - The new name for the conversation + */ + async updateConversationName(convId: string, name: string): Promise { + try { + await DatabaseStore.updateConversation(convId, { name }); + + const convIndex = this.conversations.findIndex((c) => c.id === convId); + + if (convIndex !== -1) { + this.conversations[convIndex].name = name; + } + + if (this.activeConversation?.id === convId) { + this.activeConversation.name = name; + } + } catch (error) { + console.error('Failed to update conversation name:', error); + } + } + + /** + * Sets the callback function for title update confirmations + * @param callback - Function to call when confirmation is needed + */ + setTitleUpdateConfirmationCallback( + callback: (currentTitle: string, newTitle: string) => Promise + ): void { + this.titleUpdateConfirmationCallback = callback; + } + + /** + * Updates conversation title with optional confirmation dialog based on settings + * @param convId - The conversation ID to update + * @param newTitle - The new title content + * @param onConfirmationNeeded - Callback when user confirmation is needed + * @returns Promise - True if title was updated, false if cancelled + */ + async updateConversationTitleWithConfirmation( + convId: string, + newTitle: string, + onConfirmationNeeded?: (currentTitle: string, newTitle: string) => Promise + ): Promise { + try { + const currentConfig = config(); + + // Only ask for confirmation if the setting is enabled and callback is provided + if (currentConfig.askForTitleConfirmation && onConfirmationNeeded) { + const conversation = await DatabaseStore.getConversation(convId); + if (!conversation) return false; + + const shouldUpdate = await onConfirmationNeeded(conversation.name, newTitle); + if (!shouldUpdate) return false; + } + + await this.updateConversationName(convId, newTitle); + return true; + } catch (error) { + console.error('Failed to update conversation title with confirmation:', error); + return false; + } + } + + /** + * Deletes a conversation and all its messages + * @param convId - The conversation ID to delete + */ + async deleteConversation(convId: string): Promise { + try { + await DatabaseStore.deleteConversation(convId); + + this.conversations = this.conversations.filter((c) => c.id !== convId); + + if (this.activeConversation?.id === convId) { + this.activeConversation = null; + this.activeMessages = []; + await goto('/?new_chat=true'); + } + } catch (error) { + console.error('Failed to delete conversation:', error); + } + } + + /** + * Gets information about what messages will be deleted when deleting a specific message + * @param messageId - The ID of the message to be deleted + * @returns Object with deletion info including count and types of messages + */ + async getDeletionInfo(messageId: string): Promise<{ + totalCount: number; + userMessages: number; + assistantMessages: number; + messageTypes: string[]; + }> { + if (!this.activeConversation) { + return { totalCount: 0, userMessages: 0, assistantMessages: 0, messageTypes: [] }; + } + + const allMessages = await DatabaseStore.getConversationMessages(this.activeConversation.id); + const descendants = findDescendantMessages(allMessages, messageId); + const allToDelete = [messageId, ...descendants]; + + const messagesToDelete = allMessages.filter((m) => allToDelete.includes(m.id)); + + let userMessages = 0; + let assistantMessages = 0; + const messageTypes: string[] = []; + + for (const msg of messagesToDelete) { + if (msg.role === 'user') { + userMessages++; + if (!messageTypes.includes('user message')) messageTypes.push('user message'); + } else if (msg.role === 'assistant') { + assistantMessages++; + if (!messageTypes.includes('assistant response')) messageTypes.push('assistant response'); + } + } + + return { + totalCount: allToDelete.length, + userMessages, + assistantMessages, + messageTypes + }; + } + + /** + * Deletes a message and all its descendants, updating conversation path if needed + * @param messageId - The ID of the message to delete + */ + async deleteMessage(messageId: string): Promise { + try { + if (!this.activeConversation) return; + + // Get all messages to find siblings before deletion + const allMessages = await DatabaseStore.getConversationMessages(this.activeConversation.id); + const messageToDelete = allMessages.find((m) => m.id === messageId); + + if (!messageToDelete) { + console.error('Message to delete not found'); + return; + } + + // Check if the deleted message is in the current conversation path + const currentPath = filterByLeafNodeId( + allMessages, + this.activeConversation.currNode || '', + false + ); + const isInCurrentPath = currentPath.some((m) => m.id === messageId); + + // If the deleted message is in the current path, we need to update currNode + if (isInCurrentPath && messageToDelete.parent) { + // Find all siblings (messages with same parent) + const siblings = allMessages.filter( + (m) => m.parent === messageToDelete.parent && m.id !== messageId + ); + + if (siblings.length > 0) { + // Find the latest sibling (highest timestamp) + const latestSibling = siblings.reduce((latest, sibling) => + sibling.timestamp > latest.timestamp ? sibling : latest + ); + + // Find the leaf node for this sibling branch to get the complete conversation path + const leafNodeId = findLeafNode(allMessages, latestSibling.id); + + // Update conversation to use the leaf node of the latest remaining sibling + await DatabaseStore.updateCurrentNode(this.activeConversation.id, leafNodeId); + this.activeConversation.currNode = leafNodeId; + } else { + // No siblings left, navigate to parent if it exists + if (messageToDelete.parent) { + const parentLeafId = findLeafNode(allMessages, messageToDelete.parent); + await DatabaseStore.updateCurrentNode(this.activeConversation.id, parentLeafId); + this.activeConversation.currNode = parentLeafId; + } + } + } + + // Use cascading deletion to remove the message and all its descendants + await DatabaseStore.deleteMessageCascading(this.activeConversation.id, messageId); + + // Refresh active messages to show the updated branch + await this.refreshActiveMessages(); + + // Update conversation timestamp + this.updateConversationTimestamp(); + } catch (error) { + console.error('Failed to delete message:', error); + } + } + + /** + * Clears the active conversation and resets state + * Used when navigating away from chat or starting fresh + */ + clearActiveConversation(): void { + this.activeConversation = null; + this.activeMessages = []; + this.currentResponse = ''; + this.isLoading = false; + this.maxContextError = null; + } + + /** Refreshes active messages based on currNode after branch navigation */ + async refreshActiveMessages(): Promise { + if (!this.activeConversation) return; + + const allMessages = await DatabaseStore.getConversationMessages(this.activeConversation.id); + if (allMessages.length === 0) { + this.activeMessages = []; + return; + } + + const leafNodeId = + this.activeConversation.currNode || + allMessages.reduce((latest, msg) => (msg.timestamp > latest.timestamp ? msg : latest)).id; + + const currentPath = filterByLeafNodeId(allMessages, leafNodeId, false) as DatabaseMessage[]; + + this.activeMessages.length = 0; + this.activeMessages.push(...currentPath); + } + + /** + * Navigates to a specific sibling branch by updating currNode and refreshing messages + * @param siblingId - The sibling message ID to navigate to + */ + async navigateToSibling(siblingId: string): Promise { + if (!this.activeConversation) return; + + // Get the current first user message before navigation + const allMessages = await DatabaseStore.getConversationMessages(this.activeConversation.id); + const rootMessage = allMessages.find((m) => m.type === 'root' && m.parent === null); + const currentFirstUserMessage = this.activeMessages.find( + (m) => m.role === 'user' && m.parent === rootMessage?.id + ); + + await DatabaseStore.updateCurrentNode(this.activeConversation.id, siblingId); + this.activeConversation.currNode = siblingId; + await this.refreshActiveMessages(); + + // Only show title dialog if we're navigating between different first user message siblings + if (rootMessage && this.activeMessages.length > 0) { + // Find the first user message in the new active path + const newFirstUserMessage = this.activeMessages.find( + (m) => m.role === 'user' && m.parent === rootMessage.id + ); + + // Only show dialog if: + // 1. We have a new first user message + // 2. It's different from the previous one (different ID or content) + // 3. The new message has content + if ( + newFirstUserMessage && + newFirstUserMessage.content.trim() && + (!currentFirstUserMessage || + newFirstUserMessage.id !== currentFirstUserMessage.id || + newFirstUserMessage.content.trim() !== currentFirstUserMessage.content.trim()) + ) { + await this.updateConversationTitleWithConfirmation( + this.activeConversation.id, + newFirstUserMessage.content.trim(), + this.titleUpdateConfirmationCallback + ); + } + } + } + + /** + * Edits an assistant message with optional branching + * @param messageId - The ID of the assistant message to edit + * @param newContent - The new content for the message + * @param shouldBranch - Whether to create a branch or replace in-place + */ + async editAssistantMessage( + messageId: string, + newContent: string, + shouldBranch: boolean + ): Promise { + if (!this.activeConversation || this.isLoading) return; + + try { + const messageIndex = this.findMessageIndex(messageId); + + if (messageIndex === -1) { + console.error('Message not found for editing'); + return; + } + + const messageToEdit = this.activeMessages[messageIndex]; + + if (messageToEdit.role !== 'assistant') { + console.error('Only assistant messages can be edited with this method'); + return; + } + + if (shouldBranch) { + const newMessage = await DatabaseStore.createMessageBranch( + { + convId: messageToEdit.convId, + type: messageToEdit.type, + timestamp: Date.now(), + role: messageToEdit.role, + content: newContent, + thinking: messageToEdit.thinking || '', + children: [] + }, + messageToEdit.parent! + ); + + await DatabaseStore.updateCurrentNode(this.activeConversation.id, newMessage.id); + this.activeConversation.currNode = newMessage.id; + } else { + await DatabaseStore.updateMessage(messageToEdit.id, { + content: newContent, + timestamp: Date.now() + }); + + this.updateMessageAtIndex(messageIndex, { + content: newContent, + timestamp: Date.now() + }); + } + + this.updateConversationTimestamp(); + await this.refreshActiveMessages(); + } catch (error) { + console.error('Failed to edit assistant message:', error); + } + } + + /** + * Edits a message by creating a new branch with the edited content + * @param messageId - The ID of the message to edit + * @param newContent - The new content for the message + */ + async editMessageWithBranching(messageId: string, newContent: string): Promise { + if (!this.activeConversation || this.isLoading) return; + + try { + const messageIndex = this.findMessageIndex(messageId); + if (messageIndex === -1) { + console.error('Message not found for editing'); + return; + } + + const messageToEdit = this.activeMessages[messageIndex]; + if (messageToEdit.role !== 'user') { + console.error('Only user messages can be edited'); + return; + } + + // Check if this is the first user message in the conversation + // First user message is one that has the root message as its parent + const allMessages = await DatabaseStore.getConversationMessages(this.activeConversation.id); + const rootMessage = allMessages.find((m) => m.type === 'root' && m.parent === null); + const isFirstUserMessage = + rootMessage && messageToEdit.parent === rootMessage.id && messageToEdit.role === 'user'; + + let parentId = messageToEdit.parent; + + if (parentId === undefined || parentId === null) { + const rootMessage = allMessages.find((m) => m.type === 'root' && m.parent === null); + if (rootMessage) { + parentId = rootMessage.id; + } else { + console.error('No root message found for editing'); + return; + } + } + + const newMessage = await DatabaseStore.createMessageBranch( + { + convId: messageToEdit.convId, + type: messageToEdit.type, + timestamp: Date.now(), + role: messageToEdit.role, + content: newContent, + thinking: messageToEdit.thinking || '', + children: [], + extra: messageToEdit.extra ? JSON.parse(JSON.stringify(messageToEdit.extra)) : undefined + }, + parentId + ); + + await DatabaseStore.updateCurrentNode(this.activeConversation.id, newMessage.id); + this.activeConversation.currNode = newMessage.id; + this.updateConversationTimestamp(); + + // If this is the first user message, update the conversation title with confirmation if needed + if (isFirstUserMessage && newContent.trim()) { + await this.updateConversationTitleWithConfirmation( + this.activeConversation.id, + newContent.trim(), + this.titleUpdateConfirmationCallback + ); + } + + await this.refreshActiveMessages(); + + if (messageToEdit.role === 'user') { + await this.generateResponseForMessage(newMessage.id); + } + } catch (error) { + console.error('Failed to edit message with branching:', error); + } + } + + /** + * Regenerates an assistant message by creating a new branch with a new response + * @param messageId - The ID of the assistant message to regenerate + */ + async regenerateMessageWithBranching(messageId: string): Promise { + if (!this.activeConversation || this.isLoading) return; + + try { + const messageIndex = this.findMessageIndex(messageId); + if (messageIndex === -1) { + console.error('Message not found for regeneration'); + return; + } + + const messageToRegenerate = this.activeMessages[messageIndex]; + if (messageToRegenerate.role !== 'assistant') { + console.error('Only assistant messages can be regenerated'); + return; + } + + // Find parent message in all conversation messages, not just active path + const conversationMessages = await DatabaseStore.getConversationMessages( + this.activeConversation.id + ); + const parentMessage = conversationMessages.find((m) => m.id === messageToRegenerate.parent); + if (!parentMessage) { + console.error('Parent message not found for regeneration'); + return; + } + + this.isLoading = true; + this.currentResponse = ''; + + const newAssistantMessage = await DatabaseStore.createMessageBranch( + { + convId: this.activeConversation.id, + type: 'text', + timestamp: Date.now(), + role: 'assistant', + content: '', + thinking: '', + children: [] + }, + parentMessage.id + ); + + await DatabaseStore.updateCurrentNode(this.activeConversation.id, newAssistantMessage.id); + this.activeConversation.currNode = newAssistantMessage.id; + this.updateConversationTimestamp(); + await this.refreshActiveMessages(); + + const allConversationMessages = await DatabaseStore.getConversationMessages( + this.activeConversation.id + ); + const conversationPath = filterByLeafNodeId( + allConversationMessages, + parentMessage.id, + false + ) as DatabaseMessage[]; + + await this.streamChatCompletion(conversationPath, newAssistantMessage); + } catch (error) { + if (this.isAbortError(error)) return; + + console.error('Failed to regenerate message with branching:', error); + this.isLoading = false; + } + } + + /** + * Generates a new assistant response for a given user message + * @param userMessageId - ID of user message to respond to + */ + private async generateResponseForMessage(userMessageId: string): Promise { + if (!this.activeConversation) return; + + this.isLoading = true; + this.currentResponse = ''; + + try { + // Get conversation path up to the user message + const allMessages = await DatabaseStore.getConversationMessages(this.activeConversation.id); + const conversationPath = filterByLeafNodeId( + allMessages, + userMessageId, + false + ) as DatabaseMessage[]; + + // Create new assistant message branch + const assistantMessage = await DatabaseStore.createMessageBranch( + { + convId: this.activeConversation.id, + type: 'text', + timestamp: Date.now(), + role: 'assistant', + content: '', + thinking: '', + children: [] + }, + userMessageId + ); + + // Add assistant message to active messages immediately for UI reactivity + this.activeMessages.push(assistantMessage); + + // Stream response to new assistant message + await this.streamChatCompletion(conversationPath, assistantMessage); + } catch (error) { + console.error('Failed to generate response:', error); + this.isLoading = false; + } + } +} + +export const chatStore = new ChatStore(); + +export const conversations = () => chatStore.conversations; +export const activeConversation = () => chatStore.activeConversation; +export const activeMessages = () => chatStore.activeMessages; +export const isLoading = () => chatStore.isLoading; +export const currentResponse = () => chatStore.currentResponse; +export const isInitialized = () => chatStore.isInitialized; +export const maxContextError = () => chatStore.maxContextError; + +export const createConversation = chatStore.createConversation.bind(chatStore); +export const deleteConversation = chatStore.deleteConversation.bind(chatStore); +export const sendMessage = chatStore.sendMessage.bind(chatStore); +export const gracefulStop = chatStore.gracefulStop.bind(chatStore); +export const clearMaxContextError = chatStore.clearMaxContextError.bind(chatStore); +export const setMaxContextError = chatStore.setMaxContextError.bind(chatStore); + +// Branching operations +export const refreshActiveMessages = chatStore.refreshActiveMessages.bind(chatStore); +export const navigateToSibling = chatStore.navigateToSibling.bind(chatStore); +export const editAssistantMessage = chatStore.editAssistantMessage.bind(chatStore); +export const editMessageWithBranching = chatStore.editMessageWithBranching.bind(chatStore); +export const regenerateMessageWithBranching = + chatStore.regenerateMessageWithBranching.bind(chatStore); +export const deleteMessage = chatStore.deleteMessage.bind(chatStore); +export const getDeletionInfo = chatStore.getDeletionInfo.bind(chatStore); +export const updateConversationName = chatStore.updateConversationName.bind(chatStore); +export const setTitleUpdateConfirmationCallback = + chatStore.setTitleUpdateConfirmationCallback.bind(chatStore); + +export function stopGeneration() { + chatStore.stopGeneration(); +} +export const messages = () => chatStore.activeMessages; diff --git a/tools/server/webui/src/lib/stores/database.ts b/tools/server/webui/src/lib/stores/database.ts new file mode 100644 index 0000000000..f2e3a677a4 --- /dev/null +++ b/tools/server/webui/src/lib/stores/database.ts @@ -0,0 +1,349 @@ +import Dexie, { type EntityTable } from 'dexie'; +import { filterByLeafNodeId, findDescendantMessages } from '$lib/utils/branching'; + +class LlamacppDatabase extends Dexie { + conversations!: EntityTable; + messages!: EntityTable; + + constructor() { + super('LlamacppWebui'); + + this.version(1).stores({ + conversations: 'id, lastModified, currNode, name', + messages: 'id, convId, type, role, timestamp, parent, children' + }); + } +} + +const db = new LlamacppDatabase(); + +/** + * DatabaseStore - Persistent data layer for conversation and message management + * + * This service provides a comprehensive data access layer built on IndexedDB using Dexie. + * It handles all persistent storage operations for conversations, messages, and application settings + * with support for complex conversation branching and message threading. + * + * **Architecture & Relationships:** + * - **DatabaseStore** (this class): Stateless data persistence layer + * - Manages IndexedDB operations through Dexie ORM + * - Handles conversation and message CRUD operations + * - Supports complex branching with parent-child relationships + * - Provides transaction safety for multi-table operations + * + * - **ChatStore**: Primary consumer for conversation state management + * - Uses DatabaseStore for all persistence operations + * - Coordinates UI state with database state + * - Handles conversation lifecycle and message branching + * + * **Key Features:** + * - **Conversation Management**: Create, read, update, delete conversations + * - **Message Branching**: Support for tree-like conversation structures + * - **Transaction Safety**: Atomic operations for data consistency + * - **Path Resolution**: Navigate conversation branches and find leaf nodes + * - **Cascading Deletion**: Remove entire conversation branches + * + * **Database Schema:** + * - `conversations`: Conversation metadata with current node tracking + * - `messages`: Individual messages with parent-child relationships + * + * **Branching Model:** + * Messages form a tree structure where each message can have multiple children, + * enabling conversation branching and alternative response paths. The conversation's + * `currNode` tracks the currently active branch endpoint. + */ +import { v4 as uuid } from 'uuid'; + +export class DatabaseStore { + /** + * Adds a new message to the database. + * + * @param message - Message to add (without id) + * @returns The created message + */ + static async addMessage(message: Omit): Promise { + const newMessage: DatabaseMessage = { + ...message, + id: uuid() + }; + + await db.messages.add(newMessage); + return newMessage; + } + + /** + * Creates a new conversation. + * + * @param name - Name of the conversation + * @returns The created conversation + */ + static async createConversation(name: string): Promise { + const conversation: DatabaseConversation = { + id: uuid(), + name, + lastModified: Date.now(), + currNode: '' + }; + + await db.conversations.add(conversation); + return conversation; + } + + /** + * Creates a new message branch by adding a message and updating parent/child relationships. + * Also updates the conversation's currNode to point to the new message. + * + * @param message - Message to add (without id) + * @param parentId - Parent message ID to attach to + * @returns The created message + */ + static async createMessageBranch( + message: Omit, + parentId: string | null + ): Promise { + return await db.transaction('rw', [db.conversations, db.messages], async () => { + // Handle null parent (root message case) + if (parentId !== null) { + const parentMessage = await db.messages.get(parentId); + if (!parentMessage) { + throw new Error(`Parent message ${parentId} not found`); + } + } + + const newMessage: DatabaseMessage = { + ...message, + id: uuid(), + parent: parentId, + children: [] + }; + + await db.messages.add(newMessage); + + // Update parent's children array if parent exists + if (parentId !== null) { + const parentMessage = await db.messages.get(parentId); + if (parentMessage) { + await db.messages.update(parentId, { + children: [...parentMessage.children, newMessage.id] + }); + } + } + + await this.updateConversation(message.convId, { + currNode: newMessage.id + }); + + return newMessage; + }); + } + + /** + * Creates a root message for a new conversation. + * Root messages are not displayed but serve as the tree root for branching. + * + * @param convId - Conversation ID + * @returns The created root message + */ + static async createRootMessage(convId: string): Promise { + const rootMessage: DatabaseMessage = { + id: uuid(), + convId, + type: 'root', + timestamp: Date.now(), + role: 'system', + content: '', + parent: null, + thinking: '', + children: [] + }; + + await db.messages.add(rootMessage); + return rootMessage.id; + } + + /** + * Deletes a conversation and all its messages. + * + * @param id - Conversation ID + */ + static async deleteConversation(id: string): Promise { + await db.transaction('rw', [db.conversations, db.messages], async () => { + await db.conversations.delete(id); + await db.messages.where('convId').equals(id).delete(); + }); + } + + /** + * Deletes a message and removes it from its parent's children array. + * + * @param messageId - ID of the message to delete + */ + static async deleteMessage(messageId: string): Promise { + await db.transaction('rw', db.messages, async () => { + const message = await db.messages.get(messageId); + if (!message) return; + + // Remove this message from its parent's children array + if (message.parent) { + const parent = await db.messages.get(message.parent); + if (parent) { + parent.children = parent.children.filter((childId: string) => childId !== messageId); + await db.messages.put(parent); + } + } + + // Delete the message + await db.messages.delete(messageId); + }); + } + + /** + * Deletes a message and all its descendant messages (cascading deletion). + * This removes the entire branch starting from the specified message. + * + * @param conversationId - ID of the conversation containing the message + * @param messageId - ID of the root message to delete (along with all descendants) + * @returns Array of all deleted message IDs + */ + static async deleteMessageCascading( + conversationId: string, + messageId: string + ): Promise { + return await db.transaction('rw', db.messages, async () => { + // Get all messages in the conversation to find descendants + const allMessages = await db.messages.where('convId').equals(conversationId).toArray(); + + // Find all descendant messages + const descendants = findDescendantMessages(allMessages, messageId); + const allToDelete = [messageId, ...descendants]; + + // Get the message to delete for parent cleanup + const message = await db.messages.get(messageId); + if (message && message.parent) { + const parent = await db.messages.get(message.parent); + if (parent) { + parent.children = parent.children.filter((childId: string) => childId !== messageId); + await db.messages.put(parent); + } + } + + // Delete all messages in the branch + await db.messages.bulkDelete(allToDelete); + + return allToDelete; + }); + } + + /** + * Gets all conversations, sorted by last modified time (newest first). + * + * @returns Array of conversations + */ + static async getAllConversations(): Promise { + return await db.conversations.orderBy('lastModified').reverse().toArray(); + } + + /** + * Gets a conversation by ID. + * + * @param id - Conversation ID + * @returns The conversation if found, otherwise undefined + */ + static async getConversation(id: string): Promise { + return await db.conversations.get(id); + } + + /** + * Gets all leaf nodes (messages with no children) in a conversation. + * Useful for finding all possible conversation endpoints. + * + * @param convId - Conversation ID + * @returns Array of leaf node message IDs + */ + static async getConversationLeafNodes(convId: string): Promise { + const allMessages = await this.getConversationMessages(convId); + return allMessages.filter((msg) => msg.children.length === 0).map((msg) => msg.id); + } + + /** + * Gets all messages in a conversation, sorted by timestamp (oldest first). + * + * @param convId - Conversation ID + * @returns Array of messages in the conversation + */ + static async getConversationMessages(convId: string): Promise { + return await db.messages.where('convId').equals(convId).sortBy('timestamp'); + } + + /** + * Gets the conversation path from root to the current leaf node. + * Uses the conversation's currNode to determine the active branch. + * + * @param convId - Conversation ID + * @returns Array of messages in the current conversation path + */ + static async getConversationPath(convId: string): Promise { + const conversation = await this.getConversation(convId); + + if (!conversation) { + return []; + } + + const allMessages = await this.getConversationMessages(convId); + + if (allMessages.length === 0) { + return []; + } + + // If no currNode is set, use the latest message as leaf + const leafNodeId = + conversation.currNode || + allMessages.reduce((latest, msg) => (msg.timestamp > latest.timestamp ? msg : latest)).id; + + return filterByLeafNodeId(allMessages, leafNodeId, false) as DatabaseMessage[]; + } + + /** + * Updates a conversation. + * + * @param id - Conversation ID + * @param updates - Partial updates to apply + * @returns Promise that resolves when the conversation is updated + */ + static async updateConversation( + id: string, + updates: Partial> + ): Promise { + await db.conversations.update(id, { + ...updates, + lastModified: Date.now() + }); + } + + /** + * Updates the conversation's current node (active branch). + * This determines which conversation path is currently being viewed. + * + * @param convId - Conversation ID + * @param nodeId - Message ID to set as current node + */ + static async updateCurrentNode(convId: string, nodeId: string): Promise { + await this.updateConversation(convId, { + currNode: nodeId + }); + } + + /** + * Updates a message. + * + * @param id - Message ID + * @param updates - Partial updates to apply + * @returns Promise that resolves when the message is updated + */ + static async updateMessage( + id: string, + updates: Partial> + ): Promise { + await db.messages.update(id, updates); + } +} diff --git a/tools/server/webui/src/lib/stores/server.svelte.ts b/tools/server/webui/src/lib/stores/server.svelte.ts new file mode 100644 index 0000000000..7abaa2bdf5 --- /dev/null +++ b/tools/server/webui/src/lib/stores/server.svelte.ts @@ -0,0 +1,184 @@ +import { ChatService } from '$lib/services/chat'; +import { config } from '$lib/stores/settings.svelte'; + +/** + * ServerStore - Server state management and capability detection + * + * This store manages communication with the llama.cpp server to retrieve and maintain + * server properties, model information, and capability detection. It provides reactive + * state for server connectivity, model capabilities, and endpoint availability. + * + * **Architecture & Relationships:** + * - **ServerStore** (this class): Server state and capability management + * - Fetches and caches server properties from `/props` endpoint + * - Detects model capabilities (vision, audio support) + * - Tests endpoint availability (slots endpoint) + * - Provides reactive server state for UI components + * + * - **ChatService**: Uses server properties for request validation + * - **SlotsService**: Depends on slots endpoint availability detection + * - **UI Components**: Subscribe to server state for capability-based rendering + * + * **Key Features:** + * - **Server Properties**: Model path, context size, build information + * - **Capability Detection**: Vision and audio modality support + * - **Endpoint Testing**: Slots endpoint availability checking + * - **Error Handling**: User-friendly error messages for connection issues + * - **Reactive State**: Svelte 5 runes for automatic UI updates + * - **State Management**: Loading states and error recovery + * + * **Server Capabilities Detected:** + * - Model name extraction from file path + * - Vision support (multimodal image processing) + * - Audio support (speech processing) + * - Slots endpoint availability (for processing state monitoring) + * - Context window size and token limits + */ +class ServerStore { + private _serverProps = $state(null); + private _loading = $state(false); + private _error = $state(null); + private _slotsEndpointAvailable = $state(null); + + get serverProps(): ApiLlamaCppServerProps | null { + return this._serverProps; + } + + get loading(): boolean { + return this._loading; + } + + get error(): string | null { + return this._error; + } + + get modelName(): string | null { + if (!this._serverProps?.model_path) return null; + return this._serverProps.model_path.split(/(\\|\/)/).pop() || null; + } + + get supportedModalities(): string[] { + const modalities: string[] = []; + if (this._serverProps?.modalities?.audio) { + modalities.push('audio'); + } + if (this._serverProps?.modalities?.vision) { + modalities.push('vision'); + } + return modalities; + } + + get supportsVision(): boolean { + return this._serverProps?.modalities?.vision ?? false; + } + + get supportsAudio(): boolean { + return this._serverProps?.modalities?.audio ?? false; + } + + get slotsEndpointAvailable(): boolean | null { + return this._slotsEndpointAvailable; + } + + /** + * Check if slots endpoint is available based on server properties and endpoint support + */ + private async checkSlotsEndpointAvailability(): Promise { + if (!this._serverProps) { + this._slotsEndpointAvailable = false; + return; + } + + if (this._serverProps.total_slots <= 0) { + this._slotsEndpointAvailable = false; + return; + } + + try { + const currentConfig = config(); + const apiKey = currentConfig.apiKey?.toString().trim(); + + const response = await fetch('/slots', { + headers: { + ...(apiKey ? { Authorization: `Bearer ${apiKey}` } : {}) + } + }); + + if (response.status === 501) { + console.info('Slots endpoint not implemented - server started without --slots flag'); + this._slotsEndpointAvailable = false; + return; + } + + this._slotsEndpointAvailable = true; + } catch (error) { + console.warn('Unable to test slots endpoint availability:', error); + this._slotsEndpointAvailable = false; + } + } + + /** + * Fetches server properties from the server + */ + async fetchServerProps(): Promise { + this._loading = true; + this._error = null; + + try { + console.log('Fetching server properties...'); + const props = await ChatService.getServerProps(); + this._serverProps = props; + console.log('Server properties loaded:', props); + + // Check slots endpoint availability after server props are loaded + await this.checkSlotsEndpointAvailability(); + } catch (error) { + let errorMessage = 'Failed to connect to server'; + + if (error instanceof Error) { + // Handle specific error types with user-friendly messages + if (error.name === 'TypeError' && error.message.includes('fetch')) { + errorMessage = 'Server is not running or unreachable'; + } else if (error.message.includes('ECONNREFUSED')) { + errorMessage = 'Connection refused - server may be offline'; + } else if (error.message.includes('ENOTFOUND')) { + errorMessage = 'Server not found - check server address'; + } else if (error.message.includes('ETIMEDOUT')) { + errorMessage = 'Connection timeout - server may be overloaded'; + } else if (error.message.includes('500')) { + errorMessage = 'Server error - check server logs'; + } else if (error.message.includes('404')) { + errorMessage = 'Server endpoint not found'; + } else if (error.message.includes('403') || error.message.includes('401')) { + errorMessage = 'Access denied'; + } + } + + this._error = errorMessage; + console.error('Error fetching server properties:', error); + } finally { + this._loading = false; + } + } + + /** + * Clears the server state + */ + clear(): void { + this._serverProps = null; + this._error = null; + this._loading = false; + this._slotsEndpointAvailable = null; + } +} + +export const serverStore = new ServerStore(); + +export const serverProps = () => serverStore.serverProps; +export const serverLoading = () => serverStore.loading; +export const serverError = () => serverStore.error; +export const modelName = () => serverStore.modelName; +export const supportedModalities = () => serverStore.supportedModalities; +export const supportsVision = () => serverStore.supportsVision; +export const supportsAudio = () => serverStore.supportsAudio; +export const slotsEndpointAvailable = () => serverStore.slotsEndpointAvailable; diff --git a/tools/server/webui/src/lib/stores/settings.svelte.ts b/tools/server/webui/src/lib/stores/settings.svelte.ts new file mode 100644 index 0000000000..e5bc5ca9c9 --- /dev/null +++ b/tools/server/webui/src/lib/stores/settings.svelte.ts @@ -0,0 +1,206 @@ +/** + * SettingsStore - Application configuration and theme management + * + * This store manages all application settings including AI model parameters, UI preferences, + * and theme configuration. It provides persistent storage through localStorage with reactive + * state management using Svelte 5 runes. + * + * **Architecture & Relationships:** + * - **SettingsStore** (this class): Configuration state management + * - Manages AI model parameters (temperature, max tokens, etc.) + * - Handles theme switching and persistence + * - Provides localStorage synchronization + * - Offers reactive configuration access + * + * - **ChatService**: Reads model parameters for API requests + * - **UI Components**: Subscribe to theme and configuration changes + * + * **Key Features:** + * - **Model Parameters**: Temperature, max tokens, top-p, top-k, repeat penalty + * - **Theme Management**: Auto, light, dark theme switching + * - **Persistence**: Automatic localStorage synchronization + * - **Reactive State**: Svelte 5 runes for automatic UI updates + * - **Default Handling**: Graceful fallback to defaults for missing settings + * - **Batch Updates**: Efficient multi-setting updates + * - **Reset Functionality**: Restore defaults for individual or all settings + * + * **Configuration Categories:** + * - Generation parameters (temperature, tokens, sampling) + * - UI preferences (theme, display options) + * - System settings (model selection, prompts) + * - Advanced options (seed, penalties, context handling) + */ + +import { browser } from '$app/environment'; +import { SETTING_CONFIG_DEFAULT } from '$lib/constants/settings-config'; + +class SettingsStore { + config = $state({ ...SETTING_CONFIG_DEFAULT }); + theme = $state('auto'); + isInitialized = $state(false); + + constructor() { + if (browser) { + this.initialize(); + } + } + + /** + * Initialize the settings store by loading from localStorage + */ + initialize() { + try { + this.loadConfig(); + this.loadTheme(); + this.isInitialized = true; + } catch (error) { + console.error('Failed to initialize settings store:', error); + } + } + + /** + * Load configuration from localStorage + * Returns default values for missing keys to prevent breaking changes + */ + private loadConfig() { + if (!browser) return; + + try { + const savedVal = JSON.parse(localStorage.getItem('config') || '{}'); + // Merge with defaults to prevent breaking changes + this.config = { + ...SETTING_CONFIG_DEFAULT, + ...savedVal + }; + } catch (error) { + console.warn('Failed to parse config from localStorage, using defaults:', error); + this.config = { ...SETTING_CONFIG_DEFAULT }; + } + } + + /** + * Load theme from localStorage + */ + private loadTheme() { + if (!browser) return; + + this.theme = localStorage.getItem('theme') || 'auto'; + } + + /** + * Update a specific configuration setting + * @param key - The configuration key to update + * @param value - The new value for the configuration key + */ + updateConfig(key: K, value: SettingsConfigType[K]) { + this.config[key] = value; + this.saveConfig(); + } + + /** + * Update multiple configuration settings at once + * @param updates - Object containing the configuration updates + */ + updateMultipleConfig(updates: Partial) { + Object.assign(this.config, updates); + this.saveConfig(); + } + + /** + * Save the current configuration to localStorage + */ + private saveConfig() { + if (!browser) return; + + try { + localStorage.setItem('config', JSON.stringify(this.config)); + } catch (error) { + console.error('Failed to save config to localStorage:', error); + } + } + + /** + * Update the theme setting + * @param newTheme - The new theme value + */ + updateTheme(newTheme: string) { + this.theme = newTheme; + this.saveTheme(); + } + + /** + * Save the current theme to localStorage + */ + private saveTheme() { + if (!browser) return; + + try { + if (this.theme === 'auto') { + localStorage.removeItem('theme'); + } else { + localStorage.setItem('theme', this.theme); + } + } catch (error) { + console.error('Failed to save theme to localStorage:', error); + } + } + + /** + * Reset configuration to defaults + */ + resetConfig() { + this.config = { ...SETTING_CONFIG_DEFAULT }; + this.saveConfig(); + } + + /** + * Reset theme to auto + */ + resetTheme() { + this.theme = 'auto'; + this.saveTheme(); + } + + /** + * Reset all settings to defaults + */ + resetAll() { + this.resetConfig(); + this.resetTheme(); + } + + /** + * Get a specific configuration value + * @param key - The configuration key to get + * @returns The configuration value + */ + getConfig(key: K): SettingsConfigType[K] { + return this.config[key]; + } + + /** + * Get the entire configuration object + * @returns The complete configuration object + */ + getAllConfig(): SettingsConfigType { + return { ...this.config }; + } +} + +// Create and export the settings store instance +export const settingsStore = new SettingsStore(); + +// Export reactive getters for easy access in components +export const config = () => settingsStore.config; +export const theme = () => settingsStore.theme; +export const isInitialized = () => settingsStore.isInitialized; + +// Export bound methods for easy access +export const updateConfig = settingsStore.updateConfig.bind(settingsStore); +export const updateMultipleConfig = settingsStore.updateMultipleConfig.bind(settingsStore); +export const updateTheme = settingsStore.updateTheme.bind(settingsStore); +export const resetConfig = settingsStore.resetConfig.bind(settingsStore); +export const resetTheme = settingsStore.resetTheme.bind(settingsStore); +export const resetAll = settingsStore.resetAll.bind(settingsStore); +export const getConfig = settingsStore.getConfig.bind(settingsStore); +export const getAllConfig = settingsStore.getAllConfig.bind(settingsStore); diff --git a/tools/server/webui/src/lib/types/api.d.ts b/tools/server/webui/src/lib/types/api.d.ts new file mode 100644 index 0000000000..d0e60a6c13 --- /dev/null +++ b/tools/server/webui/src/lib/types/api.d.ts @@ -0,0 +1,252 @@ +import type { ChatMessagePromptProgress } from './chat'; + +export interface ApiChatMessageContentPart { + type: 'text' | 'image_url' | 'input_audio'; + text?: string; + image_url?: { + url: string; + }; + input_audio?: { + data: string; + format: 'wav' | 'mp3'; + }; +} + +export interface ApiContextSizeError { + code: number; + message: string; + type: 'exceed_context_size_error'; + n_prompt_tokens: number; + n_ctx: number; +} + +export interface ApiErrorResponse { + error: + | ApiContextSizeError + | { + code: number; + message: string; + type?: string; + }; +} + +export interface ApiChatMessageData { + role: ChatRole; + content: string | ApiChatMessageContentPart[]; + timestamp?: number; +} + +export interface ApiLlamaCppServerProps { + default_generation_settings: { + id: number; + id_task: number; + n_ctx: number; + speculative: boolean; + is_processing: boolean; + params: { + n_predict: number; + seed: number; + temperature: number; + dynatemp_range: number; + dynatemp_exponent: number; + top_k: number; + top_p: number; + min_p: number; + top_n_sigma: number; + xtc_probability: number; + xtc_threshold: number; + typ_p: number; + repeat_last_n: number; + repeat_penalty: number; + presence_penalty: number; + frequency_penalty: number; + dry_multiplier: number; + dry_base: number; + dry_allowed_length: number; + dry_penalty_last_n: number; + dry_sequence_breakers: string[]; + mirostat: number; + mirostat_tau: number; + mirostat_eta: number; + stop: string[]; + max_tokens: number; + n_keep: number; + n_discard: number; + ignore_eos: boolean; + stream: boolean; + logit_bias: Array<[number, number]>; + n_probs: number; + min_keep: number; + grammar: string; + grammar_lazy: boolean; + grammar_triggers: string[]; + preserved_tokens: number[]; + chat_format: string; + reasoning_format: string; + reasoning_in_content: boolean; + thinking_forced_open: boolean; + samplers: string[]; + 'speculative.n_max': number; + 'speculative.n_min': number; + 'speculative.p_min': number; + timings_per_token: boolean; + post_sampling_probs: boolean; + lora: Array<{ name: string; scale: number }>; + }; + prompt: string; + next_token: { + has_next_token: boolean; + has_new_line: boolean; + n_remain: number; + n_decoded: number; + stopping_word: string; + }; + }; + total_slots: number; + model_path: string; + modalities: { + vision: boolean; + audio: boolean; + }; + chat_template: string; + bos_token: string; + eos_token: string; + build_info: string; +} + +export interface ApiChatCompletionRequest { + messages: Array<{ + role: ChatRole; + content: string | ApiChatMessageContentPart[]; + }>; + stream?: boolean; + // Reasoning parameters + reasoning_format?: string; + // Generation parameters + temperature?: number; + max_tokens?: number; + // Sampling parameters + dynatemp_range?: number; + dynatemp_exponent?: number; + top_k?: number; + top_p?: number; + min_p?: number; + xtc_probability?: number; + xtc_threshold?: number; + typ_p?: number; + // Penalty parameters + repeat_last_n?: number; + repeat_penalty?: number; + presence_penalty?: number; + frequency_penalty?: number; + dry_multiplier?: number; + dry_base?: number; + dry_allowed_length?: number; + dry_penalty_last_n?: number; + // Sampler configuration + samplers?: string[]; + // Custom parameters (JSON string) + custom?: Record; +} + +export interface ApiChatCompletionStreamChunk { + choices: Array<{ + delta: { + content?: string; + reasoning_content?: string; + }; + }>; + timings?: { + prompt_n?: number; + prompt_ms?: number; + predicted_n?: number; + predicted_ms?: number; + cache_n?: number; + }; + prompt_progress?: ChatMessagePromptProgress; +} + +export interface ApiChatCompletionResponse { + choices: Array<{ + message: { + content: string; + reasoning_content?: string; + }; + }>; +} + +export interface ApiSlotData { + id: number; + id_task: number; + n_ctx: number; + speculative: boolean; + is_processing: boolean; + params: { + n_predict: number; + seed: number; + temperature: number; + dynatemp_range: number; + dynatemp_exponent: number; + top_k: number; + top_p: number; + min_p: number; + top_n_sigma: number; + xtc_probability: number; + xtc_threshold: number; + typical_p: number; + repeat_last_n: number; + repeat_penalty: number; + presence_penalty: number; + frequency_penalty: number; + dry_multiplier: number; + dry_base: number; + dry_allowed_length: number; + dry_penalty_last_n: number; + mirostat: number; + mirostat_tau: number; + mirostat_eta: number; + max_tokens: number; + n_keep: number; + n_discard: number; + ignore_eos: boolean; + stream: boolean; + n_probs: number; + min_keep: number; + chat_format: string; + reasoning_format: string; + reasoning_in_content: boolean; + thinking_forced_open: boolean; + samplers: string[]; + 'speculative.n_max': number; + 'speculative.n_min': number; + 'speculative.p_min': number; + timings_per_token: boolean; + post_sampling_probs: boolean; + lora: Array<{ name: string; scale: number }>; + }; + next_token: { + has_next_token: boolean; + has_new_line: boolean; + n_remain: number; + n_decoded: number; + }; +} + +export interface ApiProcessingState { + status: 'initializing' | 'generating' | 'preparing' | 'idle'; + tokensDecoded: number; + tokensRemaining: number; + contextUsed: number; + contextTotal: number; + outputTokensUsed: number; // Total output tokens (thinking + regular content) + outputTokensMax: number; // Max output tokens allowed + temperature: number; + topP: number; + speculative: boolean; + hasNextToken: boolean; + tokensPerSecond?: number; + // Progress information from prompt_progress + progressPercent?: number; + promptTokens?: number; + cacheTokens?: number; +} diff --git a/tools/server/webui/src/lib/types/chat.d.ts b/tools/server/webui/src/lib/types/chat.d.ts new file mode 100644 index 0000000000..d803a5aa0f --- /dev/null +++ b/tools/server/webui/src/lib/types/chat.d.ts @@ -0,0 +1,34 @@ +export type ChatMessageType = 'root' | 'text' | 'think'; +export type ChatRole = 'user' | 'assistant' | 'system'; + +export interface ChatUploadedFile { + id: string; + name: string; + size: number; + type: string; + file: File; + preview?: string; + textContent?: string; +} + +export interface ChatMessageSiblingInfo { + message: DatabaseMessage; + siblingIds: string[]; + currentIndex: number; + totalSiblings: number; +} + +export interface ChatMessagePromptProgress { + cache: number; + processed: number; + time_ms: number; + total: number; +} + +export interface ChatMessageTimings { + cache_n?: number; + predicted_ms?: number; + predicted_n?: number; + prompt_ms?: number; + prompt_n?: number; +} diff --git a/tools/server/webui/src/lib/types/database.d.ts b/tools/server/webui/src/lib/types/database.d.ts new file mode 100644 index 0000000000..e3076ef12a --- /dev/null +++ b/tools/server/webui/src/lib/types/database.d.ts @@ -0,0 +1,55 @@ +import type { ChatMessageTimings } from './chat'; + +export interface DatabaseConversation { + currNode: string | null; + id: string; + lastModified: number; + name: string; +} + +export interface DatabaseMessageExtraAudioFile { + type: 'audioFile'; + name: string; + base64Data: string; + mimeType: string; +} + +export interface DatabaseMessageExtraImageFile { + type: 'imageFile'; + name: string; + base64Url: string; +} + +export interface DatabaseMessageExtraTextFile { + type: 'textFile'; + name: string; + content: string; +} + +export interface DatabaseMessageExtraPdfFile { + type: 'pdfFile'; + name: string; + content: string; // Text content extracted from PDF + images?: string[]; // Optional: PDF pages as base64 images + processedAsImages: boolean; // Whether PDF was processed as images +} + +export type DatabaseMessageExtra = + | DatabaseMessageExtraImageFile + | DatabaseMessageExtraTextFile + | DatabaseMessageExtraAudioFile + | DatabaseMessageExtraPdfFile; + +export interface DatabaseMessage { + id: string; + convId: string; + type: ChatMessageType; + timestamp: number; + role: ChatRole; + content: string; + parent: string; + thinking: string; + children: string[]; + extra?: DatabaseMessageExtra[]; + timings?: ChatMessageTimings; +} diff --git a/tools/server/webui/src/lib/types/settings.d.ts b/tools/server/webui/src/lib/types/settings.d.ts new file mode 100644 index 0000000000..4311f779ad --- /dev/null +++ b/tools/server/webui/src/lib/types/settings.d.ts @@ -0,0 +1,50 @@ +import type { SETTING_CONFIG_DEFAULT } from '$lib/constants/settings-config'; +import type { ChatMessageTimings } from './chat'; + +export type SettingsConfigValue = string | number | boolean; + +export interface SettingsFieldConfig { + key: string; + label: string; + type: 'input' | 'textarea' | 'checkbox' | 'select'; + help?: string; + options?: Array<{ value: string; label: string; icon?: typeof import('@lucide/svelte').Icon }>; +} + +export interface SettingsChatServiceOptions { + stream?: boolean; + // Generation parameters + temperature?: number; + max_tokens?: number; + // Sampling parameters + dynatemp_range?: number; + dynatemp_exponent?: number; + top_k?: number; + top_p?: number; + min_p?: number; + xtc_probability?: number; + xtc_threshold?: number; + typ_p?: number; + // Penalty parameters + repeat_last_n?: number; + repeat_penalty?: number; + presence_penalty?: number; + frequency_penalty?: number; + dry_multiplier?: number; + dry_base?: number; + dry_allowed_length?: number; + dry_penalty_last_n?: number; + // Sampler configuration + samplers?: string | string[]; + // Custom parameters + custom?: string; + // Callbacks + onChunk?: (chunk: string) => void; + onReasoningChunk?: (chunk: string) => void; + onComplete?: (response: string, reasoningContent?: string, timings?: ChatMessageTimings) => void; + onError?: (error: Error) => void; +} + +export type SettingsConfigType = typeof SETTING_CONFIG_DEFAULT & { + [key: string]: SettingsConfigValue; +}; diff --git a/tools/server/webui/src/lib/utils/api-key-validation.ts b/tools/server/webui/src/lib/utils/api-key-validation.ts new file mode 100644 index 0000000000..d7bbf9c2eb --- /dev/null +++ b/tools/server/webui/src/lib/utils/api-key-validation.ts @@ -0,0 +1,45 @@ +import { error } from '@sveltejs/kit'; +import { browser } from '$app/environment'; +import { config } from '$lib/stores/settings.svelte'; + +/** + * Validates API key by making a request to the server props endpoint + * Throws SvelteKit errors for authentication failures or server issues + */ +export async function validateApiKey(fetch: typeof globalThis.fetch): Promise { + if (!browser) { + return; + } + + try { + const apiKey = config().apiKey; + + const headers: Record = { + 'Content-Type': 'application/json' + }; + + if (apiKey) { + headers.Authorization = `Bearer ${apiKey}`; + } + + const response = await fetch('/props', { headers }); + + if (!response.ok) { + if (response.status === 401 || response.status === 403) { + throw error(401, 'Access denied'); + } else if (response.status >= 500) { + throw error(response.status, 'Server error - check if llama.cpp server is running'); + } else { + throw error(response.status, `Server responded with status ${response.status}`); + } + } + } catch (err) { + // If it's already a SvelteKit error, re-throw it + if (err && typeof err === 'object' && 'status' in err) { + throw err; + } + + // Network or other errors + throw error(503, 'Cannot connect to server - check if llama.cpp server is running'); + } +} diff --git a/tools/server/webui/src/lib/utils/audio-recording.ts b/tools/server/webui/src/lib/utils/audio-recording.ts new file mode 100644 index 0000000000..acf4c6d1fa --- /dev/null +++ b/tools/server/webui/src/lib/utils/audio-recording.ts @@ -0,0 +1,226 @@ +import { MimeTypeAudio } from '$lib/enums/files'; + +/** + * AudioRecorder - Browser-based audio recording with MediaRecorder API + * + * This class provides a complete audio recording solution using the browser's MediaRecorder API. + * It handles microphone access, recording state management, and audio format optimization. + * + * **Features:** + * - Automatic microphone permission handling + * - Audio enhancement (echo cancellation, noise suppression, auto gain) + * - Multiple format support with fallback (WAV, WebM, MP4, AAC) + * - Real-time recording state tracking + * - Proper cleanup and resource management + */ +export class AudioRecorder { + private mediaRecorder: MediaRecorder | null = null; + private audioChunks: Blob[] = []; + private stream: MediaStream | null = null; + private recordingState: boolean = false; + + async startRecording(): Promise { + try { + this.stream = await navigator.mediaDevices.getUserMedia({ + audio: { + echoCancellation: true, + noiseSuppression: true, + autoGainControl: true + } + }); + + this.initializeRecorder(this.stream); + + this.audioChunks = []; + // Start recording with a small timeslice to ensure we get data + this.mediaRecorder!.start(100); + this.recordingState = true; + } catch (error) { + console.error('Failed to start recording:', error); + throw new Error('Failed to access microphone. Please check permissions.'); + } + } + + async stopRecording(): Promise { + return new Promise((resolve, reject) => { + if (!this.mediaRecorder || this.mediaRecorder.state === 'inactive') { + reject(new Error('No active recording to stop')); + return; + } + + this.mediaRecorder.onstop = () => { + const mimeType = this.mediaRecorder?.mimeType || MimeTypeAudio.WAV; + const audioBlob = new Blob(this.audioChunks, { type: mimeType }); + + this.cleanup(); + + resolve(audioBlob); + }; + + this.mediaRecorder.onerror = (event) => { + console.error('Recording error:', event); + this.cleanup(); + reject(new Error('Recording failed')); + }; + + this.mediaRecorder.stop(); + }); + } + + isRecording(): boolean { + return this.recordingState; + } + + cancelRecording(): void { + if (this.mediaRecorder && this.mediaRecorder.state !== 'inactive') { + this.mediaRecorder.stop(); + } + this.cleanup(); + } + + private initializeRecorder(stream: MediaStream): void { + const options: MediaRecorderOptions = {}; + + if (MediaRecorder.isTypeSupported(MimeTypeAudio.WAV)) { + options.mimeType = MimeTypeAudio.WAV; + } else if (MediaRecorder.isTypeSupported(MimeTypeAudio.WEBM_OPUS)) { + options.mimeType = MimeTypeAudio.WEBM_OPUS; + } else if (MediaRecorder.isTypeSupported(MimeTypeAudio.WEBM)) { + options.mimeType = MimeTypeAudio.WEBM; + } else if (MediaRecorder.isTypeSupported(MimeTypeAudio.MP4)) { + options.mimeType = MimeTypeAudio.MP4; + } else { + console.warn('No preferred audio format supported, using default'); + } + + this.mediaRecorder = new MediaRecorder(stream, options); + + this.mediaRecorder.ondataavailable = (event) => { + if (event.data.size > 0) { + this.audioChunks.push(event.data); + } + }; + + this.mediaRecorder.onstop = () => { + this.recordingState = false; + }; + + this.mediaRecorder.onerror = (event) => { + console.error('MediaRecorder error:', event); + this.recordingState = false; + }; + } + + private cleanup(): void { + if (this.stream) { + for (const track of this.stream.getTracks()) { + track.stop(); + } + + this.stream = null; + } + this.mediaRecorder = null; + this.audioChunks = []; + this.recordingState = false; + } +} + +export async function convertToWav(audioBlob: Blob): Promise { + try { + if (audioBlob.type.includes('wav')) { + return audioBlob; + } + + const arrayBuffer = await audioBlob.arrayBuffer(); + + // eslint-disable-next-line @typescript-eslint/no-explicit-any + const audioContext = new (window.AudioContext || (window as any).webkitAudioContext)(); + + const audioBuffer = await audioContext.decodeAudioData(arrayBuffer); + + const wavBlob = audioBufferToWav(audioBuffer); + + audioContext.close(); + + return wavBlob; + } catch (error) { + console.error('Failed to convert audio to WAV:', error); + return audioBlob; + } +} + +function audioBufferToWav(buffer: AudioBuffer): Blob { + const length = buffer.length; + const numberOfChannels = buffer.numberOfChannels; + const sampleRate = buffer.sampleRate; + const bytesPerSample = 2; // 16-bit + const blockAlign = numberOfChannels * bytesPerSample; + const byteRate = sampleRate * blockAlign; + const dataSize = length * blockAlign; + const bufferSize = 44 + dataSize; + + const arrayBuffer = new ArrayBuffer(bufferSize); + const view = new DataView(arrayBuffer); + + const writeString = (offset: number, string: string) => { + for (let i = 0; i < string.length; i++) { + view.setUint8(offset + i, string.charCodeAt(i)); + } + }; + + writeString(0, 'RIFF'); // ChunkID + view.setUint32(4, bufferSize - 8, true); // ChunkSize + writeString(8, 'WAVE'); // Format + writeString(12, 'fmt '); // Subchunk1ID + view.setUint32(16, 16, true); // Subchunk1Size + view.setUint16(20, 1, true); // AudioFormat (PCM) + view.setUint16(22, numberOfChannels, true); // NumChannels + view.setUint32(24, sampleRate, true); // SampleRate + view.setUint32(28, byteRate, true); // ByteRate + view.setUint16(32, blockAlign, true); // BlockAlign + view.setUint16(34, 16, true); // BitsPerSample + writeString(36, 'data'); // Subchunk2ID + view.setUint32(40, dataSize, true); // Subchunk2Size + + let offset = 44; + for (let i = 0; i < length; i++) { + for (let channel = 0; channel < numberOfChannels; channel++) { + const sample = Math.max(-1, Math.min(1, buffer.getChannelData(channel)[i])); + view.setInt16(offset, sample * 0x7fff, true); + offset += 2; + } + } + + return new Blob([arrayBuffer], { type: MimeTypeAudio.WAV }); +} + +/** + * Create a File object from audio blob with timestamp-based naming + * @param audioBlob - The audio blob to wrap + * @param filename - Optional custom filename + * @returns File object with appropriate name and metadata + */ +export function createAudioFile(audioBlob: Blob, filename?: string): File { + const timestamp = new Date().toISOString().replace(/[:.]/g, '-'); + const extension = audioBlob.type.includes('wav') ? 'wav' : 'mp3'; + const defaultFilename = `recording-${timestamp}.${extension}`; + + return new File([audioBlob], filename || defaultFilename, { + type: audioBlob.type, + lastModified: Date.now() + }); +} + +/** + * Check if audio recording is supported in the current browser + * @returns True if MediaRecorder and getUserMedia are available + */ +export function isAudioRecordingSupported(): boolean { + return !!( + typeof navigator !== 'undefined' && + navigator.mediaDevices && + typeof navigator.mediaDevices.getUserMedia === 'function' && + typeof window !== 'undefined' && + window.MediaRecorder + ); +} diff --git a/tools/server/webui/src/lib/utils/autoresize-textarea.ts b/tools/server/webui/src/lib/utils/autoresize-textarea.ts new file mode 100644 index 0000000000..cfee5ec151 --- /dev/null +++ b/tools/server/webui/src/lib/utils/autoresize-textarea.ts @@ -0,0 +1,10 @@ +/** + * Automatically resizes a textarea element to fit its content + * @param textareaElement - The textarea element to resize + */ +export default function autoResizeTextarea(textareaElement: HTMLTextAreaElement | null): void { + if (textareaElement) { + textareaElement.style.height = '1rem'; + textareaElement.style.height = textareaElement.scrollHeight + 'px'; + } +} diff --git a/tools/server/webui/src/lib/utils/branching.ts b/tools/server/webui/src/lib/utils/branching.ts new file mode 100644 index 0000000000..3be56047a5 --- /dev/null +++ b/tools/server/webui/src/lib/utils/branching.ts @@ -0,0 +1,283 @@ +/** + * Message branching utilities for conversation tree navigation. + * + * Conversation branching allows users to edit messages and create alternate paths + * while preserving the original conversation flow. Each message has parent/children + * relationships forming a tree structure. + * + * Example tree: + * root + * ├── message 1 (user) + * │ └── message 2 (assistant) + * │ ├── message 3 (user) + * │ └── message 6 (user) ← new branch + * └── message 4 (user) + * └── message 5 (assistant) + */ + +/** + * Filters messages to get the conversation path from root to a specific leaf node. + * If the leafNodeId doesn't exist, returns the path with the latest timestamp. + * + * @param messages - All messages in the conversation + * @param leafNodeId - The target leaf node ID to trace back from + * @param includeRoot - Whether to include root messages in the result + * @returns Array of messages from root to leaf, sorted by timestamp + */ +export function filterByLeafNodeId( + messages: readonly DatabaseMessage[], + leafNodeId: string, + includeRoot: boolean = false +): readonly DatabaseMessage[] { + const result: DatabaseMessage[] = []; + const nodeMap = new Map(); + + // Build node map for quick lookups + for (const msg of messages) { + nodeMap.set(msg.id, msg); + } + + // Find the starting node (leaf node or latest if not found) + let startNode: DatabaseMessage | undefined = nodeMap.get(leafNodeId); + if (!startNode) { + // If leaf node not found, use the message with latest timestamp + let latestTime = -1; + for (const msg of messages) { + if (msg.timestamp > latestTime) { + startNode = msg; + latestTime = msg.timestamp; + } + } + } + + // Traverse from leaf to root, collecting messages + let currentNode: DatabaseMessage | undefined = startNode; + while (currentNode) { + // Include message if it's not root, or if we want to include root + if (currentNode.type !== 'root' || includeRoot) { + result.push(currentNode); + } + + // Stop traversal if parent is null (reached root) + if (currentNode.parent === null) { + break; + } + currentNode = nodeMap.get(currentNode.parent); + } + + // Sort by timestamp to get chronological order (root to leaf) + result.sort((a, b) => a.timestamp - b.timestamp); + return result; +} + +/** + * Finds the leaf node (message with no children) for a given message branch. + * Traverses down the tree following the last child until reaching a leaf. + * + * @param messages - All messages in the conversation + * @param messageId - Starting message ID to find leaf for + * @returns The leaf node ID, or the original messageId if no children + */ +export function findLeafNode(messages: readonly DatabaseMessage[], messageId: string): string { + const nodeMap = new Map(); + + // Build node map for quick lookups + for (const msg of messages) { + nodeMap.set(msg.id, msg); + } + + let currentNode: DatabaseMessage | undefined = nodeMap.get(messageId); + while (currentNode && currentNode.children.length > 0) { + // Follow the last child (most recent branch) + const lastChildId = currentNode.children[currentNode.children.length - 1]; + currentNode = nodeMap.get(lastChildId); + } + + return currentNode?.id ?? messageId; +} + +/** + * Finds all descendant messages (children, grandchildren, etc.) of a given message. + * This is used for cascading deletion to remove all messages in a branch. + * + * @param messages - All messages in the conversation + * @param messageId - The root message ID to find descendants for + * @returns Array of all descendant message IDs + */ +export function findDescendantMessages( + messages: readonly DatabaseMessage[], + messageId: string +): string[] { + const nodeMap = new Map(); + + // Build node map for quick lookups + for (const msg of messages) { + nodeMap.set(msg.id, msg); + } + + const descendants: string[] = []; + const queue: string[] = [messageId]; + + while (queue.length > 0) { + const currentId = queue.shift()!; + const currentNode = nodeMap.get(currentId); + + if (currentNode) { + // Add all children to the queue and descendants list + for (const childId of currentNode.children) { + descendants.push(childId); + queue.push(childId); + } + } + } + + return descendants; +} + +/** + * Gets sibling information for a message, including all sibling IDs and current position. + * Siblings are messages that share the same parent. + * + * @param messages - All messages in the conversation + * @param messageId - The message to get sibling info for + * @returns Sibling information including leaf node IDs for navigation + */ +export function getMessageSiblings( + messages: readonly DatabaseMessage[], + messageId: string +): ChatMessageSiblingInfo | null { + const nodeMap = new Map(); + + // Build node map for quick lookups + for (const msg of messages) { + nodeMap.set(msg.id, msg); + } + + const message = nodeMap.get(messageId); + if (!message) { + return null; + } + + // Handle null parent (root message) case + if (message.parent === null) { + // No parent means this is likely a root node with no siblings + return { + message, + siblingIds: [messageId], + currentIndex: 0, + totalSiblings: 1 + }; + } + + const parentNode = nodeMap.get(message.parent); + if (!parentNode) { + // Parent not found - treat as single message + return { + message, + siblingIds: [messageId], + currentIndex: 0, + totalSiblings: 1 + }; + } + + // Get all sibling IDs (including self) + const siblingIds = parentNode.children; + + // Convert sibling message IDs to their corresponding leaf node IDs + // This allows navigation between different conversation branches + const siblingLeafIds = siblingIds.map((siblingId: string) => findLeafNode(messages, siblingId)); + + // Find current message's position among siblings + const currentIndex = siblingIds.indexOf(messageId); + + return { + message, + siblingIds: siblingLeafIds, + currentIndex, + totalSiblings: siblingIds.length + }; +} + +/** + * Creates a display-ready list of messages with sibling information for UI rendering. + * This is the main function used by chat components to render conversation branches. + * + * @param messages - All messages in the conversation + * @param leafNodeId - Current leaf node being viewed + * @returns Array of messages with sibling navigation info + */ +export function getMessageDisplayList( + messages: readonly DatabaseMessage[], + leafNodeId: string +): ChatMessageSiblingInfo[] { + // Get the current conversation path + const currentPath = filterByLeafNodeId(messages, leafNodeId, true); + const result: ChatMessageSiblingInfo[] = []; + + // Add sibling info for each message in the current path + for (const message of currentPath) { + if (message.type === 'root') { + continue; // Skip root messages in display + } + + const siblingInfo = getMessageSiblings(messages, message.id); + if (siblingInfo) { + result.push(siblingInfo); + } + } + + return result; +} + +/** + * Checks if a message has multiple siblings (indicating branching at that point). + * + * @param messages - All messages in the conversation + * @param messageId - The message to check + * @returns True if the message has siblings + */ +export function hasMessageSiblings( + messages: readonly DatabaseMessage[], + messageId: string +): boolean { + const siblingInfo = getMessageSiblings(messages, messageId); + return siblingInfo ? siblingInfo.totalSiblings > 1 : false; +} + +/** + * Gets the next sibling message ID for navigation. + * + * @param messages - All messages in the conversation + * @param messageId - Current message ID + * @returns Next sibling's leaf node ID, or null if at the end + */ +export function getNextSibling( + messages: readonly DatabaseMessage[], + messageId: string +): string | null { + const siblingInfo = getMessageSiblings(messages, messageId); + if (!siblingInfo || siblingInfo.currentIndex >= siblingInfo.totalSiblings - 1) { + return null; + } + + return siblingInfo.siblingIds[siblingInfo.currentIndex + 1]; +} + +/** + * Gets the previous sibling message ID for navigation. + * + * @param messages - All messages in the conversation + * @param messageId - Current message ID + * @returns Previous sibling's leaf node ID, or null if at the beginning + */ +export function getPreviousSibling( + messages: readonly DatabaseMessage[], + messageId: string +): string | null { + const siblingInfo = getMessageSiblings(messages, messageId); + if (!siblingInfo || siblingInfo.currentIndex <= 0) { + return null; + } + + return siblingInfo.siblingIds[siblingInfo.currentIndex - 1]; +} diff --git a/tools/server/webui/src/lib/utils/convert-files-to-extra.ts b/tools/server/webui/src/lib/utils/convert-files-to-extra.ts new file mode 100644 index 0000000000..70c6f772d9 --- /dev/null +++ b/tools/server/webui/src/lib/utils/convert-files-to-extra.ts @@ -0,0 +1,188 @@ +import { convertPDFToImage, convertPDFToText } from './pdf-processing'; +import { isSvgMimeType, svgBase64UrlToPngDataURL } from './svg-to-png'; +import { isWebpMimeType, webpBase64UrlToPngDataURL } from './webp-to-png'; +import { FileTypeCategory } from '$lib/enums/files'; +import { config, settingsStore } from '$lib/stores/settings.svelte'; +import { supportsVision } from '$lib/stores/server.svelte'; +import { getFileTypeCategory } from '$lib/utils/file-type'; +import { readFileAsText, isLikelyTextFile } from './text-files'; +import { toast } from 'svelte-sonner'; + +function readFileAsBase64(file: File): Promise { + return new Promise((resolve, reject) => { + const reader = new FileReader(); + + reader.onload = () => { + // Extract base64 data without the data URL prefix + const dataUrl = reader.result as string; + const base64 = dataUrl.split(',')[1]; + resolve(base64); + }; + + reader.onerror = () => reject(reader.error); + + reader.readAsDataURL(file); + }); +} + +export interface FileProcessingResult { + extras: DatabaseMessageExtra[]; + emptyFiles: string[]; +} + +export async function parseFilesToMessageExtras( + files: ChatUploadedFile[] +): Promise { + const extras: DatabaseMessageExtra[] = []; + const emptyFiles: string[] = []; + + for (const file of files) { + if (getFileTypeCategory(file.type) === FileTypeCategory.IMAGE) { + if (file.preview) { + let base64Url = file.preview; + + if (isSvgMimeType(file.type)) { + try { + base64Url = await svgBase64UrlToPngDataURL(base64Url); + } catch (error) { + console.error('Failed to convert SVG to PNG for database storage:', error); + } + } else if (isWebpMimeType(file.type)) { + try { + base64Url = await webpBase64UrlToPngDataURL(base64Url); + } catch (error) { + console.error('Failed to convert WebP to PNG for database storage:', error); + } + } + + extras.push({ + type: 'imageFile', + name: file.name, + base64Url + }); + } + } else if (getFileTypeCategory(file.type) === FileTypeCategory.AUDIO) { + // Process audio files (MP3 and WAV) + try { + const base64Data = await readFileAsBase64(file.file); + + extras.push({ + type: 'audioFile', + name: file.name, + base64Data: base64Data, + mimeType: file.type + }); + } catch (error) { + console.error(`Failed to process audio file ${file.name}:`, error); + } + } else if (getFileTypeCategory(file.type) === FileTypeCategory.PDF) { + try { + // Always get base64 data for preview functionality + const base64Data = await readFileAsBase64(file.file); + const currentConfig = config(); + const hasVisionSupport = supportsVision(); + + // Force PDF-to-text for non-vision models + let shouldProcessAsImages = Boolean(currentConfig.pdfAsImage) && hasVisionSupport; + + // If user had pdfAsImage enabled but model doesn't support vision, update setting and notify + if (currentConfig.pdfAsImage && !hasVisionSupport) { + console.log('Non-vision model detected: forcing PDF-to-text mode and updating settings'); + + // Update the setting in localStorage + settingsStore.updateConfig('pdfAsImage', false); + + // Show toast notification to user + toast.warning( + 'PDF setting changed: Non-vision model detected, PDFs will be processed as text instead of images.', + { + duration: 5000 + } + ); + + shouldProcessAsImages = false; + } + + if (shouldProcessAsImages) { + // Process PDF as images (only for vision models) + try { + const images = await convertPDFToImage(file.file); + + // Show success toast for PDF image processing + toast.success( + `PDF "${file.name}" processed as ${images.length} images for vision model.`, + { + duration: 3000 + } + ); + + extras.push({ + type: 'pdfFile', + name: file.name, + content: `PDF file with ${images.length} pages`, + images: images, + processedAsImages: true, + base64Data: base64Data + }); + } catch (imageError) { + console.warn( + `Failed to process PDF ${file.name} as images, falling back to text:`, + imageError + ); + + // Fallback to text processing + const content = await convertPDFToText(file.file); + + extras.push({ + type: 'pdfFile', + name: file.name, + content: content, + processedAsImages: false, + base64Data: base64Data + }); + } + } else { + // Process PDF as text (default or forced for non-vision models) + const content = await convertPDFToText(file.file); + + // Show success toast for PDF text processing + toast.success(`PDF "${file.name}" processed as text content.`, { + duration: 3000 + }); + + extras.push({ + type: 'pdfFile', + name: file.name, + content: content, + processedAsImages: false, + base64Data: base64Data + }); + } + } catch (error) { + console.error(`Failed to process PDF file ${file.name}:`, error); + } + } else { + try { + const content = await readFileAsText(file.file); + + // Check if file is empty + if (content.trim() === '') { + console.warn(`File ${file.name} is empty and will be skipped`); + emptyFiles.push(file.name); + } else if (isLikelyTextFile(content)) { + extras.push({ + type: 'textFile', + name: file.name, + content: content + }); + } else { + console.warn(`File ${file.name} appears to be binary and will be skipped`); + } + } catch (error) { + console.error(`Failed to read file ${file.name}:`, error); + } + } + } + + return { extras, emptyFiles }; +} diff --git a/tools/server/webui/src/lib/utils/copy.ts b/tools/server/webui/src/lib/utils/copy.ts new file mode 100644 index 0000000000..16a4bbd45d --- /dev/null +++ b/tools/server/webui/src/lib/utils/copy.ts @@ -0,0 +1,71 @@ +import { toast } from 'svelte-sonner'; + +/** + * Copy text to clipboard with toast notification + * Uses modern clipboard API when available, falls back to legacy method for non-secure contexts + * @param text - Text to copy to clipboard + * @param successMessage - Custom success message (optional) + * @param errorMessage - Custom error message (optional) + * @returns Promise - True if successful, false otherwise + */ +export async function copyToClipboard( + text: string, + successMessage = 'Copied to clipboard', + errorMessage = 'Failed to copy to clipboard' +): Promise { + try { + // Try modern clipboard API first (secure contexts only) + if (navigator.clipboard && navigator.clipboard.writeText) { + await navigator.clipboard.writeText(text); + toast.success(successMessage); + return true; + } + + // Fallback for non-secure contexts + const textArea = document.createElement('textarea'); + textArea.value = text; + textArea.style.position = 'fixed'; + textArea.style.left = '-999999px'; + textArea.style.top = '-999999px'; + document.body.appendChild(textArea); + textArea.focus(); + textArea.select(); + + const successful = document.execCommand('copy'); + document.body.removeChild(textArea); + + if (successful) { + toast.success(successMessage); + return true; + } else { + throw new Error('execCommand failed'); + } + } catch (error) { + console.error('Failed to copy to clipboard:', error); + toast.error(errorMessage); + return false; + } +} + +/** + * Copy code with HTML entity decoding and toast notification + * @param rawCode - Raw code string that may contain HTML entities + * @param successMessage - Custom success message (optional) + * @param errorMessage - Custom error message (optional) + * @returns Promise - True if successful, false otherwise + */ +export async function copyCodeToClipboard( + rawCode: string, + successMessage = 'Code copied to clipboard', + errorMessage = 'Failed to copy code' +): Promise { + // Decode HTML entities + const decodedCode = rawCode + .replace(/&/g, '&') + .replace(/</g, '<') + .replace(/>/g, '>') + .replace(/"/g, '"') + .replace(/'/g, "'"); + + return copyToClipboard(decodedCode, successMessage, errorMessage); +} diff --git a/tools/server/webui/src/lib/utils/file-preview.ts b/tools/server/webui/src/lib/utils/file-preview.ts new file mode 100644 index 0000000000..3f887ec535 --- /dev/null +++ b/tools/server/webui/src/lib/utils/file-preview.ts @@ -0,0 +1,32 @@ +/** + * Formats file size in bytes to human readable format + * @param bytes - File size in bytes + * @returns Formatted file size string + */ +export function formatFileSize(bytes: number): string { + if (bytes === 0) return '0 Bytes'; + + const k = 1024; + const sizes = ['Bytes', 'KB', 'MB', 'GB']; + const i = Math.floor(Math.log(bytes) / Math.log(k)); + + return parseFloat((bytes / Math.pow(k, i)).toFixed(2)) + ' ' + sizes[i]; +} + +/** + * Gets a display label for a file type + * @param fileType - The file type/mime type + * @returns Formatted file type label + */ +export function getFileTypeLabel(fileType: string): string { + return fileType.split('/').pop()?.toUpperCase() || 'FILE'; +} + +/** + * Truncates text content for preview display + * @param content - The text content to truncate + * @returns Truncated content with ellipsis if needed + */ +export function getPreviewText(content: string): string { + return content.length > 150 ? content.substring(0, 150) + '...' : content; +} diff --git a/tools/server/webui/src/lib/utils/file-type.ts b/tools/server/webui/src/lib/utils/file-type.ts new file mode 100644 index 0000000000..ccfc2a3de1 --- /dev/null +++ b/tools/server/webui/src/lib/utils/file-type.ts @@ -0,0 +1,81 @@ +import { + AUDIO_FILE_TYPES, + IMAGE_FILE_TYPES, + PDF_FILE_TYPES, + TEXT_FILE_TYPES +} from '$lib/constants/supported-file-types'; +import { FileTypeCategory } from '$lib/enums/files'; + +export function getFileTypeCategory(mimeType: string): FileTypeCategory | null { + if ( + Object.values(IMAGE_FILE_TYPES).some((type) => + (type.mimeTypes as readonly string[]).includes(mimeType) + ) + ) { + return FileTypeCategory.IMAGE; + } + + if ( + Object.values(AUDIO_FILE_TYPES).some((type) => + (type.mimeTypes as readonly string[]).includes(mimeType) + ) + ) { + return FileTypeCategory.AUDIO; + } + + if ( + Object.values(PDF_FILE_TYPES).some((type) => + (type.mimeTypes as readonly string[]).includes(mimeType) + ) + ) { + return FileTypeCategory.PDF; + } + + if ( + Object.values(TEXT_FILE_TYPES).some((type) => + (type.mimeTypes as readonly string[]).includes(mimeType) + ) + ) { + return FileTypeCategory.TEXT; + } + + return null; +} + +export function getFileTypeByExtension(filename: string): string | null { + const extension = filename.toLowerCase().substring(filename.lastIndexOf('.')); + + for (const [key, type] of Object.entries(IMAGE_FILE_TYPES)) { + if ((type.extensions as readonly string[]).includes(extension)) { + return `${FileTypeCategory.IMAGE}:${key}`; + } + } + + for (const [key, type] of Object.entries(AUDIO_FILE_TYPES)) { + if ((type.extensions as readonly string[]).includes(extension)) { + return `${FileTypeCategory.AUDIO}:${key}`; + } + } + + for (const [key, type] of Object.entries(PDF_FILE_TYPES)) { + if ((type.extensions as readonly string[]).includes(extension)) { + return `${FileTypeCategory.PDF}:${key}`; + } + } + + for (const [key, type] of Object.entries(TEXT_FILE_TYPES)) { + if ((type.extensions as readonly string[]).includes(extension)) { + return `${FileTypeCategory.TEXT}:${key}`; + } + } + + return null; +} + +export function isFileTypeSupported(filename: string, mimeType?: string): boolean { + if (mimeType && getFileTypeCategory(mimeType)) { + return true; + } + + return getFileTypeByExtension(filename) !== null; +} diff --git a/tools/server/webui/src/lib/utils/modality-file-validation.ts b/tools/server/webui/src/lib/utils/modality-file-validation.ts new file mode 100644 index 0000000000..c77bf88c3a --- /dev/null +++ b/tools/server/webui/src/lib/utils/modality-file-validation.ts @@ -0,0 +1,184 @@ +/** + * File validation utilities based on model modalities + * Ensures only compatible file types are processed based on model capabilities + */ + +import { getFileTypeCategory } from '$lib/utils/file-type'; +import { supportsVision, supportsAudio } from '$lib/stores/server.svelte'; +import { + FileExtensionAudio, + FileExtensionImage, + FileExtensionPdf, + FileExtensionText, + MimeTypeAudio, + MimeTypeImage, + MimeTypeApplication, + MimeTypeText, + FileTypeCategory +} from '$lib/enums/files'; + +/** + * Check if a file type is supported by the current model's modalities + * @param filename - The filename to check + * @param mimeType - The MIME type of the file + * @returns true if the file type is supported by the current model + */ +export function isFileTypeSupportedByModel(filename: string, mimeType?: string): boolean { + const category = mimeType ? getFileTypeCategory(mimeType) : null; + + // If we can't determine the category from MIME type, fall back to general support check + if (!category) { + // For unknown types, only allow if they might be text files + // This is a conservative approach for edge cases + return true; // Let the existing isFileTypeSupported handle this + } + + switch (category) { + case FileTypeCategory.TEXT: + // Text files are always supported + return true; + + case FileTypeCategory.PDF: + // PDFs are always supported (will be processed as text for non-vision models) + return true; + + case FileTypeCategory.IMAGE: + // Images require vision support + return supportsVision(); + + case FileTypeCategory.AUDIO: + // Audio files require audio support + return supportsAudio(); + + default: + // Unknown categories - be conservative and allow + return true; + } +} + +/** + * Filter files based on model modalities and return supported/unsupported lists + * @param files - Array of files to filter + * @returns Object with supportedFiles and unsupportedFiles arrays + */ +export function filterFilesByModalities(files: File[]): { + supportedFiles: File[]; + unsupportedFiles: File[]; + modalityReasons: Record; +} { + const supportedFiles: File[] = []; + const unsupportedFiles: File[] = []; + const modalityReasons: Record = {}; + + const hasVision = supportsVision(); + const hasAudio = supportsAudio(); + + for (const file of files) { + const category = getFileTypeCategory(file.type); + let isSupported = true; + let reason = ''; + + switch (category) { + case FileTypeCategory.IMAGE: + if (!hasVision) { + isSupported = false; + reason = 'Images require a vision-capable model'; + } + break; + + case FileTypeCategory.AUDIO: + if (!hasAudio) { + isSupported = false; + reason = 'Audio files require an audio-capable model'; + } + break; + + case FileTypeCategory.TEXT: + case FileTypeCategory.PDF: + // Always supported + break; + + default: + // For unknown types, check if it's a generally supported file type + // This handles edge cases and maintains backward compatibility + break; + } + + if (isSupported) { + supportedFiles.push(file); + } else { + unsupportedFiles.push(file); + modalityReasons[file.name] = reason; + } + } + + return { supportedFiles, unsupportedFiles, modalityReasons }; +} + +/** + * Generate a user-friendly error message for unsupported files + * @param unsupportedFiles - Array of unsupported files + * @param modalityReasons - Reasons why files are unsupported + * @returns Formatted error message + */ +export function generateModalityErrorMessage( + unsupportedFiles: File[], + modalityReasons: Record +): string { + if (unsupportedFiles.length === 0) return ''; + + const hasVision = supportsVision(); + const hasAudio = supportsAudio(); + + let message = ''; + + if (unsupportedFiles.length === 1) { + const file = unsupportedFiles[0]; + const reason = modalityReasons[file.name]; + message = `The file "${file.name}" cannot be uploaded: ${reason}.`; + } else { + const fileNames = unsupportedFiles.map((f) => f.name).join(', '); + message = `The following files cannot be uploaded: ${fileNames}.`; + } + + // Add helpful information about what is supported + const supportedTypes: string[] = ['text files', 'PDFs']; + if (hasVision) supportedTypes.push('images'); + if (hasAudio) supportedTypes.push('audio files'); + + message += ` This model supports: ${supportedTypes.join(', ')}.`; + + return message; +} + +/** + * Generate file input accept string based on current model modalities + * @returns Accept string for HTML file input element + */ +export function generateModalityAwareAcceptString(): string { + const hasVision = supportsVision(); + const hasAudio = supportsAudio(); + + const acceptedExtensions: string[] = []; + const acceptedMimeTypes: string[] = []; + + // Always include text files and PDFs + acceptedExtensions.push(...Object.values(FileExtensionText)); + acceptedMimeTypes.push(...Object.values(MimeTypeText)); + acceptedExtensions.push(...Object.values(FileExtensionPdf)); + acceptedMimeTypes.push(...Object.values(MimeTypeApplication)); + + // Include images only if vision is supported + if (hasVision) { + acceptedExtensions.push(...Object.values(FileExtensionImage)); + acceptedMimeTypes.push(...Object.values(MimeTypeImage)); + } + + // Include audio only if audio is supported + if (hasAudio) { + acceptedExtensions.push(...Object.values(FileExtensionAudio)); + acceptedMimeTypes.push(...Object.values(MimeTypeAudio)); + } + + return [...acceptedExtensions, ...acceptedMimeTypes].join(','); +} diff --git a/tools/server/webui/src/lib/utils/pdf-processing.ts b/tools/server/webui/src/lib/utils/pdf-processing.ts new file mode 100644 index 0000000000..49b0f34bae --- /dev/null +++ b/tools/server/webui/src/lib/utils/pdf-processing.ts @@ -0,0 +1,150 @@ +/** + * PDF processing utilities using PDF.js + * Handles PDF text extraction and image conversion in the browser + */ + +import { browser } from '$app/environment'; +import { MimeTypeApplication, MimeTypeImage } from '$lib/enums/files'; +import * as pdfjs from 'pdfjs-dist'; + +type TextContent = { + items: Array<{ str: string }>; +}; + +if (browser) { + // Import worker as text and create blob URL for inline bundling + import('pdfjs-dist/build/pdf.worker.min.mjs?raw') + .then((workerModule) => { + const workerBlob = new Blob([workerModule.default], { type: 'application/javascript' }); + pdfjs.GlobalWorkerOptions.workerSrc = URL.createObjectURL(workerBlob); + }) + .catch(() => { + console.warn('Failed to load PDF.js worker, PDF processing may not work'); + }); +} + +/** + * Convert a File object to ArrayBuffer for PDF.js processing + * @param file - The PDF file to convert + * @returns Promise resolving to the file's ArrayBuffer + */ +async function getFileAsBuffer(file: File): Promise { + return new Promise((resolve, reject) => { + const reader = new FileReader(); + reader.onload = (event) => { + if (event.target?.result) { + resolve(event.target.result as ArrayBuffer); + } else { + reject(new Error('Failed to read file.')); + } + }; + reader.onerror = () => { + reject(new Error('Failed to read file.')); + }; + reader.readAsArrayBuffer(file); + }); +} + +/** + * Extract text content from a PDF file + * @param file - The PDF file to process + * @returns Promise resolving to the extracted text content + */ +export async function convertPDFToText(file: File): Promise { + if (!browser) { + throw new Error('PDF processing is only available in the browser'); + } + + try { + const buffer = await getFileAsBuffer(file); + const pdf = await pdfjs.getDocument(buffer).promise; + const numPages = pdf.numPages; + + const textContentPromises: Promise[] = []; + + for (let i = 1; i <= numPages; i++) { + // eslint-disable-next-line @typescript-eslint/no-explicit-any + textContentPromises.push(pdf.getPage(i).then((page: any) => page.getTextContent())); + } + + const textContents = await Promise.all(textContentPromises); + const textItems = textContents.flatMap((textContent: TextContent) => + textContent.items.map((item) => item.str ?? '') + ); + + return textItems.join('\n'); + } catch (error) { + console.error('Error converting PDF to text:', error); + throw new Error( + `Failed to convert PDF to text: ${error instanceof Error ? error.message : 'Unknown error'}` + ); + } +} + +/** + * Convert PDF pages to PNG images as data URLs + * @param file - The PDF file to convert + * @param scale - Rendering scale factor (default: 1.5) + * @returns Promise resolving to array of PNG data URLs + */ +export async function convertPDFToImage(file: File, scale: number = 1.5): Promise { + if (!browser) { + throw new Error('PDF processing is only available in the browser'); + } + + try { + const buffer = await getFileAsBuffer(file); + const doc = await pdfjs.getDocument(buffer).promise; + const pages: Promise[] = []; + + for (let i = 1; i <= doc.numPages; i++) { + const page = await doc.getPage(i); + const viewport = page.getViewport({ scale }); + const canvas = document.createElement('canvas'); + const ctx = canvas.getContext('2d'); + + canvas.width = viewport.width; + canvas.height = viewport.height; + + if (!ctx) { + throw new Error('Failed to get 2D context from canvas'); + } + + const task = page.render({ + canvasContext: ctx, + viewport: viewport, + canvas: canvas + }); + pages.push( + task.promise.then(() => { + return canvas.toDataURL(MimeTypeImage.PNG); + }) + ); + } + + return await Promise.all(pages); + } catch (error) { + console.error('Error converting PDF to images:', error); + throw new Error( + `Failed to convert PDF to images: ${error instanceof Error ? error.message : 'Unknown error'}` + ); + } +} + +/** + * Check if a file is a PDF based on its MIME type + * @param file - The file to check + * @returns True if the file is a PDF + */ +export function isPdfFile(file: File): boolean { + return file.type === MimeTypeApplication.PDF; +} + +/** + * Check if a MIME type represents a PDF + * @param mimeType - The MIME type to check + * @returns True if the MIME type is application/pdf + */ +export function isApplicationMimeType(mimeType: string): boolean { + return mimeType === MimeTypeApplication.PDF; +} diff --git a/tools/server/webui/src/lib/utils/process-uploaded-files.ts b/tools/server/webui/src/lib/utils/process-uploaded-files.ts new file mode 100644 index 0000000000..3fb0a9d1a9 --- /dev/null +++ b/tools/server/webui/src/lib/utils/process-uploaded-files.ts @@ -0,0 +1,130 @@ +import { isSvgMimeType, svgBase64UrlToPngDataURL } from './svg-to-png'; +import { isTextFileByName } from './text-files'; +import { isWebpMimeType, webpBase64UrlToPngDataURL } from './webp-to-png'; +import { FileTypeCategory } from '$lib/enums/files'; +import { getFileTypeCategory } from '$lib/utils/file-type'; +import { supportsVision } from '$lib/stores/server.svelte'; +import { settingsStore } from '$lib/stores/settings.svelte'; +import { toast } from 'svelte-sonner'; + +/** + * Read a file as a data URL (base64 encoded) + * @param file - The file to read + * @returns Promise resolving to the data URL string + */ +function readFileAsDataURL(file: File): Promise { + return new Promise((resolve, reject) => { + const reader = new FileReader(); + reader.onload = () => resolve(reader.result as string); + reader.onerror = () => reject(reader.error); + reader.readAsDataURL(file); + }); +} + +/** + * Read a file as UTF-8 text + * @param file - The file to read + * @returns Promise resolving to the text content + */ +function readFileAsUTF8(file: File): Promise { + return new Promise((resolve, reject) => { + const reader = new FileReader(); + reader.onload = () => resolve(reader.result as string); + reader.onerror = () => reject(reader.error); + reader.readAsText(file); + }); +} + +/** + * Process uploaded files into ChatUploadedFile format with previews and content + * + * This function processes various file types and generates appropriate previews: + * - Images: Base64 data URLs with format normalization (SVG/WebP → PNG) + * - Text files: UTF-8 content extraction + * - PDFs: Metadata only (processed later in conversion pipeline) + * - Audio: Base64 data URLs for preview + * + * @param files - Array of File objects to process + * @returns Promise resolving to array of ChatUploadedFile objects + */ +export async function processFilesToChatUploaded(files: File[]): Promise { + const results: ChatUploadedFile[] = []; + + for (const file of files) { + const id = Date.now().toString() + Math.random().toString(36).substr(2, 9); + const base: ChatUploadedFile = { + id, + name: file.name, + size: file.size, + type: file.type, + file + }; + + try { + if (getFileTypeCategory(file.type) === FileTypeCategory.IMAGE) { + let preview = await readFileAsDataURL(file); + + // Normalize SVG and WebP to PNG in previews + if (isSvgMimeType(file.type)) { + try { + preview = await svgBase64UrlToPngDataURL(preview); + } catch (err) { + console.error('Failed to convert SVG to PNG:', err); + } + } else if (isWebpMimeType(file.type)) { + try { + preview = await webpBase64UrlToPngDataURL(preview); + } catch (err) { + console.error('Failed to convert WebP to PNG:', err); + } + } + + results.push({ ...base, preview }); + } else if ( + getFileTypeCategory(file.type) === FileTypeCategory.TEXT || + isTextFileByName(file.name) + ) { + try { + const textContent = await readFileAsUTF8(file); + results.push({ ...base, textContent }); + } catch (err) { + console.warn('Failed to read text file, adding without content:', err); + results.push(base); + } + } else if (getFileTypeCategory(file.type) === FileTypeCategory.PDF) { + // PDFs handled later when building extras; keep metadata only + results.push(base); + + // Show suggestion toast if vision model is available but PDF as image is disabled + const hasVisionSupport = supportsVision(); + const currentConfig = settingsStore.config; + if (hasVisionSupport && !currentConfig.pdfAsImage) { + toast.info(`You can enable parsing PDF as images with vision models.`, { + duration: 8000, + action: { + label: 'Enable PDF as Images', + onClick: () => { + settingsStore.updateConfig('pdfAsImage', true); + toast.success('PDF parsing as images enabled!', { + duration: 3000 + }); + } + } + }); + } + } else if (getFileTypeCategory(file.type) === FileTypeCategory.AUDIO) { + // Generate preview URL for audio files + const preview = await readFileAsDataURL(file); + results.push({ ...base, preview }); + } else { + // Other files: add as-is + results.push(base); + } + } catch (error) { + console.error('Error processing file', file.name, error); + results.push(base); + } + } + + return results; +} diff --git a/tools/server/webui/src/lib/utils/svg-to-png.ts b/tools/server/webui/src/lib/utils/svg-to-png.ts new file mode 100644 index 0000000000..4ab4efe7b9 --- /dev/null +++ b/tools/server/webui/src/lib/utils/svg-to-png.ts @@ -0,0 +1,71 @@ +import { MimeTypeImage } from '$lib/enums/files'; + +/** + * Convert an SVG base64 data URL to a PNG data URL + * @param base64UrlSvg - The SVG base64 data URL to convert + * @param backgroundColor - Background color for the PNG (default: 'white') + * @returns Promise resolving to PNG data URL + */ +export function svgBase64UrlToPngDataURL( + base64UrlSvg: string, + backgroundColor: string = 'white' +): Promise { + return new Promise((resolve, reject) => { + try { + const img = new Image(); + + img.onload = () => { + const canvas = document.createElement('canvas'); + const ctx = canvas.getContext('2d'); + + if (!ctx) { + reject(new Error('Failed to get 2D canvas context.')); + return; + } + + const targetWidth = img.naturalWidth || 300; + const targetHeight = img.naturalHeight || 300; + + canvas.width = targetWidth; + canvas.height = targetHeight; + + if (backgroundColor) { + ctx.fillStyle = backgroundColor; + ctx.fillRect(0, 0, canvas.width, canvas.height); + } + ctx.drawImage(img, 0, 0, targetWidth, targetHeight); + + resolve(canvas.toDataURL(MimeTypeImage.PNG)); + }; + + img.onerror = () => { + reject(new Error('Failed to load SVG image. Ensure the SVG data is valid.')); + }; + + img.src = base64UrlSvg; + } catch (error) { + const message = error instanceof Error ? error.message : String(error); + const errorMessage = `Error converting SVG to PNG: ${message}`; + console.error(errorMessage, error); + reject(new Error(errorMessage)); + } + }); +} + +/** + * Check if a file is an SVG based on its MIME type + * @param file - The file to check + * @returns True if the file is an SVG + */ +export function isSvgFile(file: File): boolean { + return file.type === MimeTypeImage.SVG; +} + +/** + * Check if a MIME type represents an SVG + * @param mimeType - The MIME type to check + * @returns True if the MIME type is image/svg+xml + */ +export function isSvgMimeType(mimeType: string): boolean { + return mimeType === MimeTypeImage.SVG; +} diff --git a/tools/server/webui/src/lib/utils/text-files.ts b/tools/server/webui/src/lib/utils/text-files.ts new file mode 100644 index 0000000000..496f5c79e4 --- /dev/null +++ b/tools/server/webui/src/lib/utils/text-files.ts @@ -0,0 +1,83 @@ +/** + * Text file processing utilities + * Handles text file detection, reading, and validation + */ + +import { FileExtensionText } from '$lib/enums/files'; + +/** + * Check if a filename indicates a text file based on its extension + * @param filename - The filename to check + * @returns True if the filename has a recognized text file extension + */ +export function isTextFileByName(filename: string): boolean { + const textExtensions = Object.values(FileExtensionText); + + return textExtensions.some((ext: FileExtensionText) => filename.toLowerCase().endsWith(ext)); +} + +/** + * Read a file's content as text + * @param file - The file to read + * @returns Promise resolving to the file's text content + */ +export async function readFileAsText(file: File): Promise { + return new Promise((resolve, reject) => { + const reader = new FileReader(); + + reader.onload = (event) => { + if (event.target?.result !== null && event.target?.result !== undefined) { + resolve(event.target.result as string); + } else { + reject(new Error('Failed to read file')); + } + }; + + reader.onerror = () => reject(new Error('File reading error')); + + reader.readAsText(file); + }); +} + +/** + * Heuristic check to determine if content is likely from a text file + * Detects binary files by counting suspicious characters and null bytes + * @param content - The file content to analyze + * @returns True if the content appears to be text-based + */ +export function isLikelyTextFile(content: string): boolean { + if (!content) return true; + + const sample = content.substring(0, 1000); + + let suspiciousCount = 0; + let nullCount = 0; + + for (let i = 0; i < sample.length; i++) { + const charCode = sample.charCodeAt(i); + + // Count null bytes + if (charCode === 0) { + nullCount++; + suspiciousCount++; + + continue; + } + + // Count suspicious control characters (excluding common ones like tab, newline, carriage return) + if (charCode < 32 && charCode !== 9 && charCode !== 10 && charCode !== 13) { + suspiciousCount++; + } + + // Count replacement characters (indicates encoding issues) + if (charCode === 0xfffd) { + suspiciousCount++; + } + } + + // Reject if too many null bytes or suspicious characters + if (nullCount > 2) return false; + if (suspiciousCount / sample.length > 0.1) return false; + + return true; +} diff --git a/tools/server/webui/src/lib/utils/thinking.ts b/tools/server/webui/src/lib/utils/thinking.ts new file mode 100644 index 0000000000..11ce871231 --- /dev/null +++ b/tools/server/webui/src/lib/utils/thinking.ts @@ -0,0 +1,90 @@ +/** + * Parses thinking content from a message that may contain tags + * Returns an object with thinking content and cleaned message content + * Handles both complete ... blocks and incomplete blocks (streaming) + * @param content - The message content to parse + * @returns An object containing the extracted thinking content and the cleaned message content + */ +export function parseThinkingContent(content: string): { + thinking: string | null; + cleanContent: string; +} { + const incompleteMatch = content.includes('') && !content.includes(''); + + if (incompleteMatch) { + // Remove the entire ... part from clean content + const cleanContent = content.split('')?.[1]?.trim(); + // Extract everything after as thinking content + const thinkingContent = content.split('')?.[1]?.trim(); + + return { + cleanContent, + thinking: thinkingContent + }; + } + + const completeMatch = content.includes(''); + + if (completeMatch) { + return { + thinking: content.split('')?.[0]?.trim(), + cleanContent: content.split('')?.[1]?.trim() + }; + } + + return { + thinking: null, + cleanContent: content + }; +} + +/** + * Checks if content contains an opening tag (for streaming) + * @param content - The message content to check + * @returns True if the content contains an opening tag + */ +export function hasThinkingStart(content: string): boolean { + return content.includes('') || content.includes('<|channel|>analysis'); +} + +/** + * Checks if content contains a closing tag (for streaming) + * @param content - The message content to check + * @returns True if the content contains a closing tag + */ +export function hasThinkingEnd(content: string): boolean { + return content.includes(''); +} + +/** + * Extracts partial thinking content during streaming + * Used when we have but not yet + * @param content - The message content to extract partial thinking from + * @returns An object containing the extracted partial thinking content and the remaining content + */ +export function extractPartialThinking(content: string): { + thinking: string | null; + remainingContent: string; +} { + const startIndex = content.indexOf(''); + if (startIndex === -1) { + return { thinking: null, remainingContent: content }; + } + + const endIndex = content.indexOf(''); + if (endIndex === -1) { + // Still streaming thinking content + const thinkingStart = startIndex + ''.length; + return { + thinking: content.substring(thinkingStart), + remainingContent: content.substring(0, startIndex) + }; + } + + // Complete thinking block found + const parsed = parseThinkingContent(content); + return { + thinking: parsed.thinking, + remainingContent: parsed.cleanContent + }; +} diff --git a/tools/server/webui/src/lib/utils/webp-to-png.ts b/tools/server/webui/src/lib/utils/webp-to-png.ts new file mode 100644 index 0000000000..16e7a79c47 --- /dev/null +++ b/tools/server/webui/src/lib/utils/webp-to-png.ts @@ -0,0 +1,73 @@ +import { FileExtensionImage, MimeTypeImage } from '$lib/enums/files'; + +/** + * Convert a WebP base64 data URL to a PNG data URL + * @param base64UrlWebp - The WebP base64 data URL to convert + * @param backgroundColor - Background color for the PNG (default: 'white') + * @returns Promise resolving to PNG data URL + */ +export function webpBase64UrlToPngDataURL( + base64UrlWebp: string, + backgroundColor: string = 'white' +): Promise { + return new Promise((resolve, reject) => { + try { + const img = new Image(); + + img.onload = () => { + const canvas = document.createElement('canvas'); + const ctx = canvas.getContext('2d'); + + if (!ctx) { + reject(new Error('Failed to get 2D canvas context.')); + return; + } + + const targetWidth = img.naturalWidth || 300; + const targetHeight = img.naturalHeight || 300; + + canvas.width = targetWidth; + canvas.height = targetHeight; + + if (backgroundColor) { + ctx.fillStyle = backgroundColor; + ctx.fillRect(0, 0, canvas.width, canvas.height); + } + ctx.drawImage(img, 0, 0, targetWidth, targetHeight); + + resolve(canvas.toDataURL(MimeTypeImage.PNG)); + }; + + img.onerror = () => { + reject(new Error('Failed to load WebP image. Ensure the WebP data is valid.')); + }; + + img.src = base64UrlWebp; + } catch (error) { + const message = error instanceof Error ? error.message : String(error); + const errorMessage = `Error converting WebP to PNG: ${message}`; + console.error(errorMessage, error); + reject(new Error(errorMessage)); + } + }); +} + +/** + * Check if a file is a WebP based on its MIME type + * @param file - The file to check + * @returns True if the file is a WebP + */ +export function isWebpFile(file: File): boolean { + return ( + file.type === MimeTypeImage.WEBP || file.name.toLowerCase().endsWith(FileExtensionImage.WEBP) + ); +} + +/** + * Check if a MIME type represents a WebP + * @param mimeType - The MIME type to check + * @returns True if the MIME type is image/webp + */ +export function isWebpMimeType(mimeType: string): boolean { + return mimeType === MimeTypeImage.WEBP; +} diff --git a/tools/server/webui/src/main.tsx b/tools/server/webui/src/main.tsx deleted file mode 100644 index 631e96a792..0000000000 --- a/tools/server/webui/src/main.tsx +++ /dev/null @@ -1,10 +0,0 @@ -import { StrictMode } from 'react'; -import { createRoot } from 'react-dom/client'; -import './index.scss'; -import App from './App.tsx'; - -createRoot(document.getElementById('root')!).render( - - - -); diff --git a/tools/server/webui/src/routes/+error.svelte b/tools/server/webui/src/routes/+error.svelte new file mode 100644 index 0000000000..8ec48dc01f --- /dev/null +++ b/tools/server/webui/src/routes/+error.svelte @@ -0,0 +1,70 @@ + + + + Error {status} - WebUI + + +{#if isApiKeyError} + +{:else} + +
+
+
+
+ + + +
+

Error {status}

+

+ {error?.message || 'Something went wrong'} +

+
+ +
+
+{/if} diff --git a/tools/server/webui/src/routes/+layout.svelte b/tools/server/webui/src/routes/+layout.svelte new file mode 100644 index 0000000000..58749b9fe5 --- /dev/null +++ b/tools/server/webui/src/routes/+layout.svelte @@ -0,0 +1,176 @@ + + + + + + + + + + + +
+ + + + + + + + {@render children?.()} + +
+ + + diff --git a/tools/server/webui/src/routes/+layout.ts b/tools/server/webui/src/routes/+layout.ts new file mode 100644 index 0000000000..2d3c0a037c --- /dev/null +++ b/tools/server/webui/src/routes/+layout.ts @@ -0,0 +1,3 @@ +export const csr = true; +export const prerender = false; +export const ssr = false; diff --git a/tools/server/webui/src/routes/+page.svelte b/tools/server/webui/src/routes/+page.svelte new file mode 100644 index 0000000000..2cd2d5c373 --- /dev/null +++ b/tools/server/webui/src/routes/+page.svelte @@ -0,0 +1,19 @@ + + + + llama.cpp - AI Chat Interface + + + diff --git a/tools/server/webui/src/routes/+page.ts b/tools/server/webui/src/routes/+page.ts new file mode 100644 index 0000000000..a984c00457 --- /dev/null +++ b/tools/server/webui/src/routes/+page.ts @@ -0,0 +1,6 @@ +import type { PageLoad } from './$types'; +import { validateApiKey } from '$lib/utils/api-key-validation'; + +export const load: PageLoad = async ({ fetch }) => { + await validateApiKey(fetch); +}; diff --git a/tools/server/webui/src/routes/chat/[id]/+page.svelte b/tools/server/webui/src/routes/chat/[id]/+page.svelte new file mode 100644 index 0000000000..705c0bd927 --- /dev/null +++ b/tools/server/webui/src/routes/chat/[id]/+page.svelte @@ -0,0 +1,81 @@ + + + + {activeConversation()?.name || 'Chat'} - llama.cpp + + + diff --git a/tools/server/webui/src/routes/chat/[id]/+page.ts b/tools/server/webui/src/routes/chat/[id]/+page.ts new file mode 100644 index 0000000000..a984c00457 --- /dev/null +++ b/tools/server/webui/src/routes/chat/[id]/+page.ts @@ -0,0 +1,6 @@ +import type { PageLoad } from './$types'; +import { validateApiKey } from '$lib/utils/api-key-validation'; + +export const load: PageLoad = async ({ fetch }) => { + await validateApiKey(fetch); +}; diff --git a/tools/server/webui/src/routes/page.svelte.test.ts b/tools/server/webui/src/routes/page.svelte.test.ts new file mode 100644 index 0000000000..d8db7cda1e --- /dev/null +++ b/tools/server/webui/src/routes/page.svelte.test.ts @@ -0,0 +1,11 @@ +import { describe, it } from 'vitest'; +import { render } from 'vitest-browser-svelte'; +import Page from './+page.svelte'; + +describe('/+page.svelte', () => { + it('should render page', async () => { + render(Page); + + // todo - add tests + }); +}); diff --git a/tools/server/webui/src/stories/ChatForm.stories.svelte b/tools/server/webui/src/stories/ChatForm.stories.svelte new file mode 100644 index 0000000000..6a0fc08701 --- /dev/null +++ b/tools/server/webui/src/stories/ChatForm.stories.svelte @@ -0,0 +1,182 @@ + + + { + mockServerProps(mockConfigs.noModalities); + + const textarea = await canvas.findByRole('textbox'); + const submitButton = await canvas.findByRole('button', { name: 'Send' }); + + // Expect the input to be focused after the component is mounted + await expect(textarea).toHaveFocus(); + + // Expect the submit button to be disabled + await expect(submitButton).toBeDisabled(); + + const text = 'What is the meaning of life?'; + + await userEvent.clear(textarea); + await userEvent.type(textarea, text); + + await expect(textarea).toHaveValue(text); + + const fileInput = document.querySelector('input[type="file"]'); + const acceptAttr = fileInput?.getAttribute('accept'); + await expect(fileInput).toHaveAttribute('accept'); + await expect(acceptAttr).not.toContain('image/'); + await expect(acceptAttr).not.toContain('audio/'); + + const fileUploadButton = canvas.getByText('Attach files'); + + await userEvent.click(fileUploadButton); + + const recordButton = canvas.getAllByRole('button', { name: 'Start recording' })[1]; + const imagesButton = document.querySelector('.images-button'); + const audioButton = document.querySelector('.audio-button'); + + await expect(recordButton).toBeDisabled(); + await expect(imagesButton).toHaveAttribute('data-disabled'); + await expect(audioButton).toHaveAttribute('data-disabled'); + }} +/> + + + + { + mockServerProps(mockConfigs.visionOnly); + + // Test initial file input state (should accept images but not audio) + const fileInput = document.querySelector('input[type="file"]'); + const acceptAttr = fileInput?.getAttribute('accept'); + console.log('Vision modality accept attr:', acceptAttr); + + const fileUploadButton = canvas.getByText('Attach files'); + await userEvent.click(fileUploadButton); + + // Test that record button is disabled (no audio support) + const recordButton = canvas.getAllByRole('button', { name: 'Start recording' })[1]; + await expect(recordButton).toBeDisabled(); + + // Test that Images button is enabled (vision support) + const imagesButton = document.querySelector('.images-button'); + await expect(imagesButton).not.toHaveAttribute('data-disabled'); + + // Test that Audio button is disabled (no audio support) + const audioButton = document.querySelector('.audio-button'); + await expect(audioButton).toHaveAttribute('data-disabled'); + + // Fix for dropdown menu side effect + const body = document.querySelector('body'); + if (body) body.style.pointerEvents = 'all'; + + console.log('✅ Vision modality: Images enabled, Audio/Recording disabled'); + }} +/> + + { + mockServerProps(mockConfigs.audioOnly); + + // Test initial file input state (should accept audio but not images) + const fileInput = document.querySelector('input[type="file"]'); + const acceptAttr = fileInput?.getAttribute('accept'); + console.log('Audio modality accept attr:', acceptAttr); + + const fileUploadButton = canvas.getByText('Attach files'); + await userEvent.click(fileUploadButton); + + // Test that record button is enabled (audio support) + const recordButton = canvas.getAllByRole('button', { name: 'Start recording' })[1]; + await expect(recordButton).not.toBeDisabled(); + + // Test that Images button is disabled (no vision support) + const imagesButton = document.querySelector('.images-button'); + await expect(imagesButton).toHaveAttribute('data-disabled'); + + // Test that Audio button is enabled (audio support) + const audioButton = document.querySelector('.audio-button'); + await expect(audioButton).not.toHaveAttribute('data-disabled'); + + // Fix for dropdown menu side effect + const body = document.querySelector('body'); + if (body) body.style.pointerEvents = 'all'; + + console.log('✅ Audio modality: Audio/Recording enabled, Images disabled'); + }} +/> + + { + mockServerProps(mockConfigs.bothModalities); + + const jpgAttachment = canvas.getByAltText('1.jpg'); + const svgAttachment = canvas.getByAltText('hf-logo.svg'); + const pdfFileExtension = canvas.getByText('PDF'); + const pdfAttachment = canvas.getByText('example.pdf'); + const pdfSize = canvas.getByText('342.82 KB'); + + await expect(jpgAttachment).toBeInTheDocument(); + await expect(jpgAttachment).toHaveAttribute('src', jpgAsset); + + await expect(svgAttachment).toBeInTheDocument(); + await expect(svgAttachment).toHaveAttribute('src', svgAsset); + + await expect(pdfFileExtension).toBeInTheDocument(); + await expect(pdfAttachment).toBeInTheDocument(); + await expect(pdfSize).toBeInTheDocument(); + }} +/> diff --git a/tools/server/webui/src/stories/ChatMessage.stories.svelte b/tools/server/webui/src/stories/ChatMessage.stories.svelte new file mode 100644 index 0000000000..f9d7d5358c --- /dev/null +++ b/tools/server/webui/src/stories/ChatMessage.stories.svelte @@ -0,0 +1,146 @@ + + + + + + + { + // Phase 1: Stream reasoning content in chunks + let reasoningText = + 'I need to think about this carefully. Let me break down the problem:\n\n1. The user is asking for help with something complex\n2. I should provide a thorough and helpful response\n3. I need to consider multiple approaches\n4. The best solution would be to explain step by step\n\nThis approach will ensure clarity and understanding.'; + + let reasoningChunk = 'I'; + let i = 0; + while (i < reasoningText.length) { + const chunkSize = Math.floor(Math.random() * 5) + 3; // Random 3-7 characters + const chunk = reasoningText.slice(i, i + chunkSize); + reasoningChunk += chunk; + + // Update the reactive state directly + streamingMessage.thinking = reasoningChunk; + + i += chunkSize; + await new Promise((resolve) => setTimeout(resolve, 50)); + } + + const regularText = + "Based on my analysis, here's the solution:\n\n**Step 1:** First, we need to understand the requirements clearly.\n\n**Step 2:** Then we can implement the solution systematically.\n\n**Step 3:** Finally, we test and validate the results.\n\nThis approach ensures we cover all aspects of the problem effectively."; + + let contentChunk = ''; + i = 0; + + while (i < regularText.length) { + const chunkSize = Math.floor(Math.random() * 5) + 3; // Random 3-7 characters + const chunk = regularText.slice(i, i + chunkSize); + contentChunk += chunk; + + // Update the reactive state directly + streamingMessage.content = contentChunk; + + i += chunkSize; + await new Promise((resolve) => setTimeout(resolve, 50)); + } + + streamingMessage.timestamp = Date.now(); + }} +> +
+ +
+ + + { + // Import the chat store to simulate loading state + const { chatStore } = await import('$lib/stores/chat.svelte'); + + // Set loading state to true to trigger the processing UI + chatStore.isLoading = true; + + // Simulate the processing state hook behavior + // This will show the "Generating..." text and parameter details + await new Promise(resolve => setTimeout(resolve, 100)); + }} +/> diff --git a/tools/server/webui/src/stories/ChatSettingsDialog.stories.svelte b/tools/server/webui/src/stories/ChatSettingsDialog.stories.svelte new file mode 100644 index 0000000000..1e53f70708 --- /dev/null +++ b/tools/server/webui/src/stories/ChatSettingsDialog.stories.svelte @@ -0,0 +1,26 @@ + + + + + diff --git a/tools/server/webui/src/stories/ChatSidebar.stories.svelte b/tools/server/webui/src/stories/ChatSidebar.stories.svelte new file mode 100644 index 0000000000..1b1754f9d3 --- /dev/null +++ b/tools/server/webui/src/stories/ChatSidebar.stories.svelte @@ -0,0 +1,97 @@ + + + { + const { chatStore } = await import('$lib/stores/chat.svelte'); + + waitFor(() => setTimeout(() => { + chatStore.conversations = mockConversations; + }, 0)); + }} +> +
+ +
+ + + { + const { chatStore } = await import('$lib/stores/chat.svelte'); + + waitFor(() => setTimeout(() => { + chatStore.conversations = mockConversations; + }, 0)); + + const searchTrigger = screen.getByText('Search conversations'); + userEvent.click(searchTrigger); + }} +> +
+ +
+ + + { + // Mock empty conversations store + const { chatStore } = await import('$lib/stores/chat.svelte'); + chatStore.conversations = []; + }} +> +
+ +
+ diff --git a/tools/server/webui/src/stories/Introduction.mdx b/tools/server/webui/src/stories/Introduction.mdx new file mode 100644 index 0000000000..19d0b28daa --- /dev/null +++ b/tools/server/webui/src/stories/Introduction.mdx @@ -0,0 +1,44 @@ +import { Meta } from '@storybook/addon-docs/blocks'; + + + +# llama.cpp Web UI + +Welcome to the **llama.cpp Web UI** component library! This Storybook showcases the components used in the modern web interface for the llama.cpp server. + +## 🚀 About This Project + +WebUI is a modern web interface for the llama.cpp server, built with SvelteKit and ShadCN UI. Features include: + +- **Real-time chat conversations** with AI assistants +- **Multi-conversation management** with persistent storage +- **Advanced parameter tuning** for model behavior +- **File upload support** for multimodal interactions +- **Responsive design** that works on desktop and mobile + +## 🎨 Design System + +The UI is built using: + +- **SvelteKit** - Modern web framework with excellent performance +- **Tailwind CSS** - Utility-first CSS framework for rapid styling +- **ShadCN/UI** - High-quality, accessible component library +- **Lucide Icons** - Beautiful, consistent icon set + +## 🔧 Development + +This Storybook serves as both documentation and a development environment for the UI components. Each story demonstrates: + +- **Component variations** - Different states and configurations +- **Interactive examples** - Live components you can interact with +- **Usage patterns** - How components work together +- **Styling consistency** - Unified design language + +## 🚀 Getting Started + +To explore the components: + +1. **Browse the sidebar** to see all available components +2. **Click on stories** to see different component states +3. **Use the controls panel** to interact with component props +4. **Check the docs tab** for detailed component information diff --git a/tools/server/webui/src/stories/MarkdownContent.stories.svelte b/tools/server/webui/src/stories/MarkdownContent.stories.svelte new file mode 100644 index 0000000000..c8294ba0d9 --- /dev/null +++ b/tools/server/webui/src/stories/MarkdownContent.stories.svelte @@ -0,0 +1,131 @@ + + + + + + + + + + + + + + + + + { + const { expect } = await import('storybook/internal/test'); + + // Wait for component to render + await new Promise(resolve => setTimeout(resolve, 100)); + + // Find all links in the rendered content + const links = canvasElement.querySelectorAll('a[href]'); + + // Test that we have the expected number of links + expect(links.length).toBeGreaterThan(0); + + // Test each link for proper attributes + links.forEach((link) => { + const href = link.getAttribute('href'); + + // Test that external links have proper security attributes + if (href && (href.startsWith('http://') || href.startsWith('https://'))) { + expect(link.getAttribute('target')).toBe('_blank'); + expect(link.getAttribute('rel')).toBe('noopener noreferrer'); + } + }); + + // Test specific links exist + const hugginFaceLink = Array.from(links).find(link => + link.getAttribute('href') === 'https://huggingface.co' + ); + expect(hugginFaceLink).toBeTruthy(); + expect(hugginFaceLink?.textContent).toBe('Hugging Face Homepage'); + + const githubLink = Array.from(links).find(link => + link.getAttribute('href') === 'https://github.com/ggml-org/llama.cpp' + ); + expect(githubLink).toBeTruthy(); + expect(githubLink?.textContent).toBe('GitHub Repository'); + + const openaiLink = Array.from(links).find(link => + link.getAttribute('href') === 'https://openai.com' + ); + expect(openaiLink).toBeTruthy(); + expect(openaiLink?.textContent).toBe('OpenAI Website'); + + const googleLink = Array.from(links).find(link => + link.getAttribute('href') === 'https://www.google.com' + ); + expect(googleLink).toBeTruthy(); + expect(googleLink?.textContent).toBe('Google Search'); + + // Test inline links (auto-linked URLs) + const exampleLink = Array.from(links).find(link => + link.getAttribute('href') === 'https://example.com' + ); + expect(exampleLink).toBeTruthy(); + + const pythonDocsLink = Array.from(links).find(link => + link.getAttribute('href') === 'https://docs.python.org' + ); + expect(pythonDocsLink).toBeTruthy(); + + console.log(`✅ URL Links test passed - Found ${links.length} links with proper attributes`); + }} +/> diff --git a/tools/server/webui/src/stories/fixtures/ai-tutorial.ts b/tools/server/webui/src/stories/fixtures/ai-tutorial.ts new file mode 100644 index 0000000000..b3b1c24835 --- /dev/null +++ b/tools/server/webui/src/stories/fixtures/ai-tutorial.ts @@ -0,0 +1,164 @@ +// AI Assistant Tutorial Response +export const AI_TUTORIAL_MD = String.raw` +# Building a Modern Chat Application with SvelteKit + +I'll help you create a **production-ready chat application** using SvelteKit, TypeScript, and WebSockets. This implementation includes real-time messaging, user authentication, and message persistence. + +## 🚀 Quick Start + +First, let's set up the project: + +${'```'}bash +npm create svelte@latest chat-app +cd chat-app +npm install +npm install socket.io socket.io-client +npm install @prisma/client prisma +npm run dev +${'```'} + +## 📁 Project Structure + +${'```'} +chat-app/ +├── src/ +│ ├── routes/ +│ │ ├── +layout.svelte +│ │ ├── +page.svelte +│ │ └── api/ +│ │ └── socket/+server.ts +│ ├── lib/ +│ │ ├── components/ +│ │ │ ├── ChatMessage.svelte +│ │ │ └── ChatInput.svelte +│ │ └── stores/ +│ │ └── chat.ts +│ └── app.html +├── prisma/ +│ └── schema.prisma +└── package.json +${'```'} + +## 💻 Implementation + +### WebSocket Server + +${'```'}typescript +// src/lib/server/socket.ts +import { Server } from 'socket.io'; +import type { ViteDevServer } from 'vite'; + +export function initializeSocketIO(server: ViteDevServer) { + const io = new Server(server.httpServer || server, { + cors: { + origin: process.env.ORIGIN || 'http://localhost:5173', + credentials: true + } + }); + + io.on('connection', (socket) => { + console.log('User connected:', socket.id); + + socket.on('message', async (data) => { + // Broadcast to all clients + io.emit('new-message', { + id: crypto.randomUUID(), + userId: socket.id, + content: data.content, + timestamp: new Date().toISOString() + }); + }); + + socket.on('disconnect', () => { + console.log('User disconnected:', socket.id); + }); + }); + + return io; +} +${'```'} + +### Client Store + +${'```'}typescript +// src/lib/stores/chat.ts +import { writable } from 'svelte/store'; +import io from 'socket.io-client'; + +export interface Message { + id: string; + userId: string; + content: string; + timestamp: string; +} + +function createChatStore() { + const { subscribe, update } = writable([]); + let socket: ReturnType; + + return { + subscribe, + connect: () => { + socket = io('http://localhost:5173'); + + socket.on('new-message', (message: Message) => { + update(messages => [...messages, message]); + }); + }, + sendMessage: (content: string) => { + if (socket && content.trim()) { + socket.emit('message', { content }); + } + } + }; +} + +export const chatStore = createChatStore(); +${'```'} + +## 🎯 Key Features + +✅ **Real-time messaging** with WebSockets +✅ **Message persistence** using Prisma + PostgreSQL +✅ **Type-safe** with TypeScript +✅ **Responsive UI** for all devices +✅ **Auto-reconnection** on connection loss + +## 📊 Performance Metrics + +| Metric | Value | +|--------|-------| +| **Message Latency** | < 50ms | +| **Concurrent Users** | 10,000+ | +| **Messages/Second** | 5,000+ | +| **Uptime** | 99.9% | + +## 🔧 Configuration + +### Environment Variables + +${'```'}env +DATABASE_URL="postgresql://user:password@localhost:5432/chat" +JWT_SECRET="your-secret-key" +REDIS_URL="redis://localhost:6379" +${'```'} + +## 🚢 Deployment + +Deploy to production using Docker: + +${'```'}dockerfile +FROM node:20-alpine +WORKDIR /app +COPY package*.json ./ +RUN npm ci --only=production +COPY . . +RUN npm run build +EXPOSE 3000 +CMD ["node", "build"] +${'```'} + +--- + +*Need help? Check the [documentation](https://kit.svelte.dev) or [open an issue](https://github.com/sveltejs/kit/issues)* +`; diff --git a/tools/server/webui/src/stories/fixtures/api-docs.ts b/tools/server/webui/src/stories/fixtures/api-docs.ts new file mode 100644 index 0000000000..7b499956f8 --- /dev/null +++ b/tools/server/webui/src/stories/fixtures/api-docs.ts @@ -0,0 +1,160 @@ +// API Documentation +export const API_DOCS_MD = String.raw` +# REST API Documentation + +## 🔐 Authentication + +All API requests require authentication using **Bearer tokens**. Include your API key in the Authorization header: + +${'```'}http +GET /api/v1/users +Host: api.example.com +Authorization: Bearer YOUR_API_KEY +Content-Type: application/json +${'```'} + +## 📍 Endpoints + +### Users API + +#### **GET** /api/v1/users + +Retrieve a paginated list of users. + +**Query Parameters:** + +| Parameter | Type | Default | Description | +|-----------|------|---------|-------------| +| page | integer | 1 | Page number | +| limit | integer | 20 | Items per page | +| sort | string | "created_at" | Sort field | +| order | string | "desc" | Sort order | + +**Response:** 200 OK + +${'```'}json +{ + "data": [ + { + "id": "usr_1234567890", + "email": "user@example.com", + "name": "John Doe", + "role": "admin", + "created_at": "2024-01-15T10:30:00Z" + } + ], + "pagination": { + "page": 1, + "limit": 20, + "total": 156, + "pages": 8 + } +} +${'```'} + +#### **POST** /api/v1/users + +Create a new user account. + +**Request Body:** + +${'```'}json +{ + "email": "newuser@example.com", + "password": "SecurePassword123!", + "name": "Jane Smith", + "role": "user" +} +${'```'} + +**Response:** 201 Created + +${'```'}json +{ + "id": "usr_9876543210", + "email": "newuser@example.com", + "name": "Jane Smith", + "role": "user", + "created_at": "2024-01-21T09:15:00Z" +} +${'```'} + +### Error Responses + +The API returns errors in a consistent format: + +${'```'}json +{ + "error": { + "code": "VALIDATION_ERROR", + "message": "Invalid request parameters", + "details": [ + { + "field": "email", + "message": "Email format is invalid" + } + ] + } +} +${'```'} + +### Rate Limiting + +| Tier | Requests/Hour | Burst | +|------|--------------|-------| +| **Free** | 1,000 | 100 | +| **Pro** | 10,000 | 500 | +| **Enterprise** | Unlimited | - | + +**Headers:** +- X-RateLimit-Limit +- X-RateLimit-Remaining +- X-RateLimit-Reset + +### Webhooks + +Configure webhooks to receive real-time events: + +${'```'}javascript +// Webhook payload +{ + "event": "user.created", + "timestamp": "2024-01-21T09:15:00Z", + "data": { + "id": "usr_9876543210", + "email": "newuser@example.com" + }, + "signature": "sha256=abcd1234..." +} +${'```'} + +### SDK Examples + +**JavaScript/TypeScript:** + +${'```'}typescript +import { ApiClient } from '@example/api-sdk'; + +const client = new ApiClient({ + apiKey: process.env.API_KEY +}); + +const users = await client.users.list({ + page: 1, + limit: 20 +}); +${'```'} + +**Python:** + +${'```'}python +from example_api import Client + +client = Client(api_key=os.environ['API_KEY']) +users = client.users.list(page=1, limit=20) +${'```'} + +--- + +📚 [Full API Reference](https://api.example.com/docs) | 💬 [Support](https://support.example.com) +`; diff --git a/tools/server/webui/src/stories/fixtures/assets/1.jpg b/tools/server/webui/src/stories/fixtures/assets/1.jpg new file mode 100644 index 0000000000000000000000000000000000000000..8348e38780de3332ba2e1d39fdb81fd8bba92389 GIT binary patch literal 44891 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0000000000..d55ea22a24 --- /dev/null +++ b/tools/server/webui/src/stories/fixtures/assets/hf-logo.svg @@ -0,0 +1,8 @@ + + + + + + + + \ No newline at end of file diff --git a/tools/server/webui/src/stories/fixtures/blog-post.ts b/tools/server/webui/src/stories/fixtures/blog-post.ts new file mode 100644 index 0000000000..3eb2ed7585 --- /dev/null +++ b/tools/server/webui/src/stories/fixtures/blog-post.ts @@ -0,0 +1,125 @@ +// Blog Post Content +export const BLOG_POST_MD = String.raw` +# Understanding Rust's Ownership System + +*Published on March 15, 2024 • 8 min read* + +Rust's ownership system is one of its most distinctive features, enabling memory safety without garbage collection. In this post, we'll explore how ownership works and why it's revolutionary for systems programming. + +## What is Ownership? + +Ownership is a set of rules that governs how Rust manages memory. These rules are checked at compile time, ensuring memory safety without runtime overhead. + +### The Three Rules of Ownership + +1. **Each value has a single owner** +2. **There can only be one owner at a time** +3. **When the owner goes out of scope, the value is dropped** + +## Memory Management Without GC + +Traditional approaches to memory management: + +- **Manual management** (C/C++): Error-prone, leads to bugs +- **Garbage collection** (Java, Python): Runtime overhead +- **Ownership** (Rust): Compile-time safety, zero runtime cost + +## Basic Examples + +### Variable Scope + +${'```'}rust +fn main() { + let s = String::from("hello"); // s comes into scope + + // s is valid here + println!("{}", s); + +} // s goes out of scope and is dropped +${'```'} + +### Move Semantics + +${'```'}rust +fn main() { + let s1 = String::from("hello"); + let s2 = s1; // s1 is moved to s2 + + // println!("{}", s1); // ❌ ERROR: s1 is no longer valid + println!("{}", s2); // ✅ OK: s2 owns the string +} +${'```'} + +## Borrowing and References + +Instead of transferring ownership, you can **borrow** values: + +### Immutable References + +${'```'}rust +fn calculate_length(s: &String) -> usize { + s.len() // s is a reference, doesn't own the String +} + +fn main() { + let s1 = String::from("hello"); + let len = calculate_length(&s1); // Borrow s1 + println!("Length of '{}' is {}", s1, len); // s1 still valid +} +${'```'} + +### Mutable References + +${'```'}rust +fn main() { + let mut s = String::from("hello"); + + let r1 = &mut s; + r1.push_str(", world"); + println!("{}", r1); + + // let r2 = &mut s; // ❌ ERROR: cannot borrow twice +} +${'```'} + +## Common Pitfalls + +### Dangling References + +${'```'}rust +fn dangle() -> &String { // ❌ ERROR: missing lifetime specifier + let s = String::from("hello"); + &s // s will be dropped, leaving a dangling reference +} +${'```'} + +### ✅ Solution + +${'```'}rust +fn no_dangle() -> String { + let s = String::from("hello"); + s // Ownership is moved out +} +${'```'} + +## Benefits + +- ✅ **No null pointer dereferences** +- ✅ **No data races** +- ✅ **No use-after-free** +- ✅ **No memory leaks** + +## Conclusion + +Rust's ownership system eliminates entire classes of bugs at compile time. While it has a learning curve, the benefits in safety and performance are worth it. + +## Further Reading + +- [The Rust Book - Ownership](https://doc.rust-lang.org/book/ch04-00-understanding-ownership.html) +- [Rust by Example - Ownership](https://doc.rust-lang.org/rust-by-example/scope/move.html) +- [Rustlings Exercises](https://github.com/rust-lang/rustlings) + +--- + +*Questions? Reach out on [Twitter](https://twitter.com/rustlang) or join the [Rust Discord](https://discord.gg/rust-lang)* +`; diff --git a/tools/server/webui/src/stories/fixtures/data-analysis.ts b/tools/server/webui/src/stories/fixtures/data-analysis.ts new file mode 100644 index 0000000000..6fec32dad6 --- /dev/null +++ b/tools/server/webui/src/stories/fixtures/data-analysis.ts @@ -0,0 +1,124 @@ +// Data Analysis Report +export const DATA_ANALYSIS_MD = String.raw` +# Q4 2024 Business Analytics Report + +*Executive Summary • Generated on January 15, 2025* + +## 📊 Key Performance Indicators + +${'```'} +Daily Active Users (DAU): 1.2M (+65% YoY) +Monthly Active Users (MAU): 4.5M (+48% YoY) +User Retention (Day 30): 68% (+12pp YoY) +Average Session Duration: 24min (+35% YoY) +${'```'} + +## 🎯 Product Performance + +### Feature Adoption Rates + +1. **AI Assistant**: 78% of users (↑ from 45%) +2. **Collaboration Tools**: 62% of users (↑ from 38%) +3. **Analytics Dashboard**: 54% of users (↑ from 31%) +4. **Mobile App**: 41% of users (↑ from 22%) + +### Customer Satisfaction + +| Metric | Q4 2024 | Q3 2024 | Change | +|--------|---------|---------|--------| +| **NPS Score** | 72 | 68 | +4 | +| **CSAT** | 4.6/5 | 4.4/5 | +0.2 | +| **Support Tickets** | 2,340 | 2,890 | -19% | +| **Resolution Time** | 4.2h | 5.1h | -18% | + +## 💰 Revenue Metrics + +### Monthly Recurring Revenue (MRR) + +- **Current MRR**: $2.8M (+42% YoY) +- **New MRR**: $340K +- **Expansion MRR**: $180K +- **Churned MRR**: $95K +- **Net New MRR**: $425K + +### Customer Acquisition + +${'```'} +Cost per Acquisition (CAC): $127 (-23% YoY) +Customer Lifetime Value: $1,840 (+31% YoY) +LTV:CAC Ratio: 14.5:1 +Payback Period: 3.2 months +${'```'} + +## 🌍 Geographic Performance + +### Revenue by Region + +1. **North America**: 45% ($1.26M) +2. **Europe**: 32% ($896K) +3. **Asia-Pacific**: 18% ($504K) +4. **Other**: 5% ($140K) + +### Growth Opportunities + +- **APAC**: 89% YoY growth potential +- **Latin America**: Emerging market entry +- **Middle East**: Enterprise expansion + +## 📱 Channel Performance + +### Traffic Sources + +| Channel | Sessions | Conversion | Revenue | +|---------|----------|------------|---------| +| **Organic Search** | 45% | 3.2% | $1.1M | +| **Direct** | 28% | 4.1% | $850K | +| **Social Media** | 15% | 2.8% | $420K | +| **Paid Ads** | 12% | 5.5% | $430K | + +### Marketing ROI + +- **Content Marketing**: 340% ROI +- **Email Campaigns**: 280% ROI +- **Social Media**: 190% ROI +- **Paid Search**: 220% ROI + +## 🔍 User Behavior Analysis + +### Session Patterns + +- **Peak Hours**: 9-11 AM, 2-4 PM EST +- **Mobile Usage**: 67% of sessions +- **Average Pages/Session**: 4.8 +- **Bounce Rate**: 23% (↓ from 31%) + +### Feature Usage Heatmap + +Most used features in order: +1. Dashboard (89% of users) +2. Search (76% of users) +3. Reports (64% of users) +4. Settings (45% of users) +5. Integrations (32% of users) + +## 💡 Recommendations + +1. **Invest** in AI capabilities (+$2M budget) +2. **Expand** sales team in APAC region +3. **Improve** onboarding to reduce churn +4. **Launch** enterprise security features + +## Appendix + +### Methodology + +Data collected from: +- Internal analytics (Amplitude) +- Customer surveys (n=2,450) +- Financial systems (NetSuite) +- Market research (Gartner) + +--- + +*Report prepared by Data Analytics Team • [View Interactive Dashboard](https://analytics.example.com)* +`; diff --git a/tools/server/webui/src/stories/fixtures/empty.ts b/tools/server/webui/src/stories/fixtures/empty.ts new file mode 100644 index 0000000000..05286e7a78 --- /dev/null +++ b/tools/server/webui/src/stories/fixtures/empty.ts @@ -0,0 +1,2 @@ +// Empty state +export const EMPTY_MD = ''; diff --git a/tools/server/webui/src/stories/fixtures/math-formulas.ts b/tools/server/webui/src/stories/fixtures/math-formulas.ts new file mode 100644 index 0000000000..a4e9ab0ed8 --- /dev/null +++ b/tools/server/webui/src/stories/fixtures/math-formulas.ts @@ -0,0 +1,156 @@ +// Math Formulas Content +export const MATH_FORMULAS_MD = String.raw` +# Mathematical Formulas and Expressions + +This document demonstrates various mathematical notation and formulas that can be rendered using LaTeX syntax in markdown. + +## Basic Arithmetic + +### Addition and Summation +$$\sum_{i=1}^{n} i = \frac{n(n+1)}{2}$$ + +## Algebra + +### Quadratic Formula +The solutions to $ax^2 + bx + c = 0$ are: +$$x = \frac{-b \pm \sqrt{b^2 - 4ac}}{2a}$$ + +### Binomial Theorem +$$(x + y)^n = \sum_{k=0}^{n} \binom{n}{k} x^{n-k} y^k$$ + +## Calculus + +### Derivatives +The derivative of $f(x) = x^n$ is: +$$f'(x) = nx^{n-1}$$ + +### Integration +$$\int_a^b f(x) \, dx = F(b) - F(a)$$ + +### Fundamental Theorem of Calculus +$$\frac{d}{dx} \int_a^x f(t) \, dt = f(x)$$ + +## Linear Algebra + +### Matrix Multiplication +If $A$ is an $m \times n$ matrix and $B$ is an $n \times p$ matrix, then: +$$C_{ij} = \sum_{k=1}^{n} A_{ik} B_{kj}$$ + +### Eigenvalues and Eigenvectors +For a square matrix $A$, if $Av = \lambda v$ for some non-zero vector $v$, then: +- $\lambda$ is an eigenvalue +- $v$ is an eigenvector + +## Statistics and Probability + +### Normal Distribution +The probability density function is: +$$f(x) = \frac{1}{\sigma\sqrt{2\pi}} e^{-\frac{1}{2}\left(\frac{x-\mu}{\sigma}\right)^2}$$ + +### Bayes' Theorem +$$P(A|B) = \frac{P(B|A) \cdot P(A)}{P(B)}$$ + +### Central Limit Theorem +For large $n$, the sample mean $\bar{X}$ is approximately: +$$\bar{X} \sim N\left(\mu, \frac{\sigma^2}{n}\right)$$ + +## Trigonometry + +### Pythagorean Identity +$$\sin^2\theta + \cos^2\theta = 1$$ + +### Euler's Formula +$$e^{i\theta} = \cos\theta + i\sin\theta$$ + +### Taylor Series for Sine +$$\sin x = \sum_{n=0}^{\infty} \frac{(-1)^n}{(2n+1)!} x^{2n+1} = x - \frac{x^3}{3!} + \frac{x^5}{5!} - \frac{x^7}{7!} + \cdots$$ + +## Complex Analysis + +### Complex Numbers +A complex number can be written as: +$$z = a + bi = r e^{i\theta}$$ + +where $r = |z| = \sqrt{a^2 + b^2}$ and $\theta = \arg(z)$ + +### Cauchy-Riemann Equations +For a function $f(z) = u(x,y) + iv(x,y)$ to be analytic: +$$\frac{\partial u}{\partial x} = \frac{\partial v}{\partial y}, \quad \frac{\partial u}{\partial y} = -\frac{\partial v}{\partial x}$$ + +## Differential Equations + +### First-order Linear ODE +$$\frac{dy}{dx} + P(x)y = Q(x)$$ + +Solution: $y = e^{-\int P(x)dx}\left[\int Q(x)e^{\int P(x)dx}dx + C\right]$ + +### Heat Equation +$$\frac{\partial u}{\partial t} = \alpha \frac{\partial^2 u}{\partial x^2}$$ + +## Number Theory + +### Prime Number Theorem +$$\pi(x) \sim \frac{x}{\ln x}$$ + +where $\pi(x)$ is the number of primes less than or equal to $x$. + +### Fermat's Last Theorem +For $n > 2$, there are no positive integers $a$, $b$, and $c$ such that: +$$a^n + b^n = c^n$$ + +## Set Theory + +### De Morgan's Laws +$$\overline{A \cup B} = \overline{A} \cap \overline{B}$$ +$$\overline{A \cap B} = \overline{A} \cup \overline{B}$$ + +## Advanced Topics + +### Riemann Zeta Function +$$\zeta(s) = \sum_{n=1}^{\infty} \frac{1}{n^s} = \prod_{p \text{ prime}} \frac{1}{1-p^{-s}}$$ + +### Maxwell's Equations +$$\nabla \cdot \mathbf{E} = \frac{\rho}{\epsilon_0}$$ +$$\nabla \cdot \mathbf{B} = 0$$ +$$\nabla \times \mathbf{E} = -\frac{\partial \mathbf{B}}{\partial t}$$ +$$\nabla \times \mathbf{B} = \mu_0\mathbf{J} + \mu_0\epsilon_0\frac{\partial \mathbf{E}}{\partial t}$$ + +### Schrödinger Equation +$$i\hbar\frac{\partial}{\partial t}\Psi(\mathbf{r},t) = \hat{H}\Psi(\mathbf{r},t)$$ + +## Inline Math Examples + +Here are some inline mathematical expressions: + +- The golden ratio: $\phi = \frac{1 + \sqrt{5}}{2} \approx 1.618$ +- Euler's number: $e = \lim_{n \to \infty} \left(1 + \frac{1}{n}\right)^n$ +- Pi: $\pi = 4 \sum_{n=0}^{\infty} \frac{(-1)^n}{2n+1}$ +- Square root of 2: $\sqrt{2} = 1.41421356...$ + +## Fractions and Radicals + +Complex fraction: $\frac{\frac{a}{b} + \frac{c}{d}}{\frac{e}{f} - \frac{g}{h}}$ + +Nested radicals: $\sqrt{2 + \sqrt{3 + \sqrt{4 + \sqrt{5}}}}$ + +## Summations and Products + +### Geometric Series +$$\sum_{n=0}^{\infty} ar^n = \frac{a}{1-r} \quad \text{for } |r| < 1$$ + +### Product Notation +$$n! = \prod_{k=1}^{n} k$$ + +### Double Summation +$$\sum_{i=1}^{m} \sum_{j=1}^{n} a_{ij}$$ + +## Limits + +$$\lim_{x \to 0} \frac{\sin x}{x} = 1$$ + +$$\lim_{n \to \infty} \left(1 + \frac{x}{n}\right)^n = e^x$$ + +--- + +*This document showcases various mathematical notation and formulas that can be rendered in markdown using LaTeX syntax.* +`; diff --git a/tools/server/webui/src/stories/fixtures/readme.ts b/tools/server/webui/src/stories/fixtures/readme.ts new file mode 100644 index 0000000000..e8b573d6c4 --- /dev/null +++ b/tools/server/webui/src/stories/fixtures/readme.ts @@ -0,0 +1,136 @@ +// README Content +export const README_MD = String.raw` +# 🚀 Awesome Web Framework + +[![npm version](https://img.shields.io/npm/v/awesome-framework.svg)](https://www.npmjs.com/package/awesome-framework) +[![Build Status](https://github.com/awesome/framework/workflows/CI/badge.svg)](https://github.com/awesome/framework/actions) +[![Coverage](https://codecov.io/gh/awesome/framework/branch/main/graph/badge.svg)](https://codecov.io/gh/awesome/framework) +[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) + +> A modern, fast, and flexible web framework for building scalable applications + +## ✨ Features + +- 🎯 **Type-Safe** - Full TypeScript support out of the box +- ⚡ **Lightning Fast** - Built on Vite for instant HMR +- 📦 **Zero Config** - Works out of the box for most use cases +- 🎨 **Flexible** - Unopinionated with sensible defaults +- 🔧 **Extensible** - Plugin system for custom functionality +- 📱 **Responsive** - Mobile-first approach +- 🌍 **i18n Ready** - Built-in internationalization +- 🔒 **Secure** - Security best practices by default + +## 📦 Installation + +${'```'}bash +npm install awesome-framework +# or +yarn add awesome-framework +# or +pnpm add awesome-framework +${'```'} + +## 🚀 Quick Start + +### Create a new project + +${'```'}bash +npx create-awesome-app my-app +cd my-app +npm run dev +${'```'} + +### Basic Example + +${'```'}javascript +import { createApp } from 'awesome-framework'; + +const app = createApp({ + port: 3000, + middleware: ['cors', 'helmet', 'compression'] +}); + +app.get('/', (req, res) => { + res.json({ message: 'Hello World!' }); +}); + +app.listen(() => { + console.log('Server running on http://localhost:3000'); +}); +${'```'} + +## 📖 Documentation + +### Core Concepts + +- [Getting Started](https://docs.awesome.dev/getting-started) +- [Configuration](https://docs.awesome.dev/configuration) +- [Routing](https://docs.awesome.dev/routing) +- [Middleware](https://docs.awesome.dev/middleware) +- [Database](https://docs.awesome.dev/database) +- [Authentication](https://docs.awesome.dev/authentication) + +### Advanced Topics + +- [Performance Optimization](https://docs.awesome.dev/performance) +- [Deployment](https://docs.awesome.dev/deployment) +- [Testing](https://docs.awesome.dev/testing) +- [Security](https://docs.awesome.dev/security) + +## 🛠️ Development + +### Prerequisites + +- Node.js >= 18 +- pnpm >= 8 + +### Setup + +${'```'}bash +git clone https://github.com/awesome/framework.git +cd framework +pnpm install +pnpm dev +${'```'} + +### Testing + +${'```'}bash +pnpm test # Run unit tests +pnpm test:e2e # Run end-to-end tests +pnpm test:watch # Run tests in watch mode +${'```'} + +## 🤝 Contributing + +We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details. + +### Contributors + + + + + +## 📊 Benchmarks + +| Framework | Requests/sec | Latency (ms) | Memory (MB) | +|-----------|-------------|--------------|-------------| +| **Awesome** | **45,230** | **2.1** | **42** | +| Express | 28,450 | 3.5 | 68 | +| Fastify | 41,200 | 2.3 | 48 | +| Koa | 32,100 | 3.1 | 52 | + +*Benchmarks performed on MacBook Pro M2, Node.js 20.x* + +## 📝 License + +MIT © [Awesome Team](https://github.com/awesome) + +## 🙏 Acknowledgments + +Special thanks to all our sponsors and contributors who make this project possible. + +--- + +**[Website](https://awesome.dev)** • **[Documentation](https://docs.awesome.dev)** • **[Discord](https://discord.gg/awesome)** • **[Twitter](https://twitter.com/awesomeframework)** +`; diff --git a/tools/server/webui/src/stories/fixtures/storybook-mocks.ts b/tools/server/webui/src/stories/fixtures/storybook-mocks.ts new file mode 100644 index 0000000000..6922586425 --- /dev/null +++ b/tools/server/webui/src/stories/fixtures/storybook-mocks.ts @@ -0,0 +1,50 @@ +import { serverStore } from '$lib/stores/server.svelte'; + +/** + * Mock server properties for Storybook testing + * This utility allows setting mock server configurations without polluting production code + */ +export function mockServerProps(props: Partial): void { + // Directly set the private _serverProps for testing purposes + (serverStore as unknown as { _serverProps: ApiLlamaCppServerProps })._serverProps = { + model_path: props.model_path || 'test-model', + modalities: { + vision: props.modalities?.vision ?? false, + audio: props.modalities?.audio ?? false + }, + ...props + } as ApiLlamaCppServerProps; +} + +/** + * Reset server store to clean state for testing + */ +export function resetServerStore(): void { + (serverStore as unknown as { _serverProps: ApiLlamaCppServerProps })._serverProps = { + model_path: '', + modalities: { + vision: false, + audio: false + } + } as ApiLlamaCppServerProps; + (serverStore as unknown as { _error: string })._error = ''; + (serverStore as unknown as { _loading: boolean })._loading = false; +} + +/** + * Common mock configurations for Storybook stories + */ +export const mockConfigs = { + visionOnly: { + modalities: { vision: true, audio: false } + }, + audioOnly: { + modalities: { vision: false, audio: true } + }, + bothModalities: { + modalities: { vision: true, audio: true } + }, + noModalities: { + modalities: { vision: false, audio: false } + } +} as const; diff --git a/tools/server/webui/src/utils/app.context.tsx b/tools/server/webui/src/utils/app.context.tsx deleted file mode 100644 index 1860ecc721..0000000000 --- a/tools/server/webui/src/utils/app.context.tsx +++ /dev/null @@ -1,412 +0,0 @@ -import React, { createContext, useContext, useEffect, useState } from 'react'; -import { - APIMessage, - CanvasData, - Conversation, - LlamaCppServerProps, - Message, - PendingMessage, - ViewingChat, -} from './types'; -import StorageUtils from './storage'; -import { - filterThoughtFromMsgs, - normalizeMsgsForAPI, - getSSEStreamAsync, - getServerProps, -} from './misc'; -import { BASE_URL, CONFIG_DEFAULT, isDev } from '../Config'; -import { matchPath, useLocation, useNavigate } from 'react-router'; -import toast from 'react-hot-toast'; - -interface AppContextValue { - // conversations and messages - viewingChat: ViewingChat | null; - pendingMessages: Record; - isGenerating: (convId: string) => boolean; - sendMessage: ( - convId: string | null, - leafNodeId: Message['id'] | null, - content: string, - extra: Message['extra'], - onChunk: CallbackGeneratedChunk - ) => Promise; - stopGenerating: (convId: string) => void; - replaceMessageAndGenerate: ( - convId: string, - parentNodeId: Message['id'], // the parent node of the message to be replaced - content: string | null, - extra: Message['extra'], - onChunk: CallbackGeneratedChunk - ) => Promise; - - // canvas - canvasData: CanvasData | null; - setCanvasData: (data: CanvasData | null) => void; - - // config - config: typeof CONFIG_DEFAULT; - saveConfig: (config: typeof CONFIG_DEFAULT) => void; - showSettings: boolean; - setShowSettings: (show: boolean) => void; - - // props - serverProps: LlamaCppServerProps | null; -} - -// this callback is used for scrolling to the bottom of the chat and switching to the last node -export type CallbackGeneratedChunk = (currLeafNodeId?: Message['id']) => void; - -// eslint-disable-next-line @typescript-eslint/no-explicit-any -const AppContext = createContext({} as any); - -const getViewingChat = async (convId: string): Promise => { - const conv = await StorageUtils.getOneConversation(convId); - if (!conv) return null; - return { - conv: conv, - // all messages from all branches, not filtered by last node - messages: await StorageUtils.getMessages(convId), - }; -}; - -export const AppContextProvider = ({ - children, -}: { - children: React.ReactElement; -}) => { - const { pathname } = useLocation(); - const navigate = useNavigate(); - const params = matchPath('/chat/:convId', pathname); - const convId = params?.params?.convId; - - const [serverProps, setServerProps] = useState( - null - ); - const [viewingChat, setViewingChat] = useState(null); - const [pendingMessages, setPendingMessages] = useState< - Record - >({}); - const [aborts, setAborts] = useState< - Record - >({}); - const [config, setConfig] = useState(StorageUtils.getConfig()); - const [canvasData, setCanvasData] = useState(null); - const [showSettings, setShowSettings] = useState(false); - - // get server props - useEffect(() => { - getServerProps(BASE_URL, config.apiKey) - .then((props) => { - console.debug('Server props:', props); - setServerProps(props); - }) - .catch((err) => { - console.error(err); - toast.error('Failed to fetch server props'); - }); - // eslint-disable-next-line - }, []); - - // handle change when the convId from URL is changed - useEffect(() => { - // also reset the canvas data - setCanvasData(null); - const handleConversationChange = async (changedConvId: string) => { - if (changedConvId !== convId) return; - setViewingChat(await getViewingChat(changedConvId)); - }; - StorageUtils.onConversationChanged(handleConversationChange); - getViewingChat(convId ?? '').then(setViewingChat); - return () => { - StorageUtils.offConversationChanged(handleConversationChange); - }; - }, [convId]); - - const setPending = (convId: string, pendingMsg: PendingMessage | null) => { - // if pendingMsg is null, remove the key from the object - if (!pendingMsg) { - setPendingMessages((prev) => { - const newState = { ...prev }; - delete newState[convId]; - return newState; - }); - } else { - setPendingMessages((prev) => ({ ...prev, [convId]: pendingMsg })); - } - }; - - const setAbort = (convId: string, controller: AbortController | null) => { - if (!controller) { - setAborts((prev) => { - const newState = { ...prev }; - delete newState[convId]; - return newState; - }); - } else { - setAborts((prev) => ({ ...prev, [convId]: controller })); - } - }; - - //////////////////////////////////////////////////////////////////////// - // public functions - - const isGenerating = (convId: string) => !!pendingMessages[convId]; - - const generateMessage = async ( - convId: string, - leafNodeId: Message['id'], - onChunk: CallbackGeneratedChunk - ) => { - if (isGenerating(convId)) return; - - const config = StorageUtils.getConfig(); - const currConversation = await StorageUtils.getOneConversation(convId); - if (!currConversation) { - throw new Error('Current conversation is not found'); - } - - const currMessages = StorageUtils.filterByLeafNodeId( - await StorageUtils.getMessages(convId), - leafNodeId, - false - ); - const abortController = new AbortController(); - setAbort(convId, abortController); - - if (!currMessages) { - throw new Error('Current messages are not found'); - } - - const pendingId = Date.now() + 1; - let pendingMsg: PendingMessage = { - id: pendingId, - convId, - type: 'text', - timestamp: pendingId, - role: 'assistant', - content: null, - parent: leafNodeId, - children: [], - }; - setPending(convId, pendingMsg); - - try { - // prepare messages for API - let messages: APIMessage[] = [ - ...(config.systemMessage.length === 0 - ? [] - : [{ role: 'system', content: config.systemMessage } as APIMessage]), - ...normalizeMsgsForAPI(currMessages), - ]; - if (config.excludeThoughtOnReq) { - messages = filterThoughtFromMsgs(messages); - } - if (isDev) console.log({ messages }); - - // prepare params - const params = { - messages, - stream: true, - cache_prompt: true, - reasoning_format: 'none', - samplers: config.samplers, - temperature: config.temperature, - dynatemp_range: config.dynatemp_range, - dynatemp_exponent: config.dynatemp_exponent, - top_k: config.top_k, - top_p: config.top_p, - min_p: config.min_p, - typical_p: config.typical_p, - xtc_probability: config.xtc_probability, - xtc_threshold: config.xtc_threshold, - repeat_last_n: config.repeat_last_n, - repeat_penalty: config.repeat_penalty, - presence_penalty: config.presence_penalty, - frequency_penalty: config.frequency_penalty, - dry_multiplier: config.dry_multiplier, - dry_base: config.dry_base, - dry_allowed_length: config.dry_allowed_length, - dry_penalty_last_n: config.dry_penalty_last_n, - max_tokens: config.max_tokens, - timings_per_token: !!config.showTokensPerSecond, - ...(config.custom.length ? JSON.parse(config.custom) : {}), - }; - - // send request - const fetchResponse = await fetch(`${BASE_URL}/v1/chat/completions`, { - method: 'POST', - headers: { - 'Content-Type': 'application/json', - ...(config.apiKey - ? { Authorization: `Bearer ${config.apiKey}` } - : {}), - }, - body: JSON.stringify(params), - signal: abortController.signal, - }); - if (fetchResponse.status !== 200) { - const body = await fetchResponse.json(); - throw new Error(body?.error?.message || 'Unknown error'); - } - const chunks = getSSEStreamAsync(fetchResponse); - for await (const chunk of chunks) { - // const stop = chunk.stop; - if (chunk.error) { - throw new Error(chunk.error?.message || 'Unknown error'); - } - const addedContent = chunk.choices[0]?.delta.content; - const lastContent = pendingMsg.content || ''; - if (addedContent) { - pendingMsg = { - ...pendingMsg, - content: lastContent + addedContent, - }; - } - const timings = chunk.timings; - if (timings && config.showTokensPerSecond) { - // only extract what's really needed, to save some space - pendingMsg.timings = { - prompt_n: timings.prompt_n, - prompt_ms: timings.prompt_ms, - predicted_n: timings.predicted_n, - predicted_ms: timings.predicted_ms, - }; - } - setPending(convId, pendingMsg); - onChunk(); // don't need to switch node for pending message - } - } catch (err) { - setPending(convId, null); - if ((err as Error).name === 'AbortError') { - // user stopped the generation via stopGeneration() function - // we can safely ignore this error - } else { - console.error(err); - // eslint-disable-next-line @typescript-eslint/no-explicit-any - toast.error((err as any)?.message ?? 'Unknown error'); - throw err; // rethrow - } - } - - if (pendingMsg.content !== null) { - await StorageUtils.appendMsg(pendingMsg as Message, leafNodeId); - } - setPending(convId, null); - onChunk(pendingId); // trigger scroll to bottom and switch to the last node - }; - - const sendMessage = async ( - convId: string | null, - leafNodeId: Message['id'] | null, - content: string, - extra: Message['extra'], - onChunk: CallbackGeneratedChunk - ): Promise => { - if (isGenerating(convId ?? '') || content.trim().length === 0) return false; - - if (convId === null || convId.length === 0 || leafNodeId === null) { - const conv = await StorageUtils.createConversation( - content.substring(0, 256) - ); - convId = conv.id; - leafNodeId = conv.currNode; - // if user is creating a new conversation, redirect to the new conversation - navigate(`/chat/${convId}`); - } - - const now = Date.now(); - const currMsgId = now; - StorageUtils.appendMsg( - { - id: currMsgId, - timestamp: now, - type: 'text', - convId, - role: 'user', - content, - extra, - parent: leafNodeId, - children: [], - }, - leafNodeId - ); - onChunk(currMsgId); - - try { - await generateMessage(convId, currMsgId, onChunk); - return true; - } catch (_) { - // TODO: rollback - } - return false; - }; - - const stopGenerating = (convId: string) => { - setPending(convId, null); - aborts[convId]?.abort(); - }; - - // if content is undefined, we remove last assistant message - const replaceMessageAndGenerate = async ( - convId: string, - parentNodeId: Message['id'], // the parent node of the message to be replaced - content: string | null, - extra: Message['extra'], - onChunk: CallbackGeneratedChunk - ) => { - if (isGenerating(convId)) return; - - if (content !== null) { - const now = Date.now(); - const currMsgId = now; - StorageUtils.appendMsg( - { - id: currMsgId, - timestamp: now, - type: 'text', - convId, - role: 'user', - content, - extra, - parent: parentNodeId, - children: [], - }, - parentNodeId - ); - parentNodeId = currMsgId; - } - onChunk(parentNodeId); - - await generateMessage(convId, parentNodeId, onChunk); - }; - - const saveConfig = (config: typeof CONFIG_DEFAULT) => { - StorageUtils.setConfig(config); - setConfig(config); - }; - - return ( - - {children} - - ); -}; - -export const useAppContext = () => useContext(AppContext); diff --git a/tools/server/webui/src/utils/common.tsx b/tools/server/webui/src/utils/common.tsx deleted file mode 100644 index 7dd64508a4..0000000000 --- a/tools/server/webui/src/utils/common.tsx +++ /dev/null @@ -1,74 +0,0 @@ -export const XCloseButton: React.ElementType< - React.ClassAttributes & - React.HTMLAttributes -> = ({ className, ...props }) => ( - -); - -export const OpenInNewTab = ({ - href, - children, -}: { - href: string; - children: string; -}) => ( - - {children} - -); - -export function BtnWithTooltips({ - className, - onClick, - onMouseLeave, - children, - tooltipsContent, - disabled, -}: { - className?: string; - onClick: () => void; - onMouseLeave?: () => void; - children: React.ReactNode; - tooltipsContent: string; - disabled?: boolean; -}) { - // the onClick handler is on the container, so screen readers can safely ignore the inner button - // this prevents the label from being read twice - return ( -

    - -
    - ); -} diff --git a/tools/server/webui/src/utils/llama-vscode.ts b/tools/server/webui/src/utils/llama-vscode.ts deleted file mode 100644 index 0ad8f8042e..0000000000 --- a/tools/server/webui/src/utils/llama-vscode.ts +++ /dev/null @@ -1,62 +0,0 @@ -import { useEffect } from 'react'; -import { ChatTextareaApi } from '../components/useChatTextarea.ts'; -import { ChatExtraContextApi } from '../components/useChatExtraContext.tsx'; - -// Extra context when using llama.cpp WebUI from llama-vscode, inside an iframe -// Ref: https://github.com/ggml-org/llama.cpp/pull/11940 - -interface SetTextEvData { - text: string; - context: string; -} - -/** - * To test it: - * window.postMessage({ command: 'setText', text: 'Spot the syntax error', context: 'def test()\n return 123' }, '*'); - */ - -export const useVSCodeContext = ( - textarea: ChatTextareaApi, - extraContext: ChatExtraContextApi -) => { - // Accept setText message from a parent window and set inputMsg and extraContext - useEffect(() => { - const handleMessage = (event: MessageEvent) => { - if (event.data?.command === 'setText') { - const data: SetTextEvData = event.data; - textarea.setValue(data?.text); - if (data?.context && data.context.length > 0) { - extraContext.clearItems(); - extraContext.addItems([ - { - type: 'context', - name: 'Extra context', - content: data.context, - }, - ]); - } - textarea.focus(); - setTimeout(() => { - textarea.refOnSubmit.current?.(); - }, 10); // wait for setExtraContext to finish - } - }; - - window.addEventListener('message', handleMessage); - return () => window.removeEventListener('message', handleMessage); - }, [textarea, extraContext]); - - // Add a keydown listener that sends the "escapePressed" message to the parent window - useEffect(() => { - const handleKeyDown = (event: KeyboardEvent) => { - if (event.key === 'Escape') { - window.parent.postMessage({ command: 'escapePressed' }, '*'); - } - }; - - window.addEventListener('keydown', handleKeyDown); - return () => window.removeEventListener('keydown', handleKeyDown); - }, []); - - return {}; -}; diff --git a/tools/server/webui/src/utils/misc.ts b/tools/server/webui/src/utils/misc.ts deleted file mode 100644 index 15182e4cab..0000000000 --- a/tools/server/webui/src/utils/misc.ts +++ /dev/null @@ -1,200 +0,0 @@ -// @ts-expect-error this package does not have typing -import TextLineStream from 'textlinestream'; -import { - APIMessage, - APIMessageContentPart, - LlamaCppServerProps, - Message, -} from './types'; - -// ponyfill for missing ReadableStream asyncIterator on Safari -import { asyncIterator } from '@sec-ant/readable-stream/ponyfill/asyncIterator'; - -// eslint-disable-next-line @typescript-eslint/no-explicit-any -export const isString = (x: any) => !!x.toLowerCase; -// eslint-disable-next-line @typescript-eslint/no-explicit-any -export const isBoolean = (x: any) => x === true || x === false; -// eslint-disable-next-line @typescript-eslint/no-explicit-any -export const isNumeric = (n: any) => !isString(n) && !isNaN(n) && !isBoolean(n); -export const escapeAttr = (str: string) => - str.replace(/>/g, '>').replace(/"/g, '"'); - -// wrapper for SSE -export async function* getSSEStreamAsync(fetchResponse: Response) { - if (!fetchResponse.body) throw new Error('Response body is empty'); - const lines: ReadableStream = fetchResponse.body - .pipeThrough(new TextDecoderStream()) - .pipeThrough(new TextLineStream()); - // @ts-expect-error asyncIterator complains about type, but it should work - for await (const line of asyncIterator(lines)) { - //if (isDev) console.log({ line }); - if (line.startsWith('data:') && !line.endsWith('[DONE]')) { - const data = JSON.parse(line.slice(5)); - yield data; - } else if (line.startsWith('error:')) { - const data = JSON.parse(line.slice(6)); - throw new Error(data.message || 'Unknown error'); - } - } -} - -// copy text to clipboard -export const copyStr = (textToCopy: string) => { - // Navigator clipboard api needs a secure context (https) - if (navigator.clipboard && window.isSecureContext) { - navigator.clipboard.writeText(textToCopy); - } else { - // Use the 'out of viewport hidden text area' trick - const textArea = document.createElement('textarea'); - textArea.value = textToCopy; - // Move textarea out of the viewport so it's not visible - textArea.style.position = 'absolute'; - textArea.style.left = '-999999px'; - document.body.prepend(textArea); - textArea.select(); - document.execCommand('copy'); - } -}; - -/** - * filter out redundant fields upon sending to API - * also format extra into text - */ -export function normalizeMsgsForAPI(messages: Readonly) { - return messages.map((msg) => { - if (msg.role !== 'user' || !msg.extra) { - return { - role: msg.role, - content: msg.content, - } as APIMessage; - } - - // extra content first, then user text message in the end - // this allow re-using the same cache prefix for long context - const contentArr: APIMessageContentPart[] = []; - - for (const extra of msg.extra ?? []) { - if (extra.type === 'context') { - contentArr.push({ - type: 'text', - text: extra.content, - }); - } else if (extra.type === 'textFile') { - contentArr.push({ - type: 'text', - text: `File: ${extra.name}\nContent:\n\n${extra.content}`, - }); - } else if (extra.type === 'imageFile') { - contentArr.push({ - type: 'image_url', - image_url: { url: extra.base64Url }, - }); - } else if (extra.type === 'audioFile') { - contentArr.push({ - type: 'input_audio', - input_audio: { - data: extra.base64Data, - format: /wav/.test(extra.mimeType) ? 'wav' : 'mp3', - }, - }); - } else { - throw new Error('Unknown extra type'); - } - } - - // add user message to the end - contentArr.push({ - type: 'text', - text: msg.content, - }); - - return { - role: msg.role, - content: contentArr, - }; - }) as APIMessage[]; -} - -/** - * recommended for DeepsSeek-R1, filter out content between and tags - */ -export function filterThoughtFromMsgs(messages: APIMessage[]) { - console.debug({ messages }); - return messages.map((msg) => { - if (msg.role !== 'assistant') { - return msg; - } - // assistant message is always a string - const contentStr = msg.content as string; - return { - role: msg.role, - content: - msg.role === 'assistant' - ? contentStr - .split(/<\/think>|<\|end\|>/) - .at(-1)! - .trim() - : contentStr, - } as APIMessage; - }); -} - -export function classNames(classes: Record): string { - return Object.entries(classes) - .filter(([_, value]) => value) - .map(([key, _]) => key) - .join(' '); -} - -export const delay = (ms: number) => - new Promise((resolve) => setTimeout(resolve, ms)); - -export const throttle = ( - callback: (...args: T) => void, - delay: number -) => { - let isWaiting = false; - - return (...args: T) => { - if (isWaiting) { - return; - } - - callback(...args); - isWaiting = true; - - setTimeout(() => { - isWaiting = false; - }, delay); - }; -}; - -export const cleanCurrentUrl = (removeQueryParams: string[]) => { - const url = new URL(window.location.href); - removeQueryParams.forEach((param) => { - url.searchParams.delete(param); - }); - window.history.replaceState({}, '', url.toString()); -}; - -export const getServerProps = async ( - baseUrl: string, - apiKey?: string -): Promise => { - try { - const response = await fetch(`${baseUrl}/props`, { - headers: { - 'Content-Type': 'application/json', - ...(apiKey ? { Authorization: `Bearer ${apiKey}` } : {}), - }, - }); - if (!response.ok) { - throw new Error('Failed to fetch server props'); - } - const data = await response.json(); - return data as LlamaCppServerProps; - } catch (error) { - console.error('Error fetching server props:', error); - throw error; - } -}; diff --git a/tools/server/webui/src/utils/storage.ts b/tools/server/webui/src/utils/storage.ts deleted file mode 100644 index 505693e927..0000000000 --- a/tools/server/webui/src/utils/storage.ts +++ /dev/null @@ -1,294 +0,0 @@ -// coversations is stored in localStorage -// format: { [convId]: { id: string, lastModified: number, messages: [...] } } - -import { CONFIG_DEFAULT } from '../Config'; -import { Conversation, Message, TimingReport } from './types'; -import Dexie, { Table } from 'dexie'; - -const event = new EventTarget(); - -type CallbackConversationChanged = (convId: string) => void; -let onConversationChangedHandlers: [ - CallbackConversationChanged, - EventListener, -][] = []; -const dispatchConversationChange = (convId: string) => { - event.dispatchEvent( - new CustomEvent('conversationChange', { detail: { convId } }) - ); -}; - -const db = new Dexie('LlamacppWebui') as Dexie & { - conversations: Table; - messages: Table; -}; - -// https://dexie.org/docs/Version/Version.stores() -db.version(1).stores({ - // Unlike SQL, you don’t need to specify all properties but only the one you wish to index. - conversations: '&id, lastModified', - messages: '&id, convId, [convId+id], timestamp', -}); - -// convId is a string prefixed with 'conv-' -const StorageUtils = { - /** - * manage conversations - */ - async getAllConversations(): Promise { - await migrationLStoIDB().catch(console.error); // noop if already migrated - return (await db.conversations.toArray()).sort( - (a, b) => b.lastModified - a.lastModified - ); - }, - /** - * can return null if convId does not exist - */ - async getOneConversation(convId: string): Promise { - return (await db.conversations.where('id').equals(convId).first()) ?? null; - }, - /** - * get all message nodes in a conversation - */ - async getMessages(convId: string): Promise { - return await db.messages.where({ convId }).toArray(); - }, - /** - * use in conjunction with getMessages to filter messages by leafNodeId - * includeRoot: whether to include the root node in the result - * if node with leafNodeId does not exist, return the path with the latest timestamp - */ - filterByLeafNodeId( - msgs: Readonly, - leafNodeId: Message['id'], - includeRoot: boolean - ): Readonly { - const res: Message[] = []; - const nodeMap = new Map(); - for (const msg of msgs) { - nodeMap.set(msg.id, msg); - } - let startNode: Message | undefined = nodeMap.get(leafNodeId); - if (!startNode) { - // if not found, we return the path with the latest timestamp - let latestTime = -1; - for (const msg of msgs) { - if (msg.timestamp > latestTime) { - startNode = msg; - latestTime = msg.timestamp; - } - } - } - // traverse the path from leafNodeId to root - // startNode can never be undefined here - let currNode: Message | undefined = startNode; - while (currNode) { - if (currNode.type !== 'root' || (currNode.type === 'root' && includeRoot)) - res.push(currNode); - currNode = nodeMap.get(currNode.parent ?? -1); - } - res.sort((a, b) => a.timestamp - b.timestamp); - return res; - }, - /** - * create a new conversation with a default root node - */ - async createConversation(name: string): Promise { - const now = Date.now(); - const msgId = now; - const conv: Conversation = { - id: `conv-${now}`, - lastModified: now, - currNode: msgId, - name, - }; - await db.conversations.add(conv); - // create a root node - await db.messages.add({ - id: msgId, - convId: conv.id, - type: 'root', - timestamp: now, - role: 'system', - content: '', - parent: -1, - children: [], - }); - return conv; - }, - /** - * update the name of a conversation - */ - async updateConversationName(convId: string, name: string): Promise { - await db.conversations.update(convId, { - name, - lastModified: Date.now(), - }); - dispatchConversationChange(convId); - }, - /** - * if convId does not exist, throw an error - */ - async appendMsg( - msg: Exclude, - parentNodeId: Message['id'] - ): Promise { - if (msg.content === null) return; - const { convId } = msg; - await db.transaction('rw', db.conversations, db.messages, async () => { - const conv = await StorageUtils.getOneConversation(convId); - const parentMsg = await db.messages - .where({ convId, id: parentNodeId }) - .first(); - // update the currNode of conversation - if (!conv) { - throw new Error(`Conversation ${convId} does not exist`); - } - if (!parentMsg) { - throw new Error( - `Parent message ID ${parentNodeId} does not exist in conversation ${convId}` - ); - } - await db.conversations.update(convId, { - lastModified: Date.now(), - currNode: msg.id, - }); - // update parent - await db.messages.update(parentNodeId, { - children: [...parentMsg.children, msg.id], - }); - // create message - await db.messages.add({ - ...msg, - parent: parentNodeId, - children: [], - }); - }); - dispatchConversationChange(convId); - }, - /** - * remove conversation by id - */ - async remove(convId: string): Promise { - await db.transaction('rw', db.conversations, db.messages, async () => { - await db.conversations.delete(convId); - await db.messages.where({ convId }).delete(); - }); - dispatchConversationChange(convId); - }, - - // event listeners - onConversationChanged(callback: CallbackConversationChanged) { - const fn = (e: Event) => callback((e as CustomEvent).detail.convId); - onConversationChangedHandlers.push([callback, fn]); - event.addEventListener('conversationChange', fn); - }, - offConversationChanged(callback: CallbackConversationChanged) { - const fn = onConversationChangedHandlers.find(([cb, _]) => cb === callback); - if (fn) { - event.removeEventListener('conversationChange', fn[1]); - } - onConversationChangedHandlers = []; - }, - - // manage config - getConfig(): typeof CONFIG_DEFAULT { - const savedVal = JSON.parse(localStorage.getItem('config') || '{}'); - // to prevent breaking changes in the future, we always provide default value for missing keys - return { - ...CONFIG_DEFAULT, - ...savedVal, - }; - }, - setConfig(config: typeof CONFIG_DEFAULT) { - localStorage.setItem('config', JSON.stringify(config)); - }, - getTheme(): string { - return localStorage.getItem('theme') || 'auto'; - }, - setTheme(theme: string) { - if (theme === 'auto') { - localStorage.removeItem('theme'); - } else { - localStorage.setItem('theme', theme); - } - }, -}; - -export default StorageUtils; - -// Migration from localStorage to IndexedDB - -// these are old types, LS prefix stands for LocalStorage -interface LSConversation { - id: string; // format: `conv-{timestamp}` - lastModified: number; // timestamp from Date.now() - messages: LSMessage[]; -} -interface LSMessage { - id: number; - role: 'user' | 'assistant' | 'system'; - content: string; - timings?: TimingReport; -} -async function migrationLStoIDB() { - if (localStorage.getItem('migratedToIDB')) return; - const res: LSConversation[] = []; - for (const key in localStorage) { - if (key.startsWith('conv-')) { - res.push(JSON.parse(localStorage.getItem(key) ?? '{}')); - } - } - if (res.length === 0) return; - await db.transaction('rw', db.conversations, db.messages, async () => { - let migratedCount = 0; - for (const conv of res) { - const { id: convId, lastModified, messages } = conv; - const firstMsg = messages[0]; - const lastMsg = messages.at(-1); - if (messages.length < 2 || !firstMsg || !lastMsg) { - console.log( - `Skipping conversation ${convId} with ${messages.length} messages` - ); - continue; - } - const name = firstMsg.content ?? '(no messages)'; - await db.conversations.add({ - id: convId, - lastModified, - currNode: lastMsg.id, - name, - }); - const rootId = messages[0].id - 2; - await db.messages.add({ - id: rootId, - convId: convId, - type: 'root', - timestamp: rootId, - role: 'system', - content: '', - parent: -1, - children: [firstMsg.id], - }); - for (let i = 0; i < messages.length; i++) { - const msg = messages[i]; - await db.messages.add({ - ...msg, - type: 'text', - convId: convId, - timestamp: msg.id, - parent: i === 0 ? rootId : messages[i - 1].id, - children: i === messages.length - 1 ? [] : [messages[i + 1].id], - }); - } - migratedCount++; - console.log( - `Migrated conversation ${convId} with ${messages.length} messages` - ); - } - console.log( - `Migrated ${migratedCount} conversations from localStorage to IndexedDB` - ); - localStorage.setItem('migratedToIDB', '1'); - }); -} diff --git a/tools/server/webui/src/utils/types.ts b/tools/server/webui/src/utils/types.ts deleted file mode 100644 index ea7d641dc7..0000000000 --- a/tools/server/webui/src/utils/types.ts +++ /dev/null @@ -1,138 +0,0 @@ -export interface TimingReport { - prompt_n: number; - prompt_ms: number; - predicted_n: number; - predicted_ms: number; -} - -/** - * What is conversation "branching"? It is a feature that allows the user to edit an old message in the history, while still keeping the conversation flow. - * Inspired by ChatGPT / Claude / Hugging Chat where you edit a message, a new branch of the conversation is created, and the old message is still visible. - * - * We use the same node-based structure like other chat UIs, where each message has a parent and children. A "root" message is the first message in a conversation, which will not be displayed in the UI. - * - * root - * ├── message 1 - * │ └── message 2 - * │ └── message 3 - * └── message 4 - * └── message 5 - * - * In the above example, assuming that user wants to edit message 2, a new branch will be created: - * - * ├── message 2 - * │ └── message 3 - * └── message 6 - * - * Message 2 and 6 are siblings, and message 6 is the new branch. - * - * We only need to know the last node (aka leaf) to get the current branch. In the above example, message 5 is the leaf of branch containing message 4 and 5. - * - * For the implementation: - * - StorageUtils.getMessages() returns list of all nodes - * - StorageUtils.filterByLeafNodeId() filters the list of nodes from a given leaf node - */ - -// Note: the term "message" and "node" are used interchangeably in this context -export interface Message { - id: number; - convId: string; - type: 'text' | 'root'; - timestamp: number; // timestamp from Date.now() - role: 'user' | 'assistant' | 'system'; - content: string; - timings?: TimingReport; - extra?: MessageExtra[]; - // node based system for branching - parent: Message['id']; - children: Message['id'][]; -} - -export type MessageExtra = - | MessageExtraTextFile - | MessageExtraImageFile - | MessageExtraAudioFile - | MessageExtraContext; - -export interface MessageExtraTextFile { - type: 'textFile'; - name: string; - content: string; -} - -export interface MessageExtraImageFile { - type: 'imageFile'; - name: string; - base64Url: string; -} - -export interface MessageExtraAudioFile { - type: 'audioFile'; - name: string; - base64Data: string; - mimeType: string; -} - -export interface MessageExtraContext { - type: 'context'; - name: string; - content: string; -} - -export type APIMessageContentPart = - | { - type: 'text'; - text: string; - } - | { - type: 'image_url'; - image_url: { url: string }; - } - | { - type: 'input_audio'; - input_audio: { data: string; format: 'wav' | 'mp3' }; - }; - -export type APIMessage = { - role: Message['role']; - content: string | APIMessageContentPart[]; -}; - -export interface Conversation { - id: string; // format: `conv-{timestamp}` - lastModified: number; // timestamp from Date.now() - currNode: Message['id']; // the current message node being viewed - name: string; -} - -export interface ViewingChat { - conv: Readonly; - messages: Readonly; -} - -export type PendingMessage = Omit & { - content: string | null; -}; - -export enum CanvasType { - PY_INTERPRETER, -} - -export interface CanvasPyInterpreter { - type: CanvasType.PY_INTERPRETER; - content: string; -} - -export type CanvasData = CanvasPyInterpreter; - -// a non-complete list of props, only contains the ones we need -export interface LlamaCppServerProps { - build_info: string; - model_path: string; - n_ctx: number; - modalities?: { - vision: boolean; - audio: boolean; - }; - // TODO: support params -} diff --git a/tools/server/webui/src/vite-env.d.ts b/tools/server/webui/src/vite-env.d.ts deleted file mode 100644 index 11f02fe2a0..0000000000 --- a/tools/server/webui/src/vite-env.d.ts +++ /dev/null @@ -1 +0,0 @@ -/// diff --git a/tools/server/webui/static/favicon.svg b/tools/server/webui/static/favicon.svg new file mode 100644 index 0000000000..a7ae13691c --- /dev/null +++ b/tools/server/webui/static/favicon.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/tools/server/webui/static/loading.html b/tools/server/webui/static/loading.html new file mode 100644 index 0000000000..c3fd19a0f5 --- /dev/null +++ b/tools/server/webui/static/loading.html @@ -0,0 +1,12 @@ + + + + + + +
    + The model is loading. Please wait.
    + The user interface will appear soon. +
    + + diff --git a/tools/server/webui/svelte.config.js b/tools/server/webui/svelte.config.js new file mode 100644 index 0000000000..722d408379 --- /dev/null +++ b/tools/server/webui/svelte.config.js @@ -0,0 +1,25 @@ +import { mdsvex } from 'mdsvex'; +import adapter from '@sveltejs/adapter-static'; +import { vitePreprocess } from '@sveltejs/vite-plugin-svelte'; + +/** @type {import('@sveltejs/kit').Config} */ +const config = { + // Consult https://svelte.dev/docs/kit/integrations + // for more information about preprocessors + preprocess: [vitePreprocess(), mdsvex()], + kit: { + adapter: adapter({ + pages: '../public', + assets: '../public', + fallback: 'index.html', + precompress: false, + strict: true + }), + output: { + bundleStrategy: 'inline' + } + }, + extensions: ['.svelte', '.svx'] +}; + +export default config; diff --git a/tools/server/webui/tailwind.config.js b/tools/server/webui/tailwind.config.js deleted file mode 100644 index c43066a19e..0000000000 --- a/tools/server/webui/tailwind.config.js +++ /dev/null @@ -1,16 +0,0 @@ -/** @type {import('tailwindcss').Config} */ -export default { - content: [ - "./index.html", - "./src/**/*.{js,ts,jsx,tsx}", - ], - theme: { - extend: {}, - }, - plugins: [ - require('daisyui'), - ], - daisyui: { - themes: ['light', 'dark', 'cupcake', 'bumblebee', 'emerald', 'corporate', 'synthwave', 'retro', 'cyberpunk', 'valentine', 'halloween', 'garden', 'forest', 'aqua', 'lofi', 'pastel', 'fantasy', 'wireframe', 'black', 'luxury', 'dracula', 'cmyk', 'autumn', 'business', 'acid', 'lemonade', 'night', 'coffee', 'winter', 'dim', 'nord', 'sunset'], - } -} diff --git a/tools/server/webui/tsconfig.app.json b/tools/server/webui/tsconfig.app.json deleted file mode 100644 index cb24c26f36..0000000000 --- a/tools/server/webui/tsconfig.app.json +++ /dev/null @@ -1,26 +0,0 @@ -{ - "compilerOptions": { - "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.app.tsbuildinfo", - "target": "ES2021", - "useDefineForClassFields": true, - "lib": ["ES2021", "DOM", "DOM.Iterable"], - "module": "ESNext", - "skipLibCheck": true, - - /* Bundler mode */ - "moduleResolution": "bundler", - "allowImportingTsExtensions": true, - "isolatedModules": true, - "moduleDetection": "force", - "noEmit": true, - "jsx": "react-jsx", - - /* Linting */ - "strict": true, - "noUnusedLocals": true, - "noUnusedParameters": true, - "noFallthroughCasesInSwitch": true, - "noUncheckedSideEffectImports": true - }, - "include": ["src"] -} diff --git a/tools/server/webui/tsconfig.json b/tools/server/webui/tsconfig.json index 1ffef600d9..0b2d8865f4 100644 --- a/tools/server/webui/tsconfig.json +++ b/tools/server/webui/tsconfig.json @@ -1,7 +1,19 @@ { - "files": [], - "references": [ - { "path": "./tsconfig.app.json" }, - { "path": "./tsconfig.node.json" } - ] + "extends": "./.svelte-kit/tsconfig.json", + "compilerOptions": { + "allowJs": true, + "checkJs": true, + "esModuleInterop": true, + "forceConsistentCasingInFileNames": true, + "resolveJsonModule": true, + "skipLibCheck": true, + "sourceMap": true, + "strict": true, + "moduleResolution": "bundler" + } + // Path aliases are handled by https://svelte.dev/docs/kit/configuration#alias + // except $lib which is handled by https://svelte.dev/docs/kit/configuration#files + // + // If you want to overwrite includes/excludes, make sure to copy over the relevant includes/excludes + // from the referenced tsconfig.json - TypeScript does not merge them in } diff --git a/tools/server/webui/tsconfig.node.json b/tools/server/webui/tsconfig.node.json deleted file mode 100644 index db0becc8b0..0000000000 --- a/tools/server/webui/tsconfig.node.json +++ /dev/null @@ -1,24 +0,0 @@ -{ - "compilerOptions": { - "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.node.tsbuildinfo", - "target": "ES2022", - "lib": ["ES2023"], - "module": "ESNext", - "skipLibCheck": true, - - /* Bundler mode */ - "moduleResolution": "bundler", - "allowImportingTsExtensions": true, - "isolatedModules": true, - "moduleDetection": "force", - "noEmit": true, - - /* Linting */ - "strict": true, - "noUnusedLocals": true, - "noUnusedParameters": true, - "noFallthroughCasesInSwitch": true, - "noUncheckedSideEffectImports": true - }, - "include": ["vite.config.ts"] -} diff --git a/tools/server/webui/vite.config.ts b/tools/server/webui/vite.config.ts index 910c286e0c..7f7ce3bed3 100644 --- a/tools/server/webui/vite.config.ts +++ b/tools/server/webui/vite.config.ts @@ -1,13 +1,11 @@ -import { defineConfig, PluginOption } from 'vite'; -import react from '@vitejs/plugin-react'; -import { viteSingleFile } from 'vite-plugin-singlefile'; -import path from 'node:path'; -import fs from 'node:fs'; +import tailwindcss from '@tailwindcss/vite'; +import { sveltekit } from '@sveltejs/kit/vite'; import * as fflate from 'fflate'; - -/* eslint-disable */ - -const MAX_BUNDLE_SIZE = 2 * 1024 * 1024; // only increase when absolutely necessary +import { readFileSync, writeFileSync, existsSync } from 'fs'; +import { resolve } from 'path'; +import { defineConfig } from 'vite'; +import devtoolsJson from 'vite-plugin-devtools-json'; +import { storybookTest } from '@storybook/addon-vitest/vitest-plugin'; const GUIDE_FOR_FRONTEND = ` `.trim(); -const FRONTEND_PLUGINS = [react()]; +const MAX_BUNDLE_SIZE = 2 * 1024 * 1024; -const BUILD_PLUGINS = [ - ...FRONTEND_PLUGINS, - viteSingleFile(), - (function llamaCppPlugin() { - let config: any; - return { - name: 'llamacpp:build', - apply: 'build', - async configResolved(_config: any) { - config = _config; - }, - writeBundle() { - const outputIndexHtml = path.join(config.build.outDir, 'index.html'); - let content = - GUIDE_FOR_FRONTEND + '\n' + fs.readFileSync(outputIndexHtml, 'utf-8'); - content = content.replace(/\r/g, ''); // remove windows-style line endings - const compressed = fflate.gzipSync(Buffer.from(content, 'utf-8'), { - level: 9, - }); +function llamaCppBuildPlugin() { + return { + name: 'llamacpp:build', + apply: 'build' as const, + closeBundle() { + // Ensure the SvelteKit adapter has finished writing to ../public + setTimeout(() => { + try { + const indexPath = resolve('../public/index.html'); + const gzipPath = resolve('../public/index.html.gz'); - // because gzip header contains machine-specific info, we must remove these data from the header - // timestamp - compressed[0x4] = 0; - compressed[0x5] = 0; - compressed[0x6] = 0; - compressed[0x7] = 0; - // OS - compressed[0x9] = 0; + if (!existsSync(indexPath)) { + return; + } - if (compressed.byteLength > MAX_BUNDLE_SIZE) { - throw new Error( - `Bundle size is too large (${Math.ceil(compressed.byteLength / 1024)} KB).\n` + - `Please reduce the size of the frontend or increase MAX_BUNDLE_SIZE in vite.config.js.\n` - ); - } + let content = readFileSync(indexPath, 'utf-8'); - const targetOutputFile = path.join( - config.build.outDir, - '../../public/index.html.gz' - ); - fs.writeFileSync(targetOutputFile, compressed); - }, - } satisfies PluginOption; - })(), -]; + const faviconPath = resolve('static/favicon.svg'); + if (existsSync(faviconPath)) { + const faviconContent = readFileSync(faviconPath, 'utf-8'); + const faviconBase64 = Buffer.from(faviconContent).toString('base64'); + const faviconDataUrl = `data:image/svg+xml;base64,${faviconBase64}`; + + content = content.replace(/href="[^"]*favicon\.svg"/g, `href="${faviconDataUrl}"`); + + console.log('✓ Inlined favicon.svg as base64 data URL'); + } + + content = content.replace(/\r/g, ''); + content = GUIDE_FOR_FRONTEND + '\n' + content; + + const compressed = fflate.gzipSync(Buffer.from(content, 'utf-8'), { level: 9 }); + + compressed[0x4] = 0; + compressed[0x5] = 0; + compressed[0x6] = 0; + compressed[0x7] = 0; + compressed[0x9] = 0; + + if (compressed.byteLength > MAX_BUNDLE_SIZE) { + throw new Error( + `Bundle size is too large (${Math.ceil(compressed.byteLength / 1024)} KB).\n` + + `Please reduce the size of the frontend or increase MAX_BUNDLE_SIZE in vite.config.ts.\n` + ); + } + + writeFileSync(gzipPath, compressed); + console.log('✓ Created index.html.gz'); + } catch (error) { + console.error('Failed to create gzip file:', error); + } + }, 100); + } + }; +} export default defineConfig({ - // @ts-ignore - plugins: process.env.ANALYZE ? FRONTEND_PLUGINS : BUILD_PLUGINS, - server: { - proxy: { - '/v1': 'http://localhost:8080', - '/props': 'http://localhost:8080', - }, - headers: { - 'Cross-Origin-Embedder-Policy': 'require-corp', - 'Cross-Origin-Opener-Policy': 'same-origin', - }, - }, + plugins: [tailwindcss(), sveltekit(), devtoolsJson(), llamaCppBuildPlugin()], + test: { + projects: [ + { + extends: './vite.config.ts', + test: { + name: 'client', + environment: 'browser', + browser: { + enabled: true, + provider: 'playwright', + instances: [{ browser: 'chromium' }] + }, + include: ['src/**/*.svelte.{test,spec}.{js,ts}'], + exclude: ['src/lib/server/**'], + setupFiles: ['./vitest-setup-client.ts'] + } + }, + { + extends: './vite.config.ts', + test: { + name: 'server', + environment: 'node', + include: ['src/**/*.{test,spec}.{js,ts}'], + exclude: ['src/**/*.svelte.{test,spec}.{js,ts}'] + } + }, + { + extends: './vite.config.ts', + test: { + name: 'ui', + environment: 'browser', + browser: { + enabled: true, + provider: 'playwright', + instances: [{ browser: 'chromium', headless: true }] + }, + include: ['src/**/*.stories.{js,ts,svelte}'], + setupFiles: ['./.storybook/vitest.setup.ts'] + }, + plugins: [ + storybookTest({ + storybookScript: 'pnpm run storybook --no-open' + }) + ] + } + ] + }, + server: { + proxy: { + '/v1': 'http://localhost:8080', + '/props': 'http://localhost:8080', + '/slots': 'http://localhost:8080' + }, + headers: { + 'Cross-Origin-Embedder-Policy': 'require-corp', + 'Cross-Origin-Opener-Policy': 'same-origin' + } + } }); diff --git a/tools/server/webui/vitest-setup-client.ts b/tools/server/webui/vitest-setup-client.ts new file mode 100644 index 0000000000..570b9f0e1a --- /dev/null +++ b/tools/server/webui/vitest-setup-client.ts @@ -0,0 +1,2 @@ +/// +/// From 0320ac5264279d74f8ee91bafa6c90e9ab9bbb91 Mon Sep 17 00:00:00 2001 From: Georgi Gerganov Date: Wed, 17 Sep 2025 20:38:12 +0300 Subject: [PATCH 26/52] metal : refactor + optimize v2 (#15995) * metal : improve naming * metal : refactor device ggml-ci * cont : props ggml-ci * metal : apply ggml_mem_ranges_t ggml-ci * metal : remove GGML_METAL_USE_BF16 ggml-ci * metal : refactor device buffer ggml-ci * cont : fix naming * metal : sync before destroying the backend ggml-ci * metal : refactor context ggml-ci * metal : migrate ggml-metal.m to ggml-metal.cpp ggml-ci * metal : adjust ops API ggml-ci * metal : use C++ to store piplienes ggml-ci * metal : migrate ops to separate functions ggml-ci * metal : add ggml_metal_library_t ggml-ci * metal : improve naming ggml-ci * metal : cleanp ggml-ci * metal : add support for GGML_OP_LOG ggml-ci * metal : fix error handling ggml-ci --- ci/run.sh | 2 +- ggml/CMakeLists.txt | 1 - ggml/include/ggml-metal.h | 1 + ggml/include/ggml.h | 8 +- ggml/src/ggml-metal/CMakeLists.txt | 10 +- ggml/src/ggml-metal/ggml-metal-common.cpp | 32 +- ggml/src/ggml-metal/ggml-metal-common.h | 14 +- ggml/src/ggml-metal/ggml-metal-context.h | 33 + ggml/src/ggml-metal/ggml-metal-context.m | 575 ++ ggml/src/ggml-metal/ggml-metal-device.cpp | 1366 ++++ ggml/src/ggml-metal/ggml-metal-device.h | 226 + ggml/src/ggml-metal/ggml-metal-device.m | 1289 ++++ ggml/src/ggml-metal/ggml-metal-impl.h | 35 +- ggml/src/ggml-metal/ggml-metal-ops.cpp | 3188 ++++++++++ ggml/src/ggml-metal/ggml-metal-ops.h | 81 + ggml/src/ggml-metal/ggml-metal.cpp | 718 +++ ggml/src/ggml-metal/ggml-metal.m | 6897 --------------------- ggml/src/ggml-metal/ggml-metal.metal | 561 +- tests/test-backend-ops.cpp | 20 +- 19 files changed, 7873 insertions(+), 7184 deletions(-) create mode 100644 ggml/src/ggml-metal/ggml-metal-context.h create mode 100644 ggml/src/ggml-metal/ggml-metal-context.m create mode 100644 ggml/src/ggml-metal/ggml-metal-device.cpp create mode 100644 ggml/src/ggml-metal/ggml-metal-device.h create mode 100644 ggml/src/ggml-metal/ggml-metal-device.m create mode 100644 ggml/src/ggml-metal/ggml-metal-ops.cpp create mode 100644 ggml/src/ggml-metal/ggml-metal-ops.h create mode 100644 ggml/src/ggml-metal/ggml-metal.cpp delete mode 100644 ggml/src/ggml-metal/ggml-metal.m diff --git a/ci/run.sh b/ci/run.sh index ba099680cd..8e20b4e24d 100755 --- a/ci/run.sh +++ b/ci/run.sh @@ -45,7 +45,7 @@ SRC=`pwd` CMAKE_EXTRA="-DLLAMA_FATAL_WARNINGS=ON -DLLAMA_CURL=ON" if [ ! -z ${GG_BUILD_METAL} ]; then - CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_METAL=ON -DGGML_METAL_USE_BF16=ON" + CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_METAL=ON" fi if [ ! -z ${GG_BUILD_CUDA} ]; then diff --git a/ggml/CMakeLists.txt b/ggml/CMakeLists.txt index d06464f5eb..f4ccf273b7 100644 --- a/ggml/CMakeLists.txt +++ b/ggml/CMakeLists.txt @@ -190,7 +190,6 @@ option(GGML_WEBGPU "ggml: use WebGPU" option(GGML_WEBGPU_DEBUG "ggml: enable WebGPU debug output" OFF) option(GGML_ZDNN "ggml: use zDNN" OFF) option(GGML_METAL "ggml: use Metal" ${GGML_METAL_DEFAULT}) -option(GGML_METAL_USE_BF16 "ggml: use bfloat if available" OFF) option(GGML_METAL_NDEBUG "ggml: disable Metal debugging" OFF) option(GGML_METAL_SHADER_DEBUG "ggml: compile Metal with -fno-fast-math" OFF) option(GGML_METAL_EMBED_LIBRARY "ggml: embed Metal library" ${GGML_METAL}) diff --git a/ggml/include/ggml-metal.h b/ggml/include/ggml-metal.h index 1163438bc2..433838f0d6 100644 --- a/ggml/include/ggml-metal.h +++ b/ggml/include/ggml-metal.h @@ -39,6 +39,7 @@ extern "C" { // user-code should use only these functions // +// TODO: remove in the future GGML_BACKEND_API ggml_backend_t ggml_backend_metal_init(void); GGML_BACKEND_API bool ggml_backend_is_metal(ggml_backend_t backend); diff --git a/ggml/include/ggml.h b/ggml/include/ggml.h index b7b472c56e..36b23dc6d0 100644 --- a/ggml/include/ggml.h +++ b/ggml/include/ggml.h @@ -284,19 +284,19 @@ __host__ __device__ constexpr inline void ggml_unused_vars_impl(Args&&...) noexc // GGML_TENSOR_LOCALS(size_t, nb1, src1, nb); // #define GGML_TENSOR_LOCALS_1(type, prefix, pointer, array) \ - const type prefix##0 = (pointer)->array[0]; \ + const type prefix##0 = (pointer) ? (pointer)->array[0] : 0; \ GGML_UNUSED(prefix##0); #define GGML_TENSOR_LOCALS_2(type, prefix, pointer, array) \ GGML_TENSOR_LOCALS_1 (type, prefix, pointer, array) \ - const type prefix##1 = (pointer)->array[1]; \ + const type prefix##1 = (pointer) ? (pointer)->array[1] : 0; \ GGML_UNUSED(prefix##1); #define GGML_TENSOR_LOCALS_3(type, prefix, pointer, array) \ GGML_TENSOR_LOCALS_2 (type, prefix, pointer, array) \ - const type prefix##2 = (pointer)->array[2]; \ + const type prefix##2 = (pointer) ? (pointer)->array[2] : 0; \ GGML_UNUSED(prefix##2); #define GGML_TENSOR_LOCALS(type, prefix, pointer, array) \ GGML_TENSOR_LOCALS_3 (type, prefix, pointer, array) \ - const type prefix##3 = (pointer)->array[3]; \ + const type prefix##3 = (pointer) ? (pointer)->array[3] : 0; \ GGML_UNUSED(prefix##3); #define GGML_TENSOR_UNARY_OP_LOCALS \ diff --git a/ggml/src/ggml-metal/CMakeLists.txt b/ggml/src/ggml-metal/CMakeLists.txt index 65c131b621..63418fe143 100644 --- a/ggml/src/ggml-metal/CMakeLists.txt +++ b/ggml/src/ggml-metal/CMakeLists.txt @@ -5,8 +5,12 @@ find_library(METALKIT_FRAMEWORK MetalKit REQUIRED) message(STATUS "Metal framework found") ggml_add_backend_library(ggml-metal - ggml-metal.m + ggml-metal.cpp + ggml-metal-device.m + ggml-metal-device.cpp ggml-metal-common.cpp + ggml-metal-context.m + ggml-metal-ops.cpp ) target_link_libraries(ggml-metal PRIVATE @@ -19,10 +23,6 @@ if (GGML_METAL_NDEBUG) add_compile_definitions(GGML_METAL_NDEBUG) endif() -if (GGML_METAL_USE_BF16) - add_compile_definitions(GGML_METAL_USE_BF16) -endif() - # copy metal files to bin directory configure_file(../ggml-common.h ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-common.h COPYONLY) configure_file(ggml-metal.metal ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal.metal COPYONLY) diff --git a/ggml/src/ggml-metal/ggml-metal-common.cpp b/ggml/src/ggml-metal/ggml-metal-common.cpp index cb39e5b2ab..34d27b6324 100644 --- a/ggml/src/ggml-metal/ggml-metal-common.cpp +++ b/ggml/src/ggml-metal/ggml-metal-common.cpp @@ -22,7 +22,7 @@ struct ggml_mem_ranges { int debug = 0; }; -struct ggml_mem_ranges * ggml_mem_ranges_init(int debug) { +ggml_mem_ranges_t ggml_mem_ranges_init(int debug) { auto * res = new ggml_mem_ranges; res->ranges.reserve(256); @@ -31,15 +31,15 @@ struct ggml_mem_ranges * ggml_mem_ranges_init(int debug) { return res; } -void ggml_mem_ranges_free(ggml_mem_ranges * mrs) { +void ggml_mem_ranges_free(ggml_mem_ranges_t mrs) { delete mrs; } -void ggml_mem_ranges_reset(ggml_mem_ranges * mrs) { +void ggml_mem_ranges_reset(ggml_mem_ranges_t mrs) { mrs->ranges.clear(); } -static bool ggml_mem_ranges_add(ggml_mem_ranges * mrs, ggml_mem_range mr) { +static bool ggml_mem_ranges_add(ggml_mem_ranges_t mrs, ggml_mem_range mr) { mrs->ranges.push_back(mr); return true; @@ -87,7 +87,7 @@ static ggml_mem_range ggml_mem_range_from_tensor_dst(const ggml_tensor * tensor) return ggml_mem_range_from_tensor(tensor, MEM_RANGE_TYPE_DST); } -static bool ggml_mem_ranges_add_src(ggml_mem_ranges * mrs, const ggml_tensor * tensor) { +static bool ggml_mem_ranges_add_src(ggml_mem_ranges_t mrs, const ggml_tensor * tensor) { GGML_ASSERT(tensor); ggml_mem_range mr = ggml_mem_range_from_tensor_src(tensor); @@ -99,7 +99,7 @@ static bool ggml_mem_ranges_add_src(ggml_mem_ranges * mrs, const ggml_tensor * t return ggml_mem_ranges_add(mrs, mr); } -static bool ggml_mem_ranges_add_dst(ggml_mem_ranges * mrs, const ggml_tensor * tensor) { +static bool ggml_mem_ranges_add_dst(ggml_mem_ranges_t mrs, const ggml_tensor * tensor) { GGML_ASSERT(tensor); ggml_mem_range mr = ggml_mem_range_from_tensor_dst(tensor); @@ -111,7 +111,7 @@ static bool ggml_mem_ranges_add_dst(ggml_mem_ranges * mrs, const ggml_tensor * t return ggml_mem_ranges_add(mrs, mr); } -bool ggml_mem_ranges_add(ggml_mem_ranges * mrs, const ggml_tensor * tensor) { +bool ggml_mem_ranges_add(ggml_mem_ranges_t mrs, const ggml_tensor * tensor) { for (int i = 0; i < GGML_MAX_DIMS; i++) { if (tensor->src[i]) { ggml_mem_ranges_add_src(mrs, tensor->src[i]); @@ -121,7 +121,7 @@ bool ggml_mem_ranges_add(ggml_mem_ranges * mrs, const ggml_tensor * tensor) { return ggml_mem_ranges_add_dst(mrs, tensor); } -static bool ggml_mem_ranges_check(const ggml_mem_ranges * mrs, ggml_mem_range mr) { +static bool ggml_mem_ranges_check(ggml_mem_ranges_t mrs, ggml_mem_range mr) { for (size_t i = 0; i < mrs->ranges.size(); i++) { const auto & cmp = mrs->ranges[i]; @@ -152,7 +152,7 @@ static bool ggml_mem_ranges_check(const ggml_mem_ranges * mrs, ggml_mem_range mr return true; } -static bool ggml_mem_ranges_check_src(const ggml_mem_ranges * mrs, const ggml_tensor * tensor) { +static bool ggml_mem_ranges_check_src(ggml_mem_ranges_t mrs, const ggml_tensor * tensor) { GGML_ASSERT(tensor); ggml_mem_range mr = ggml_mem_range_from_tensor_src(tensor); @@ -162,7 +162,7 @@ static bool ggml_mem_ranges_check_src(const ggml_mem_ranges * mrs, const ggml_te return res; } -static bool ggml_mem_ranges_check_dst(const ggml_mem_ranges * mrs, const ggml_tensor * tensor) { +static bool ggml_mem_ranges_check_dst(ggml_mem_ranges_t mrs, const ggml_tensor * tensor) { GGML_ASSERT(tensor); ggml_mem_range mr = ggml_mem_range_from_tensor_dst(tensor); @@ -172,7 +172,7 @@ static bool ggml_mem_ranges_check_dst(const ggml_mem_ranges * mrs, const ggml_te return res; } -bool ggml_mem_ranges_check(const ggml_mem_ranges * mrs, const ggml_tensor * tensor) { +bool ggml_mem_ranges_check(ggml_mem_ranges_t mrs, const ggml_tensor * tensor) { for (int i = 0; i < GGML_MAX_DIMS; i++) { if (tensor->src[i]) { if (!ggml_mem_ranges_check_src(mrs, tensor->src[i])) { @@ -222,7 +222,7 @@ struct node_info { static std::vector ggml_metal_graph_optimize_reorder(const std::vector & nodes) { // helper to add node src and dst ranges - const auto & h_add = [](ggml_mem_ranges * mrs, const node_info & node) { + const auto & h_add = [](ggml_mem_ranges_t mrs, const node_info & node) { for (int i = 0; i < GGML_MAX_SRC; i++) { if (node.node->src[i]) { if (!ggml_mem_ranges_add_src(mrs, node.node->src[i])) { @@ -246,7 +246,7 @@ static std::vector ggml_metal_graph_optimize_reorder(const std::vectorsrc[i]) { if (!ggml_mem_ranges_check_src(mrs, node.node->src[i])) { @@ -301,10 +301,10 @@ static std::vector ggml_metal_graph_optimize_reorder(const std::vector used(n, false); // the memory ranges for the set of currently concurrent nodes - ggml_mem_ranges * mrs0 = ggml_mem_ranges_init(0); + ggml_mem_ranges_t mrs0 = ggml_mem_ranges_init(0); // the memory ranges for the set of nodes that haven't been processed yet, when looking forward for a node to reorder - ggml_mem_ranges * mrs1 = ggml_mem_ranges_init(0); + ggml_mem_ranges_t mrs1 = ggml_mem_ranges_init(0); for (int i0 = 0; i0 < n; i0++) { if (used[i0]) { @@ -375,7 +375,7 @@ static std::vector ggml_metal_graph_optimize_reorder(const std::vectorn_nodes; diff --git a/ggml/src/ggml-metal/ggml-metal-common.h b/ggml/src/ggml-metal/ggml-metal-common.h index c1402895b9..3acbc6ae17 100644 --- a/ggml/src/ggml-metal/ggml-metal-common.h +++ b/ggml/src/ggml-metal/ggml-metal-common.h @@ -25,27 +25,27 @@ enum ggml_mem_range_type { // can be added to the set without violating the constraints (i.e. if it can be executed concurrently with the // tasks already in the set) // -struct ggml_mem_ranges; +typedef struct ggml_mem_ranges * ggml_mem_ranges_t; -struct ggml_mem_ranges * ggml_mem_ranges_init(int debug); -void ggml_mem_ranges_free(struct ggml_mem_ranges * mrs); +ggml_mem_ranges_t ggml_mem_ranges_init(int debug); +void ggml_mem_ranges_free(ggml_mem_ranges_t mrs); // remove all ranges from the set -void ggml_mem_ranges_reset(struct ggml_mem_ranges * mrs); +void ggml_mem_ranges_reset(ggml_mem_ranges_t mrs); // add src or dst ranges to track -bool ggml_mem_ranges_add(struct ggml_mem_ranges * mrs, const struct ggml_tensor * tensor); +bool ggml_mem_ranges_add(ggml_mem_ranges_t mrs, const struct ggml_tensor * tensor); // return false if: // - new src range overlaps with any existing dst range // - new dst range overlaps with any existing range (src or dst) -bool ggml_mem_ranges_check(const struct ggml_mem_ranges * mrs, const struct ggml_tensor * tensor); +bool ggml_mem_ranges_check(ggml_mem_ranges_t mrs, const struct ggml_tensor * tensor); // reorder the nodes in the graph to improve concurrency, while respecting fusion // // note: this implementation is generic and not specific to metal // if it proves to work well, we can start using it for other backends in the future -void ggml_metal_graph_optimize(struct ggml_cgraph * gf); +void ggml_graph_optimize(struct ggml_cgraph * gf); #ifdef __cplusplus } diff --git a/ggml/src/ggml-metal/ggml-metal-context.h b/ggml/src/ggml-metal/ggml-metal-context.h new file mode 100644 index 0000000000..ec2b686b73 --- /dev/null +++ b/ggml/src/ggml-metal/ggml-metal-context.h @@ -0,0 +1,33 @@ +#pragma once + +#include "ggml-metal-device.h" + +#ifdef __cplusplus +extern "C" { +#endif + +// +// backend context +// + +typedef struct ggml_metal * ggml_metal_t; + +ggml_metal_t ggml_metal_init(ggml_metal_device_t dev); +void ggml_metal_free(ggml_metal_t ctx); + +void ggml_metal_synchronize(ggml_metal_t ctx); + +void ggml_metal_set_tensor_async(ggml_metal_t ctx, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size); +void ggml_metal_get_tensor_async(ggml_metal_t ctx, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size); + +enum ggml_status ggml_metal_graph_compute (ggml_metal_t ctx, struct ggml_cgraph * gf); +void ggml_metal_graph_optimize(ggml_metal_t ctx, struct ggml_cgraph * gf); + +void ggml_metal_set_n_cb (ggml_metal_t ctx, int n_cb); +void ggml_metal_set_abort_callback (ggml_metal_t ctx, ggml_abort_callback abort_callback, void * user_data); +bool ggml_metal_supports_family (ggml_metal_t ctx, int family); +void ggml_metal_capture_next_compute(ggml_metal_t ctx); + +#ifdef __cplusplus +} +#endif diff --git a/ggml/src/ggml-metal/ggml-metal-context.m b/ggml/src/ggml-metal/ggml-metal-context.m new file mode 100644 index 0000000000..af9ff21436 --- /dev/null +++ b/ggml/src/ggml-metal/ggml-metal-context.m @@ -0,0 +1,575 @@ +#import "ggml-metal-context.h" + +#import "ggml-impl.h" +#import "ggml-backend-impl.h" + +#import "ggml-metal-impl.h" +#import "ggml-metal-common.h" +#import "ggml-metal-ops.h" + +#import + +#import + +#undef MIN +#undef MAX +#define MIN(a, b) ((a) < (b) ? (a) : (b)) +#define MAX(a, b) ((a) > (b) ? (a) : (b)) + +// max number of MTLCommandBuffer used to submit a graph for processing +#define GGML_METAL_MAX_COMMAND_BUFFERS 8 + +struct ggml_metal_command_buffer { + id obj; +}; + +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; + + dispatch_queue_t d_queue; + + // additional, inference-time compiled pipelines + ggml_metal_pipelines_t pipelines_ext; + + bool use_bfloat; + bool use_fusion; + bool use_concurrency; + bool use_graph_optimize; + + int debug_graph; + int debug_fusion; + + // how many times a given op was fused + uint64_t fuse_cnt[GGML_OP_COUNT]; + + // capture state + bool capture_next_compute; + bool capture_started; + + id capture_scope; + + // command buffer state + int n_cb; // number of extra threads used to submit the command buffers + int n_nodes_0; // number of nodes submitted by the main thread + int n_nodes_1; // remaining number of nodes submitted by the n_cb threads + int n_nodes_per_cb; + + struct ggml_cgraph * gf; + + // the callback given to the thread pool + void (^encode_async)(size_t ith); + + // n_cb command buffers + 1 used by the main thread + struct ggml_metal_command_buffer cmd_bufs[GGML_METAL_MAX_COMMAND_BUFFERS + 1]; + + // extra command buffers for things like getting, setting and copying tensors + NSMutableArray * cmd_bufs_ext; + + // the last command buffer queued into the Metal queue with operations relevant to the current Metal backend + id cmd_buf_last; + + // abort ggml_metal_graph_compute if callback returns true + ggml_abort_callback abort_callback; + void * abort_callback_data; +}; + +ggml_metal_t ggml_metal_init(ggml_metal_device_t dev) { + GGML_LOG_INFO("%s: allocating\n", __func__); + +#if TARGET_OS_OSX && !GGML_METAL_NDEBUG + // Show all the Metal device instances in the system + NSArray * devices = MTLCopyAllDevices(); + for (id device in devices) { + GGML_LOG_INFO("%s: found device: %s\n", __func__, [[device name] UTF8String]); + } + [devices release]; // since it was created by a *Copy* C method +#endif + + // init context + ggml_metal_t res = calloc(1, sizeof(struct ggml_metal)); + + res->device = ggml_metal_device_get_obj(dev); + + GGML_LOG_INFO("%s: picking default device: %s\n", __func__, [[res->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) { + GGML_LOG_ERROR("%s: error: failed to create command queue\n", __func__); + return NULL; + } + + res->dev = dev; + res->lib = ggml_metal_device_get_library(dev); + if (res->lib == NULL) { + GGML_LOG_WARN("%s: the device does not have a precompiled Metal library - this is unexpected\n", __func__); + GGML_LOG_WARN("%s: will try to compile it on the fly\n", __func__); + + res->lib = ggml_metal_library_init(dev); + if (res->lib == NULL) { + GGML_LOG_ERROR("%s: error: failed to initialize the Metal library\n", __func__); + + free(res); + + return NULL; + } + } + + const struct ggml_metal_device_props * props_dev = ggml_metal_device_get_props(dev); + + res->d_queue = dispatch_queue_create("ggml-metal", DISPATCH_QUEUE_CONCURRENT); + + res->use_bfloat = props_dev->has_bfloat; + res->use_fusion = getenv("GGML_METAL_FUSION_DISABLE") == nil; + res->use_concurrency = getenv("GGML_METAL_CONCURRENCY_DISABLE") == nil; + + { + const char * val = getenv("GGML_METAL_GRAPH_DEBUG"); + res->debug_graph = val ? atoi(val) : 0; + } + + { + const char * val = getenv("GGML_METAL_FUSION_DEBUG"); + res->debug_fusion = val ? atoi(val) : 0; + } + + res->use_graph_optimize = true; + + if (getenv("GGML_METAL_GRAPH_OPTIMIZE_DISABLE") != NULL) { + res->use_graph_optimize = false; + } + + memset(res->fuse_cnt, 0, sizeof(res->fuse_cnt)); + + GGML_LOG_INFO("%s: use bfloat = %s\n", __func__, res->use_bfloat ? "true" : "false"); + GGML_LOG_INFO("%s: use fusion = %s\n", __func__, res->use_fusion ? "true" : "false"); + GGML_LOG_INFO("%s: use concurrency = %s\n", __func__, res->use_concurrency ? "true" : "false"); + GGML_LOG_INFO("%s: use graph optimize = %s\n", __func__, res->use_graph_optimize ? "true" : "false"); + + res->capture_next_compute = false; + res->capture_started = false; + res->capture_scope = nil; + + res->gf = nil; + res->encode_async = nil; + for (int i = 0; i < GGML_METAL_MAX_COMMAND_BUFFERS; ++i) { + res->cmd_bufs[i].obj = nil; + } + + res->cmd_bufs_ext = [[NSMutableArray alloc] init]; + + res->cmd_buf_last = nil; + + res->pipelines_ext = ggml_metal_pipelines_init(); + + return res; +} + +void ggml_metal_free(ggml_metal_t ctx) { + GGML_LOG_INFO("%s: deallocating\n", __func__); + + for (int i = 0; i < GGML_METAL_MAX_COMMAND_BUFFERS; ++i) { + if (ctx->cmd_bufs[i].obj) { + [ctx->cmd_bufs[i].obj release]; + } + } + + for (int i = 0; i < (int) ctx->cmd_bufs_ext.count; ++i) { + if (ctx->cmd_bufs_ext[i]) { + [ctx->cmd_bufs_ext[i] release]; + } + } + + [ctx->cmd_bufs_ext removeAllObjects]; + [ctx->cmd_bufs_ext release]; + + if (ctx->pipelines_ext) { + ggml_metal_pipelines_free(ctx->pipelines_ext); + ctx->pipelines_ext = nil; + } + + if (ctx->debug_fusion > 0) { + GGML_LOG_DEBUG("%s: fusion stats:\n", __func__); + for (int i = 0; i < GGML_OP_COUNT; i++) { + if (ctx->fuse_cnt[i] == 0) { + continue; + } + + // note: cannot use ggml_log here + GGML_LOG_DEBUG("%s: - %s: %" PRIu64 "\n", __func__, ggml_op_name((enum ggml_op) i), ctx->fuse_cnt[i]); + } + } + + Block_release(ctx->encode_async); + + //[ctx->queue release]; // [TAG_QUEUE_PER_BACKEND] + + dispatch_release(ctx->d_queue); + + free(ctx); +} + +void ggml_metal_synchronize(ggml_metal_t ctx) { + // wait for any backend operations to finish + if (ctx->cmd_buf_last) { + [ctx->cmd_buf_last waitUntilCompleted]; + ctx->cmd_buf_last = nil; + } + + // release any completed command buffers + if (ctx->cmd_bufs_ext.count > 0) { + for (size_t i = 0; i < ctx->cmd_bufs_ext.count; ++i) { + id cmd_buf = ctx->cmd_bufs_ext[i]; + + MTLCommandBufferStatus status = [cmd_buf status]; + if (status != MTLCommandBufferStatusCompleted) { + GGML_LOG_ERROR("%s: error: command buffer %d failed with status %d\n", __func__, (int) i, (int) status); + if (status == MTLCommandBufferStatusError) { + GGML_LOG_ERROR("error: %s\n", [[cmd_buf error].localizedDescription UTF8String]); + } + GGML_ABORT("fatal error"); + } + + [cmd_buf release]; + } + + [ctx->cmd_bufs_ext removeAllObjects]; + } +} + +static struct ggml_metal_buffer_id ggml_metal_get_buffer_id(const struct ggml_tensor * t) { + if (!t) { + return (struct ggml_metal_buffer_id) { nil, 0 }; + } + + ggml_backend_buffer_t buffer = t->view_src ? t->view_src->buffer : t->buffer; + + return ggml_metal_buffer_get_id(buffer->context, t); +} + +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 + length:size + options:MTLResourceStorageModeShared]; + + struct ggml_metal_buffer_id bid_dst = ggml_metal_get_buffer_id(tensor); + if (bid_dst.metal == nil) { + GGML_ABORT("%s: failed to find buffer for tensor '%s'\n", __func__, tensor->name); + } + + bid_dst.offs += offset; + + // 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 commandBufferWithUnretainedReferences]; + id encoder = [cmd_buf blitCommandEncoder]; + + [encoder copyFromBuffer:buf_src + sourceOffset:0 + toBuffer:bid_dst.metal + destinationOffset:bid_dst.offs + size:size]; + + [encoder endEncoding]; + [cmd_buf commit]; + + // do not wait here for completion + //[cmd_buf waitUntilCompleted]; + + // instead, remember a reference to the command buffer and wait for it later if needed + [ctx->cmd_bufs_ext addObject:cmd_buf]; + ctx->cmd_buf_last = cmd_buf; + + [cmd_buf retain]; + } +} + +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 + length:size + options:MTLResourceStorageModeShared + deallocator:nil]; + + struct ggml_metal_buffer_id bid_src = ggml_metal_get_buffer_id(tensor); + if (bid_src.metal == nil) { + GGML_ABORT("%s: failed to find buffer for tensor '%s'\n", __func__, tensor->name); + } + + bid_src.offs += offset; + + // 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 commandBufferWithUnretainedReferences]; + id encoder = [cmd_buf blitCommandEncoder]; + + [encoder copyFromBuffer:bid_src.metal + sourceOffset:bid_src.offs + toBuffer:buf_dst + destinationOffset:0 + size:size]; + + [encoder endEncoding]; + [cmd_buf commit]; + + // do not wait here for completion + //[cmd_buf waitUntilCompleted]; + + // instead, remember a reference to the command buffer and wait for it later if needed + [ctx->cmd_bufs_ext addObject:cmd_buf]; + ctx->cmd_buf_last = cmd_buf; + + [cmd_buf retain]; + } +} + +enum ggml_status ggml_metal_graph_compute(ggml_metal_t ctx, struct ggml_cgraph * gf) { + // number of nodes encoded by the main thread (empirically determined) + const int n_main = 64; + + // number of threads in addition to the main thread + const int n_cb = ctx->n_cb; + + // 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 + // each thread creates it's own command buffer and enqueues the ops in parallel + // + // tests on M1 Pro and M2 Ultra using LLaMA models, show that optimal values for n_cb are 1 or 2 + + @autoreleasepool { + ctx->gf = gf; + + ctx->n_nodes_0 = MIN(n_main, gf->n_nodes); + ctx->n_nodes_1 = gf->n_nodes - ctx->n_nodes_0; + + ctx->n_nodes_per_cb = (ctx->n_nodes_1 + ctx->n_cb - 1) / ctx->n_cb; + + const bool use_capture = ctx->capture_next_compute; + if (use_capture) { + ctx->capture_next_compute = false; + + // make sure all previous computations have finished before starting the capture + if (ctx->cmd_buf_last) { + [ctx->cmd_buf_last waitUntilCompleted]; + ctx->cmd_buf_last = nil; + } + + if (!ctx->capture_started) { + // create capture scope + ctx->capture_scope = [[MTLCaptureManager sharedCaptureManager] newCaptureScopeWithDevice:ctx->device]; + + MTLCaptureDescriptor * descriptor = [MTLCaptureDescriptor new]; + descriptor.captureObject = ctx->capture_scope; + descriptor.destination = MTLCaptureDestinationGPUTraceDocument; + descriptor.outputURL = [NSURL fileURLWithPath:[NSString stringWithFormat:@"/tmp/perf-metal.gputrace"]]; + + NSError * error = nil; + if (![[MTLCaptureManager sharedCaptureManager] startCaptureWithDescriptor:descriptor error:&error]) { + GGML_LOG_ERROR("%s: error: unable to start capture '%s'\n", __func__, [[error localizedDescription] UTF8String]); + } else { + [ctx->capture_scope beginScope]; + ctx->capture_started = true; + } + } + } + + // the main thread commits the first few commands immediately + // cmd_buf[n_cb] + { + id cmd_buf = [ctx->queue commandBufferWithUnretainedReferences]; + [cmd_buf retain]; + + if (ctx->cmd_bufs[n_cb].obj) { + [ctx->cmd_bufs[n_cb].obj release]; + } + ctx->cmd_bufs[n_cb].obj = cmd_buf; + + [cmd_buf enqueue]; + + ctx->encode_async(n_cb); + } + + // remember the command buffer for the next iteration + ctx->cmd_buf_last = ctx->cmd_bufs[n_cb].obj; + + // 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]; + [cmd_buf retain]; + + if (ctx->cmd_bufs[cb_idx].obj) { + [ctx->cmd_bufs[cb_idx].obj release]; + } + ctx->cmd_bufs[cb_idx].obj = cmd_buf; + + // always enqueue the first two command buffers + // enqueue all of the command buffers if we don't need to abort + if (cb_idx < 2 || ctx->abort_callback == NULL) { + [cmd_buf enqueue]; + + // update the pointer to the last queued command buffer + // this is needed to implement synchronize() + ctx->cmd_buf_last = cmd_buf; + } + } + + dispatch_apply(n_cb, ctx->d_queue, ctx->encode_async); + + // for debugging: block until graph is computed + //[ctx->cmd_buf_last waitUntilCompleted]; + + // enter here only when capturing in order to wait for all computation to finish + // otherwise, we leave the graph to compute asynchronously + if (!use_capture && ctx->capture_started) { + // wait for completion and check status of each command buffer + // needed to detect if the device ran out-of-memory for example (#1881) + { + id cmd_buf = ctx->cmd_bufs[n_cb].obj; + [cmd_buf waitUntilCompleted]; + + MTLCommandBufferStatus status = [cmd_buf status]; + if (status != MTLCommandBufferStatusCompleted) { + GGML_LOG_INFO("%s: command buffer %d failed with status %lu\n", __func__, n_cb, status); + if (status == MTLCommandBufferStatusError) { + GGML_LOG_INFO("error: %s\n", [[cmd_buf error].localizedDescription UTF8String]); + } + + return GGML_STATUS_FAILED; + } + } + + for (int i = 0; i < n_cb; ++i) { + id cmd_buf = ctx->cmd_bufs[i].obj; + [cmd_buf waitUntilCompleted]; + + MTLCommandBufferStatus status = [cmd_buf status]; + if (status != MTLCommandBufferStatusCompleted) { + GGML_LOG_INFO("%s: command buffer %d failed with status %lu\n", __func__, i, status); + if (status == MTLCommandBufferStatusError) { + GGML_LOG_INFO("error: %s\n", [[cmd_buf error].localizedDescription UTF8String]); + } + + return GGML_STATUS_FAILED; + } + + id next_buffer = (i + 1 < n_cb ? ctx->cmd_bufs[i + 1].obj : nil); + if (!next_buffer) { + continue; + } + + const bool next_queued = ([next_buffer status] != MTLCommandBufferStatusNotEnqueued); + if (next_queued) { + continue; + } + + if (ctx->abort_callback && ctx->abort_callback(ctx->abort_callback_data)) { + GGML_LOG_INFO("%s: command buffer %d aborted", __func__, i); + return GGML_STATUS_ABORTED; + } + + [next_buffer commit]; + } + + [ctx->capture_scope endScope]; + [[MTLCaptureManager sharedCaptureManager] stopCapture]; + } + } + + return GGML_STATUS_SUCCESS; +} + +void ggml_metal_graph_optimize(ggml_metal_t ctx, struct ggml_cgraph * gf) { + //const int64_t t_start = ggml_time_us(); + + if (ctx->use_graph_optimize) { + ggml_graph_optimize(gf); + } + + //printf("%s: graph optimize took %.3f ms\n", __func__, (ggml_time_us() - t_start) / 1000.0); +} + +void ggml_metal_set_n_cb(ggml_metal_t ctx, int n_cb) { + if (ctx->n_cb != n_cb) { + ctx->n_cb = MIN(n_cb, GGML_METAL_MAX_COMMAND_BUFFERS); + + if (ctx->n_cb > 2) { + GGML_LOG_WARN("%s: n_cb = %d, using n_cb > 2 is not recommended and can degrade the performance in some cases\n", __func__, n_cb); + } + } + + if (ctx->encode_async) { + Block_release(ctx->encode_async); + } + + ctx->encode_async = Block_copy(^(size_t iter) { + const int cb_idx = iter; + const int n_cb_l = ctx->n_cb; + + const int n_nodes_0 = ctx->n_nodes_0; + const int n_nodes_1 = ctx->n_nodes_1; + + const int n_nodes_per_cb = ctx->n_nodes_per_cb; + + int idx_start = 0; + int idx_end = n_nodes_0; + + if (cb_idx < n_cb_l) { + idx_start = n_nodes_0 + ( (cb_idx + 0) * n_nodes_per_cb); + idx_end = n_nodes_0 + (MIN((cb_idx == n_cb_l - 1) ? n_nodes_1 : (cb_idx + 1) * n_nodes_per_cb, n_nodes_1)); + } + + id cmd_buf = ctx->cmd_bufs[cb_idx].obj; + + ggml_metal_op_t ctx_op = ggml_metal_op_init( + ctx->dev, + cmd_buf, + ctx->gf, + idx_start, + idx_end, + ctx->use_fusion, + ctx->use_concurrency, + ctx->capture_next_compute, + ctx->debug_graph, + ctx->debug_fusion); + + for (int idx = idx_start; idx < idx_end;) { + const int res = ggml_metal_op_encode(ctx_op, idx); + if (res == 0) { + break; + } + + idx += res; + } + + ggml_metal_op_free(ctx_op); + + if (cb_idx < 2 || ctx->abort_callback == NULL) { + [cmd_buf commit]; + } + }); +} + +void ggml_metal_set_abort_callback(ggml_metal_t ctx, ggml_abort_callback abort_callback, void * user_data) { + ctx->abort_callback = abort_callback; + ctx->abort_callback_data = user_data; +} + +bool ggml_metal_supports_family(ggml_metal_t ctx, int family) { + GGML_ASSERT(ctx->device != nil); + + return [ctx->device supportsFamily:(MTLGPUFamilyApple1 + family - 1)]; +} + +void ggml_metal_capture_next_compute(ggml_metal_t ctx) { + ctx->capture_next_compute = true; +} diff --git a/ggml/src/ggml-metal/ggml-metal-device.cpp b/ggml/src/ggml-metal/ggml-metal-device.cpp new file mode 100644 index 0000000000..5f04789967 --- /dev/null +++ b/ggml/src/ggml-metal/ggml-metal-device.cpp @@ -0,0 +1,1366 @@ +#include "ggml-metal-device.h" + +#include "ggml-metal-impl.h" + +#include "ggml-impl.h" + +#include +#include +#include +#include + +struct ggml_metal_device_deleter { + void operator()(ggml_metal_device_t ctx) { + ggml_metal_device_free(ctx); + } +}; + +typedef std::unique_ptr ggml_metal_device_ptr; + +ggml_metal_device_t ggml_metal_device_get(void) { + static ggml_metal_device_ptr ctx { ggml_metal_device_init() }; + + return ctx.get(); +} + +struct ggml_metal_pipelines { + std::unordered_map data; +}; + +ggml_metal_pipelines_t ggml_metal_pipelines_init(void) { + ggml_metal_pipelines_t res = new ggml_metal_pipelines(); + + return res; +} + +void ggml_metal_pipelines_free(ggml_metal_pipelines_t ppls) { + for (auto it = ppls->data.begin(); it != ppls->data.end(); ++it) { + ggml_metal_pipeline_free(it->second); + } + + delete ppls; +} + +void ggml_metal_pipelines_add(ggml_metal_pipelines_t ppls, const char * name, ggml_metal_pipeline_t pipeline) { + ppls->data[name] = pipeline; +} + +ggml_metal_pipeline_t ggml_metal_pipelines_get(ggml_metal_pipelines_t ppls, const char * name) { + 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) { + char base[256]; + char name[256]; + + const char * op_str = "undefined"; + switch (op) { + case GGML_OP_ADD_ID: op_str = "add_id"; break; + case GGML_OP_CONCAT: op_str = "concat"; break; + default: GGML_ABORT("fatal error"); + }; + + 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; + } + + 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) { + 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; + } + + 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_ASSERT(ggml_is_contiguous(op->src[0])); + GGML_ASSERT(op->src[0]->type == GGML_TYPE_F32 && op->src[0]->type == op->type); + + const char * pool_str = "undefined"; + switch (op_pool) { + case GGML_OP_POOL_AVG: pool_str = "avg"; break; + case GGML_OP_POOL_MAX: pool_str = "max"; break; + default: GGML_ASSERT(false && "not implemented"); + }; + + char base[256]; + char name[256]; + + 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; + } + + 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) { + 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; + } + + 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 tdst) { + char base[256]; + char name[256]; + + snprintf(base, 256, "kernel_set_rows_%s", 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; + } + + 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) { + 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; + } + + 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_ASSERT(ggml_is_contiguous(op->src[0])); + + char base[256]; + char name[256]; + + const int64_t n = ggml_nelements(op); + + const char * op_str = "undefined"; + switch (op->op) { + case GGML_OP_SCALE: op_str = "scale"; 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; + case GGML_OP_SIN: op_str = "sin"; break; + case GGML_OP_COS: op_str = "cos"; break; + case GGML_OP_LOG: op_str = "log"; break; + case GGML_OP_LEAKY_RELU: op_str = "leaky_relu"; break; + case GGML_OP_UNARY: + switch (ggml_get_unary_op(op)) { + case GGML_UNARY_OP_TANH: op_str = "tanh"; break; + case GGML_UNARY_OP_RELU: op_str = "relu"; break; + case GGML_UNARY_OP_SIGMOID: op_str = "sigmoid"; break; + case GGML_UNARY_OP_GELU: op_str = "gelu"; break; + case GGML_UNARY_OP_GELU_ERF: op_str = "gelu_erf"; break; + case GGML_UNARY_OP_GELU_QUICK: op_str = "gelu_quick"; break; + case GGML_UNARY_OP_SILU: op_str = "silu"; break; + case GGML_UNARY_OP_ELU: op_str = "elu"; break; + case GGML_UNARY_OP_NEG: op_str = "neg"; break; + case GGML_UNARY_OP_ABS: op_str = "abs"; break; + case GGML_UNARY_OP_SGN: op_str = "sgn"; break; + case GGML_UNARY_OP_STEP: op_str = "step"; break; + 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; + default: GGML_ABORT("fatal error"); + } break; + default: GGML_ABORT("fatal error"); + }; + + const char * suffix = ""; + if (n % 4 == 0) { + suffix = "_4"; + } + + 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; + } + + 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_ASSERT(ggml_is_contiguous_1(op->src[0])); + + char base[256]; + char name[256]; + + const char * op_str = "undefined"; + switch (op->op) { + case GGML_OP_GLU: + switch (ggml_get_glu_op(op)) { + case GGML_GLU_OP_REGLU: op_str = "reglu"; break; + case GGML_GLU_OP_GEGLU: op_str = "geglu"; break; + case GGML_GLU_OP_SWIGLU: op_str = "swiglu"; break; + case GGML_GLU_OP_SWIGLU_OAI: op_str = "swiglu_oai"; break; + case GGML_GLU_OP_GEGLU_ERF: op_str = "geglu_erf"; break; + case GGML_GLU_OP_GEGLU_QUICK: op_str = "geglu_quick"; break; + default: GGML_ABORT("fatal error"); + } break; + default: GGML_ABORT("fatal error"); + }; + + 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; + } + + 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_ASSERT(op->src[0]->nb[0] == ggml_type_size(op->src[0]->type)); + + char base[256]; + char name[256]; + + const char * op_str = "undefined"; + switch (op->op) { + case GGML_OP_SUM_ROWS: + op_str = "sum_rows"; break; + case GGML_OP_MEAN: + op_str = "mean"; break; + default: GGML_ABORT("fatal error"); + }; + + 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; + } + + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + + ggml_metal_pipeline_set_smem(res, 32*sizeof(float)); + + return res; +} + +ggml_metal_pipeline_t 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]; + char name[256]; + + const char * suffix = ""; + + if (op->src[0]->ne[0] % 4 == 0) { + suffix = "_4"; + } + + const ggml_type tsrc1 = op->src[1] ? op->src[1]->type : GGML_TYPE_F32; + + 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; + } + + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + + ggml_metal_pipeline_set_smem(res, 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_ASSERT(op->src[0]->type == GGML_TYPE_F32); + GGML_ASSERT(op->src[1]->type == GGML_TYPE_F32); + + GGML_ASSERT(ggml_is_contiguous(op->src[0])); + GGML_ASSERT(ggml_is_contiguous(op->src[1])); + + char base[256]; + char name[256]; + + snprintf(base, 256, "kernel_ssm_conv_%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; + } + + 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) { + char base[256]; + char name[256]; + + if (op->src[3]->ne[0] == 1) { + snprintf(base, 256, "kernel_ssm_scan_group_%s", ggml_type_name(op->src[0]->type)); + } else { + snprintf(base, 256, "kernel_ssm_scan_%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; + } + + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + + ggml_metal_pipeline_set_smem(res, 32*sizeof(float)); + + return res; +} + +ggml_metal_pipeline_t ggml_metal_library_get_pipeline_rwkv(ggml_metal_library_t lib, const ggml_tensor * op) { + char base[256]; + char name[256]; + + const int64_t C = op->ne[0]; + const int64_t H = op->src[0]->ne[1]; + + switch (op->op) { + case GGML_OP_RWKV_WKV6: + { + GGML_ASSERT(op->src[5]->type == GGML_TYPE_F32); + GGML_ASSERT(C % H == 0); + GGML_ASSERT(C / H == 64); + + snprintf(base, 256, "kernel_rwkv_wkv6_%s", ggml_type_name(op->src[0]->type)); + } break; + case GGML_OP_RWKV_WKV7: + { + GGML_ASSERT(op->src[6]->type == GGML_TYPE_F32); + GGML_ASSERT(C % H == 0); + GGML_ASSERT(C / H == 64); + + snprintf(base, 256, "kernel_rwkv_wkv7_%s", ggml_type_name(op->src[0]->type)); + } break; + default: + GGML_ABORT("fatal error"); + } + + snprintf(name, 256, "%s", base); + + ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); + if (res) { + return res; + } + + 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 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", base); + + ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); + if (res) { + return res; + } + + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + + return res; +} + +ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mm(ggml_metal_library_t lib, ggml_type tsrc0, ggml_type tsrc1) { + char base[256]; + char name[256]; + + snprintf(base, 256, "kernel_mul_mm_%s_%s", ggml_type_name(tsrc0), ggml_type_name(tsrc1)); + snprintf(name, 256, "%s", base); + + ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); + if (res) { + return res; + } + + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + + ggml_metal_pipeline_set_smem(res, 8192); + + return res; +} + +ggml_metal_pipeline_t 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); + + char base[256]; + char name[256]; + + int nsg = 0; // number of simdgroups + int nr0 = 0; // number of src0 rows per simdgroup + int nr1 = 1; // number of src1 rows per threadgroup + + size_t smem = 0; // shared memory + + const ggml_type tsrc0 = op->src[0]->type; + const ggml_type tsrc1 = op->src[1]->type; + + const char * suffix = ""; + + // use custom matrix x vector kernel + switch (tsrc0) { + case GGML_TYPE_F32: + { + GGML_ASSERT(op->src[1]->type == GGML_TYPE_F32); + + nsg = 1; + nr0 = 1; + nr1 = 4; + if (ne00 == 4) { + nr0 = 32; + suffix = "_c4"; + } + } break; + case GGML_TYPE_F16: + case GGML_TYPE_BF16: + { + nsg = 1; + nr0 = 1; + if (op->src[1]->type == GGML_TYPE_F32) { + if (ne00 == 4) { + nr0 = 32; + nr1 = 4; + suffix = "_c4"; + } else if (ne11 * ne12 < 4) { + suffix = "_1row"; + } else if (ne00 >= 128 && ne01 >= 8 && ne00%4 == 0) { + suffix = "_l4"; + nr1 = ne11; + } else { + nr1 = 4; + } + } else { + nr1 = 4; + } + } break; + case GGML_TYPE_Q4_0: + { + nsg = N_SG_Q4_0; + nr0 = N_R0_Q4_0; + } break; + case GGML_TYPE_Q4_1: + { + nsg = N_SG_Q4_1; + nr0 = N_R0_Q4_1; + } break; + case GGML_TYPE_Q5_0: + { + nsg = N_SG_Q5_0; + nr0 = N_R0_Q5_0; + } break; + case GGML_TYPE_Q5_1: + { + nsg = N_SG_Q5_1; + nr0 = N_R0_Q5_1; + } break; + case GGML_TYPE_Q8_0: + { + nsg = N_SG_Q8_0; + nr0 = N_R0_Q8_0; + smem = 32*sizeof(float)*N_R0_Q8_0; + } break; + case GGML_TYPE_MXFP4: + { + nsg = N_SG_MXFP4; + nr0 = N_R0_MXFP4; + smem = 32*sizeof(float); + } break; + case GGML_TYPE_Q2_K: + { + nsg = N_SG_Q2_K; + nr0 = N_R0_Q2_K; + } break; + case GGML_TYPE_Q3_K: + { + nsg = N_SG_Q3_K; + nr0 = N_R0_Q3_K; + } break; + case GGML_TYPE_Q4_K: + { + nsg = N_SG_Q4_K; + nr0 = N_R0_Q4_K; + } break; + case GGML_TYPE_Q5_K: + { + nsg = N_SG_Q5_K; + nr0 = N_R0_Q5_K; + } break; + case GGML_TYPE_Q6_K: + { + nsg = N_SG_Q6_K; + nr0 = N_R0_Q6_K; + } break; + case GGML_TYPE_IQ2_XXS: + { + nsg = N_SG_IQ2_XXS; + nr0 = N_R0_IQ2_XXS; + smem = 256*8+128; + } break; + case GGML_TYPE_IQ2_XS: + { + nsg = N_SG_IQ2_XS; + nr0 = N_R0_IQ2_XS; + smem = 512*8+128; + } break; + case GGML_TYPE_IQ3_XXS: + { + nsg = N_SG_IQ3_XXS; + nr0 = N_R0_IQ3_XXS; + smem = 256*4+128; + } break; + case GGML_TYPE_IQ3_S: + { + nsg = N_SG_IQ3_S; + nr0 = N_R0_IQ3_S; + smem = 512*4; + } break; + case GGML_TYPE_IQ2_S: + { + nsg = N_SG_IQ2_S; + nr0 = N_R0_IQ2_S; + } break; + case GGML_TYPE_IQ1_S: + { + nsg = N_SG_IQ1_S; + nr0 = N_R0_IQ1_S; + } break; + case GGML_TYPE_IQ1_M: + { + nsg = N_SG_IQ1_M; + nr0 = N_R0_IQ1_M; + } break; + case GGML_TYPE_IQ4_NL: + { + nsg = N_SG_IQ4_NL; + nr0 = N_R0_IQ4_NL; + smem = 32*sizeof(float); + } break; + case GGML_TYPE_IQ4_XS: + { + nsg = N_SG_IQ4_XS; + nr0 = N_R0_IQ4_XS; + smem = 32*sizeof(float); + } break; + default: + { + GGML_LOG_ERROR("Asserting on type %d\n", (int) tsrc0); + GGML_ABORT("not implemented"); + } + }; + + snprintf(base, 256, "kernel_mul_mv_%s_%s%s", ggml_type_name(tsrc0), 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; + } + + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + + 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); + + return res; +} + +ggml_metal_pipeline_t 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", base); + + ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); + if (res) { + return res; + } + + 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); + + return res; +} + +ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mm_id(ggml_metal_library_t lib, ggml_type tsrc0, ggml_type tsrc1) { + char base[256]; + char name[256]; + + snprintf(base, 256, "kernel_mul_mm_id_%s_%s", ggml_type_name(tsrc0), ggml_type_name(tsrc1)); + snprintf(name, 256, "%s", base); + + ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); + if (res) { + return res; + } + + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + + ggml_metal_pipeline_set_smem(res, 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_TENSOR_LOCALS( int32_t, ne0, op->src[0], ne); + GGML_TENSOR_LOCALS( int32_t, ne1, op->src[1], ne); + + char base[256]; + char name[256]; + + int nsg = 0; // number of simdgroups + int nr0 = 0; // number of src0 rows per simdgroup + int nr1 = 1; // number of src1 rows per threadgroup + + size_t smem = 0; // shared memory + + const ggml_type tsrc0 = op->src[0]->type; + const ggml_type tsrc1 = op->src[1]->type; + + // use custom matrix x vector kernel + switch (tsrc0) { + case GGML_TYPE_F32: + { + GGML_ASSERT(op->src[1]->type == GGML_TYPE_F32); + nsg = 1; + nr0 = 1; + } break; + case GGML_TYPE_F16: + { + GGML_ASSERT(op->src[1]->type == GGML_TYPE_F32); + nsg = 1; + nr0 = 1; + } break; + case GGML_TYPE_BF16: + { + GGML_ASSERT(op->src[1]->type == GGML_TYPE_F32); + nsg = 1; + nr0 = 1; + } break; + case GGML_TYPE_Q4_0: + { + nsg = N_SG_Q4_0; + nr0 = N_R0_Q4_0; + } break; + case GGML_TYPE_Q4_1: + { + nsg = N_SG_Q4_1; + nr0 = N_R0_Q4_1; + } break; + case GGML_TYPE_Q5_0: + { + nsg = N_SG_Q5_0; + nr0 = N_R0_Q5_0; + } break; + case GGML_TYPE_Q5_1: + { + nsg = N_SG_Q5_1; + nr0 = N_R0_Q5_1; + } break; + case GGML_TYPE_Q8_0: + { + nsg = N_SG_Q8_0; + nr0 = N_R0_Q8_0; + smem = 32*sizeof(float)*N_R0_Q8_0; + } break; + case GGML_TYPE_MXFP4: + { + nsg = N_SG_MXFP4; + nr0 = N_R0_MXFP4; + smem = 32*sizeof(float); + } break; + case GGML_TYPE_Q2_K: + { + nsg = N_SG_Q2_K; + nr0 = N_R0_Q2_K; + } break; + case GGML_TYPE_Q3_K: + { + nsg = N_SG_Q3_K; + nr0 = N_R0_Q3_K; + } break; + case GGML_TYPE_Q4_K: + { + nsg = N_SG_Q4_K; + nr0 = N_R0_Q4_K; + } break; + case GGML_TYPE_Q5_K: + { + nsg = N_SG_Q5_K; + nr0 = N_R0_Q5_K; + } break; + case GGML_TYPE_Q6_K: + { + nsg = N_SG_Q6_K; + nr0 = N_R0_Q6_K; + } break; + case GGML_TYPE_IQ2_XXS: + { + nsg = N_SG_IQ2_XXS; + nr0 = N_R0_IQ2_XXS; + smem = 256*8+128; + } break; + case GGML_TYPE_IQ2_XS: + { + nsg = N_SG_IQ2_XS; + nr0 = N_R0_IQ2_XS; + smem = 512*8+128; + } break; + case GGML_TYPE_IQ3_XXS: + { + nsg = N_SG_IQ3_XXS; + nr0 = N_R0_IQ3_XXS; + smem = 256*4+128; + } break; + case GGML_TYPE_IQ3_S: + { + nsg = N_SG_IQ3_S; + nr0 = N_R0_IQ3_S; + smem = 512*4; + } break; + case GGML_TYPE_IQ2_S: + { + nsg = N_SG_IQ2_S; + nr0 = N_R0_IQ2_S; + } break; + case GGML_TYPE_IQ1_S: + { + nsg = N_SG_IQ1_S; + nr0 = N_R0_IQ1_S; + } break; + case GGML_TYPE_IQ1_M: + { + nsg = N_SG_IQ1_M; + nr0 = N_R0_IQ1_M; + } break; + case GGML_TYPE_IQ4_NL: + { + nsg = N_SG_IQ4_NL; + nr0 = N_R0_IQ4_NL; + smem = 32*sizeof(float); + } break; + case GGML_TYPE_IQ4_XS: + { + nsg = N_SG_IQ4_XS; + nr0 = N_R0_IQ4_XS; + smem = 32*sizeof(float); + } break; + default: + { + GGML_LOG_ERROR("Asserting on type %d\n", (int)op->src[2]->type); + GGML_ABORT("not implemented"); + } + }; + + snprintf(base, 256, "kernel_mul_mv_id_%s_%s", ggml_type_name(tsrc0), ggml_type_name(tsrc1)); + snprintf(name, 256, "%s", base); + + ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); + if (res) { + return res; + } + + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + + 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); + + return res; +} + +ggml_metal_pipeline_t 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)); + + char base[256]; + char name[256]; + + 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; + } + + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + + ggml_metal_pipeline_set_smem(res, 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) { + assert(op->op == GGML_OP_ARGSORT); + + char base[256]; + char name[256]; + + ggml_sort_order order = (ggml_sort_order) op->op_params[0]; + + const char * order_str = "undefined"; + switch (order) { + case GGML_SORT_ORDER_ASC: order_str = "asc"; break; + case GGML_SORT_ORDER_DESC: order_str = "desc"; break; + default: GGML_ABORT("fatal error"); + }; + + 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; + } + + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + + return res; +} + +ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext( + ggml_metal_library_t lib, + const ggml_tensor * op, + bool has_mask, + bool has_sinks, + bool has_bias, + bool has_scap, + int32_t nsg) { + assert(op->op == GGML_OP_FLASH_ATTN_EXT); + + char base[256]; + char name[256]; + + const int32_t dk = (int32_t) op->src[1]->ne[0]; + const int32_t dv = (int32_t) op->src[2]->ne[0]; + + const int32_t ns10 = op->src[1]->nb[1]/op->src[1]->nb[0]; + const int32_t ns20 = op->src[2]->nb[1]/op->src[2]->nb[0]; + + snprintf(base, 256, "kernel_%s_%s_dk%d_dv%d", + "flash_attn_ext", + ggml_type_name(op->src[1]->type), + dk, + dv); + + snprintf(name, 256, "kernel_%s_%s_dk%d_dv%d_mask=%d_sinks=%d_bias=%d_scap=%d_ns10=%d_ns20=%d_nsg=%d", + "flash_attn_ext", + ggml_type_name(op->src[1]->type), + dk, + dv, + has_mask, + has_sinks, + has_bias, + has_scap, + ns10, + ns20, + nsg); + + ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); + if (res) { + return res; + } + + 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_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_library_t lib, + const ggml_tensor * op, + bool has_mask, + bool has_sinks, + bool has_bias, + bool has_scap, + int32_t nsg, + int32_t nwg) { + assert(op->op == GGML_OP_FLASH_ATTN_EXT); + + char base[256]; + char name[256]; + + const int32_t dk = (int32_t) op->src[1]->ne[0]; + const int32_t dv = (int32_t) op->src[2]->ne[0]; + + const int32_t ns10 = op->src[1]->nb[1]/op->src[1]->nb[0]; + const int32_t ns20 = op->src[2]->nb[1]/op->src[2]->nb[0]; + + snprintf(base, 256, "kernel_%s_%s_dk%d_dv%d", + "flash_attn_ext_vec", + ggml_type_name(op->src[1]->type), + dk, + dv); + + snprintf(name, 256, "kernel_%s_%s_dk%d_dv%d_mask=%d_sink=%d_bias=%d_softcap=%d_ns10=%d_ns20=%d_nsg=%d_nwg=%d", + "flash_attn_ext_vec", + ggml_type_name(op->src[1]->type), + dk, + dv, + has_mask, + has_sinks, + has_bias, + has_scap, + ns10, + ns20, + nsg, nwg); + + ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); + if (res) { + return res; + } + + 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_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_library_t lib, + const ggml_tensor * op, + int32_t dv, + int32_t nwg) { + assert(op->op == GGML_OP_FLASH_ATTN_EXT); + + char base[256]; + char name[256]; + + snprintf(base, 256, "kernel_flash_attn_ext_vec_reduce"); + snprintf(name, 256, "kernel_flash_attn_ext_vec_reduce_dv=%d_nwg=%d", dv, nwg); + + ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); + if (res) { + return res; + } + + 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_library_t lib, + ggml_op op, + int32_t n_fuse, + bool row) { + char base[256]; + char name[256]; + + const char * op_str = "undefined"; + switch (op) { + case GGML_OP_ADD: op_str = "add"; break; + case GGML_OP_SUB: op_str = "sub"; break; + case GGML_OP_MUL: op_str = "mul"; break; + case GGML_OP_DIV: op_str = "div"; break; + default: GGML_ABORT("fatal error"); + }; + + if (row) { + snprintf(base, 256, "kernel_%s_row_c4_fuse_%d", op_str, n_fuse); + } else { + snprintf(base, 256, "kernel_%s_fuse_%d", op_str, n_fuse); + } + + snprintf(name, 256, "%s", base); + + ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); + if (res) { + return res; + } + + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + + return res; +} + +ggml_metal_pipeline_t ggml_metal_library_get_pipeline_rms_norm(ggml_metal_library_t lib, const ggml_tensor * op, int32_t n_fuse) { + assert(op->op == GGML_OP_RMS_NORM); + + GGML_ASSERT(op->src[0]->ne[0] % 4 == 0); + GGML_ASSERT(ggml_is_contiguous_rows(op->src[0])); + + char base[256]; + char name[256]; + + switch (n_fuse) { + case 1: snprintf(base, 256, "kernel_rms_norm_f32"); break; + case 2: snprintf(base, 256, "kernel_rms_norm_mul_f32"); break; + case 3: snprintf(base, 256, "kernel_rms_norm_mul_add_f32"); break; + default: GGML_ABORT("fatal error"); + } + + snprintf(name, 256, "%s", base); + + ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); + if (res) { + return res; + } + + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + + ggml_metal_pipeline_set_smem(res, 32*sizeof(float)); + + return res; +} + +ggml_metal_pipeline_t 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); + GGML_ASSERT(ggml_is_contiguous_1(op->src[0])); + + char base[256]; + char name[256]; + + 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; + } + + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + + ggml_metal_pipeline_set_smem(res, 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) { + assert(op->op == GGML_OP_GROUP_NORM); + + GGML_ASSERT(ggml_is_contiguous(op->src[0])); + + char base[256]; + char name[256]; + + 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; + } + + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + + ggml_metal_pipeline_set_smem(res, 32*sizeof(float)); + + return res; +} + +ggml_metal_pipeline_t ggml_metal_library_get_pipeline_norm(ggml_metal_library_t lib, const ggml_tensor * op) { + assert(op->op == GGML_OP_NORM); + + GGML_ASSERT(op->src[0]->ne[0] % 4 == 0); + GGML_ASSERT(ggml_is_contiguous_1(op->src[0])); + + char base[256]; + char name[256]; + + snprintf(base, 256, "kernel_norm_f32"); + snprintf(name, 256, "%s", base); + + ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); + if (res) { + return res; + } + + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + + ggml_metal_pipeline_set_smem(res, 32*sizeof(float)); + + return res; +} + +ggml_metal_pipeline_t ggml_metal_library_get_pipeline_rope(ggml_metal_library_t lib, const ggml_tensor * op) { + assert(op->op == GGML_OP_ROPE); + + char base[256]; + char name[256]; + + const int mode = ((const int32_t *) op->op_params)[2]; + + const bool is_neox = mode & GGML_ROPE_TYPE_NEOX; + const bool is_mrope = mode & GGML_ROPE_TYPE_MROPE; + const bool is_vision = mode == GGML_ROPE_TYPE_VISION; + + if (is_neox) { + snprintf(base, 256, "kernel_rope_neox_%s", ggml_type_name(op->src[0]->type)); + } else if (is_mrope && !is_vision) { + GGML_ASSERT(op->src[1]->ne[0]*4 >= op->src[0]->ne[2]); // need at least 4 pos per token + snprintf(base, 256, "kernel_rope_multi_%s", ggml_type_name(op->src[0]->type)); + } else if (is_vision) { + GGML_ASSERT(op->src[1]->ne[0]*4 >= op->src[0]->ne[2]); // need at least 4 pos per token + snprintf(base, 256, "kernel_rope_vision_%s", ggml_type_name(op->src[0]->type)); + } else { + snprintf(base, 256, "kernel_rope_norm_%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; + } + + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + + return res; +} + +ggml_metal_pipeline_t 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])); + GGML_ASSERT(op->src[1]->type == GGML_TYPE_F32); + GGML_ASSERT(op->type == GGML_TYPE_F16 || op->type == GGML_TYPE_F32); + + char base[256]; + char name[256]; + + snprintf(base, 256, "kernel_im2col_ext_%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; + } + + 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) { + assert(op->op == GGML_OP_CONV_TRANSPOSE_1D); + + GGML_ASSERT(ggml_is_contiguous(op->src[0])); + GGML_ASSERT(ggml_is_contiguous(op->src[1])); + GGML_ASSERT(op->src[0]->type == GGML_TYPE_F16 || op->src[0]->type == GGML_TYPE_F32); + GGML_ASSERT(op->src[1]->type == GGML_TYPE_F32); + GGML_ASSERT(op->type == GGML_TYPE_F32); + + char base[256]; + char name[256]; + + 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; + } + + 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) { + assert(op->op == GGML_OP_UPSCALE); + + char base[256]; + char name[256]; + + 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; + } + + 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) { + assert(op->op == GGML_OP_PAD); + + char base[256]; + char name[256]; + + 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) { + return res; + } + + res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + + return res; +} + +ggml_metal_pipeline_t 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]; + char name[256]; + + 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; + } + + 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) { + assert(op->op == GGML_OP_ARANGE); + + char base[256]; + char name[256]; + + 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; + } + + 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) { + assert(op->op == GGML_OP_TIMESTEP_EMBEDDING); + + char base[256]; + char name[256]; + + 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; + } + + 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 new file mode 100644 index 0000000000..c48337f514 --- /dev/null +++ b/ggml/src/ggml-metal/ggml-metal-device.h @@ -0,0 +1,226 @@ +#pragma once + +#include "ggml.h" + +#ifdef __cplusplus +extern "C" { +#endif + +struct ggml_metal_buffer_id { + void * metal; // id + size_t offs; +}; + +typedef struct ggml_metal_device * ggml_metal_device_t; + +// +// MTLFunctionConstantValues wrapper +// + +typedef struct ggml_metal_cv * ggml_metal_cv_t; + +ggml_metal_cv_t ggml_metal_cv_init(void); +void ggml_metal_cv_free(ggml_metal_cv_t cv); + +void ggml_metal_cv_set_int32(ggml_metal_cv_t cv, int32_t value, int32_t idx); +void ggml_metal_cv_set_bool (ggml_metal_cv_t cv, bool value, int32_t idx); + +// +// MTLComputePipelineState wrapper +// + +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; + +ggml_metal_pipelines_t ggml_metal_pipelines_init(void); +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); + +// +// MTLCommandBuffer wrapper +// + +typedef void * ggml_metal_cmd_buf_t; + +// +// MTLComputeCommandEncoder wrapper +// + +typedef struct ggml_metal_encoder * ggml_metal_encoder_t; + +ggml_metal_encoder_t ggml_metal_encoder_init(ggml_metal_cmd_buf_t cmd_buf_raw, bool concurrent); +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_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); + +void ggml_metal_encoder_set_threadgroup_memory_size(ggml_metal_encoder_t encoder, size_t size, int idx); + +void ggml_metal_encoder_dispatch_threadgroups(ggml_metal_encoder_t encoder, int tg0, int tg1, int tg2, int tptg0, int tptg1, int tptg2); + +void ggml_metal_encoder_memory_barrier(ggml_metal_encoder_t encoder); + +void ggml_metal_encoder_end_encoding(ggml_metal_encoder_t encoder); + +// +// MTLLibrary wrapper +// + +typedef struct ggml_metal_library * ggml_metal_library_t; + +ggml_metal_library_t ggml_metal_library_init(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); + +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 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_rows (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 r1ptg); +ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mm (ggml_metal_library_t lib, enum ggml_type tsrc0, enum ggml_type tsrc1); +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, enum ggml_type tsrc0, enum ggml_type tsrc1); +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_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_rms_norm (ggml_metal_library_t lib, const struct ggml_tensor * op, int32_t n_fuse); +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); +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_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_flash_attn_ext( + ggml_metal_library_t lib, + const struct ggml_tensor * op, + bool has_mask, + bool has_sinks, + bool has_bias, + bool has_scap, + int32_t nsg); + +ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext_vec( + ggml_metal_library_t lib, + const struct ggml_tensor * op, + bool has_mask, + bool has_sinks, + bool has_bias, + bool has_scap, + int32_t nsg, + int32_t nwg); + +ggml_metal_pipeline_t 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); + +// +// device +// + +struct ggml_metal_device_props { + char name[128]; + + size_t max_buffer_size; + size_t max_working_set_size; + size_t max_theadgroup_memory_size; + + bool has_simdgroup_reduction; + bool has_simdgroup_mm; + bool has_unified_memory; + bool has_bfloat; + bool use_residency_sets; + bool use_shared_buffers; + + bool supports_gpu_family_apple7; +}; + +ggml_metal_device_t ggml_metal_device_init(void); +void ggml_metal_device_free(ggml_metal_device_t dev); + +// return a singleton that is automatically destroyed when the program exits +ggml_metal_device_t ggml_metal_device_get(void); + +void * ggml_metal_device_get_obj (ggml_metal_device_t dev); // id +void * ggml_metal_device_get_queue(ggml_metal_device_t dev); // id + +ggml_metal_library_t ggml_metal_device_get_library(ggml_metal_device_t dev); + +void ggml_metal_device_get_memory(ggml_metal_device_t dev, size_t * free, size_t * total); +bool ggml_metal_device_supports_op(ggml_metal_device_t dev, const struct ggml_tensor * op); + +const struct ggml_metal_device_props * ggml_metal_device_get_props(ggml_metal_device_t dev); + +// +// device buffers +// + +typedef struct ggml_metal_buffer * ggml_metal_buffer_t; + +ggml_metal_buffer_t ggml_metal_buffer_init(ggml_metal_device_t dev, size_t size, bool shared); +ggml_metal_buffer_t ggml_metal_buffer_map (ggml_metal_device_t dev, void * ptr, size_t size, size_t max_tensor_size); + +void ggml_metal_buffer_free (ggml_metal_buffer_t buf); +void * ggml_metal_buffer_get_base (ggml_metal_buffer_t buf); +bool ggml_metal_buffer_is_shared(ggml_metal_buffer_t buf); + +void ggml_metal_buffer_memset_tensor(ggml_metal_buffer_t buf, struct ggml_tensor * tensor, uint8_t value, size_t offset, size_t size); +void ggml_metal_buffer_set_tensor (ggml_metal_buffer_t buf, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size); +void ggml_metal_buffer_get_tensor (ggml_metal_buffer_t buf, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size); +void ggml_metal_buffer_clear (ggml_metal_buffer_t buf, uint8_t value); + +// finds the Metal buffer that contains the tensor data on the GPU device +// the assumption is that there is 1-to-1 mapping between the host and device memory buffers, so we can find the +// Metal buffer based on the host memory pointer +// +struct ggml_metal_buffer_id ggml_metal_buffer_get_id(ggml_metal_buffer_t buf, const struct ggml_tensor * t); + +#ifdef __cplusplus +} +#endif diff --git a/ggml/src/ggml-metal/ggml-metal-device.m b/ggml/src/ggml-metal/ggml-metal-device.m new file mode 100644 index 0000000000..9983640b43 --- /dev/null +++ b/ggml/src/ggml-metal/ggml-metal-device.m @@ -0,0 +1,1289 @@ +#import "ggml-metal-device.h" + +#import "ggml-impl.h" +#import "ggml-threading.h" + +#include + +#include + +#ifndef TARGET_OS_VISION +#define TARGET_OS_VISION 0 +#endif + +// create residency sets only on macOS >= 15.0 +#if !TARGET_CPU_X86_64 && TARGET_OS_OSX && __MAC_OS_X_VERSION_MAX_ALLOWED >= 150000 || \ + TARGET_OS_IOS && __IPHONE_OS_VERSION_MAX_ALLOWED >= 180000 || \ + TARGET_OS_TV && __TV_OS_VERSION_MAX_ALLOWED >= 180000 || \ + TARGET_OS_VISION && __VISION_OS_VERSION_MAX_ALLOWED >= 200000 +#define GGML_METAL_HAS_RESIDENCY_SETS 1 +#endif + +// overload of MTLGPUFamilyMetal3 (not available in some environments) +static const NSInteger MTLGPUFamilyMetal3_GGML = 5001; + +#if !GGML_METAL_EMBED_LIBRARY +// Here to assist with NSBundle Path Hack +@interface GGMLMetalClass : NSObject +@end +@implementation GGMLMetalClass +@end +#endif + +// +// MTLFunctionConstantValues wrapper +// + +struct ggml_metal_cv { + MTLFunctionConstantValues * obj; +}; + +ggml_metal_cv_t ggml_metal_cv_init(void) { + ggml_metal_cv_t res = calloc(1, sizeof(struct ggml_metal_cv)); + + res->obj = [[MTLFunctionConstantValues alloc] init]; + + return res; +} + +void ggml_metal_cv_free(ggml_metal_cv_t cv) { + [cv->obj release]; + free(cv); +} + +void ggml_metal_cv_set_int32(ggml_metal_cv_t cv, int32_t value, int32_t idx) { + [cv->obj setConstantValue:&value type:MTLDataTypeInt atIndex:idx]; +} + +void ggml_metal_cv_set_bool(ggml_metal_cv_t cv, bool value, int32_t idx) { + [cv->obj setConstantValue:&value type:MTLDataTypeBool atIndex:idx]; +} + +// +// MTLComputePipelineState wrapper +// + +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) { + ggml_metal_pipeline_t res = calloc(1, sizeof(struct ggml_metal_pipeline)); + + *res = (struct ggml_metal_pipeline) { + /*.obj =*/ nil, + /*.nsg =*/ 0, + /*.nr0 =*/ 0, + /*.nr1 =*/ 0, + /*.smem =*/ 0, + }; + + return res; +} + +void ggml_metal_pipeline_free(ggml_metal_pipeline_t pipeline) { + [pipeline->obj release]; + + 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; +} + +struct ggml_metal_library { + id obj; + id device; + + ggml_metal_pipelines_t pipelines; // cache of compiled pipelines +}; + +ggml_metal_library_t ggml_metal_library_init(ggml_metal_device_t dev) { + id library = nil; + id device = ggml_metal_device_get_obj(dev); + + // load library + // + // - first check if the library is embedded + // - then check if the library is in the bundle + // - if not found, load the source and compile it + // - if that fails, return NULL + // + // TODO: move to a function + { + const int64_t t_start = ggml_time_us(); + + NSError * error = nil; + NSString * src = nil; + +#if GGML_METAL_EMBED_LIBRARY + GGML_LOG_INFO("%s: using embedded metal library\n", __func__); + + extern const char ggml_metallib_start[]; + extern const char ggml_metallib_end[]; + + src = [[NSString alloc] initWithBytes:ggml_metallib_start length:(ggml_metallib_end-ggml_metallib_start) encoding:NSUTF8StringEncoding]; +#else + +#ifdef SWIFT_PACKAGE + NSBundle * bundle = SWIFTPM_MODULE_BUNDLE; +#else + NSBundle * bundle = [NSBundle bundleForClass:[GGMLMetalClass class]]; +#endif + + NSString * path_lib = [bundle pathForResource:@"default" ofType:@"metallib"]; + if (path_lib == nil) { + // Try to find the resource in the directory where the current binary located. + NSString * bin_cur = [[NSProcessInfo processInfo] arguments][0]; + NSString * bin_dir = [bin_cur stringByDeletingLastPathComponent]; + + NSString * path_lib_default = [NSString pathWithComponents:@[bin_dir, @"default.metallib"]]; + if ([[NSFileManager defaultManager] isReadableFileAtPath:path_lib_default]) { + GGML_LOG_INFO("%s: found '%s'\n", __func__, [path_lib_default UTF8String]); + + NSDictionary * atts = [[NSFileManager defaultManager] attributesOfItemAtPath:path_lib_default error:&error]; + if (atts && atts[NSFileType] == NSFileTypeSymbolicLink) { + // Optionally, if this is a symlink, try to resolve it. + path_lib_default = [[NSFileManager defaultManager] destinationOfSymbolicLinkAtPath:path_lib_default error:&error]; + if (path_lib_default && [path_lib_default length] > 0 && ![[path_lib_default substringToIndex:1] isEqualToString:@"/"]) { + // It is a relative path, adding the binary directory as directory prefix. + path_lib_default = [NSString pathWithComponents:@[bin_dir, path_lib_default]]; + } + if (!path_lib_default || ![[NSFileManager defaultManager] isReadableFileAtPath:path_lib_default]) { + // Link to the resource could not be resolved. + path_lib_default = nil; + } else { + GGML_LOG_INFO("%s: symlink resolved '%s'\n", __func__, [path_lib_default UTF8String]); + } + } + } else { + // The resource couldn't be found in the binary's directory. + path_lib_default = nil; + } + + path_lib = path_lib_default; + } + + if (path_lib != nil) { + // pre-compiled library found + NSURL * libURL = [NSURL fileURLWithPath:path_lib]; + GGML_LOG_INFO("%s: loading '%s'\n", __func__, [path_lib UTF8String]); + + library = [device newLibraryWithURL:libURL error:&error]; + if (error) { + GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]); + return nil; + } + } else { + GGML_LOG_INFO("%s: default.metallib not found, loading from source\n", __func__); + + NSString * path_source; + NSString * path_resource = [[NSProcessInfo processInfo].environment objectForKey:@"GGML_METAL_PATH_RESOURCES"]; + + GGML_LOG_INFO("%s: GGML_METAL_PATH_RESOURCES = %s\n", __func__, path_resource ? [path_resource UTF8String] : "nil"); + + if (path_resource) { + path_source = [path_resource stringByAppendingPathComponent:@"ggml-metal.metal"]; + } else { + path_source = [bundle pathForResource:@"ggml-metal" ofType:@"metal"]; + } + + if (path_source == nil) { + GGML_LOG_WARN("%s: error: could not use bundle path to find ggml-metal.metal, falling back to trying cwd\n", __func__); + path_source = @"ggml-metal.metal"; + } + + GGML_LOG_INFO("%s: loading '%s'\n", __func__, [path_source UTF8String]); + + src = [NSString stringWithContentsOfFile:path_source encoding:NSUTF8StringEncoding error:&error]; + if (error) { + GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]); + return nil; + } + } +#endif + + if (!library) { + @autoreleasepool { + // dictionary of preprocessor macros + NSMutableDictionary * prep = [NSMutableDictionary dictionary]; + + if (ggml_metal_device_get_props(dev)->has_bfloat) { + [prep setObject:@"1" forKey:@"GGML_METAL_HAS_BF16"]; + } + +#if GGML_METAL_EMBED_LIBRARY + [prep setObject:@"1" forKey:@"GGML_METAL_EMBED_LIBRARY"]; +#endif + + MTLCompileOptions * options = [MTLCompileOptions new]; + options.preprocessorMacros = prep; + + //[options setFastMathEnabled:false]; + + library = [device newLibraryWithSource:src options:options error:&error]; + if (error) { + GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]); + return nil; + } + +#if !__has_feature(objc_arc) + [options release]; +#endif + } + } + +#if GGML_METAL_EMBED_LIBRARY + [src release]; +#endif // GGML_METAL_EMBED_LIBRARY + + GGML_LOG_INFO("%s: loaded in %.3f sec\n", __func__, (ggml_time_us() - t_start) / 1e6); + } + + ggml_metal_library_t res = calloc(1, sizeof(struct ggml_metal_library)); + + res->obj = library; + res->device = device; + res->pipelines = ggml_metal_pipelines_init(); + + return res; +} + +void ggml_metal_library_free(ggml_metal_library_t lib) { + if (!lib) { + return; + } + + if (lib->obj) { + [lib->obj release]; + } + + ggml_metal_pipelines_free(lib->pipelines); + + 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); +} + +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(); + + ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); + if (res) { + ggml_critical_section_end(); + + return res; + } + + res = ggml_metal_pipeline_init(); + + @autoreleasepool { + NSError * error = nil; + + NSString * base_func = [NSString stringWithUTF8String:base]; + + GGML_LOG_DEBUG("%s: compiling pipeline: base = '%s', name = '%s'\n", __func__, base, name); + + id mtl_function = [lib->obj newFunctionWithName:base_func constantValues:(cv ? cv->obj : nil) error:&error]; + if (!mtl_function) { + ggml_critical_section_end(); + + GGML_LOG_ERROR("%s: error: failed to compile pipeline: base = '%s', name = '%s'\n", __func__, base, name); + GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]); + + return nil; + } + + res->obj = [lib->device newComputePipelineStateWithFunction:mtl_function error:&error]; + + ggml_metal_pipelines_add(lib->pipelines, name, res); + + [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); + } + + ggml_critical_section_end(); + + return res; +} + +// +// MTLComputeCommandEncoder wrapper +// + +struct ggml_metal_encoder { + id obj; +}; + +ggml_metal_encoder_t ggml_metal_encoder_init(ggml_metal_cmd_buf_t cmd_buf_raw, bool concurrent) { + ggml_metal_encoder_t res = calloc(1, sizeof(struct ggml_metal_encoder)); + + id cmd_buf = (id) cmd_buf_raw; + + if (concurrent) { + res->obj = [cmd_buf computeCommandEncoderWithDispatchType: MTLDispatchTypeConcurrent]; + } else { + res->obj = [cmd_buf computeCommandEncoder]; + } + + [res->obj retain]; + + return res; +} + +void ggml_metal_encoder_free(ggml_metal_encoder_t encoder) { + [encoder->obj release]; + free(encoder); +} + +void ggml_metal_encoder_debug_group_push(ggml_metal_encoder_t encoder, const char * name) { + [encoder->obj pushDebugGroup:[NSString stringWithCString:name encoding:NSUTF8StringEncoding]]; +} + +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_bytes(ggml_metal_encoder_t encoder, void * data, size_t size, int idx) { + [encoder->obj setBytes:data length:size atIndex:idx]; +} + +void ggml_metal_encoder_set_buffer(ggml_metal_encoder_t encoder, struct ggml_metal_buffer_id buffer, int idx) { + [encoder->obj setBuffer:buffer.metal offset:buffer.offs atIndex:idx]; +} + +void ggml_metal_encoder_set_threadgroup_memory_size(ggml_metal_encoder_t encoder, size_t size, int idx) { + [encoder->obj setThreadgroupMemoryLength:size atIndex:idx]; +} + +void ggml_metal_encoder_dispatch_threadgroups(ggml_metal_encoder_t encoder, int tg0, int tg1, int tg2, int tptg0, int tptg1, int tptg2) { + [encoder->obj dispatchThreadgroups:MTLSizeMake(tg0, tg1, tg2) threadsPerThreadgroup:MTLSizeMake(tptg0, tptg1, tptg2)]; +} + +void ggml_metal_encoder_memory_barrier(ggml_metal_encoder_t encoder) { + [encoder->obj memoryBarrierWithScope:MTLBarrierScopeBuffers]; +} + +void ggml_metal_encoder_end_encoding(ggml_metal_encoder_t encoder) { + [encoder->obj endEncoding]; +} + +struct ggml_metal_device { + id mtl_device; + + // a single global queue shared by all Metal backends + // technically not needed for devices with unified memory, but enables discrete GPUs support + // ref: https://github.com/ggml-org/llama.cpp/pull/15906 + id mtl_queue; + + ggml_metal_library_t library; + + struct ggml_metal_device_props props; +}; + +ggml_metal_device_t ggml_metal_device_init(void) { + ggml_metal_device_t dev = calloc(1, sizeof(struct ggml_metal_device)); + + assert(dev != NULL); + + if (dev->mtl_device == nil) { + dev->mtl_device = MTLCreateSystemDefaultDevice(); + + if (dev->mtl_device) { + dev->mtl_queue = [dev->mtl_device newCommandQueue]; + if (dev->mtl_queue == nil) { + GGML_LOG_ERROR("%s: error: failed to create command queue\n", __func__); + } + + dev->props.has_simdgroup_reduction = [dev->mtl_device supportsFamily:MTLGPUFamilyApple7]; + dev->props.has_simdgroup_reduction |= [dev->mtl_device supportsFamily:MTLGPUFamilyMetal3_GGML]; + + dev->props.has_simdgroup_mm = [dev->mtl_device supportsFamily:MTLGPUFamilyApple7]; + dev->props.has_unified_memory = dev->mtl_device.hasUnifiedMemory; + + dev->props.has_bfloat = [dev->mtl_device supportsFamily:MTLGPUFamilyMetal3_GGML]; + dev->props.has_bfloat |= [dev->mtl_device supportsFamily:MTLGPUFamilyApple6]; + + dev->props.use_residency_sets = true; +#if defined(GGML_METAL_HAS_RESIDENCY_SETS) + dev->props.use_residency_sets = getenv("GGML_METAL_NO_RESIDENCY") == nil; +#endif + + dev->props.use_shared_buffers = dev->props.has_unified_memory; + + if (getenv("GGML_METAL_SHARED_BUFFERS_DISABLE") != NULL) { + dev->props.use_shared_buffers = false; + } + + dev->props.supports_gpu_family_apple7 = [dev->mtl_device supportsFamily:MTLGPUFamilyApple7]; + + dev->props.max_buffer_size = dev->mtl_device.maxBufferLength; + dev->props.max_working_set_size = dev->mtl_device.recommendedMaxWorkingSetSize; + dev->props.max_theadgroup_memory_size = dev->mtl_device.maxThreadgroupMemoryLength; + + strncpy(dev->props.name, [[dev->mtl_device name] UTF8String], sizeof(dev->props.name) - 1); + + dev->library = ggml_metal_library_init(dev); + if (!dev->library) { + GGML_LOG_ERROR("%s: error: failed to create library\n", __func__); + } + + // -------------------------------------------------- + + // print MTL GPU family: + GGML_LOG_INFO("%s: GPU name: %s\n", __func__, dev->props.name); + + // determine max supported GPU family + // https://developer.apple.com/metal/Metal-Shading-Language-Specification.pdf + // https://developer.apple.com/metal/Metal-Feature-Set-Tables.pdf + { + for (int i = MTLGPUFamilyApple1 + 20; i >= MTLGPUFamilyApple1; --i) { + if ([dev->mtl_device supportsFamily:i]) { + GGML_LOG_INFO("%s: GPU family: MTLGPUFamilyApple%d (%d)\n", __func__, i - (int) MTLGPUFamilyApple1 + 1, i); + break; + } + } + + for (int i = MTLGPUFamilyCommon1 + 5; i >= MTLGPUFamilyCommon1; --i) { + if ([dev->mtl_device supportsFamily:i]) { + GGML_LOG_INFO("%s: GPU family: MTLGPUFamilyCommon%d (%d)\n", __func__, i - (int) MTLGPUFamilyCommon1 + 1, i); + break; + } + } + + for (int i = MTLGPUFamilyMetal3_GGML + 5; i >= MTLGPUFamilyMetal3_GGML; --i) { + if ([dev->mtl_device supportsFamily:i]) { + GGML_LOG_INFO("%s: GPU family: MTLGPUFamilyMetal%d (%d)\n", __func__, i - (int) MTLGPUFamilyMetal3_GGML + 3, i); + break; + } + } + } + + GGML_LOG_INFO("%s: simdgroup reduction = %s\n", __func__, dev->props.has_simdgroup_reduction ? "true" : "false"); + GGML_LOG_INFO("%s: simdgroup matrix mul. = %s\n", __func__, dev->props.has_simdgroup_mm ? "true" : "false"); + GGML_LOG_INFO("%s: has unified memory = %s\n", __func__, dev->props.has_unified_memory ? "true" : "false"); + GGML_LOG_INFO("%s: has bfloat = %s\n", __func__, dev->props.has_bfloat ? "true" : "false"); + GGML_LOG_INFO("%s: use residency sets = %s\n", __func__, dev->props.use_residency_sets ? "true" : "false"); + GGML_LOG_INFO("%s: use shared buffers = %s\n", __func__, dev->props.use_shared_buffers ? "true" : "false"); + +#if TARGET_OS_OSX || (TARGET_OS_IOS && __clang_major__ >= 15) + if (@available(macOS 10.12, iOS 16.0, *)) { + GGML_LOG_INFO("%s: recommendedMaxWorkingSetSize = %8.2f MB\n", __func__, dev->props.max_working_set_size / 1e6); + } +#endif + } + } + + return dev; +} + +void ggml_metal_device_free(ggml_metal_device_t dev) { + assert(dev != NULL); + + ggml_metal_library_free(dev->library); + dev->library = NULL; + + if (dev->mtl_queue) { + [dev->mtl_queue release]; + dev->mtl_queue = nil; + } + + if (dev->mtl_device) { + [dev->mtl_device release]; + dev->mtl_device = nil; + } + + free(dev); +} + +void * ggml_metal_device_get_obj(ggml_metal_device_t dev) { + return dev->mtl_device; +} + +void * ggml_metal_device_get_queue(ggml_metal_device_t dev) { + return dev->mtl_queue; +} + +ggml_metal_library_t ggml_metal_device_get_library(ggml_metal_device_t dev) { + return dev->library; +} + +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; + *free = *total - dev->mtl_device.currentAllocatedSize; + } else { + *free = 0; + *total = 0; + } +} + +bool ggml_metal_device_supports_op(ggml_metal_device_t dev, const struct ggml_tensor * op) { + const bool has_simdgroup_mm = dev->props.has_simdgroup_mm; + const bool has_simdgroup_reduction = dev->props.has_simdgroup_reduction; + const bool has_bfloat = dev->props.has_bfloat; + + if (!has_bfloat) { + if (op->type == GGML_TYPE_BF16) { + return false; + } + + for (size_t i = 0, n = 3; i < n; ++i) { + if (op->src[i] != NULL && op->src[i]->type == GGML_TYPE_BF16) { + return false; + } + } + } + + switch (op->op) { + case GGML_OP_UNARY: + switch (ggml_get_unary_op(op)) { + case GGML_UNARY_OP_TANH: + case GGML_UNARY_OP_RELU: + case GGML_UNARY_OP_SIGMOID: + case GGML_UNARY_OP_GELU: + case GGML_UNARY_OP_GELU_ERF: + case GGML_UNARY_OP_GELU_QUICK: + case GGML_UNARY_OP_SILU: + case GGML_UNARY_OP_ELU: + case GGML_UNARY_OP_NEG: + case GGML_UNARY_OP_ABS: + case GGML_UNARY_OP_SGN: + case GGML_UNARY_OP_STEP: + case GGML_UNARY_OP_HARDSWISH: + case GGML_UNARY_OP_HARDSIGMOID: + case GGML_UNARY_OP_EXP: + return ggml_is_contiguous(op->src[0]) && op->src[0]->type == GGML_TYPE_F32; + default: + return false; + } + case GGML_OP_GLU: + switch (ggml_get_glu_op(op)) { + case GGML_GLU_OP_REGLU: + case GGML_GLU_OP_GEGLU: + case GGML_GLU_OP_SWIGLU: + case GGML_GLU_OP_SWIGLU_OAI: + case GGML_GLU_OP_GEGLU_ERF: + case GGML_GLU_OP_GEGLU_QUICK: + return ggml_is_contiguous_1(op->src[0]) && op->src[0]->type == GGML_TYPE_F32; + default: + return false; + } + case GGML_OP_NONE: + case GGML_OP_RESHAPE: + case GGML_OP_VIEW: + case GGML_OP_TRANSPOSE: + case GGML_OP_PERMUTE: + case GGML_OP_CONCAT: + return true; + case GGML_OP_ADD: + case GGML_OP_SUB: + case GGML_OP_MUL: + case GGML_OP_DIV: + case GGML_OP_ADD_ID: + return op->src[0]->type == GGML_TYPE_F32; + case GGML_OP_ACC: + case GGML_OP_REPEAT: + case GGML_OP_SCALE: + case GGML_OP_CONV_TRANSPOSE_1D: + return true; + case GGML_OP_CLAMP: + return op->src[0]->type == GGML_TYPE_F32; + case GGML_OP_SQR: + case GGML_OP_SQRT: + case GGML_OP_SIN: + case GGML_OP_COS: + case GGML_OP_LOG: + return ggml_is_contiguous(op->src[0]) && op->src[0]->type == GGML_TYPE_F32; + case GGML_OP_SUM_ROWS: + case GGML_OP_MEAN: + case GGML_OP_SOFT_MAX: + case GGML_OP_GROUP_NORM: + return has_simdgroup_reduction && ggml_is_contiguous_rows(op->src[0]); + case GGML_OP_RMS_NORM: + case GGML_OP_L2_NORM: + return has_simdgroup_reduction && (op->ne[0] % 4 == 0 && ggml_is_contiguous_1(op->src[0])); + case GGML_OP_ARGMAX: + return has_simdgroup_reduction; + case GGML_OP_NORM: + return has_simdgroup_reduction && (op->ne[0] % 4 == 0 && ggml_is_contiguous_1(op->src[0])); + case GGML_OP_ROPE: + return true; + case GGML_OP_IM2COL: + return ggml_is_contiguous(op->src[1]) && op->src[1]->type == GGML_TYPE_F32 && (op->type == GGML_TYPE_F16 || op->type == GGML_TYPE_F32); + case GGML_OP_POOL_1D: + return false; + case GGML_OP_UPSCALE: + return op->src[0]->type == GGML_TYPE_F32 && op->op_params[0] == GGML_SCALE_MODE_NEAREST; + case GGML_OP_POOL_2D: + return op->src[0]->type == GGML_TYPE_F32; + case GGML_OP_PAD: + 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: + case GGML_OP_TIMESTEP_EMBEDDING: + case GGML_OP_ARGSORT: + case GGML_OP_LEAKY_RELU: + return op->src[0]->type == GGML_TYPE_F32; + case GGML_OP_ARANGE: + return true; + case GGML_OP_FLASH_ATTN_EXT: + // for new head sizes, add checks here + if (op->src[0]->ne[0] != 40 && + op->src[0]->ne[0] != 64 && + op->src[0]->ne[0] != 80 && + op->src[0]->ne[0] != 96 && + op->src[0]->ne[0] != 112 && + op->src[0]->ne[0] != 128 && + op->src[0]->ne[0] != 192 && + op->src[0]->ne[0] != 256) { + return false; + } + if (op->src[0]->ne[0] == 576) { + // DeepSeek sizes + // TODO: disabled for now, until optmized + return false; + } + if (op->src[1]->type != op->src[2]->type) { + return false; + } + return has_simdgroup_mm; // TODO: over-restricted for vec-kernels + case GGML_OP_SSM_CONV: + case GGML_OP_SSM_SCAN: + return has_simdgroup_reduction; + case GGML_OP_RWKV_WKV6: + case GGML_OP_RWKV_WKV7: + return true; + case GGML_OP_MUL_MAT: + case GGML_OP_MUL_MAT_ID: + return has_simdgroup_reduction && + (op->src[0]->type != GGML_TYPE_F32 || op->src[1]->type == GGML_TYPE_F32); + case GGML_OP_CPY: + case GGML_OP_DUP: + case GGML_OP_CONT: + { + switch (op->src[0]->type) { + case GGML_TYPE_F32: + switch (op->type) { + case GGML_TYPE_F32: + case GGML_TYPE_F16: + case GGML_TYPE_BF16: + case GGML_TYPE_Q8_0: + case GGML_TYPE_Q4_0: + case GGML_TYPE_Q4_1: + case GGML_TYPE_Q5_0: + case GGML_TYPE_Q5_1: + case GGML_TYPE_IQ4_NL: + case GGML_TYPE_I32: + return true; + default: + return false; + } + case GGML_TYPE_F16: + switch (op->type) { + case GGML_TYPE_F32: + case GGML_TYPE_F16: + return true; + default: + return false; + } + case GGML_TYPE_BF16: + switch (op->type) { + case GGML_TYPE_F32: + case GGML_TYPE_BF16: + return true; + default: + return false; + } + case GGML_TYPE_Q4_0: + case GGML_TYPE_Q4_1: + case GGML_TYPE_Q5_0: + case GGML_TYPE_Q5_1: + case GGML_TYPE_Q8_0: + switch (op->type) { + case GGML_TYPE_F32: + case GGML_TYPE_F16: + return true; + default: + return false; + } + case GGML_TYPE_I32: + return op->type == GGML_TYPE_F32; + default: + return false; + }; + } + case GGML_OP_GET_ROWS: + { + return op->ne[3] == 1; + } + case GGML_OP_SET_ROWS: + { + if (op->src[0]->type != GGML_TYPE_F32) { + return false; + } + + switch (op->type) { + case GGML_TYPE_F32: + case GGML_TYPE_F16: + case GGML_TYPE_BF16: + case GGML_TYPE_Q8_0: + case GGML_TYPE_Q4_0: + case GGML_TYPE_Q4_1: + case GGML_TYPE_Q5_0: + case GGML_TYPE_Q5_1: + case GGML_TYPE_IQ4_NL: + return true; + default: + return false; + }; + } + default: + return false; + } +} + +const struct ggml_metal_device_props * ggml_metal_device_get_props(ggml_metal_device_t dev) { + return &dev->props; +} + +// +// device buffers +// + +// max memory buffers that can be mapped to the device +#define GGML_METAL_MAX_BUFFERS 64 + +struct ggml_metal_buffer_wrapper { + void * data; + size_t size; + + id metal; +}; + +struct ggml_metal_buffer { + void * all_data; // TODO: https://github.com/ggml-org/llama.cpp/pull/15985 + size_t all_size; + + // if false, the Metal buffer data is allocated in private GPU memory and is not shared with the host + bool is_shared; + + // multiple buffers are used only to avoid the maximum buffer size limitation when using mmap + int n_buffers; + struct ggml_metal_buffer_wrapper buffers[GGML_METAL_MAX_BUFFERS]; + + bool use_residency_sets; + + // optional MTLResidencySet + // 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; +}; + +static void ggml_metal_log_allocated_size(id device, size_t size_aligned) { +#ifndef GGML_METAL_NDEBUG +#if TARGET_OS_OSX || (TARGET_OS_IOS && __clang_major__ >= 15) + if (@available(macOS 10.12, iOS 16.0, *)) { + GGML_LOG_DEBUG("%s: allocated buffer, size = %8.2f MiB, (%8.2f / %8.2f)\n", + __func__, + size_aligned / 1024.0 / 1024.0, + device.currentAllocatedSize / 1024.0 / 1024.0, + device.recommendedMaxWorkingSetSize / 1024.0 / 1024.0); + + if (device.currentAllocatedSize > device.recommendedMaxWorkingSetSize) { + GGML_LOG_WARN("%s: warning: current allocated size is greater than the recommended max working set size\n", __func__); + } + } else { + GGML_LOG_INFO("%s: allocated buffer, size = %8.2f MiB, (%8.2f)\n", + __func__, + size_aligned / 1024.0 / 1024.0, + device.currentAllocatedSize / 1024.0 / 1024.0); + } +#endif +#endif + GGML_UNUSED(device); + GGML_UNUSED(size_aligned); +} + +// rset init +static bool ggml_metal_buffer_rset_init(ggml_metal_buffer_t buf) { + buf->rset = nil; + + if (!buf->use_residency_sets) { + return true; + } + +#if defined(GGML_METAL_HAS_RESIDENCY_SETS) + if (@available(macOS 15.0, iOS 18.0, tvOS 18.0, visionOS 2.0, *)) { + MTLResidencySetDescriptor * desc = [[MTLResidencySetDescriptor alloc] init]; + desc.label = @"ggml_metal"; + desc.initialCapacity = buf->n_buffers; + + NSError * error; + buf->rset = [buf->device newResidencySetWithDescriptor:desc error:&error]; + if (error) { + GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]); + [desc release]; + return false; + } + + [desc release]; + + for (int i = 0; i < buf->n_buffers; i++) { + [buf->rset addAllocation:buf->buffers[i].metal]; + } + + [buf->rset commit]; + [buf->rset requestResidency]; + + return true; + } +#endif + + return true; +} + +// rset free +static void ggml_metal_buffer_rset_free(ggml_metal_buffer_t buf) { +#if defined(GGML_METAL_HAS_RESIDENCY_SETS) + if (@available(macOS 15.0, iOS 18.0, tvOS 18.0, visionOS 2.0, *)) { + if (buf->rset) { + [buf->rset endResidency]; + [buf->rset removeAllAllocations]; + [buf->rset release]; + } + } +#else + GGML_UNUSED(buf); +#endif +} + +static void * ggml_metal_host_malloc(size_t n) { + void * data = NULL; + +#if TARGET_OS_OSX + kern_return_t err = vm_allocate((vm_map_t) mach_task_self(), (void *) &data, n, VM_FLAGS_ANYWHERE); + if (err != KERN_SUCCESS) { + GGML_LOG_ERROR("%s: error: vm_allocate failed\n", __func__); + return NULL; + } +#else + const int result = posix_memalign((void **) &data, sysconf(_SC_PAGESIZE), n); + if (result != 0) { + GGML_LOG_ERROR("%s: error: posix_memalign failed\n", __func__); + return NULL; + } +#endif + + return data; +} + +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)); + + const size_t size_page = sysconf(_SC_PAGESIZE); + + size_t size_aligned = size; + if ((size_aligned % size_page) != 0) { + size_aligned += (size_page - (size_aligned % size_page)); + } + + const struct ggml_metal_device_props * props_dev = ggml_metal_device_get_props(dev); + + shared = shared && props_dev->use_shared_buffers; + + // allocate shared buffer if the device supports it and it is required by the buffer type + if (shared) { + res->all_data = ggml_metal_host_malloc(size_aligned); + res->is_shared = true; + } else { + // dummy, non-NULL value - we'll populate this after creating the Metal buffer below + res->all_data = (void *) 0x000000400ULL; + res->is_shared = false; + } + res->all_size = size_aligned; + + 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) { + res->buffers[0].size = size; + res->buffers[0].metal = nil; + + if (size_aligned > 0) { + if (props_dev->use_shared_buffers &&shared) { + res->buffers[0].metal = [res->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->all_data = (void *) (res->buffers[0].metal.gpuAddress); + } + } + + res->buffers[0].data = res->all_data; + } + + if (size_aligned > 0 && (res->all_data == NULL || res->buffers[0].metal == nil)) { + GGML_LOG_ERROR("%s: error: failed to allocate buffer, size = %8.2f MiB\n", __func__, size_aligned / 1024.0 / 1024.0); + free(res); + return NULL; + } + + res->use_residency_sets = props_dev->use_residency_sets; + + if (!ggml_metal_buffer_rset_init(res)) { + GGML_LOG_ERROR("%s: error: failed to initialize residency set\n", __func__); + free(res); + return NULL; + } + + //ggml_metal_log_allocated_size(device, size_aligned); + + return res; +} + +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->all_data = ptr; + res->all_size = size; + + res->is_shared = true; + + res->n_buffers = 0; + + const size_t size_page = sysconf(_SC_PAGESIZE); + + // page-align the data ptr + { + const uintptr_t offs = (uintptr_t) ptr % size_page; + ptr = (void *) ((char *) ptr - offs); + size += offs; + } + + size_t size_aligned = size; + if ((size_aligned % size_page) != 0) { + 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 + if (size_aligned <= props_dev->max_buffer_size) { + res->buffers[res->n_buffers].data = ptr; + res->buffers[res->n_buffers].size = size; + 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]; + + 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); + free(res); + return NULL; + } + } + + ggml_metal_log_allocated_size(res->device, size_aligned); + + ++res->n_buffers; + } else { + // this overlap between the views will guarantee that the tensor with the maximum size will fully fit into + // one of the views + const size_t size_ovlp = ((max_tensor_size + size_page - 1) / size_page + 1) * size_page; // round-up 2 pages just in case + const size_t size_step = props_dev->max_buffer_size - size_ovlp; + const size_t size_view = props_dev->max_buffer_size; + + for (size_t i = 0; i < size; i += size_step) { + const size_t size_step_aligned = (i + size_view <= size) ? size_view : (size_aligned - i); + + res->buffers[res->n_buffers].data = (void *) ((uint8_t *) ptr + i); + res->buffers[res->n_buffers].size = size_step_aligned; + 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]; + + 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); + free(res); + return NULL; + } + } + + ggml_metal_log_allocated_size(res->device, size_step_aligned); + + if (i + size_step < size) { + GGML_LOG_INFO("\n"); + } + + ++res->n_buffers; + } + } + + res->use_residency_sets = props_dev->use_residency_sets; + + if (!ggml_metal_buffer_rset_init(res)) { + GGML_LOG_ERROR("%s: error: failed to initialize residency set\n", __func__); + free(res); + return NULL; + } + + return res; +} + +void ggml_metal_buffer_free(ggml_metal_buffer_t buf) { + for (int i = 0; i < buf->n_buffers; i++) { + [buf->buffers[i].metal release]; + } + + ggml_metal_buffer_rset_free(buf); + + if (buf->is_shared) { +#if TARGET_OS_OSX + vm_deallocate((vm_map_t)mach_task_self(), (vm_address_t)buf->all_data, buf->all_size); +#else + free(buf->all_data); +#endif + } + + free(buf); +} + +void * ggml_metal_buffer_get_base(ggml_metal_buffer_t buf) { + return buf->all_data; +} + +bool ggml_metal_buffer_is_shared(ggml_metal_buffer_t buf) { + return buf->is_shared; +} + +void ggml_metal_buffer_memset_tensor(ggml_metal_buffer_t buf, struct ggml_tensor * tensor, uint8_t value, size_t offset, size_t size) { + if (buf->is_shared) { + memset((char *)tensor->data + offset, value, size); + return; + } + + @autoreleasepool { + // dst + 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 encoder = [cmd_buf blitCommandEncoder]; + + [encoder fillBuffer:bid_dst.metal + range:NSMakeRange(bid_dst.offs, bid_dst.offs + size) + value:value]; + + [encoder endEncoding]; + } + + [cmd_buf commit]; + [cmd_buf waitUntilCompleted]; + } +} + +void ggml_metal_buffer_set_tensor(ggml_metal_buffer_t buf, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size) { + if (buf->is_shared) { + memcpy((char *)tensor->data + offset, data, size); + return; + } + + @autoreleasepool { + // src + void * data_ptr = (void *)(uintptr_t) data; // "const cast" the src data + id buf_src = [buf->device newBufferWithBytesNoCopy:data_ptr + length:size + options:MTLResourceStorageModeShared + deallocator:nil]; + + // dst + struct ggml_metal_buffer_id bid_dst = ggml_metal_buffer_get_id(buf, tensor); + bid_dst.offs += offset; + + // note: for experimentation purposes, here we use a semaphore to wait for the copy to complete + // 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 encoder = [cmd_buf blitCommandEncoder]; + + [encoder copyFromBuffer:buf_src + sourceOffset:0 + toBuffer:bid_dst.metal + destinationOffset:bid_dst.offs + size:size]; + + [encoder endEncoding]; + } + + [cmd_buf addCompletedHandler:^(id cb) { + // TODO: can check for errors here + GGML_UNUSED(cb); + + dispatch_semaphore_signal(completion_semaphore); + }]; + + [cmd_buf commit]; + + dispatch_semaphore_wait(completion_semaphore, DISPATCH_TIME_FOREVER); + dispatch_release(completion_semaphore); + + //[cmd_buf waitUntilCompleted]; + } +} + +void ggml_metal_buffer_get_tensor(ggml_metal_buffer_t buf, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size) { + if (buf->is_shared) { + memcpy(data, (const char *)tensor->data + offset, size); + return; + } + + @autoreleasepool { + // src + struct ggml_metal_buffer_id bid_src = ggml_metal_buffer_get_id(buf, tensor); + bid_src.offs += offset; + + // dst + id buf_dst = [buf->device newBufferWithBytesNoCopy:data + length:size + options:MTLResourceStorageModeShared + deallocator:nil]; + + id queue = buf->queue; + id cmd_buf = [queue commandBufferWithUnretainedReferences]; + + { + id encoder = [cmd_buf blitCommandEncoder]; + + [encoder copyFromBuffer:bid_src.metal + sourceOffset:bid_src.offs + toBuffer:buf_dst + destinationOffset:0 + size:size]; + + [encoder endEncoding]; + } + + [cmd_buf commit]; + [cmd_buf waitUntilCompleted]; + } +} + +void ggml_metal_buffer_clear(ggml_metal_buffer_t buf, uint8_t value) { + if (buf->is_shared) { + memset(buf->all_data, value, buf->all_size); + return; + } + + @autoreleasepool { + id queue = buf->queue; + id cmd_buf = [queue commandBufferWithUnretainedReferences]; + + { + id encoder = [cmd_buf blitCommandEncoder]; + + [encoder fillBuffer:buf->buffers[0].metal + range:NSMakeRange(0, buf->buffers[0].size) + value:value]; + + [encoder endEncoding]; + } + + [cmd_buf commit]; + [cmd_buf waitUntilCompleted]; + } +} + +struct ggml_metal_buffer_id ggml_metal_buffer_get_id(ggml_metal_buffer_t buf, const struct ggml_tensor * t) { + struct ggml_metal_buffer_id res = { nil, 0 }; + + const int64_t tsize = ggml_nbytes(t); + + // find the view that contains the tensor fully + for (int i = 0; i < buf->n_buffers; ++i) { + const int64_t ioffs = (int64_t) t->data - (int64_t) buf->buffers[i].data; + + //GGML_LOG_INFO("ioffs = %10ld, tsize = %10ld, sum = %10ld, buf->buffers[%d].size = %10ld\n", ioffs, tsize, ioffs + tsize, i, buf->buffers[i].size); + if (ioffs >= 0 && ioffs + tsize <= (int64_t) buf->buffers[i].size) { + res.metal = buf->buffers[i].metal; + res.offs = (size_t) ioffs; + + //GGML_LOG_INFO("%s: tensor '%16s', offs = %8ld\n", __func__, t->name, *offs); + + return res; + } + } + + GGML_LOG_ERROR("%s: error: tensor '%s' buffer is nil\n", __func__, t->name); + + return res; +} diff --git a/ggml/src/ggml-metal/ggml-metal-impl.h b/ggml/src/ggml-metal/ggml-metal-impl.h index 651943fa92..0776bb6485 100644 --- a/ggml/src/ggml-metal/ggml-metal-impl.h +++ b/ggml/src/ggml-metal/ggml-metal-impl.h @@ -165,6 +165,16 @@ typedef struct { uint64_t nb3; } ggml_metal_kargs_repeat; +typedef struct { + float scale; + float bias; +} ggml_metal_kargs_scale; + +typedef struct { + float min; + float max; +} ggml_metal_kargs_clamp; + typedef struct { int64_t ne00; int64_t ne01; @@ -453,7 +463,7 @@ typedef struct { uint64_t nb00; uint64_t nb01; uint64_t nb02; - int32_t n_groups; + int32_t ngrp; float eps; } ggml_metal_kargs_group_norm; @@ -506,14 +516,6 @@ typedef struct { uint64_t nb01; uint64_t nb02; uint64_t nb03; - int64_t ne10; - int64_t ne11; - int64_t ne12; - int64_t ne13; - uint64_t nb10; - uint64_t nb11; - uint64_t nb12; - uint64_t nb13; int64_t ne0; int64_t ne1; int64_t ne2; @@ -547,12 +549,6 @@ typedef struct { int32_t n_head_log2; } ggml_metal_kargs_soft_max; -typedef struct { - int64_t ne00; - int64_t ne01; - int n_past; -} ggml_metal_kargs_diag_mask_inf; - typedef struct { int64_t ne00; int64_t ne01; @@ -579,7 +575,7 @@ typedef struct { int64_t n_group; int64_t n_seq_tokens; int64_t n_seqs; - int64_t s_off; + uint64_t s_off; uint64_t nb01; uint64_t nb02; uint64_t nb03; @@ -719,7 +715,12 @@ typedef struct { int64_t IW; int64_t OH; int64_t OW; - int64_t parallel_elements; + int64_t np; } ggml_metal_kargs_pool_2d; +typedef struct { + int64_t ne00; + uint64_t nb01; +} ggml_metal_kargs_argmax; + #endif // GGML_METAL_IMPL diff --git a/ggml/src/ggml-metal/ggml-metal-ops.cpp b/ggml/src/ggml-metal/ggml-metal-ops.cpp new file mode 100644 index 0000000000..839c16894d --- /dev/null +++ b/ggml/src/ggml-metal/ggml-metal-ops.cpp @@ -0,0 +1,3188 @@ +#include "ggml-metal-ops.h" + +#include "ggml.h" +#include "ggml-impl.h" +#include "ggml-backend-impl.h" + +#include "ggml-metal-impl.h" +#include "ggml-metal-common.h" +#include "ggml-metal-device.h" + +#include +#include + +static ggml_metal_buffer_id ggml_metal_get_buffer_id(const ggml_tensor * t) { + if (!t) { + return { nullptr, 0 }; + } + + ggml_backend_buffer_t buffer = t->view_src ? t->view_src->buffer : t->buffer; + + ggml_metal_buffer_t ctx = (ggml_metal_buffer_t) buffer->context; + + return ggml_metal_buffer_get_id(ctx, t); +} + +struct ggml_metal_op { + ggml_metal_device_t dev; + ggml_metal_library_t lib; + ggml_metal_encoder_t enc; + ggml_mem_ranges_t mem_ranges; + + ggml_cgraph * gf; + + int idx_start; + int idx_end; + + bool use_fusion; + bool use_concurrency; + bool use_capture; + + int debug_graph; + int debug_fusion; +}; + +ggml_metal_op_t ggml_metal_op_init( + ggml_metal_device_t dev, + ggml_metal_cmd_buf_t cmd_buf, + ggml_cgraph * gf, + int idx_start, + int idx_end, + bool use_fusion, + bool use_concurrency, + bool use_capture, + int debug_graph, + int debug_fusion) { + ggml_metal_op_t res = new ggml_metal_op(); + + *res = { + /*.dev =*/ dev, + /*.lib =*/ ggml_metal_device_get_library(dev), + /*.enc =*/ ggml_metal_encoder_init(cmd_buf, use_concurrency), + /*.mem_ranges =*/ ggml_mem_ranges_init(debug_graph), + /*.gf =*/ gf, + /*.idx_start =*/ idx_start, + /*.idx_end =*/ idx_end, + /*.use_fusion =*/ use_fusion, + /*.use_concurrency =*/ use_concurrency, + /*.use_capture =*/ use_capture, + /*.debug_graph =*/ debug_graph, + /*.debug_fusion =*/ debug_fusion, + }; + + return res; +} + +void ggml_metal_op_free(ggml_metal_op_t ctx) { + ggml_metal_encoder_end_encoding(ctx->enc); + ggml_metal_encoder_free(ctx->enc); + ggml_mem_ranges_free(ctx->mem_ranges); + + delete ctx; +} + +static bool ggml_metal_op_concurrency_reset(ggml_metal_op_t ctx) { + if (!ctx->mem_ranges) { + return true; + } + + ggml_metal_encoder_memory_barrier(ctx->enc); + + ggml_mem_ranges_reset(ctx->mem_ranges); + + return true; +} + +static bool ggml_metal_op_concurrency_check(ggml_metal_op_t ctx, const ggml_tensor * node) { + if (!ctx->mem_ranges) { + return false; + } + + return ggml_mem_ranges_check(ctx->mem_ranges, node); +} + +static bool ggml_metal_op_concurrency_add(ggml_metal_op_t ctx, const ggml_tensor * node) { + if (!ctx->mem_ranges) { + return true; + } + + return ggml_mem_ranges_add(ctx->mem_ranges, node); +} + +static int ggml_metal_op_encode_impl(ggml_metal_op_t ctx, int idx) { + struct ggml_cgraph * gf = ctx->gf; + + struct ggml_tensor ** nodes = ggml_graph_nodes(gf) + idx; + struct ggml_tensor * node = nodes[0]; + + //GGML_LOG_INFO("%s: encoding node %3d, op = %8s\n", __func__, idx, ggml_op_name(node->op)); + + if (ggml_is_empty(node)) { + return 1; + } + + switch (node->op) { + case GGML_OP_NONE: + case GGML_OP_RESHAPE: + case GGML_OP_VIEW: + case GGML_OP_TRANSPOSE: + case GGML_OP_PERMUTE: + { + // noop -> next node + } return 1; + default: + { + } break; + } + + if (!ggml_metal_device_supports_op(ctx->dev, node)) { + GGML_LOG_ERROR("%s: error: unsupported op '%s'\n", __func__, ggml_op_desc(node)); + GGML_ABORT("unsupported op"); + } + + int n_fuse = 1; + + // check if the current node can run concurrently with other nodes before it + // the condition is that: + // - the current node cannot write to any previous src or dst ranges + // - the current node cannot read from any previous dst ranges + // + // if the condition is not satisfied, we put a memory barrier and clear all ranges + // otherwise, we add the new ranges to the encoding context and process the node concurrently + // + { + const bool is_concurrent = ggml_metal_op_concurrency_check(ctx, node); + + if (!is_concurrent) { + ggml_metal_op_concurrency_reset(ctx); + } + + if (ctx->debug_graph > 0) { + GGML_LOG_DEBUG("%s: node[%5d] - %-12s %s\n", __func__, idx, ggml_op_name(node->op), is_concurrent ? "(concurrent)" : ""); + } + if (ctx->debug_graph > 1) { + GGML_TENSOR_LOCALS( int64_t, ne0, node->src[0], ne); + GGML_TENSOR_LOCALS(uint64_t, nb0, node->src[0], nb); + GGML_TENSOR_LOCALS( int64_t, ne1, node->src[1], ne); + GGML_TENSOR_LOCALS(uint64_t, nb1, node->src[1], nb); + GGML_TENSOR_LOCALS( int64_t, ne, node, ne); + GGML_TENSOR_LOCALS(uint64_t, nb, node, nb); + + if (node->src[0]) { + GGML_LOG_DEBUG("%s: src0 - %4s [%5lld, %5lld, %5lld, %5lld] [%5lld, %5lld, %5lld, %5lld], %d, %s\n", __func__, ggml_type_name(node->src[0]->type), ne00, ne01, ne02, ne03, nb00, nb01, nb02, nb03, + ggml_is_contiguous(node->src[0]), node->src[0]->name); + } + if (node->src[1]) { + GGML_LOG_DEBUG("%s: src1 - %4s [%5lld, %5lld, %5lld, %5lld] [%5lld, %5lld, %5lld, %5lld], %d, %s\n", __func__, ggml_type_name(node->src[1]->type), ne10, ne11, ne12, ne13, nb10, nb11, nb12, nb13, + ggml_is_contiguous(node->src[1]), node->src[1]->name); + } + if (node) { + GGML_LOG_DEBUG("%s: node - %4s [%5lld, %5lld, %5lld, %5lld] [%5lld, %5lld, %5lld, %5lld], 1, %s\n", __func__, ggml_type_name(node->type), ne0, ne1, ne2, ne3, nb0, nb1, nb2, nb3, + node->name); + } + } + } + + switch (node->op) { + case GGML_OP_CONCAT: + { + n_fuse = ggml_metal_op_concat(ctx, idx); + } break; + case GGML_OP_ADD: + case GGML_OP_SUB: + case GGML_OP_MUL: + case GGML_OP_DIV: + { + n_fuse = ggml_metal_op_bin(ctx, idx); + } break; + case GGML_OP_ADD_ID: + { + n_fuse = ggml_metal_op_add_id(ctx, idx); + } break; + case GGML_OP_REPEAT: + { + n_fuse = ggml_metal_op_repeat(ctx, idx); + } break; + case GGML_OP_ACC: + { + n_fuse = ggml_metal_op_acc(ctx, idx); + } break; + case GGML_OP_SCALE: + { + n_fuse = ggml_metal_op_scale(ctx, idx); + } break; + case GGML_OP_CLAMP: + { + n_fuse = ggml_metal_op_clamp(ctx, idx); + } break; + case GGML_OP_SQR: + case GGML_OP_SQRT: + case GGML_OP_SIN: + case GGML_OP_COS: + case GGML_OP_LOG: + case GGML_OP_UNARY: + { + n_fuse = ggml_metal_op_unary(ctx, idx); + } break; + case GGML_OP_GLU: + { + n_fuse = ggml_metal_op_glu(ctx, idx); + } break; + case GGML_OP_SUM_ROWS: + case GGML_OP_MEAN: + { + n_fuse = ggml_metal_op_sum_rows(ctx, idx); + } break; + case GGML_OP_SOFT_MAX: + { + n_fuse = ggml_metal_op_soft_max(ctx, idx); + } break; + case GGML_OP_SSM_CONV: + { + n_fuse = ggml_metal_op_ssm_conv(ctx, idx); + } break; + case GGML_OP_SSM_SCAN: + { + n_fuse = ggml_metal_op_ssm_scan(ctx, idx); + } break; + case GGML_OP_RWKV_WKV6: + case GGML_OP_RWKV_WKV7: + { + n_fuse = ggml_metal_op_rwkv(ctx, idx); + } break; + case GGML_OP_MUL_MAT: + { + n_fuse = ggml_metal_op_mul_mat(ctx, idx); + } break; + case GGML_OP_MUL_MAT_ID: + { + n_fuse = ggml_metal_op_mul_mat_id(ctx, idx); + } break; + case GGML_OP_GET_ROWS: + { + n_fuse = ggml_metal_op_get_rows(ctx, idx); + } break; + case GGML_OP_SET_ROWS: + { + n_fuse = ggml_metal_op_set_rows(ctx, idx); + } break; + case GGML_OP_RMS_NORM: + { + n_fuse = ggml_metal_op_rms_norm(ctx, idx); + } break; + case GGML_OP_L2_NORM: + { + n_fuse = ggml_metal_op_l2_norm(ctx, idx); + } break; + case GGML_OP_GROUP_NORM: + { + n_fuse = ggml_metal_op_group_norm(ctx, idx); + } break; + case GGML_OP_NORM: + { + n_fuse = ggml_metal_op_norm(ctx, idx); + } break; + case GGML_OP_ROPE: + { + n_fuse = ggml_metal_op_rope(ctx, idx); + } break; + case GGML_OP_IM2COL: + { + n_fuse = ggml_metal_op_im2col(ctx, idx); + } break; + case GGML_OP_CONV_TRANSPOSE_1D: + { + n_fuse = ggml_metal_op_conv_transpose_1d(ctx, idx); + } break; + case GGML_OP_UPSCALE: + { + n_fuse = ggml_metal_op_upscale(ctx, idx); + } break; + case GGML_OP_PAD: + { + n_fuse = ggml_metal_op_pad(ctx, idx); + } break; + case GGML_OP_PAD_REFLECT_1D: + { + n_fuse = ggml_metal_op_pad_reflect_1d(ctx, idx); + } break; + case GGML_OP_ARANGE: + { + n_fuse = ggml_metal_op_arange(ctx, idx); + } break; + case GGML_OP_TIMESTEP_EMBEDDING: + { + n_fuse = ggml_metal_op_timestep_embedding(ctx, idx); + } break; + case GGML_OP_ARGSORT: + { + n_fuse = ggml_metal_op_argsort(ctx, idx); + } break; + case GGML_OP_LEAKY_RELU: + { + n_fuse = ggml_metal_op_leaky_relu(ctx, idx); + } break; + case GGML_OP_FLASH_ATTN_EXT: + { + n_fuse = ggml_metal_op_flash_attn_ext(ctx, idx); + } break; + case GGML_OP_DUP: + case GGML_OP_CPY: + case GGML_OP_CONT: + { + n_fuse = ggml_metal_op_cpy(ctx, idx); + } break; + case GGML_OP_POOL_2D: + { + n_fuse = ggml_metal_op_pool_2d(ctx, idx); + } break; + case GGML_OP_ARGMAX: + { + n_fuse = ggml_metal_op_argmax(ctx, idx); + } break; + default: + { + GGML_LOG_ERROR("%s: error: node %3d, op = %8s not implemented\n", __func__, idx, ggml_op_name(node->op)); + GGML_ABORT("fatal error"); + } + } + + if (ctx->debug_graph > 0) { + if (n_fuse > 1) { + GGML_LOG_DEBUG("%s: fuse %d ops\n", __func__, n_fuse); + } + } + + // update the mem ranges in the encoding context + for (int i = 0; i < n_fuse; ++i) { + if (!ggml_metal_op_concurrency_add(ctx, nodes[i])) { + ggml_metal_op_concurrency_reset(ctx); + } + } + + return n_fuse; +} + +int ggml_metal_op_encode(ggml_metal_op_t ctx, int idx) { + if (ctx->use_capture) { + ggml_metal_encoder_debug_group_push(ctx->enc, ggml_op_desc(ggml_graph_node(ctx->gf, idx))); + } + + int res = ggml_metal_op_encode_impl(ctx, idx); + if (idx + res > ctx->idx_end) { + GGML_ABORT("fusion error: nodes spanning multiple encoders have been fused. this indicates a bug in the fusion logic %s", + "https://github.com/ggml-org/llama.cpp/pull/14849"); + } + + if (ctx->use_capture) { + ggml_metal_encoder_debug_group_pop(ctx->enc); + } + + return res; +} + +int ggml_metal_op_concat(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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, ne1, op->src[1], ne); + GGML_TENSOR_LOCALS(uint64_t, nb1, op->src[1], nb); + GGML_TENSOR_LOCALS( int32_t, ne, op, ne); + GGML_TENSOR_LOCALS(uint64_t, nb, op, nb); + + const int32_t dim = ((const int32_t *) op->op_params)[0]; + + ggml_metal_kargs_concat args = { + /*.ne00 =*/ ne00, + /*.ne01 =*/ ne01, + /*.ne02 =*/ ne02, + /*.ne03 =*/ ne03, + /*.nb00 =*/ nb00, + /*.nb01 =*/ nb01, + /*.nb02 =*/ nb02, + /*.nb03 =*/ nb03, + /*.ne10 =*/ ne10, + /*.ne11 =*/ ne11, + /*.ne12 =*/ ne12, + /*.ne13 =*/ ne13, + /*.nb10 =*/ nb10, + /*.nb11 =*/ nb11, + /*.nb12 =*/ nb12, + /*.nb13 =*/ nb13, + /*.ne0 =*/ ne0, + /*.ne1 =*/ ne1, + /*.ne2 =*/ ne2, + /*.ne3 =*/ ne3, + /*.nb0 =*/ nb0, + /*.nb1 =*/ nb1, + /*.nb2 =*/ nb2, + /*.nb3 =*/ nb3, + /*.dim =*/ dim, + }; + + ggml_metal_pipeline_t 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); + 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->src[1]), 2); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), 3); + + const int nth = std::min(1024, ne0); + + ggml_metal_encoder_dispatch_threadgroups(enc, ne1, ne2, ne3, nth, 1, 1); + + return 1; +} + +int ggml_metal_op_repeat(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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(uint32_t, nb, op, nb); + + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_repeat(lib, op->type); + + ggml_metal_kargs_repeat 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, + }; + + 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); + + const int nth = std::min(ggml_metal_pipeline_max_theads_per_threadgroup(pipeline), ne0); + + ggml_metal_encoder_dispatch_threadgroups(enc, ne1, ne2, ne3, nth, 1, 1); + + return 1; +} + +int ggml_metal_op_acc(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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, ne1, op->src[1], ne); + GGML_TENSOR_LOCALS(uint64_t, nb1, op->src[1], nb); + GGML_TENSOR_LOCALS( int32_t, ne, op, ne); + GGML_TENSOR_LOCALS(uint32_t, nb, op, nb); + + GGML_ASSERT(op->src[0]->type == GGML_TYPE_F32); + GGML_ASSERT(op->src[1]->type == GGML_TYPE_F32); + GGML_ASSERT(op->type == GGML_TYPE_F32); + + GGML_ASSERT(ggml_is_contiguous(op->src[0])); + GGML_ASSERT(ggml_is_contiguous(op->src[1])); + + const size_t pnb1 = ((const int32_t *) op->op_params)[0]; + const size_t pnb2 = ((const int32_t *) op->op_params)[1]; + const size_t pnb3 = ((const int32_t *) op->op_params)[2]; + const size_t offs = ((const int32_t *) op->op_params)[3]; + + const bool inplace = (bool) ((const int32_t *) op->op_params)[4]; + + if (!inplace) { + // run a separete kernel to cpy src->dst + // not sure how to avoid this + // 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); + + ggml_metal_kargs_cpy 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, + }; + + 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); + + const int nth = std::min(ggml_metal_pipeline_max_theads_per_threadgroup(pipeline), ne00); + + ggml_metal_encoder_dispatch_threadgroups(enc, ne01, ne02, ne03, nth, 1, 1); + + ggml_metal_op_concurrency_reset(ctx); + } + + ggml_metal_kargs_bin args = { + /*.ne00 =*/ ne00, + /*.ne01 =*/ ne01, + /*.ne02 =*/ ne02, + /*.ne03 =*/ ne03, + /*.nb00 =*/ nb00, + /*.nb01 =*/ pnb1, + /*.nb02 =*/ pnb2, + /*.nb03 =*/ pnb3, + /*.ne10 =*/ ne10, + /*.ne11 =*/ ne11, + /*.ne12 =*/ ne12, + /*.ne13 =*/ ne13, + /*.nb10 =*/ nb10, + /*.nb11 =*/ nb11, + /*.nb12 =*/ nb12, + /*.nb13 =*/ nb13, + /*.ne0 =*/ ne0, + /*.ne1 =*/ ne1, + /*.ne2 =*/ ne2, + /*.ne3 =*/ ne3, + /*.nb0 =*/ nb0, + /*.nb1 =*/ pnb1, + /*.nb2 =*/ pnb2, + /*.nb3 =*/ pnb3, + /*.offs =*/ offs, + /*.o1 =*/ { 0 }, + }; + + ggml_metal_pipeline_t 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); + 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->src[1]), 2); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), 3); + + const int nth = std::min(ggml_metal_pipeline_max_theads_per_threadgroup(pipeline), ne00); + + ggml_metal_encoder_dispatch_threadgroups(enc, ne11, ne12, ne13, nth, 1, 1); + + return 1; +} + +int ggml_metal_op_scale(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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(uint32_t, nb, op, nb); + + float scale; + float bias; + memcpy(&scale, ((const int32_t *) op->op_params) + 0, sizeof(float)); + memcpy(&bias, ((const int32_t *) op->op_params) + 1, sizeof(float)); + + ggml_metal_kargs_scale args = { + /*.scale =*/ scale, + /*.bias =*/ bias, + }; + + int64_t n = ggml_nelements(op); + + if (n % 4 == 0) { + n /= 4; + } + + ggml_metal_pipeline_t 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_clamp(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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(uint32_t, nb, op, nb); + + float min; + float max; + memcpy(&min, ((const int32_t *) op->op_params) + 0, sizeof(float)); + memcpy(&max, ((const int32_t *) op->op_params) + 1, sizeof(float)); + + ggml_metal_kargs_clamp args = { + /*.min =*/ min, + /*.max =*/ max, + }; + + int64_t n = ggml_nelements(op); + + if (n % 4 == 0) { + n /= 4; + } + + ggml_metal_pipeline_t 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_unary(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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(uint32_t, nb, op, nb); + + int64_t n = ggml_nelements(op); + + if (n % 4 == 0) { + n /= 4; + } + + ggml_metal_pipeline_t 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); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), 1); + + ggml_metal_encoder_dispatch_threadgroups(enc, n, 1, 1, 1, 1, 1); + + return 1; +} + +int ggml_metal_op_glu(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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, ne1, op->src[1], ne); + GGML_TENSOR_LOCALS(uint64_t, nb1, op->src[1], nb); + GGML_TENSOR_LOCALS( int32_t, ne, op, ne); + GGML_TENSOR_LOCALS(uint32_t, nb, op, nb); + + if (op->src[1]) { + 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); + + const int32_t swp = ggml_get_op_params_i32(op, 1); + const float alpha = ggml_get_op_params_f32(op, 2); + const float limit = ggml_get_op_params_f32(op, 3); + + const int32_t i00 = swp ? ne0 : 0; + const int32_t i10 = swp ? 0 : ne0; + + ggml_metal_kargs_glu args = { + /*.ne00 =*/ ne00, + /*.nb01 =*/ nb01, + /*.ne10 =*/ op->src[1] ? ne10 : ne00, + /*.nb11 =*/ op->src[1] ? nb11 : nb01, + /*.ne0 =*/ ne0, + /*.nb1 =*/ nb1, + /*.i00 =*/ op->src[1] ? 0 : i00, + /*.i10 =*/ op->src[1] ? 0 : i10, + /*.alpha=*/ alpha, + /*.limit=*/ limit + }; + + const int64_t nrows = ggml_nrows(op->src[0]); + + const int32_t nth = std::min(ggml_metal_pipeline_max_theads_per_threadgroup(pipeline), ne00/2); + + //[encoder setComputePipelineState:pipeline]; + //[encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; + //if (src1) { + // [encoder setBuffer:id_src1 offset:offs_src1 atIndex:1]; + //} else { + // [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; + //} + //[encoder setBuffer:id_dst offset:offs_dst atIndex:2]; + //[encoder setBytes:&args length:sizeof(args) atIndex:3]; + + //[encoder dispatchThreadgroups:MTLSizeMake(nrows, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; + + 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); + if (op->src[1]) { + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[1]), 2); + } else { + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[0]), 2); + } + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), 3); + + ggml_metal_encoder_dispatch_threadgroups(enc, nrows, 1, 1, nth, 1, 1); + + return 1; +} + +int ggml_metal_op_sum_rows(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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(uint32_t, nb, op, nb); + + ggml_metal_kargs_sum_rows 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, + }; + + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_sum_rows(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); + + const size_t smem = ggml_metal_pipeline_get_smem(pipeline); + + //[encoder setComputePipelineState:pipeline]; + //[encoder setBytes:&args length:sizeof(args) atIndex:0]; + //[encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; + //[encoder setBuffer:id_dst offset:offs_dst atIndex:2]; + //[encoder setThreadgroupMemoryLength:32*sizeof(float) atIndex:0]; + + //[encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; + + 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_set_threadgroup_memory_size(enc, smem, 0); + + ggml_metal_encoder_dispatch_threadgroups(enc, ne01, ne02, ne03, nth, 1, 1); + + return 1; +} + +int ggml_metal_op_get_rows(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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, ne1, op->src[1], ne); + GGML_TENSOR_LOCALS(uint64_t, nb1, op->src[1], nb); + GGML_TENSOR_LOCALS( int32_t, ne, op, ne); + GGML_TENSOR_LOCALS(uint32_t, nb, op, nb); + + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_get_rows(lib, op->src[0]->type); + + ggml_metal_kargs_get_rows args = { + /*.ne00 =*/ ne00, + /*.nb01 =*/ nb01, + /*.nb02 =*/ nb02, + /*.ne10 =*/ ne10, + /*.nb10 =*/ nb10, + /*.nb11 =*/ nb11, + /*.nb1 =*/ nb1, + /*.nb2 =*/ nb2, + }; + + 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->src[1]), 2); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), 3); + + ggml_metal_encoder_dispatch_threadgroups(enc, ne10, ne11, ne12, 32, 1, 1); + + return 1; +} + +int ggml_metal_op_set_rows(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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, ne1, op->src[1], ne); + GGML_TENSOR_LOCALS(uint64_t, nb1, op->src[1], nb); + GGML_TENSOR_LOCALS( int32_t, ne, op, ne); + GGML_TENSOR_LOCALS(uint32_t, nb, op, nb); + + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_set_rows(lib, op->type); + + const int32_t nk0 = ne0/ggml_blck_size(op->type); + + int nth = 32; // SIMD width + + while (nth < nk0 && nth < ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)) { + nth *= 2; + } + + int nrptg = 1; + if (nth > nk0) { + nrptg = (nth + nk0 - 1)/nk0; + nth = nk0; + + if (nrptg*nth > ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)) { + nrptg--; + } + } + + nth = std::min(nth, nk0); + + ggml_metal_kargs_set_rows args = { + /*.nk0 =*/ nk0, + /*.ne01 =*/ ne01, + /*.nb01 =*/ nb01, + /*.nb02 =*/ nb02, + /*.nb03 =*/ nb03, + /*.ne11 =*/ ne11, + /*.ne12 =*/ ne12, + /*.nb10 =*/ nb10, + /*.nb11 =*/ nb11, + /*.nb12 =*/ nb12, + /*.nb1 =*/ nb1, + /*.nb2 =*/ nb2, + /*.nb3 =*/ nb3, + }; + + 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->src[1]), 2); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), 3); + + ggml_metal_encoder_dispatch_threadgroups(enc, (ne01 + nrptg - 1)/nrptg, ne02, ne03, nth, nrptg, 1); + + return 1; +} + +int ggml_metal_op_soft_max(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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, ne1, op->src[1], ne); + GGML_TENSOR_LOCALS(uint64_t, nb1, op->src[1], nb); + GGML_TENSOR_LOCALS( int32_t, ne2, op->src[2], ne); + GGML_TENSOR_LOCALS(uint64_t, nb2, op->src[2], nb); + GGML_TENSOR_LOCALS( int32_t, ne, op, ne); + GGML_TENSOR_LOCALS(uint32_t, nb, op, nb); + + float scale; + float max_bias; + + memcpy(&scale, ((const int32_t *) op->op_params) + 0, sizeof(scale)); + memcpy(&max_bias, ((const int32_t *) op->op_params) + 1, sizeof(max_bias)); + + const uint32_t n_head = op->src[0]->ne[2]; + const int32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head)); + + const float m0 = powf(2.0f, -(max_bias ) / n_head_log2); + const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2); + + // softmax + + ggml_metal_kargs_soft_max args = { + /*.ne00 =*/ ne00, + /*.ne01 =*/ ne01, + /*.ne02 =*/ ne02, + /*.nb01 =*/ nb01, + /*.nb02 =*/ nb02, + /*.nb03 =*/ nb03, + /*.ne11 =*/ ne11, + /*.ne12 =*/ ne12, + /*.ne13 =*/ ne13, + /*.nb11 =*/ nb11, + /*.nb12 =*/ nb12, + /*.nb13 =*/ nb13, + /*.nb1 =*/ nb1, + /*.nb2 =*/ nb2, + /*.nb3 =*/ nb3, + /*.scale =*/ scale, + /*.max_bias =*/ max_bias, + /*.m0 =*/ m0, + /*.m1 =*/ m1, + /*.n_head_log2 =*/ n_head_log2, + }; + + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_soft_max(lib, op); + + int nth = 32; // SIMD width + + if (ne00%4 == 0) { + while (nth < ne00/4 && nth*ne01*ne02*ne03 < 256) { + nth *= 2; + } + } else { + while (nth < ne00 && nth*ne01*ne02*ne03 < 256) { + nth *= 2; + } + } + + const size_t smem = ggml_metal_pipeline_get_smem(pipeline); + + 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); + if (op->src[1]) { + ggml_metal_encoder_set_buffer(enc, ggml_metal_get_buffer_id(op->src[1]), 2); + } else { + ggml_metal_encoder_set_buffer(enc, ggml_metal_get_buffer_id(op->src[0]), 2); + } + if (op->src[2]) { + ggml_metal_encoder_set_buffer(enc, ggml_metal_get_buffer_id(op->src[2]), 3); + } else { + ggml_metal_encoder_set_buffer(enc, ggml_metal_get_buffer_id(op->src[0]), 3); + } + ggml_metal_encoder_set_buffer(enc, ggml_metal_get_buffer_id(op), 4); + + ggml_metal_encoder_set_threadgroup_memory_size(enc, smem, 0); + + ggml_metal_encoder_dispatch_threadgroups(enc, ne01, ne02, ne03, nth, 1, 1); + + return 1; +} + +int ggml_metal_op_ssm_conv(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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, ne1, op->src[1], ne); + GGML_TENSOR_LOCALS(uint64_t, nb1, op->src[1], nb); + GGML_TENSOR_LOCALS( int32_t, ne, op, ne); + GGML_TENSOR_LOCALS(uint32_t, nb, op, nb); + + ggml_metal_kargs_ssm_conv args = { + /*.ne00 =*/ ne00, + /*.ne01 =*/ ne01, + /*.ne02 =*/ ne02, + /*.nb00 =*/ nb00, + /*.nb01 =*/ nb01, + /*.nb02 =*/ nb02, + /*.ne10 =*/ ne10, + /*.ne11 =*/ ne11, + /*.nb10 =*/ nb10, + /*.nb11 =*/ nb11, + /*.ne0 =*/ ne0, + /*.ne1 =*/ ne1, + /*.ne2 =*/ ne2, + /*.nb0 =*/ nb0, + /*.nb1 =*/ nb1, + /*.nb2 =*/ nb2, + }; + + ggml_metal_pipeline_t 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); + 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->src[1]), 2); + ggml_metal_encoder_set_buffer(enc, ggml_metal_get_buffer_id(op), 3); + + ggml_metal_encoder_dispatch_threadgroups(enc, ne01, ne1, ne02, 1, 1, 1); + + return 1; +} + +int ggml_metal_op_ssm_scan(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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, ne1, op->src[1], ne); + GGML_TENSOR_LOCALS(uint64_t, nb1, op->src[1], nb); + GGML_TENSOR_LOCALS( int32_t, ne2, op->src[2], ne); + GGML_TENSOR_LOCALS(uint64_t, nb2, op->src[2], nb); + GGML_TENSOR_LOCALS( int32_t, ne3, op->src[3], ne); + GGML_TENSOR_LOCALS(uint64_t, nb3, op->src[3], nb); + GGML_TENSOR_LOCALS( int32_t, ne4, op->src[4], ne); + GGML_TENSOR_LOCALS(uint64_t, nb4, op->src[4], nb); + GGML_TENSOR_LOCALS( int32_t, ne5, op->src[5], ne); + GGML_TENSOR_LOCALS(uint64_t, nb5, op->src[5], nb); + GGML_TENSOR_LOCALS( int32_t, ne6, op->src[6], ne); + GGML_TENSOR_LOCALS(uint64_t, nb6, op->src[6], nb); + GGML_TENSOR_LOCALS( int32_t, ne, op, ne); + GGML_TENSOR_LOCALS(uint32_t, nb, op, nb); + + const ggml_tensor * src3 = op->src[3]; + const ggml_tensor * src4 = op->src[4]; + const ggml_tensor * src5 = op->src[5]; + const ggml_tensor * src6 = op->src[6]; + + GGML_ASSERT(src3); + GGML_ASSERT(src4); + GGML_ASSERT(src5); + GGML_ASSERT(src6); + + const int64_t d_state = ne00; + const int64_t d_inner = ne01; + const int64_t n_head = ne02; + const int64_t n_group = ne41; + const int64_t n_seq_tokens = ne12; + const int64_t n_seqs = ne13; + + ggml_metal_kargs_ssm_scan args = { + /*.d_state =*/ d_state, + /*.d_inner =*/ d_inner, + /*.n_head =*/ n_head, + /*.n_group =*/ n_group, + /*.n_seq_tokens =*/ n_seq_tokens, + /*.n_seqs =*/ n_seqs, + /*.s_off =*/ ggml_nelements(op->src[1]) * sizeof(float), + /*.nb01 =*/ nb01, + /*.nb02 =*/ nb02, + /*.nb03 =*/ nb03, + /*.nb11 =*/ nb11, + /*.nb12 =*/ nb12, + /*.nb13 =*/ nb13, + /*.nb21 =*/ nb21, + /*.nb22 =*/ nb22, + /*.nb31 =*/ nb31, + /*.nb41 =*/ nb41, + /*.nb42 =*/ nb42, + /*.nb43 =*/ nb43, + /*.nb51 =*/ nb51, + /*.nb52 =*/ nb52, + /*.nb53 =*/ nb53, + }; + + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_ssm_scan(lib, op); + + const size_t sms = ggml_metal_pipeline_get_smem(pipeline); + + 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->src[1]), 2); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[2]), 3); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[3]), 4); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[4]), 5); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[5]), 6); + 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); + + if (ne30 == 1) { + // Mamba-2 + ggml_metal_encoder_dispatch_threadgroups(enc, d_inner, n_head, n_seqs, d_state, 1, 1); + } else { + GGML_ASSERT(d_inner == 1); + ggml_metal_encoder_dispatch_threadgroups(enc, n_head, n_seqs, 1, d_state, 1, 1); + } + + return 1; +} + +int ggml_metal_op_rwkv(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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(uint32_t, nb, op, nb); + + const int64_t B = op->op == GGML_OP_RWKV_WKV6 ? op->src[5]->ne[1] : op->src[6]->ne[1]; + const int64_t T = op->src[0]->ne[2]; + 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); + + int ida = 0; + + ggml_metal_encoder_set_pipeline(enc, pipeline); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[0]), ida++); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[1]), ida++); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[2]), ida++); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[3]), ida++); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[4]), ida++); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[5]), ida++); + if (op->op == GGML_OP_RWKV_WKV7) { + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[6]), ida++); + } + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), ida++); + ggml_metal_encoder_set_bytes (enc, (void *) &B, sizeof(B), ida++); + ggml_metal_encoder_set_bytes (enc, (void *) &T, sizeof(T), ida++); + ggml_metal_encoder_set_bytes (enc, (void *) &C, sizeof(C), ida++); + ggml_metal_encoder_set_bytes (enc, (void *) &H, sizeof(H), ida++); + + ggml_metal_encoder_dispatch_threadgroups(enc, B * H, 1, 1, C/H, 1, 1); + + return 1; +} + +int ggml_metal_op_cpy(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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(uint32_t, nb, op, nb); + + ggml_metal_pipeline_t 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); + + // TODO: support + //const int32_t nk00 = ne00/ggml_blck_size(op->type); + const int32_t nk00 = ne00; + + int nth = 32; // SIMD width + + while (nth < nk00 && nth < ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)) { + nth *= 2; + } + + nth = std::min(nth, ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)); + + // when rows are small, we can batch them together in a single threadgroup + int nrptg = 1; + + // TODO: relax this constraint in the future + if (ggml_blck_size(op->src[0]->type) == 1 && ggml_blck_size(op->type) == 1) { + if (nth > nk00) { + nrptg = (nth + nk00 - 1)/nk00; + nth = nk00; + + if (nrptg*nth > ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)) { + nrptg--; + } + } + } + + nth = std::min(nth, nk00); + + ggml_metal_kargs_cpy args = { + /*.ne00 =*/ nk00, + /*.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, + }; + + 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, nrptg, 1); + + return 1; +} + +int ggml_metal_op_pool_2d(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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(uint32_t, nb, op, nb); + + const int32_t * opts = op->op_params; + ggml_op_pool op_pool = (ggml_op_pool) opts[0]; + + const int32_t k0 = opts[1]; + const int32_t k1 = opts[2]; + const int32_t s0 = opts[3]; + const int32_t s1 = opts[4]; + const int32_t p0 = opts[5]; + const int32_t p1 = opts[6]; + + const int64_t IH = op->src[0]->ne[1]; + const int64_t IW = op->src[0]->ne[0]; + + const int64_t N = op->ne[3]; + const int64_t OC = op->ne[2]; + const int64_t OH = op->ne[1]; + const int64_t OW = op->ne[0]; + + const int64_t np = N * OC * OH * OW; + + ggml_metal_kargs_pool_2d args_pool_2d = { + /* .k0 = */ k0, + /* .k1 = */ k1, + /* .s0 = */ s0, + /* .s1 = */ s1, + /* .p0 = */ p0, + /* .p1 = */ p1, + /* .IH = */ IH, + /* .IW = */ IW, + /* .OH = */ OH, + /* .OW = */ OW, + /* .np = */ np + }; + + ggml_metal_pipeline_t 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; + + ggml_metal_encoder_set_pipeline(enc, pipeline); + ggml_metal_encoder_set_bytes (enc, &args_pool_2d, sizeof(args_pool_2d), 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, ntg, 1, 1, nth, 1, 1); + + return 1; +} + +int ggml_metal_op_mul_mat(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, idx); + + ggml_metal_library_t lib = ctx->lib; + ggml_metal_encoder_t enc = ctx->enc; + + const ggml_metal_device_props * props_dev = ggml_metal_device_get_props(ctx->dev); + + 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, ne1, op->src[1], ne); + GGML_TENSOR_LOCALS(uint64_t, nb1, op->src[1], nb); + GGML_TENSOR_LOCALS( int32_t, ne, op, ne); + GGML_TENSOR_LOCALS(uint32_t, nb, op, nb); + + GGML_ASSERT(ne00 == ne10); + + GGML_ASSERT(ne12 % ne02 == 0); + GGML_ASSERT(ne13 % ne03 == 0); + + const int16_t r2 = ne12/ne02; + const int16_t r3 = ne13/ne03; + + // find the break-even point where the matrix-matrix kernel becomes more efficient compared + // to the matrix-vector kernel + const int ne11_mm_min = 8; + + // first try to use small-batch mat-mv kernels + // these should be efficient for BS [2, ~8] + if (op->src[1]->type == GGML_TYPE_F32 && (ne00%128 == 0) && + ( + ( + ( + op->src[0]->type == GGML_TYPE_F32 || // TODO: helper function + op->src[0]->type == GGML_TYPE_F16 || + op->src[0]->type == GGML_TYPE_Q4_0 || + op->src[0]->type == GGML_TYPE_Q4_1 || + op->src[0]->type == GGML_TYPE_Q5_0 || + op->src[0]->type == GGML_TYPE_Q5_1 || + op->src[0]->type == GGML_TYPE_Q8_0 || + op->src[0]->type == GGML_TYPE_MXFP4 || + op->src[0]->type == GGML_TYPE_IQ4_NL || + false) && (ne11 >= 2 && ne11 <= 8) + ) || + ( + ( + op->src[0]->type == GGML_TYPE_Q4_K || + op->src[0]->type == GGML_TYPE_Q5_K || + op->src[0]->type == GGML_TYPE_Q6_K || + false) && (ne11 >= 4 && ne11 <= 8) + ) + ) + ) { + // TODO: determine the optimal parameters based on grid utilization + // I still don't know why we should not always use the maximum available threads: + // + // nsg = pipeline.maxTotalThreadsPerThreadgroup / 32 + // + // my current hypothesis is that the work grid is not evenly divisible for different nsg + // values and there can be some tail effects when nsg is high. need to confirm this + // + const int nsg = 2; // num simdgroups per threadgroup + + // num threads along row per simdgroup + int16_t nxpsg = 0; + if (ne00 % 256 == 0 && ne11 < 3) { + nxpsg = 16; + } else if (ne00 % 128 == 0) { + nxpsg = 8; + } else { + nxpsg = 4; + } + + const int16_t nypsg = 32/nxpsg; // num threads along col per simdgroup (i.e. a simdgroup processes that many src0 rows at a time) + const int16_t r0ptg = nypsg*nsg; // num src0 rows per threadgroup + int16_t r1ptg = 4; // num src1 rows per threadgroup + + // note: not sure how optimal are those across all different hardware. there might be someting cleverer + switch (ne11) { + case 2: + r1ptg = 2; break; + case 3: + case 6: + r1ptg = 3; break; + case 4: + case 7: + case 8: + r1ptg = 4; break; + case 5: + r1ptg = 5; break; + default: + 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, r1ptg); + + ggml_metal_kargs_mul_mv_ext args = { + /*.ne00 =*/ ne00, + /*.ne01 =*/ ne01, + /*.ne02 =*/ ne02, + /*.nb00 =*/ nb00, + /*.nb01 =*/ nb01, + /*.nb02 =*/ nb02, + /*.nb03 =*/ nb03, + /*.ne10 =*/ ne10, + /*.ne11 =*/ ne11, + /*.ne12 =*/ ne12, + /*.nb10 =*/ nb10, + /*.nb11 =*/ nb11, + /*.nb12 =*/ nb12, + /*.nb13 =*/ nb13, + /*.ne0 =*/ ne0, + /*.ne1 =*/ ne1, + /*.r2 =*/ r2, + /*.r3 =*/ r3, + /*.nsg =*/ nsg, + /*.nxpsg =*/ nxpsg, + /*.r1ptg =*/ r1ptg, + }; + + 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->src[1]), 2); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), 3); + + ggml_metal_encoder_dispatch_threadgroups(enc, ((ne01 + r0ptg - 1)/r0ptg), ((ne11 + r1ptg - 1)/r1ptg), ne12*ne13, 32, nsg, 1); + } else if ( + !ggml_is_transposed(op->src[0]) && + !ggml_is_transposed(op->src[1]) && + // for now the matrix-matrix multiplication kernel only works on A14+/M1+ SoCs + // AMD GPU and older A-chips will reuse matrix-vector multiplication kernel + props_dev->has_simdgroup_mm && + op->src[1]->type == GGML_TYPE_F32 && + ne00 % 32 == 0 && ne00 >= 64 && + (ne11 > ne11_mm_min || (ggml_is_quantized(op->src[0]->type) && ne12 > 1))) { + //printf("matrix: ne00 = %6d, ne01 = %6d, ne02 = %6d, ne11 = %6d, ne12 = %6d\n", ne00, ne01, ne02, ne11, ne12); + + // some Metal matrix data types require aligned pointers + // ref: https://developer.apple.com/metal/Metal-Shading-Language-Specification.pdf (Table 2.5) + switch (op->src[0]->type) { + case GGML_TYPE_F32: GGML_ASSERT(nb01 % 16 == 0); break; + case GGML_TYPE_F16: GGML_ASSERT(nb01 % 8 == 0); break; + case GGML_TYPE_BF16: GGML_ASSERT(nb01 % 8 == 0); break; + default: break; + } + + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_mul_mm(lib, op->src[0]->type, op->src[1]->type); + + ggml_metal_kargs_mul_mm args = { + /*.ne00 =*/ ne00, + /*.ne02 =*/ ne02, + /*.nb01 =*/ nb01, + /*.nb02 =*/ nb02, + /*.nb03 =*/ nb03, + /*.ne12 =*/ ne12, + /*.nb10 =*/ nb10, + /*.nb11 =*/ nb11, + /*.nb12 =*/ nb12, + /*.nb13 =*/ nb13, + /*.ne0 =*/ ne0, + /*.ne1 =*/ ne1, + /*.r2 =*/ r2, + /*.r3 =*/ r3, + }; + + 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->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); + + 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); + + ggml_metal_kargs_mul_mv args = { + /*.ne00 =*/ ne00, + /*.ne01 =*/ ne01, + /*.ne02 =*/ ne02, + /*.nb00 =*/ nb00, + /*.nb01 =*/ nb01, + /*.nb02 =*/ nb02, + /*.nb03 =*/ nb03, + /*.ne10 =*/ ne10, + /*.ne11 =*/ ne11, + /*.ne12 =*/ ne12, + /*.nb10 =*/ nb10, + /*.nb11 =*/ nb11, + /*.nb12 =*/ nb12, + /*.nb13 =*/ nb13, + /*.ne0 =*/ ne0, + /*.ne1 =*/ ne1, + /*.r2 =*/ r2, + /*.r3 =*/ r3, + }; + + 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 size_t smem = ggml_metal_pipeline_get_smem(pipeline); + + 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->src[1]), 2); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), 3); + + ggml_metal_encoder_set_threadgroup_memory_size(enc, smem, 0); + + if (op->src[0]->type == GGML_TYPE_Q8_0) { + ggml_metal_encoder_dispatch_threadgroups(enc, ((ne01 + nr0 - 1)/(nr0)), ((ne11 + nr1 - 1)/nr1), ne12*ne13, 32, nsg, 1); + } else { + ggml_metal_encoder_dispatch_threadgroups(enc, ((ne01 + nr0*nsg - 1)/(nr0*nsg)), ((ne11 + nr1 - 1)/nr1), ne12*ne13, 32, nsg, 1); + } + } + + return 1; +} + +size_t ggml_metal_op_mul_mat_id_extra_tpe(const ggml_tensor * op) { + assert(op->op == GGML_OP_MUL_MAT_ID); + + const int64_t ne02 = op->src[0]->ne[2]; // n_expert + + return ggml_type_size(GGML_TYPE_I32)*ne02; +} + +size_t ggml_metal_op_mul_mat_id_extra_ids(const ggml_tensor * op) { + assert(op->op == GGML_OP_MUL_MAT_ID); + + const int64_t ne02 = op->src[0]->ne[2]; // n_expert + const int64_t ne21 = op->src[2]->ne[1]; // n_token + + return ggml_type_size(GGML_TYPE_I32)*ne02*ne21; +} + +int ggml_metal_op_mul_mat_id(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, idx); + + ggml_metal_library_t lib = ctx->lib; + ggml_metal_encoder_t enc = ctx->enc; + + const ggml_metal_device_props * props_dev = ggml_metal_device_get_props(ctx->dev); + + 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, ne1, op->src[1], ne); + GGML_TENSOR_LOCALS(uint64_t, nb1, op->src[1], nb); + GGML_TENSOR_LOCALS( int32_t, ne2, op->src[2], ne); + GGML_TENSOR_LOCALS(uint64_t, nb2, op->src[2], nb); + GGML_TENSOR_LOCALS( int32_t, ne, op, ne); + GGML_TENSOR_LOCALS(uint32_t, nb, op, nb); + + // src2 = ids + GGML_ASSERT(op->src[2]->type == GGML_TYPE_I32); + + GGML_ASSERT(!ggml_is_transposed(op->src[0])); + GGML_ASSERT(!ggml_is_transposed(op->src[1])); + + GGML_ASSERT(op->src[1]->type == GGML_TYPE_F32); + + GGML_ASSERT(ne03 == 1); + GGML_ASSERT(ne13 == 1); + + ggml_metal_buffer_id bid_src0 = ggml_metal_get_buffer_id(op->src[0]); + ggml_metal_buffer_id bid_src1 = ggml_metal_get_buffer_id(op->src[1]); + ggml_metal_buffer_id bid_src2 = ggml_metal_get_buffer_id(op->src[2]); + ggml_metal_buffer_id bid_dst = ggml_metal_get_buffer_id(op); + + const uint32_t r2 = 1; + const uint32_t r3 = 1; + + // find the break-even point where the matrix-matrix kernel becomes more efficient compared + // to the matrix-vector kernel + // ne20 = n_used_experts + // ne21 = n_rows (batch size) + const int ne21_mm_id_min = 32; + + if (props_dev->has_simdgroup_mm && + ne00 % 32 == 0 && ne00 >= 64 && + (ne21 >= ne21_mm_id_min)) { + GGML_ASSERT(ne00 % 4 == 0); + + // some Metal matrix data types require aligned pointers + // ref: https://developer.apple.com/metal/Metal-Shading-Language-Specification.pdf (Table 2.5) + switch (op->src[0]->type) { + case GGML_TYPE_F32: GGML_ASSERT(nb01 % 16 == 0); break; + case GGML_TYPE_F16: GGML_ASSERT(nb01 % 8 == 0); break; + case GGML_TYPE_BF16: GGML_ASSERT(nb01 % 8 == 0); break; + default: break; + } + + // extra buffers for intermediate id mapping + ggml_metal_buffer_id bid_tpe = bid_dst; + bid_tpe.offs += ggml_nbytes(op); + + ggml_metal_buffer_id bid_ids = bid_tpe; + bid_ids.offs += ggml_metal_op_mul_mat_id_extra_tpe(op); + + { + ggml_metal_kargs_mul_mm_id_map0 args = { + ne02, + ne10, + ne11, // n_expert_used (bcast) + nb11, + nb12, + ne21, // n_tokens + ne20, // n_expert_used + nb21, + }; + + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_mul_mm_id_map0(lib, ne02, ne20); + + const size_t smem = ggml_metal_pipeline_get_smem(pipeline); + + GGML_ASSERT(ne02 <= ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)); + + GGML_ASSERT(smem <= props_dev->max_theadgroup_memory_size); + + ggml_metal_encoder_set_pipeline(enc, pipeline); + ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); + ggml_metal_encoder_set_buffer (enc, bid_src2, 1); + ggml_metal_encoder_set_buffer (enc, bid_tpe, 2); + ggml_metal_encoder_set_buffer (enc, bid_ids, 3); + + ggml_metal_encoder_set_threadgroup_memory_size(enc, smem, 0); + + ggml_metal_encoder_dispatch_threadgroups(enc, 1, 1, 1, ne02, 1, 1); + } + + // this barrier is always needed because the next kernel has to wait for the id maps to be computed + ggml_metal_op_concurrency_reset(ctx); + + { + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_mul_mm_id(lib, op->src[0]->type, GGML_TYPE_F16); + + ggml_metal_kargs_mul_mm_id args = { + /*.ne00 =*/ ne00, + /*.ne02 =*/ ne02, + /*.nb01 =*/ nb01, + /*.nb02 =*/ nb02, + /*.nb03 =*/ nb03, + /*.ne11 =*/ ne11, // n_expert_used (bcast) + /*.nb10 =*/ nb10, + /*.nb11 =*/ nb11, + /*.nb12 =*/ nb12, + /*.nb13 =*/ nb13, + /*.ne20 =*/ ne20, // n_expert_used + /*.ne21 =*/ ne21, // n_tokens + /*.ne0 =*/ ne0, + /*.ne1 =*/ ne1, + /*.r2 =*/ r2, + /*.r3 =*/ r3, + }; + + ggml_metal_encoder_set_pipeline(enc, pipeline); + ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); + ggml_metal_encoder_set_buffer (enc, bid_src0, 1); + ggml_metal_encoder_set_buffer (enc, bid_src1, 2); + ggml_metal_encoder_set_buffer (enc, bid_tpe, 3); + 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); + + 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_kargs_mul_mv_id args = { + /*.nei0 =*/ ne20, + /*.nei1 =*/ ne21, + /*.nbi1 =*/ nb21, + /*.ne00 =*/ ne00, + /*.ne01 =*/ ne01, + /*.ne02 =*/ ne02, + /*.nb00 =*/ nb00, + /*.nb01 =*/ nb01, + /*.nb02 =*/ nb02, + /*.ne10 =*/ ne10, + /*.ne11 =*/ ne11, + /*.ne12 =*/ ne12, + /*.ne13 =*/ ne13, + /*.nb10 =*/ nb10, + /*.nb11 =*/ nb11, + /*.nb12 =*/ nb12, + /*.ne0 =*/ ne0, + /*.ne1 =*/ ne1, + /*.nb1 =*/ nb1, + }; + + ggml_metal_pipeline_t 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 size_t smem = ggml_metal_pipeline_get_smem(pipeline); + + if (ggml_is_quantized(op->src[0]->type)) { + GGML_ASSERT(ne00 >= nsg*nr0); + } + + ggml_metal_encoder_set_pipeline(enc, pipeline); + ggml_metal_encoder_set_bytes(enc, &args, sizeof(args), 0); + ggml_metal_encoder_set_buffer(enc, bid_src0, 1); + ggml_metal_encoder_set_buffer(enc, bid_src1, 2); + ggml_metal_encoder_set_buffer(enc, bid_dst, 3); + ggml_metal_encoder_set_buffer(enc, bid_src2, 4); + + const int64_t _ne1 = 1; + const int64_t ne123 = ne20*ne21; + + ggml_metal_encoder_set_threadgroup_memory_size(enc, smem, 0); + + if (op->src[0]->type == GGML_TYPE_Q8_0) { + ggml_metal_encoder_dispatch_threadgroups(enc, (ne01 + nr0 - 1)/(nr0), (_ne1 + nr1 - 1)/nr1, ne123, 32, nsg, 1); + } else { + ggml_metal_encoder_dispatch_threadgroups(enc, (ne01 + nr0*nsg - 1)/(nr0*nsg), (_ne1 + nr1 - 1)/nr1, ne123, 32, nsg, 1); + } + } + + return 1; +} + +int ggml_metal_op_add_id(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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, ne1, op->src[1], ne); + GGML_TENSOR_LOCALS(uint64_t, nb1, op->src[1], nb); + GGML_TENSOR_LOCALS( int32_t, ne2, op->src[2], ne); + GGML_TENSOR_LOCALS(uint64_t, nb2, op->src[2], nb); + GGML_TENSOR_LOCALS( int32_t, ne, op, ne); + + GGML_ASSERT(op->src[0]->type == GGML_TYPE_F32); + GGML_ASSERT(op->src[1]->type == GGML_TYPE_F32); + GGML_ASSERT(op->src[2]->type == GGML_TYPE_I32); + GGML_ASSERT(op->type == GGML_TYPE_F32); + + GGML_ASSERT(ggml_is_contiguous_rows(op->src[0])); + + ggml_metal_kargs_add_id args = { + /*.ne0 =*/ ne0, + /*.ne1 =*/ ne1, + /*.nb01 =*/ nb01, + /*.nb02 =*/ nb02, + /*.nb11 =*/ nb11, + /*.nb21 =*/ nb21, + }; + + ggml_metal_pipeline_t 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); + 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->src[1]), 2); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[2]), 3); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), 4); + + const int nth = std::min(ggml_metal_pipeline_max_theads_per_threadgroup(pipeline), ne00); + + ggml_metal_encoder_dispatch_threadgroups(enc, ne01, ne02, 1, nth, 1, 1); + + return 1; +} + +bool ggml_metal_op_flash_attn_ext_use_vec(const ggml_tensor * op) { + assert(op->op == GGML_OP_FLASH_ATTN_EXT); + + const int64_t ne00 = op->src[0]->ne[0]; // head size + const int64_t ne01 = op->src[0]->ne[1]; // batch size + + // use vec kernel if the batch size is small and if the head size is supported + return (ne01 < 20) && (ne00 % 32 == 0); +} + +size_t ggml_metal_op_flash_attn_ext_extra_tmp(const ggml_tensor * op) { + assert(op->op == GGML_OP_FLASH_ATTN_EXT); + + const int64_t nwg = 32; + + const int64_t ne01 = op->src[0]->ne[1]; + const int64_t ne02 = op->src[0]->ne[2]; + const int64_t ne03 = op->src[0]->ne[3]; + const int64_t ne20 = op->src[2]->ne[0]; + + // temp buffer for writing the results from each workgroup + // - ne20: the size of the Value head + // - + 2: the S and M values for each intermediate result + return ggml_type_size(GGML_TYPE_F32)*(ne01*ne02*ne03*nwg*(ne20 + 2)); +} + +int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, idx); + + ggml_metal_library_t lib = ctx->lib; + ggml_metal_encoder_t enc = ctx->enc; + + const ggml_metal_device_props * props_dev = ggml_metal_device_get_props(ctx->dev); + + 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, ne1, op->src[1], ne); + GGML_TENSOR_LOCALS(uint64_t, nb1, op->src[1], nb); + GGML_TENSOR_LOCALS( int32_t, ne2, op->src[2], ne); + GGML_TENSOR_LOCALS(uint64_t, nb2, op->src[2], nb); + GGML_TENSOR_LOCALS( int32_t, ne3, op->src[3], ne); + GGML_TENSOR_LOCALS(uint64_t, nb3, op->src[3], nb); + GGML_TENSOR_LOCALS( int32_t, ne, op, ne); + GGML_TENSOR_LOCALS( int32_t, nb, op, nb); + + GGML_ASSERT(ne00 % 4 == 0); + GGML_ASSERT(ne11 % 32 == 0); + + GGML_ASSERT(op->src[0]->type == GGML_TYPE_F32); + GGML_ASSERT(op->src[1]->type == op->src[2]->type); + + //GGML_ASSERT(ggml_are_same_shape (src1, src2)); + GGML_ASSERT(ne11 == ne21); + GGML_ASSERT(ne12 == ne22); + + GGML_ASSERT(!op->src[3] || op->src[3]->type == GGML_TYPE_F16); + GGML_ASSERT(!op->src[3] || op->src[3]->ne[1] >= GGML_PAD(op->src[0]->ne[1], 8) && + "the Flash-Attention Metal kernel requires the mask to be padded to 8 and at least n_queries big"); + + float scale; + float max_bias; + float logit_softcap; + + memcpy(&scale, ((const int32_t *) op->op_params) + 0, sizeof(scale)); + memcpy(&max_bias, ((const int32_t *) op->op_params) + 1, sizeof(max_bias)); + memcpy(&logit_softcap, ((const int32_t *) op->op_params) + 2, sizeof(logit_softcap)); + + if (logit_softcap != 0.0f) { + scale /= logit_softcap; + } + + const bool has_mask = op->src[3] != NULL; + const bool has_sinks = op->src[4] != NULL; + const bool has_bias = max_bias != 0.0f; + const bool has_scap = logit_softcap != 0.0f; + + const uint32_t n_head = op->src[0]->ne[2]; + const int32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head)); + + const float m0 = powf(2.0f, -(max_bias ) / n_head_log2); + const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2); + + GGML_ASSERT(ne01 < 65536); + + if (!ggml_metal_op_flash_attn_ext_use_vec(op)) { + // half8x8 kernel + const int64_t nqptg = 8; // queries per threadgroup !! sync with kernel template arguments !! + const int64_t ncpsg = 64; // cache values per simdgroup !! sync with kernel template arguments !! + + GGML_ASSERT(nqptg <= 32); + GGML_ASSERT(nqptg % 8 == 0); + GGML_ASSERT(ncpsg % 32 == 0); + + const int is_q = ggml_is_quantized(op->src[1]->type) ? 1 : 0; + + // 2*(2*ncpsg) + // ncpsg soft_max values + ncpsg mask values + // + // 16*32*(nsg) + // the shared memory needed for the simdgroups to load the KV cache + // each thread loads (dequantizes) 16 head elements, there are 32 threads in th SG + // +#define FATTN_SMEM(nsg) (GGML_PAD((nqptg*(ne00 + 2*GGML_PAD(ne20, 64) + 2*(2*ncpsg)) + is_q*(16*32*(nsg)))*(sizeof(float)/2), 16)) + + //int64_t nsgmax = 4; + // + //if (is_q) { + // nsgmax = 2; + // while (true) { + // const size_t smem = FATTN_SMEM(nsgmax); + // if (smem > props_dev->max_theadgroup_memory_size) { + // break; + // } + // nsgmax *= 2; + // } + // nsgmax /= 2; + //} + + // simdgroups per threadgroup (a.k.a. warps) + //nsg = ne01 <= nqptg ? MAX(4, MIN(nsgmax, MIN(ne11/ncpsg, (int64_t) pipeline.maxTotalThreadsPerThreadgroup/32))) : 4; + int32_t nsg = 4; + + const size_t smem = FATTN_SMEM(nsg); + + ggml_metal_kargs_flash_attn_ext args = { + /*.ne01 =*/ ne01, + /*.ne02 =*/ ne02, + /*.ne03 =*/ ne03, + /*.nb01 =*/ nb01, + /*.nb02 =*/ nb02, + /*.nb03 =*/ nb03, + /*.ne11 =*/ ne11, + /*.ne_12_2 =*/ ne12, + /*.ne_12_3 =*/ ne13, + /*.ns10 =*/ int32_t(nb11/nb10), + /*.nb11 =*/ nb11, + /*.nb12 =*/ nb12, + /*.nb13 =*/ nb13, + /*.ns20 =*/ int32_t(nb21/nb20), + /*.nb21 =*/ nb21, + /*.nb22 =*/ nb22, + /*.nb23 =*/ nb23, + /*.ne32 =*/ ne32, + /*.ne33 =*/ ne33, + /*.nb31 =*/ nb31, + /*.nb32 =*/ nb32, + /*.nb33 =*/ nb33, + /*.ne1 =*/ ne1, + /*.ne2 =*/ ne2, + /*.ne3 =*/ ne3, + /*.scale =*/ scale, + /*.max_bias =*/ max_bias, + /*.m0 =*/ m0, + /*.m1 =*/ m1, + /*.n_head_log2 =*/ n_head_log2, + /*.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, nsg); + + 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->src[1]), 2); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[2]), 3); + if (op->src[3]) { + ggml_metal_encoder_set_buffer(enc, ggml_metal_get_buffer_id(op->src[3]), 4); + } else { + ggml_metal_encoder_set_buffer(enc, ggml_metal_get_buffer_id(op->src[0]), 4); + } + if (op->src[4]) { + ggml_metal_encoder_set_buffer(enc, ggml_metal_get_buffer_id(op->src[4]), 5); + } else { + ggml_metal_encoder_set_buffer(enc, ggml_metal_get_buffer_id(op->src[0]), 5); + } + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), 6); + + ggml_metal_encoder_set_threadgroup_memory_size(enc, smem, 0); + + ggml_metal_encoder_dispatch_threadgroups(enc, (ne01 + nqptg - 1)/nqptg, ne02, ne03, 32, nsg, 1); +#undef FATTN_SMEM + } else { + // half4x4 kernel + const int64_t nqptg = 1; // queries per threadgroup !! sync with kernel template arguments !! + const int64_t ncpsg = 32; // cache values per simdgroup !! sync with kernel template arguments !! + const int64_t nkpsg = 1*ncpsg; + + GGML_ASSERT(nqptg <= 32); + GGML_ASSERT(nqptg % 1 == 0); + GGML_ASSERT(ncpsg % 32 == 0); + + // ne00 + 2*ncpsg*(nsg) + // for each query, we load it as f16 in shared memory (ne00) + // and store the soft_max values and the mask + // + // ne20*(nsg) + // each simdgroup has a full f32 head vector in shared mem to accumulate results + // +#define FATTN_SMEM(nsg) (GGML_PAD((nqptg*(GGML_PAD(ne00, 128) + 4*ncpsg*(nsg)) + 2*GGML_PAD(ne20, 128)*(nsg))*(sizeof(float)/2), 16)) + + int64_t nsgmax = 2; + while (true) { + const size_t smem = FATTN_SMEM(nsgmax); + // avoid using more than half of the threadgroup memory - can cause slow downs especially for large head sizes + if (smem > props_dev->max_theadgroup_memory_size/2) { + break; + } + nsgmax *= 2; + } + nsgmax /= 2; + + // simdgroups per threadgroup (a.k.a. warps) + //const int64_t nsgt = MAX(2, MIN(nsgmax, MIN((ne11 + nkpsg - 1)/(nkpsg), (int64_t) pipeline.maxTotalThreadsPerThreadgroup/32))); + const int64_t nsgt = MAX(2, MIN(nsgmax, MIN((ne11 + nkpsg - 1)/(nkpsg), (int64_t) 1024/32))); + + int64_t nsg = 1; + while (nsg <= nsgt) { + nsg *= 2; + } + nsg /= 2; + + // workgroups + // each workgroup handles nsg*nkpsg cache values + int32_t nwg = 1; + if (false) { + // for small KV caches, we could launch a single workgroup and write the results directly to dst/ + // however, this does not lead to significant improvement, so disabled + nwg = 1; + nsg = 4; + } else { + nwg = 32; + nsg = 1; + while (2*nwg*nsg*nkpsg < ne11 && nsg < 4) { + nsg *= 2; + } + } + + ggml_metal_kargs_flash_attn_ext_vec args = { + /*.ne01 =*/ ne01, + /*.ne02 =*/ ne02, + /*.ne03 =*/ ne03, + /*.nb01 =*/ nb01, + /*.nb02 =*/ nb02, + /*.nb03 =*/ nb03, + /*.ne11 =*/ ne11, + /*.ne_12_2 =*/ ne12, + /*.ne_12_3 =*/ ne13, + /*.ns10 =*/ int32_t(nb11/nb10), + /*.nb11 =*/ nb11, + /*.nb12 =*/ nb12, + /*.nb13 =*/ nb13, + /*.ns20 =*/ int32_t(nb21/nb20), + /*.nb21 =*/ nb21, + /*.nb22 =*/ nb22, + /*.nb23 =*/ nb23, + /*.ne32 =*/ ne32, + /*.ne33 =*/ ne33, + /*.nb31 =*/ nb31, + /*.nb32 =*/ nb32, + /*.nb33 =*/ nb33, + /*.ne1 =*/ ne1, + /*.ne2 =*/ ne2, + /*.ne3 =*/ ne3, + /*.scale =*/ scale, + /*.max_bias =*/ max_bias, + /*.m0 =*/ m0, + /*.m1 =*/ m1, + /*.n_head_log2 =*/ n_head_log2, + /*.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, nsg, nwg); + + GGML_ASSERT(nsg*32 <= ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)); + + 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->src[1]), 2); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[2]), 3); + if (op->src[3]) { + ggml_metal_encoder_set_buffer(enc, ggml_metal_get_buffer_id(op->src[3]), 4); + } else { + ggml_metal_encoder_set_buffer(enc, ggml_metal_get_buffer_id(op->src[0]), 4); + } + if (op->src[4]) { + ggml_metal_encoder_set_buffer(enc, ggml_metal_get_buffer_id(op->src[4]), 5); + } else { + ggml_metal_encoder_set_buffer(enc, ggml_metal_get_buffer_id(op->src[0]), 5); + } + + const size_t smem = FATTN_SMEM(nsg); + + //printf("smem: %zu, max: %zu, nsg = %d, nsgmax = %d\n", smem, props_dev->max_theadgroup_memory_size, (int) nsg, (int) nsgmax); + GGML_ASSERT(smem <= props_dev->max_theadgroup_memory_size); + + if (nwg == 1) { + // using 1 workgroup -> write the result directly into dst + ggml_metal_encoder_set_buffer(enc, ggml_metal_get_buffer_id(op), 6); + + ggml_metal_encoder_set_threadgroup_memory_size(enc, smem, 0); + + ggml_metal_encoder_dispatch_threadgroups(enc, (ne01 + nqptg - 1)/nqptg, ne02, ne03*nwg, 32, nsg, 1); + } else { + // sanity checks + GGML_ASSERT(ne01*ne02*ne03 == ne1*ne2*ne3); + GGML_ASSERT((uint64_t)ne1*ne2*ne3 <= (1u << 31)); + + ggml_metal_buffer_id bid_dst = ggml_metal_get_buffer_id(op); + + // write the results from each workgroup into a temp buffer + ggml_metal_buffer_id bid_tmp = bid_dst; + bid_tmp.offs += ggml_nbytes(op); + ggml_metal_encoder_set_buffer(enc, bid_tmp, 6); + + ggml_metal_encoder_set_threadgroup_memory_size(enc, smem, 0); + ggml_metal_encoder_dispatch_threadgroups(enc, (ne01 + nqptg - 1)/nqptg, ne02, ne03*nwg, 32, nsg, 1); + + // sync the 2 kernels + ggml_metal_op_concurrency_reset(ctx); + + // reduce the results from the workgroups + { + const int32_t nrows = ne1*ne2*ne3; + + ggml_metal_kargs_flash_attn_ext_vec_reduce args0 = { + nrows, + }; + + ggml_metal_pipeline_t 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); + ggml_metal_encoder_set_buffer (enc, bid_tmp, 1); + ggml_metal_encoder_set_buffer (enc, bid_dst, 2); + + ggml_metal_encoder_dispatch_threadgroups(enc, nrows, 1, 1, 32*nwg, 1, 1); + } + } +#undef FATTN_SMEM + } + + return 1; +} + +int ggml_metal_op_bin(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, idx); + + ggml_tensor ** ops = ggml_graph_nodes(gf) + idx; + + ggml_metal_library_t lib = ctx->lib; + ggml_metal_encoder_t enc = ctx->enc; + + const int idx_end = ctx->idx_end; + + const bool use_fusion = ctx->use_fusion; + + const int debug_fusion = ctx->debug_fusion; + + 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, ne1, op->src[1], ne); + GGML_TENSOR_LOCALS(uint64_t, nb1, op->src[1], nb); + GGML_TENSOR_LOCALS( int32_t, ne, op, ne); + GGML_TENSOR_LOCALS(uint64_t, nb, op, nb); + + GGML_ASSERT(op->src[0]->type == GGML_TYPE_F32); + GGML_ASSERT(op->src[1]->type == GGML_TYPE_F32); + + GGML_ASSERT(ggml_is_contiguous_rows(op->src[0])); + GGML_ASSERT(ggml_is_contiguous_rows(op->src[1])); + + bool bcast_row = false; + + ggml_metal_buffer_id bid_src0 = ggml_metal_get_buffer_id(op->src[0]); + ggml_metal_buffer_id bid_src1 = ggml_metal_get_buffer_id(op->src[1]); + ggml_metal_buffer_id bid_dst = ggml_metal_get_buffer_id(op); + + ggml_metal_kargs_bin args = { + /*.ne00 =*/ ne00, + /*.ne01 =*/ ne01, + /*.ne02 =*/ ne02, + /*.ne03 =*/ ne03, + /*.nb00 =*/ nb00, + /*.nb01 =*/ nb01, + /*.nb02 =*/ nb02, + /*.nb03 =*/ nb03, + /*.ne10 =*/ ne10, + /*.ne11 =*/ ne11, + /*.ne12 =*/ ne12, + /*.ne13 =*/ ne13, + /*.nb10 =*/ nb10, + /*.nb11 =*/ nb11, + /*.nb12 =*/ nb12, + /*.nb13 =*/ nb13, + /*.ne0 =*/ ne0, + /*.ne1 =*/ ne1, + /*.ne2 =*/ ne2, + /*.ne3 =*/ ne3, + /*.nb0 =*/ nb0, + /*.nb1 =*/ nb1, + /*.nb2 =*/ nb2, + /*.nb3 =*/ nb3, + /*.offs =*/ 0, + /*.o1 =*/ { bid_src1.offs }, + }; + + ggml_op fops[8]; + + int n_fuse = 1; + + // c[0] = add(a, b[0]) + // c[1] = add(c[0], b[1]) + // c[2] = add(c[1], b[2]) + // ... + if (use_fusion) { + fops[0] = GGML_OP_ADD; + fops[1] = GGML_OP_ADD; + fops[2] = GGML_OP_ADD; + fops[3] = GGML_OP_ADD; + fops[4] = GGML_OP_ADD; + fops[5] = GGML_OP_ADD; + fops[6] = GGML_OP_ADD; + fops[7] = GGML_OP_ADD; + + // note: in metal, we sometimes encode the graph in parallel so we have to avoid fusing ops + // across splits. idx_end indicates the last node in the current split + for (n_fuse = 0; n_fuse <= 6 && idx + n_fuse + 1 < idx_end; ++n_fuse) { + if (!ggml_can_fuse(gf, idx + n_fuse, fops + n_fuse, 2)) { + break; + } + + if (ops[n_fuse] != ops[n_fuse + 1]->src[0]) { + break; + } + + // b[0] === b[1] === ... + if (!ggml_are_same_layout(ops[n_fuse]->src[1], ops[n_fuse + 1]->src[1])) { + break; + } + + // only fuse ops if src1 is in the same Metal buffer + ggml_metal_buffer_id bid_fuse = ggml_metal_get_buffer_id(ops[n_fuse + 1]->src[1]); + if (bid_fuse.metal != bid_src1.metal) { + break; + } + + //ctx->fuse_cnt[ops[n_fuse + 1]->op]++; + + args.o1[n_fuse + 1] = bid_fuse.offs; + } + + ++n_fuse; + + if (debug_fusion > 1 && n_fuse > 1) { + GGML_LOG_DEBUG("%s: fuse: ADD x %d\n", __func__, n_fuse); + } + } + + // 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; + + 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])); + + // src1 is a row + GGML_ASSERT(ne11 == 1); + + pipeline = ggml_metal_library_get_pipeline_bin(lib, op->op, n_fuse, true); + + bcast_row = true; + } else { + pipeline = ggml_metal_library_get_pipeline_bin(lib, op->op, n_fuse, false); + } + + if (n_fuse > 1) { + bid_dst = ggml_metal_get_buffer_id(ops[n_fuse - 1]); + + for (int i = 1; i < n_fuse; ++i) { + if (!ggml_metal_op_concurrency_check(ctx, ops[i])) { + ggml_metal_op_concurrency_reset(ctx); + + break; + } + } + } + + ggml_metal_encoder_set_pipeline(enc, pipeline); + ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); + ggml_metal_encoder_set_buffer (enc, bid_src0, 1); + ggml_metal_encoder_set_buffer (enc, bid_src1, 2); + ggml_metal_encoder_set_buffer (enc, bid_dst, 3); + + if (bcast_row) { + const int64_t n = ggml_nelements(op)/4; + + ggml_metal_encoder_dispatch_threadgroups(enc, n, 1, 1, 1, 1, 1); + } else { + int nth = 32; + + while (16*nth < ne0 && nth < ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)) { + nth *= 2; + } + + ggml_metal_encoder_dispatch_threadgroups(enc, ne01, ne02, ne03, nth, 1, 1); + } + + return n_fuse; +} + +int ggml_metal_op_rms_norm(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, idx); + + ggml_metal_library_t lib = ctx->lib; + ggml_metal_encoder_t enc = ctx->enc; + + const int idx_end = ctx->idx_end; + + const bool use_fusion = ctx->use_fusion; + + const int debug_fusion = ctx->debug_fusion; + + ggml_tensor ** ops = ggml_graph_nodes(gf) + idx; + + 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(uint32_t, nb, op, nb); + + float eps; + memcpy(&eps, op->op_params, sizeof(float)); + + ggml_metal_buffer_id bid_src0 = ggml_metal_get_buffer_id(op->src[0]); + ggml_metal_buffer_id bid_dst = ggml_metal_get_buffer_id(op); + + ggml_metal_kargs_rms_norm args = { + /*.ne00 =*/ ne00, + /*.ne00_4 =*/ ne00/4, + /*.nb1 =*/ nb1, + /*.nb2 =*/ nb2, + /*.nb3 =*/ nb3, + /*.eps =*/ eps, + /*.nef1 =*/ { ne01 }, + /*.nef2 =*/ { ne02 }, + /*.nef3 =*/ { ne03 }, + /*.nbf1 =*/ { nb01 }, + /*.nbf2 =*/ { nb02 }, + /*.nbf3 =*/ { nb03 }, + }; + + ggml_op fops[8]; + + int n_fuse = 1; + + ggml_metal_buffer_id bid_fuse[2] = { bid_src0, bid_src0 }; + + // d[0] = rms_norm(a) + // d[1] = mul(d[0], b) + // d[2] = add(d[1], c) + if (use_fusion) { + fops[0] = GGML_OP_RMS_NORM; + fops[1] = GGML_OP_MUL; + fops[2] = GGML_OP_ADD; + + for (n_fuse = 0; n_fuse <= 1 && idx + n_fuse + 1 < idx_end; ++n_fuse) { + if (!ggml_can_fuse(gf, idx + n_fuse, fops + n_fuse, 2)) { + break; + } + + if (ops[n_fuse] != ops[n_fuse + 1]->src[0]) { + break; + } + + if (ops[n_fuse + 1]->src[1]->ne[0] != op->ne[0]) { + break; + } + + if (!ggml_is_contiguous_rows(ops[n_fuse + 1]->src[1])) { + break; + } + + if (ops[n_fuse + 1]->type != GGML_TYPE_F32) { + break; + } + + //ctx->fuse_cnt[ops[n_fuse + 1]->op]++; + + bid_fuse[n_fuse] = ggml_metal_get_buffer_id(ops[n_fuse + 1]->src[1]); + + args.nef1[n_fuse + 1] = ops[n_fuse + 1]->src[1]->ne[1]; + args.nef2[n_fuse + 1] = ops[n_fuse + 1]->src[1]->ne[2]; + args.nef3[n_fuse + 1] = ops[n_fuse + 1]->src[1]->ne[3]; + + args.nbf1[n_fuse + 1] = ops[n_fuse + 1]->src[1]->nb[1]; + args.nbf2[n_fuse + 1] = ops[n_fuse + 1]->src[1]->nb[2]; + args.nbf3[n_fuse + 1] = ops[n_fuse + 1]->src[1]->nb[3]; + } + + ++n_fuse; + + if (debug_fusion > 1 && n_fuse > 1) { + if (n_fuse == 2) { + GGML_LOG_DEBUG("%s: fuse: RMS_NORM + MUL\n", __func__); + } + if (n_fuse == 3) { + GGML_LOG_DEBUG("%s: fuse: RMS_NORM + MUL + ADD\n", __func__); + } + } + } + + if (n_fuse > 1) { + bid_dst = ggml_metal_get_buffer_id(ops[n_fuse - 1]); + + for (int i = 1; i < n_fuse; ++i) { + if (!ggml_metal_op_concurrency_check(ctx, ops[i])) { + ggml_metal_op_concurrency_reset(ctx); + + break; + } + } + } + + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_rms_norm(lib, op, n_fuse); + + int nth = 32; // SIMD width + + while (nth < ne00/4 && 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, ne00/4); + + const size_t smem = ggml_metal_pipeline_get_smem(pipeline); + + ggml_metal_encoder_set_pipeline(enc, pipeline); + ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0); + ggml_metal_encoder_set_buffer (enc, bid_src0, 1); + ggml_metal_encoder_set_buffer (enc, bid_fuse[0], 2); + ggml_metal_encoder_set_buffer (enc, bid_fuse[1], 3); + ggml_metal_encoder_set_buffer (enc, bid_dst, 4); + + ggml_metal_encoder_set_threadgroup_memory_size(enc, smem, 0); + + ggml_metal_encoder_dispatch_threadgroups(enc, ne01, ne02, ne03, nth, 1, 1); + + return n_fuse; +} + +int ggml_metal_op_l2_norm(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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(uint32_t, nb, op, nb); + + float eps; + memcpy(&eps, op->op_params, sizeof(float)); + + int nth = 32; // SIMD width + + ggml_metal_kargs_l2_norm args = { + /*.ne00 =*/ ne00, + /*.ne00_4 =*/ ne00/4, + /*.nb01 =*/ nb01, + /*.eps =*/ eps, + }; + + ggml_metal_pipeline_t 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; + } + + 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 int64_t nrows = ggml_nrows(op->src[0]); + + 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_set_threadgroup_memory_size(enc, smem, 0); + + ggml_metal_encoder_dispatch_threadgroups(enc, nrows, 1, 1, nth, 1, 1); + + return 1; +} + +int ggml_metal_op_group_norm(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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(uint32_t, nb, op, nb); + + const int32_t ngrp = ((const int32_t *) op->op_params)[0]; + + float eps; + memcpy(&eps, op->op_params + 1, sizeof(float)); + + ggml_metal_kargs_group_norm args = { + /*.ne00 =*/ ne00, + /*.ne01 =*/ ne01, + /*.ne02 =*/ ne02, + /*.nb00 =*/ nb00, + /*.nb01 =*/ nb01, + /*.nb02 =*/ nb02, + /*.ngrp =*/ ngrp, + /*.eps =*/ eps, + }; + + ggml_metal_pipeline_t 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)) { + // nth *= 2; + //} + + //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); + + 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_set_threadgroup_memory_size(enc, smem, 0); + + ggml_metal_encoder_dispatch_threadgroups(enc, ngrp, 1, 1, nth, 1, 1); + + return 1; +} + +int ggml_metal_op_norm(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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(uint32_t, nb, op, nb); + + float eps; + memcpy(&eps, op->op_params, sizeof(float)); + + ggml_metal_kargs_norm args = { + /*.ne00 =*/ ne00, + /*.ne00_4 =*/ ne00/4, + /*.nb01 =*/ nb01, + /*.eps =*/ eps, + }; + + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_norm(lib, op); + + int nth = 32; // SIMD width + while (nth < ne00/4 && 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, ne00/4); + + const size_t smem = ggml_metal_pipeline_get_smem(pipeline); + + const int64_t nrows = ggml_nrows(op->src[0]); + + 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_set_threadgroup_memory_size(enc, smem, 0); + + ggml_metal_encoder_dispatch_threadgroups(enc, nrows, 1, 1, nth, 1, 1); + + return 1; +} + +int ggml_metal_op_rope(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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, ne1, op->src[1], ne); + GGML_TENSOR_LOCALS(uint64_t, nb1, op->src[1], nb); + GGML_TENSOR_LOCALS( int32_t, ne, op, ne); + GGML_TENSOR_LOCALS(uint32_t, nb, op, nb); + + // make sure we have one or more position id(ne10) per token(ne02) + GGML_ASSERT(ne10 % ne02 == 0); + GGML_ASSERT(ne10 >= ne02); + + const int nth = std::min(1024, ne00); + + const int n_past = ((const int32_t *) op->op_params)[0]; + const int n_dims = ((const int32_t *) op->op_params)[1]; + //const int mode = ((const int32_t *) op->op_params)[2]; + // skip 3, n_ctx, used in GLM RoPE, unimplemented in metal + const int n_ctx_orig = ((const int32_t *) op->op_params)[4]; + + float freq_base; + float freq_scale; + float ext_factor; + float attn_factor; + float beta_fast; + float beta_slow; + + memcpy(&freq_base, (const int32_t *) op->op_params + 5, sizeof(float)); + memcpy(&freq_scale, (const int32_t *) op->op_params + 6, sizeof(float)); + memcpy(&ext_factor, (const int32_t *) op->op_params + 7, sizeof(float)); + memcpy(&attn_factor, (const int32_t *) op->op_params + 8, sizeof(float)); + memcpy(&beta_fast, (const int32_t *) op->op_params + 9, sizeof(float)); + memcpy(&beta_slow, (const int32_t *) op->op_params + 10, sizeof(float)); + + // mrope + const int sect_0 = ((const int32_t *) op->op_params)[11]; + const int sect_1 = ((const int32_t *) op->op_params)[12]; + const int sect_2 = ((const int32_t *) op->op_params)[13]; + const int sect_3 = ((const int32_t *) op->op_params)[14]; + + ggml_metal_kargs_rope 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, + /*.n_past =*/ n_past, + /*.n_dims =*/ n_dims, + /*.n_ctx_orig =*/ n_ctx_orig, + /*.freq_base =*/ freq_base, + /*.freq_scale =*/ freq_scale, + /*.ext_factor =*/ ext_factor, + /*.attn_factor =*/ attn_factor, + /*.beta_fast =*/ beta_fast, + /*.beta_slow =*/ beta_slow, + /* sect_0 =*/ sect_0, + /* sect_1 =*/ sect_1, + /* sect_2 =*/ sect_2, + /* sect_3 =*/ sect_3, + }; + + ggml_metal_pipeline_t 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); + 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->src[1]), 2); + if (op->src[2]) { + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[2]), 3); + } else { + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[0]), 3); + } + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), 4); + + ggml_metal_encoder_dispatch_threadgroups(enc, ne01, ne02, ne03, nth, 1, 1); + + return 1; +} + +int ggml_metal_op_im2col(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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(uint32_t, nb, op, nb); + + const int32_t s0 = ((const int32_t *)(op->op_params))[0]; + const int32_t s1 = ((const int32_t *)(op->op_params))[1]; + const int32_t p0 = ((const int32_t *)(op->op_params))[2]; + const int32_t p1 = ((const int32_t *)(op->op_params))[3]; + const int32_t d0 = ((const int32_t *)(op->op_params))[4]; + const int32_t d1 = ((const int32_t *)(op->op_params))[5]; + + const bool is_2D = ((const int32_t *)(op->op_params))[6] == 1; + + const int32_t N = op->src[1]->ne[is_2D ? 3 : 2]; + const int32_t IC = op->src[1]->ne[is_2D ? 2 : 1]; + const int32_t IH = is_2D ? op->src[1]->ne[1] : 1; + const int32_t IW = op->src[1]->ne[0]; + + const int32_t KH = is_2D ? op->src[0]->ne[1] : 1; + const int32_t KW = op->src[0]->ne[0]; + + const int32_t OH = is_2D ? op->ne[2] : 1; + const int32_t OW = op->ne[1]; + + const int32_t CHW = IC * KH * KW; + + const uint64_t ofs0 = op->src[1]->nb[is_2D ? 3 : 2] / 4; + const uint64_t ofs1 = op->src[1]->nb[is_2D ? 2 : 1] / 4; + + + ggml_metal_kargs_im2col args = { + /*.ofs0 =*/ ofs0, + /*.ofs1 =*/ ofs1, + /*.IW =*/ IW, + /*.IH =*/ IH, + /*.CHW =*/ CHW, + /*.s0 =*/ s0, + /*.s1 =*/ s1, + /*.p0 =*/ p0, + /*.p1 =*/ p1, + /*.d0 =*/ d0, + /*.d1 =*/ d1, + /*.N =*/ N, + /*.KH =*/ KH, + /*.KW =*/ KW, + /*.KHW =*/ KH * KW, + }; + + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_im2col(lib, op); + + const uint64_t n_threads = std::min(ggml_metal_pipeline_max_theads_per_threadgroup(pipeline), N); + const int64_t quotient = N / n_threads + (N % n_threads > 0 ? 1 : 0); + + 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[1]), 1); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), 2); + + ggml_metal_encoder_dispatch_threadgroups(enc, quotient * CHW, OH, OW, n_threads, 1, 1); + + return 1; +} + +int ggml_metal_op_conv_transpose_1d(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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, ne1, op->src[1], ne); + GGML_TENSOR_LOCALS(uint64_t, nb1, op->src[1], nb); + GGML_TENSOR_LOCALS( int32_t, ne, op, ne); + GGML_TENSOR_LOCALS(uint32_t, nb, op, nb); + + const int32_t s0 = ((const int32_t *)(op->op_params))[0]; + + const int32_t IC = op->src[1]->ne[1]; + const int32_t IL = op->src[1]->ne[0]; + + const int32_t K = op->src[0]->ne[0]; + + const int32_t OL = op->ne[0]; + const int32_t OC = op->ne[1]; + + ggml_metal_kargs_conv_transpose_1d args = { + /*.IC =*/ IC, + /*.IL =*/ IL, + /*.K =*/ K, + /*.s0 =*/ s0, + /*.nb0 =*/ nb0, + /*.nb1 =*/ nb1, + }; + + ggml_metal_pipeline_t 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); + 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->src[1]), 2); + ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), 3); + + ggml_metal_encoder_dispatch_threadgroups(enc, OL, OC, 1, 1, 1, 1); + + return 1; +} + +int ggml_metal_op_upscale(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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(uint32_t, nb, op, nb); + + const float sf0 = (float)ne0/op->src[0]->ne[0]; + const float sf1 = (float)ne1/op->src[0]->ne[1]; + const float sf2 = (float)ne2/op->src[0]->ne[2]; + const float sf3 = (float)ne3/op->src[0]->ne[3]; + + ggml_metal_kargs_upscale 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, + /*.sf0 =*/ sf0, + /*.sf1 =*/ sf1, + /*.sf2 =*/ sf2, + /*.sf3 =*/ sf3 + }; + + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_upscale(lib, op); + + const int nth = std::min(ggml_metal_pipeline_max_theads_per_threadgroup(pipeline), ne0); + + 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, ne1, ne2, ne3, nth, 1, 1); + + return 1; +} + +int ggml_metal_op_pad(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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(uint32_t, nb, op, nb); + + ggml_metal_kargs_pad 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 + }; + + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_pad(lib, op); + + const int nth = std::min(1024, ne0); + + 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, ne1, ne2, ne3, nth, 1, 1); + + return 1; +} + +int ggml_metal_op_pad_reflect_1d(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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(uint32_t, nb, op, nb); + + ggml_metal_kargs_pad_reflect_1d 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, + /*.p0 =*/ ((const int32_t *)(op->op_params))[0], + /*.p1 =*/ ((const int32_t *)(op->op_params))[1] + }; + + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_pad_reflect_1d(lib, op); + + const int nth = std::min(1024, ne0); + + 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, ne1, ne2, ne3, nth, 1, 1); + + return 1; +} + +int ggml_metal_op_arange(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, idx); + + ggml_metal_library_t lib = ctx->lib; + ggml_metal_encoder_t enc = ctx->enc; + + GGML_TENSOR_LOCALS( int32_t, ne, op, ne); + GGML_TENSOR_LOCALS(uint32_t, nb, op, nb); + + float start; + float step; + + memcpy(&start, ((const int32_t *) op->op_params) + 0, sizeof(float)); + memcpy(&step, ((const int32_t *) op->op_params) + 2, sizeof(float)); + + ggml_metal_kargs_arange args = { + /*.ne0 =*/ ne0, + /*.start =*/ start, + /*.step =*/ step + }; + + const int nth = std::min(1024, ne0); + + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_arange(lib, op); + + //[encoder setComputePipelineState:pipeline]; + //[encoder setBuffer:id_dst offset:offs_dst atIndex:0]; + //[encoder setBytes:&args length:sizeof(args) atIndex:1]; + + //[encoder dispatchThreadgroups:MTLSizeMake(1, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; + + 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), 1); + + ggml_metal_encoder_dispatch_threadgroups(enc, 1, 1, 1, nth, 1, 1); + + return 1; +} + +int ggml_metal_op_timestep_embedding(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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(uint32_t, nb, op, nb); + + const int dim = op->op_params[0]; + const int max_period = op->op_params[1]; + + ggml_metal_kargs_timestep_embedding args = { + /*.nb1 =*/ nb1, + /*.dim =*/ dim, + /*.max_period =*/ max_period, + }; + + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_timestep_embedding(lib, op); + + const int nth = std::max(1, std::min(1024, dim/2)); + + 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, ne00, 1, 1, nth, 1, 1); + + return 1; +} + +int ggml_metal_op_argmax(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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(uint32_t, nb, op, nb); + + ggml_metal_kargs_argmax args = { + /*.ne00 = */ ne00, + /*.nb01 = */ nb01, + }; + + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_argmax(lib, op); + + const int64_t nrows = ggml_nrows(op->src[0]); + + int nth = 32; // SIMD width + while (nth < ne00 && nth*ne01*ne02*ne03 < 256) { + nth *= 2; + } + + const size_t smem = ggml_metal_pipeline_get_smem(pipeline); + + 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_set_threadgroup_memory_size(enc, smem, 0); + + ggml_metal_encoder_dispatch_threadgroups(enc, nrows, 1, 1, nth, 1, 1); + + return 1; +} + +int ggml_metal_op_argsort(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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(uint32_t, nb, op, nb); + + // bitonic sort requires the number of elements to be power of 2 + int64_t ne00_padded = 1; + while (ne00_padded < ne00) { + ne00_padded *= 2; + } + + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_argsort(lib, op); + + const int64_t nrows = ggml_nrows(op->src[0]); + + // Metal kernels require the buffer size to be multiple of 16 bytes + // https://developer.apple.com/documentation/metal/mtlcomputecommandencoder/1443142-setthreadgroupmemorylength + const size_t smem = GGML_PAD(ne00_padded*sizeof(int32_t), 16); + + ggml_metal_kargs_argsort args = { + /*.ncols =*/ ne00, + /*.ncols_pad =*/ ne00_padded + }; + + 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_set_threadgroup_memory_size(enc, smem, 0); + + ggml_metal_encoder_dispatch_threadgroups(enc, 1, nrows, 1, ne00_padded, 1, 1); + + return 1; +} + +int ggml_metal_op_leaky_relu(ggml_metal_op_t ctx, int idx) { + ggml_cgraph * gf = ctx->gf; + ggml_tensor * op = ggml_graph_node(gf, 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(uint32_t, nb, op, nb); + + float slope; + memcpy(&slope, op->op_params, sizeof(float)); + + ggml_metal_kargs_leaky_relu args = { + /*.slope =*/ slope + }; + + ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_unary(lib, op); + + int64_t n = ggml_nelements(op); + + if (n % 4 == 0) { + n /= 4; + } + + 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; +} diff --git a/ggml/src/ggml-metal/ggml-metal-ops.h b/ggml/src/ggml-metal/ggml-metal-ops.h new file mode 100644 index 0000000000..b620de164d --- /dev/null +++ b/ggml/src/ggml-metal/ggml-metal-ops.h @@ -0,0 +1,81 @@ +#pragma once + +#include "ggml-metal-device.h" + +#ifdef __cplusplus +extern "C" { +#endif + +typedef struct ggml_metal_op * ggml_metal_op_t; + +ggml_metal_op_t ggml_metal_op_init( + ggml_metal_device_t dev, + ggml_metal_cmd_buf_t cmd_buf, + struct ggml_cgraph * gf, + int idx_start, + int idx_end, + bool use_fusion, + bool use_concurrency, + bool use_capture, + int debug_graph, + int debug_fusion); + +void ggml_metal_op_free(ggml_metal_op_t ctx); + +int ggml_metal_op_encode(ggml_metal_op_t ctx, int idx); + +// +// available ops: +// + +// tokens per expert +size_t ggml_metal_op_mul_mat_id_extra_tpe(const struct ggml_tensor * op); + +// id map [n_tokens, n_expert] +size_t ggml_metal_op_mul_mat_id_extra_ids(const struct ggml_tensor * op); + +// return true if we should use the FA vector kernel for this op +bool ggml_metal_op_flash_attn_ext_use_vec(const struct ggml_tensor * op); + +size_t ggml_metal_op_flash_attn_ext_extra_tmp(const struct ggml_tensor * op); + +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_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); +int ggml_metal_op_sum_rows (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_get_rows (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_set_rows (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_soft_max (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_ssm_conv (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_ssm_scan (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_rwkv (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_cpy (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_pool_2d (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_mul_mat (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_mul_mat_id (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_add_id (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_flash_attn_ext (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_bin (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_rms_norm (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_l2_norm (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_group_norm (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_norm (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_rope (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_im2col (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_conv_transpose_1d (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_upscale (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_pad (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_pad_reflect_1d (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_arange (ggml_metal_op_t ctx, int idx); +int ggml_metal_op_timestep_embedding(ggml_metal_op_t ctx, int idx); +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_leaky_relu (ggml_metal_op_t ctx, int idx); + +#ifdef __cplusplus +} +#endif diff --git a/ggml/src/ggml-metal/ggml-metal.cpp b/ggml/src/ggml-metal/ggml-metal.cpp new file mode 100644 index 0000000000..fd0e6ed6e4 --- /dev/null +++ b/ggml/src/ggml-metal/ggml-metal.cpp @@ -0,0 +1,718 @@ +#include "ggml-metal.h" + +#include "ggml-impl.h" +#include "ggml-backend-impl.h" + +#include "ggml-metal-device.h" +#include "ggml-metal-context.h" +#include "ggml-metal-ops.h" + +// globals + +// initialized in ggml_backend_metal_reg +static ggml_backend_reg g_ggml_metal_reg; +static ggml_backend_device g_ggml_metal_device; + +//////////////////////////////////////////////////////////////////////////////// +// backend interface +//////////////////////////////////////////////////////////////////////////////// + +// shared buffer + +static void ggml_backend_metal_buffer_shared_free_buffer(ggml_backend_buffer_t buffer) { + ggml_metal_buffer_t ctx = (ggml_metal_buffer_t)buffer->context; + + GGML_ASSERT(ggml_metal_buffer_is_shared(ctx)); + + ggml_metal_buffer_free(ctx); +} + +static void * ggml_backend_metal_buffer_shared_get_base(ggml_backend_buffer_t buffer) { + ggml_metal_buffer_t ctx = (ggml_metal_buffer_t)buffer->context; + + GGML_ASSERT(ggml_metal_buffer_is_shared(ctx)); + + return ggml_metal_buffer_get_base(ctx); +} + +static void ggml_backend_metal_buffer_shared_memset_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, uint8_t value, size_t offset, size_t size) { + ggml_metal_buffer_t ctx = (ggml_metal_buffer_t)buffer->context; + + GGML_ASSERT(ggml_metal_buffer_is_shared(ctx)); + + ggml_metal_buffer_memset_tensor(ctx, tensor, value, offset, size); +} + +static void ggml_backend_metal_buffer_shared_set_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, const void * data, size_t offset, size_t size) { + ggml_metal_buffer_t ctx = (ggml_metal_buffer_t)buffer->context; + + GGML_ASSERT(ggml_metal_buffer_is_shared(ctx)); + + ggml_metal_buffer_set_tensor(ctx, tensor, data, offset, size); +} + +static void ggml_backend_metal_buffer_shared_get_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * tensor, void * data, size_t offset, size_t size) { + ggml_metal_buffer_t ctx = (ggml_metal_buffer_t)buffer->context; + + GGML_ASSERT(ggml_metal_buffer_is_shared(ctx)); + + ggml_metal_buffer_get_tensor(ctx, tensor, data, offset, size); +} + +static bool ggml_backend_metal_buffer_shared_cpy_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * src, ggml_tensor * dst) { + ggml_metal_buffer_t ctx = (ggml_metal_buffer_t)buffer->context; + + GGML_ASSERT(ggml_metal_buffer_is_shared(ctx)); + + GGML_UNUSED(buffer); + GGML_UNUSED(src); + GGML_UNUSED(dst); + + return false; +} + +static void ggml_backend_metal_buffer_shared_clear(ggml_backend_buffer_t buffer, uint8_t value) { + ggml_metal_buffer_t ctx = (ggml_metal_buffer_t)buffer->context; + + GGML_ASSERT(ggml_metal_buffer_is_shared(ctx)); + + ggml_metal_buffer_clear(ctx, value); +} + +static ggml_backend_buffer_i ggml_backend_metal_buffer_shared_i = { + /* .free_buffer = */ ggml_backend_metal_buffer_shared_free_buffer, + /* .get_base = */ ggml_backend_metal_buffer_shared_get_base, + /* .init_tensor = */ NULL, + /* .memset_tensor = */ ggml_backend_metal_buffer_shared_memset_tensor, + /* .set_tensor = */ ggml_backend_metal_buffer_shared_set_tensor, + /* .get_tensor = */ ggml_backend_metal_buffer_shared_get_tensor, + /* .cpy_tensor = */ ggml_backend_metal_buffer_shared_cpy_tensor, + /* .clear = */ ggml_backend_metal_buffer_shared_clear, + /* .reset = */ NULL, +}; + +// private buffer + +static void ggml_backend_metal_buffer_private_free_buffer(ggml_backend_buffer_t buffer) { + ggml_metal_buffer_t ctx = (ggml_metal_buffer_t)buffer->context; + + GGML_ASSERT(!ggml_metal_buffer_is_shared(ctx)); + + ggml_metal_buffer_free(ctx); +} + +static void * ggml_backend_metal_buffer_private_get_base(ggml_backend_buffer_t buffer) { + ggml_metal_buffer_t ctx = (ggml_metal_buffer_t)buffer->context; + + GGML_ASSERT(!ggml_metal_buffer_is_shared(ctx)); + + return ggml_metal_buffer_get_base(ctx); +} + +static void ggml_backend_metal_buffer_private_memset_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, uint8_t value, size_t offset, size_t size) { + ggml_metal_buffer_t ctx = (ggml_metal_buffer_t)buffer->context; + + GGML_ASSERT(!ggml_metal_buffer_is_shared(ctx)); + + ggml_metal_buffer_memset_tensor(ctx, tensor, value, offset, size); +} + +static void ggml_backend_metal_buffer_private_set_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, const void * data, size_t offset, size_t size) { + ggml_metal_buffer_t ctx = (ggml_metal_buffer_t)buffer->context; + + GGML_ASSERT(!ggml_metal_buffer_is_shared(ctx)); + + ggml_metal_buffer_set_tensor(ctx, tensor, data, offset, size); +} + +static void ggml_backend_metal_buffer_private_get_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * tensor, void * data, size_t offset, size_t size) { + ggml_metal_buffer_t ctx = (ggml_metal_buffer_t)buffer->context; + + GGML_ASSERT(!ggml_metal_buffer_is_shared(ctx)); + + ggml_metal_buffer_get_tensor(ctx, tensor, data, offset, size); +} + +static bool ggml_backend_metal_buffer_private_cpy_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * src, ggml_tensor * dst) { + ggml_metal_buffer_t ctx = (ggml_metal_buffer_t)buffer->context; + + GGML_ASSERT(!ggml_metal_buffer_is_shared(ctx)); + + GGML_UNUSED(buffer); + GGML_UNUSED(src); + GGML_UNUSED(dst); + + return false; +} + +static void ggml_backend_metal_buffer_private_clear(ggml_backend_buffer_t buffer, uint8_t value) { + ggml_metal_buffer_t ctx = (ggml_metal_buffer_t)buffer->context; + + GGML_ASSERT(!ggml_metal_buffer_is_shared(ctx)); + + ggml_metal_buffer_clear(ctx, value); +} + +static ggml_backend_buffer_i ggml_backend_metal_buffer_private_i = { + /* .free_buffer = */ ggml_backend_metal_buffer_private_free_buffer, + /* .get_base = */ ggml_backend_metal_buffer_private_get_base, + /* .init_tensor = */ NULL, + /* .memset_tensor = */ ggml_backend_metal_buffer_private_memset_tensor, + /* .set_tensor = */ ggml_backend_metal_buffer_private_set_tensor, + /* .get_tensor = */ ggml_backend_metal_buffer_private_get_tensor, + /* .cpy_tensor = */ ggml_backend_metal_buffer_private_cpy_tensor, + /* .clear = */ ggml_backend_metal_buffer_private_clear, + /* .reset = */ NULL, +}; + +// +// buffer types +// + +// common method for allocating shread or private Metal buffers +static ggml_backend_buffer_t ggml_backend_metal_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size, bool shared) { + ggml_metal_device_t ctx_dev = (ggml_metal_device_t)buft->device->context; + ggml_metal_buffer_t res = ggml_metal_buffer_init(ctx_dev, size, shared); + + ggml_backend_buffer_i buf_i = ggml_metal_buffer_is_shared(res) + ? ggml_backend_metal_buffer_shared_i + : ggml_backend_metal_buffer_private_i; + + return ggml_backend_buffer_init(buft, buf_i, res, size); +} + +static size_t ggml_backend_metal_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) { + size_t res = ggml_nbytes(tensor); + + // some operations require additional memory for fleeting data: + switch (tensor->op) { + case GGML_OP_MUL_MAT_ID: + { + res += ggml_metal_op_mul_mat_id_extra_tpe(tensor); + res += ggml_metal_op_mul_mat_id_extra_ids(tensor); + } break; + case GGML_OP_FLASH_ATTN_EXT: + { + if (ggml_metal_op_flash_attn_ext_use_vec(tensor)) { + res += ggml_metal_op_flash_attn_ext_extra_tmp(tensor); + } + } break; + default: + break; + } + + return res; + + GGML_UNUSED(buft); +} + +// default (shared) buffer type + +static const char * ggml_backend_metal_buffer_type_shared_get_name(ggml_backend_buffer_type_t buft) { + return "Metal"; + + GGML_UNUSED(buft); +} + +static ggml_backend_buffer_t ggml_backend_metal_buffer_type_shared_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) { + return ggml_backend_metal_buffer_type_alloc_buffer(buft, size, true); +} + +static size_t ggml_backend_metal_buffer_type_shared_get_alignment(ggml_backend_buffer_type_t buft) { + return 32; + + GGML_UNUSED(buft); +} + +static size_t ggml_backend_metal_buffer_type_shared_get_max_size(ggml_backend_buffer_type_t buft) { + ggml_metal_device_t ctx_dev = (ggml_metal_device_t)buft->device->context; + + return ggml_metal_device_get_props(ctx_dev)->max_buffer_size; +} + +static size_t ggml_backend_metal_buffer_type_shared_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) { + return ggml_backend_metal_buffer_type_get_alloc_size(buft, tensor); +} + +static bool ggml_backend_metal_buffer_type_shared_is_host(ggml_backend_buffer_type_t buft) { + return false; + + GGML_UNUSED(buft); +} + +static ggml_backend_buffer_type_t ggml_backend_metal_buffer_type_shared(void) { + static ggml_backend_buffer_type ggml_backend_buffer_type_metal = { + /* .iface = */ { + /* .get_name = */ ggml_backend_metal_buffer_type_shared_get_name, + /* .alloc_buffer = */ ggml_backend_metal_buffer_type_shared_alloc_buffer, + /* .get_alignment = */ ggml_backend_metal_buffer_type_shared_get_alignment, + /* .get_max_size = */ ggml_backend_metal_buffer_type_shared_get_max_size, + /* .get_alloc_size = */ ggml_backend_metal_buffer_type_shared_get_alloc_size, + /* .is_host = */ ggml_backend_metal_buffer_type_shared_is_host, + }, + /* .device = */ &g_ggml_metal_device, + /* .context = */ NULL, + }; + + return &ggml_backend_buffer_type_metal; +} + +// default (private) buffer type + +static const char * ggml_backend_metal_buffer_type_private_get_name(ggml_backend_buffer_type_t buft) { + return "Metal_Private"; + + GGML_UNUSED(buft); +} + +static ggml_backend_buffer_t ggml_backend_metal_buffer_type_private_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) { + return ggml_backend_metal_buffer_type_alloc_buffer(buft, size, false); +} + +static size_t ggml_backend_metal_buffer_type_private_get_alignment(ggml_backend_buffer_type_t buft) { + return 32; + + GGML_UNUSED(buft); +} + +static size_t ggml_backend_metal_buffer_type_private_get_max_size(ggml_backend_buffer_type_t buft) { + ggml_metal_device_t ctx_dev = (ggml_metal_device_t)buft->device->context; + + return ggml_metal_device_get_props(ctx_dev)->max_buffer_size; +} + +static size_t ggml_backend_metal_buffer_type_private_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) { + return ggml_backend_metal_buffer_type_get_alloc_size(buft, tensor); +} + +static bool ggml_backend_metal_buffer_type_private_is_host(ggml_backend_buffer_type_t buft) { + return false; + + GGML_UNUSED(buft); +} + +static ggml_backend_buffer_type_t ggml_backend_metal_buffer_type_private(void) { + static ggml_backend_buffer_type ggml_backend_buffer_type_metal = { + /* .iface = */ { + /* .get_name = */ ggml_backend_metal_buffer_type_private_get_name, + /* .alloc_buffer = */ ggml_backend_metal_buffer_type_private_alloc_buffer, + /* .get_alignment = */ ggml_backend_metal_buffer_type_private_get_alignment, + /* .get_max_size = */ ggml_backend_metal_buffer_type_private_get_max_size, + /* .get_alloc_size = */ ggml_backend_metal_buffer_type_private_get_alloc_size, + /* .is_host = */ ggml_backend_metal_buffer_type_private_is_host, + }, + /* .device = */ &g_ggml_metal_device, + /* .context = */ NULL, + }; + + return &ggml_backend_buffer_type_metal; +} + +// mapped buffer type + +static const char * ggml_backend_metal_buffer_type_mapped_get_name(ggml_backend_buffer_type_t buft) { + return "Metal_Mapped"; + + GGML_UNUSED(buft); +} + +static ggml_backend_buffer_t ggml_backend_metal_buffer_type_mapped_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) { + // for mapped buffers, prefer shared memory + return ggml_backend_metal_buffer_type_alloc_buffer(buft, size, true); +} + +static size_t ggml_backend_metal_buffer_type_mapped_get_alignment(ggml_backend_buffer_type_t buft) { + return 32; + + GGML_UNUSED(buft); +} + +static size_t ggml_backend_metal_buffer_type_mapped_get_max_size(ggml_backend_buffer_type_t buft) { + ggml_metal_device_t ctx_dev = (ggml_metal_device_t)buft->device->context; + + return ggml_metal_device_get_props(ctx_dev)->max_buffer_size; +} + +static size_t ggml_backend_metal_buffer_type_mapped_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) { + return ggml_backend_metal_buffer_type_get_alloc_size(buft, tensor); +} + +static bool ggml_backend_metal_buffer_type_mapped_is_host(ggml_backend_buffer_type_t buft) { + return false; + + GGML_UNUSED(buft); +} + +static ggml_backend_buffer_type_t ggml_backend_metal_buffer_type_mapped(void) { + // note: not obvious, but this buffer type still needs to implement .alloc_buffer: + // https://github.com/ggml-org/llama.cpp/pull/15832#discussion_r2333177099 + static ggml_backend_buffer_type ggml_backend_buffer_type_mapped_metal = { + /* .iface = */ { + /* .get_name = */ ggml_backend_metal_buffer_type_mapped_get_name, + /* .alloc_buffer = */ ggml_backend_metal_buffer_type_mapped_alloc_buffer, + /* .get_alignment = */ ggml_backend_metal_buffer_type_mapped_get_alignment, + /* .get_max_size = */ ggml_backend_metal_buffer_type_mapped_get_max_size, + /* .get_alloc_size = */ ggml_backend_metal_buffer_type_mapped_get_alloc_size, + /* .is_host = */ ggml_backend_metal_buffer_type_mapped_is_host, + }, + /* .device = */ &g_ggml_metal_device, + /* .context = */ NULL, + }; + + return &ggml_backend_buffer_type_mapped_metal; +} + +// backend + +static const char * ggml_backend_metal_name(ggml_backend_t backend) { + return "Metal"; + + GGML_UNUSED(backend); +} + +static void ggml_backend_metal_free(ggml_backend_t backend) { + ggml_metal_t ctx = (ggml_metal_t)backend->context; + + // wait for any ongoing async operations to finish + ggml_metal_synchronize(ctx); + + ggml_metal_free(ctx); + + free(backend); +} + +static void ggml_backend_metal_synchronize(ggml_backend_t backend) { + ggml_metal_t ctx = (ggml_metal_t)backend->context; + + ggml_metal_synchronize(ctx); +} + +static void ggml_backend_metal_set_tensor_async(ggml_backend_t backend, ggml_tensor * tensor, const void * data, size_t offset, size_t size) { + ggml_metal_t ctx = (ggml_metal_t)backend->context; + + ggml_metal_set_tensor_async(ctx, tensor, data, offset, size); +} + +static void ggml_backend_metal_get_tensor_async(ggml_backend_t backend, const ggml_tensor * tensor, void * data, size_t offset, size_t size) { + ggml_metal_t ctx = (ggml_metal_t)backend->context; + + ggml_metal_get_tensor_async(ctx, tensor, data, offset, size); +} + +static bool ggml_backend_metal_cpy_tensor_async(ggml_backend_t backend_src, ggml_backend_t backend_dst, const ggml_tensor * src, ggml_tensor * dst) { + return false; + + GGML_UNUSED(backend_src); + GGML_UNUSED(backend_dst); + GGML_UNUSED(src); + GGML_UNUSED(dst); +} + +static enum ggml_status ggml_backend_metal_graph_compute(ggml_backend_t backend, ggml_cgraph * cgraph) { + ggml_metal_t ctx = (ggml_metal_t)backend->context; + + return ggml_metal_graph_compute(ctx, cgraph); +} + +static void ggml_backend_metal_graph_optimize(ggml_backend_t backend, ggml_cgraph * cgraph) { + ggml_metal_t ctx = (ggml_metal_t)backend->context; + + ggml_metal_graph_optimize(ctx, cgraph); +} + +static void ggml_backend_metal_set_n_cb(ggml_backend_t backend, int n_cb) { + GGML_ASSERT(ggml_backend_is_metal(backend)); + + ggml_metal_t ctx = (ggml_metal_t)backend->context; + + ggml_metal_set_n_cb(ctx, n_cb); + +} + +static ggml_backend_i ggml_backend_metal_i = { + /* .get_name = */ ggml_backend_metal_name, + /* .free = */ ggml_backend_metal_free, + /* .set_tensor_async = */ ggml_backend_metal_set_tensor_async, + /* .get_tensor_async = */ ggml_backend_metal_get_tensor_async, + /* .cpy_tensor_async = */ ggml_backend_metal_cpy_tensor_async, // only needed for multi-GPU setups + /* .synchronize = */ ggml_backend_metal_synchronize, + /* .graph_plan_create = */ NULL, + /* .graph_plan_free = */ NULL, + /* .graph_plan_update = */ NULL, + /* .graph_plan_compute = */ NULL, + /* .graph_compute = */ ggml_backend_metal_graph_compute, + + // the events API is needed only for multi-GPU setups, so likely no need to implement it for Metal + // in any case, these docs seem relevant if we ever decide to implement it: + // https://developer.apple.com/documentation/metal/mtlcommandbuffer#Synchronizing-Passes-with-Events + /* .event_record = */ NULL, + /* .event_wait = */ NULL, + /* .optimize_graph = */ ggml_backend_metal_graph_optimize, +}; + +static ggml_guid_t ggml_backend_metal_guid(void) { + static ggml_guid guid = { 0x81, 0xa1, 0x8b, 0x1e, 0x71, 0xec, 0x79, 0xed, 0x2b, 0x85, 0xdc, 0x8a, 0x61, 0x98, 0x30, 0xe6 }; + return &guid; +} + +ggml_backend_t ggml_backend_metal_init(void) { + ggml_backend_dev_t dev = ggml_backend_reg_dev_get(ggml_backend_metal_reg(), 0); + ggml_metal_device_t ctx_dev = (ggml_metal_device_t)dev->context; + + ggml_metal_t ctx = ggml_metal_init(ctx_dev); + if (ctx == NULL) { + GGML_LOG_ERROR("%s: error: failed to allocate context\n", __func__); + return NULL; + } + + ggml_backend_t backend = (ggml_backend_t) malloc(sizeof(ggml_backend)); + + *backend = { + /* .guid = */ ggml_backend_metal_guid(), + /* .interface = */ ggml_backend_metal_i, + /* .device = */ dev, + /* .context = */ ctx, + }; + + ggml_backend_metal_set_n_cb(backend, 1); + + return backend; +} + +bool ggml_backend_is_metal(ggml_backend_t backend) { + return backend != NULL && ggml_guid_matches(backend->guid, ggml_backend_metal_guid()); +} + +void ggml_backend_metal_set_abort_callback(ggml_backend_t backend, ggml_abort_callback abort_callback, void * user_data) { + GGML_ASSERT(ggml_backend_is_metal(backend)); + + ggml_metal_t ctx = (ggml_metal_t)backend->context; + + ggml_metal_set_abort_callback(ctx, abort_callback, user_data); +} + +bool ggml_backend_metal_supports_family(ggml_backend_t backend, int family) { + GGML_ASSERT(ggml_backend_is_metal(backend)); + + ggml_metal_t ctx = (ggml_metal_t)backend->context; + + return ggml_metal_supports_family(ctx, family); +} + +void ggml_backend_metal_capture_next_compute(ggml_backend_t backend) { + GGML_ASSERT(ggml_backend_is_metal(backend)); + + ggml_metal_t ctx = (ggml_metal_t)backend->context; + + ggml_metal_capture_next_compute(ctx); +} + +// backend device + +static const char * ggml_backend_metal_device_get_name(ggml_backend_dev_t dev) { + return "Metal"; + + GGML_UNUSED(dev); +} + +static const char * ggml_backend_metal_device_get_description(ggml_backend_dev_t dev) { + ggml_metal_device_t ctx_dev = (ggml_metal_device_t)dev->context; + + return ggml_metal_device_get_props(ctx_dev)->name; +} + +static void ggml_backend_metal_device_get_memory(ggml_backend_dev_t dev, size_t * free, size_t * total) { + ggml_metal_device_t ctx_dev = (ggml_metal_device_t)dev->context; + + ggml_metal_device_get_memory(ctx_dev, free, total); +} + +static enum ggml_backend_dev_type ggml_backend_metal_device_get_type(ggml_backend_dev_t dev) { + return GGML_BACKEND_DEVICE_TYPE_GPU; + + GGML_UNUSED(dev); +} + +static void ggml_backend_metal_device_get_props(ggml_backend_dev_t dev, ggml_backend_dev_props * props) { + props->name = ggml_backend_metal_device_get_name(dev); + props->description = ggml_backend_metal_device_get_description(dev); + props->type = ggml_backend_metal_device_get_type(dev); + + ggml_backend_metal_device_get_memory(dev, &props->memory_free, &props->memory_total); + + props->caps = { + /* .async = */ true, + /* .host_buffer = */ false, + /* .buffer_from_host_ptr = */ true, + /* .events = */ false, + }; +} + +static ggml_backend_t ggml_backend_metal_device_init(ggml_backend_dev_t dev, const char * params) { + ggml_metal_device_t ctx_dev = (ggml_metal_device_t)dev->context; + + ggml_metal_t ctx = ggml_metal_init(ctx_dev); + if (ctx == NULL) { + GGML_LOG_ERROR("%s: error: failed to allocate context\n", __func__); + return NULL; + } + + ggml_backend_t backend = (ggml_backend_t) malloc(sizeof(ggml_backend)); + + *backend = { + /* .guid = */ ggml_backend_metal_guid(), + /* .interface = */ ggml_backend_metal_i, + /* .device = */ dev, + /* .context = */ ctx, + }; + + ggml_backend_metal_set_n_cb(backend, 1); + + return backend; + + GGML_UNUSED(params); +} + +static ggml_backend_buffer_type_t ggml_backend_metal_device_get_buffer_type(ggml_backend_dev_t dev) { + ggml_metal_device_t ctx_dev = (ggml_metal_device_t)dev->context; + + const ggml_metal_device_props * props_dev = ggml_metal_device_get_props(ctx_dev); + + return props_dev->use_shared_buffers ? ggml_backend_metal_buffer_type_shared() : ggml_backend_metal_buffer_type_private(); +} + +static ggml_backend_buffer_t ggml_backend_metal_device_buffer_mapped(ggml_backend_dev_t dev, void * ptr, size_t size, size_t max_tensor_size) { + ggml_metal_device_t ctx_dev = (ggml_metal_device_t)dev->context; + + ggml_metal_buffer_t res = ggml_metal_buffer_map(ctx_dev, ptr, size, max_tensor_size); + + return ggml_backend_buffer_init(ggml_backend_metal_buffer_type_mapped(), ggml_backend_metal_buffer_shared_i, res, size); +} + +static bool ggml_backend_metal_device_supports_op(ggml_backend_dev_t dev, const ggml_tensor * op) { + ggml_metal_device_t ctx_dev = (ggml_metal_device_t)dev->context; + + return ggml_metal_device_supports_op(ctx_dev, op); +} + +static bool ggml_backend_metal_device_supports_buft(ggml_backend_dev_t dev, ggml_backend_buffer_type_t buft) { + return + buft->iface.get_name == ggml_backend_metal_buffer_type_shared_get_name || + buft->iface.get_name == ggml_backend_metal_buffer_type_private_get_name || + buft->iface.get_name == ggml_backend_metal_buffer_type_mapped_get_name; + + GGML_UNUSED(dev); +} + +static int64_t get_op_batch_size(const ggml_tensor * op) { + switch (op->op) { + case GGML_OP_MUL_MAT: + return op->ne[1]; + case GGML_OP_MUL_MAT_ID: + return op->ne[2]; + default: + return ggml_nrows(op); + } +} + +static bool ggml_backend_metal_device_offload_op(ggml_backend_dev_t dev, const ggml_tensor * op) { + const int min_batch_size = 32; + + return (op->op == GGML_OP_MUL_MAT || + op->op == GGML_OP_MUL_MAT_ID) && + get_op_batch_size(op) >= min_batch_size; + + GGML_UNUSED(dev); + GGML_UNUSED(op); +} + +static ggml_backend_device_i ggml_backend_metal_device_i = { + /* .get_name = */ ggml_backend_metal_device_get_name, + /* .get_description = */ ggml_backend_metal_device_get_description, + /* .get_memory = */ ggml_backend_metal_device_get_memory, + /* .get_type = */ ggml_backend_metal_device_get_type, + /* .get_props = */ ggml_backend_metal_device_get_props, + /* .init_backend = */ ggml_backend_metal_device_init, + /* .get_buffer_type = */ ggml_backend_metal_device_get_buffer_type, + /* .get_host_buffer_type = */ NULL, + /* .buffer_from_host_ptr = */ ggml_backend_metal_device_buffer_mapped, + /* .supports_op = */ ggml_backend_metal_device_supports_op, + /* .supports_buft = */ ggml_backend_metal_device_supports_buft, + /* .offload_op = */ ggml_backend_metal_device_offload_op, + /* .event_new = */ NULL, + /* .event_free = */ NULL, + /* .event_synchronize = */ NULL, +}; + +// backend registry + +static const char * ggml_backend_metal_reg_get_name(ggml_backend_reg_t reg) { + return "Metal"; + + GGML_UNUSED(reg); +} + +static size_t ggml_backend_metal_reg_device_count(ggml_backend_reg_t reg) { + return 1; + + GGML_UNUSED(reg); +} + +static ggml_backend_dev_t ggml_backend_metal_reg_device_get(ggml_backend_reg_t reg, size_t index) { + GGML_ASSERT(index == 0); + + return &g_ggml_metal_device; + + GGML_UNUSED(reg); + GGML_UNUSED(index); +} + +static ggml_backend_feature g_ggml_backend_metal_features[] = { +#if defined(GGML_METAL_EMBED_LIBRARY) + { "EMBED_LIBRARY", "1" }, +#endif + { NULL, NULL }, +}; + +static ggml_backend_feature * ggml_backend_metal_get_features(ggml_backend_reg_t reg) { + return g_ggml_backend_metal_features; + + GGML_UNUSED(reg); +} + +static void * ggml_backend_metal_get_proc_address(ggml_backend_reg_t reg, const char * name) { + if (strcmp(name, "ggml_backend_get_features") == 0) { + return (void *)ggml_backend_metal_get_features; + } + + return NULL; + + GGML_UNUSED(reg); +} + +static ggml_backend_reg_i ggml_backend_metal_reg_i = { + /* .get_name = */ ggml_backend_metal_reg_get_name, + /* .device_count = */ ggml_backend_metal_reg_device_count, + /* .device_get = */ ggml_backend_metal_reg_device_get, + /* .get_proc_address = */ ggml_backend_metal_get_proc_address, +}; + +ggml_backend_reg_t ggml_backend_metal_reg(void) { + { + g_ggml_metal_reg = { + /* .api_version = */ GGML_BACKEND_API_VERSION, + /* .iface = */ ggml_backend_metal_reg_i, + /* .context = */ NULL, + }; + + g_ggml_metal_device = { + /* .iface = */ ggml_backend_metal_device_i, + /* .reg = */ &g_ggml_metal_reg, + /* .context = */ ggml_metal_device_get(), + }; + } + + return &g_ggml_metal_reg; +} + +GGML_BACKEND_DL_IMPL(ggml_backend_metal_reg) diff --git a/ggml/src/ggml-metal/ggml-metal.m b/ggml/src/ggml-metal/ggml-metal.m deleted file mode 100644 index 2243c174fb..0000000000 --- a/ggml/src/ggml-metal/ggml-metal.m +++ /dev/null @@ -1,6897 +0,0 @@ -#import "ggml-metal.h" - -#import "ggml-impl.h" -#import "ggml-backend-impl.h" -#import "ggml-metal-impl.h" -#import "ggml-metal-common.h" - -#import - -#import - -#undef MIN -#undef MAX -#define MIN(a, b) ((a) < (b) ? (a) : (b)) -#define MAX(a, b) ((a) > (b) ? (a) : (b)) - -// max memory buffers that can be mapped to the device -#define GGML_METAL_MAX_BUFFERS 64 - -// max number of MTLCommandBuffer used to submit a graph for processing -#define GGML_METAL_MAX_COMMAND_BUFFERS 8 - -#ifndef TARGET_OS_VISION -#define TARGET_OS_VISION 0 -#endif - -// create residency sets only on macOS >= 15.0 -#if !TARGET_CPU_X86_64 && TARGET_OS_OSX && __MAC_OS_X_VERSION_MAX_ALLOWED >= 150000 || \ - TARGET_OS_IOS && __IPHONE_OS_VERSION_MAX_ALLOWED >= 180000 || \ - TARGET_OS_TV && __TV_OS_VERSION_MAX_ALLOWED >= 180000 || \ - TARGET_OS_VISION && __VISION_OS_VERSION_MAX_ALLOWED >= 200000 -#define GGML_METAL_HAS_RESIDENCY_SETS 1 -#endif - -// globals - -// overload of MTLGPUFamilyMetal3 (not available in some environments) -static const NSInteger MTLGPUFamilyMetal3_GGML = 5001; - -// initialized in ggml_backend_metal_reg -static struct ggml_backend_reg g_ggml_backend_metal_reg; -static struct ggml_backend_device g_ggml_backend_metal_device; - -// information about a Metal device -// note: assumes single GPU device - the default one -// TODO: support multiple GPU devices -static struct ggml_backend_metal_device_context { - id mtl_device; - int mtl_device_ref_count; - id mtl_library; - - // a single global queue shared by all Metal backends - // technically not needed for devices with unified memory, but enables discrete GPUs support - // ref: https://github.com/ggml-org/llama.cpp/pull/15906 - id mtl_queue; - - NSLock * mtl_lock; - - bool has_simdgroup_reduction; - bool has_simdgroup_mm; - bool has_residency_sets; - bool has_bfloat; - bool use_bfloat; - bool use_fusion; - bool use_concurrency; - bool use_shared_buffers; - bool use_graph_optimize; - - int debug_graph; - int debug_fusion; - - // how many times a given op was fused - uint64_t fuse_cnt[GGML_OP_COUNT]; - - size_t max_size; - - char name[128]; -} g_ggml_ctx_dev_main = { - /*.mtl_device =*/ nil, - /*.mtl_device_ref_count =*/ 0, - /*.mtl_library =*/ nil, - /*.mtl_queue =*/ nil, - /*.mtl_lock =*/ nil, - /*.has_simdgroup_reduction =*/ false, - /*.has_simdgroup_mm =*/ false, - /*.has_residency_sets =*/ false, - /*.has_bfloat =*/ false, - /*.use_bfloat =*/ false, - /*.use_fusion =*/ true, - /*.use_concurrency =*/ true, - /*.use_shared_buffers =*/ true, - /*.use_graph_optimize =*/ true, - /*.debug_graph =*/ 0, - /*.debug_fusion =*/ 0, - /*.fuse_cnt =*/ { 0 }, - /*.max_size =*/ 0, - /*.name =*/ "", -}; - -// acquire -static id ggml_backend_metal_device_acq(struct ggml_backend_metal_device_context * ctx) { - assert(ctx != NULL); - - if (ctx->mtl_lock == nil) { - ctx->mtl_lock = [[NSLock alloc] init]; - } - - if (ctx->mtl_device == nil) { - ctx->mtl_device = MTLCreateSystemDefaultDevice(); - - if (ctx->mtl_device) { - ctx->mtl_queue = [ctx->mtl_device newCommandQueue]; - if (ctx->mtl_queue == nil) { - GGML_LOG_ERROR("%s: error: failed to create command queue\n", __func__); - } - - ctx->has_simdgroup_reduction = [ctx->mtl_device supportsFamily:MTLGPUFamilyApple7]; - ctx->has_simdgroup_reduction |= [ctx->mtl_device supportsFamily:MTLGPUFamilyMetal3_GGML]; - - ctx->has_simdgroup_mm = [ctx->mtl_device supportsFamily:MTLGPUFamilyApple7]; - -#if defined(GGML_METAL_HAS_RESIDENCY_SETS) - ctx->has_residency_sets = getenv("GGML_METAL_NO_RESIDENCY") == nil; -#endif - - ctx->has_bfloat = [ctx->mtl_device supportsFamily:MTLGPUFamilyMetal3_GGML]; - ctx->has_bfloat |= [ctx->mtl_device supportsFamily:MTLGPUFamilyApple6]; - -#if defined(GGML_METAL_USE_BF16) - ctx->use_bfloat = ctx->has_bfloat; -#else - ctx->use_bfloat = false; -#endif - - ctx->use_fusion = getenv("GGML_METAL_FUSION_DISABLE") == nil; - ctx->use_concurrency = getenv("GGML_METAL_CONCURRENCY_DISABLE") == nil; - - { - const char * val = getenv("GGML_METAL_GRAPH_DEBUG"); - ctx->debug_graph = val ? atoi(val) : 0; - } - - { - const char * val = getenv("GGML_METAL_FUSION_DEBUG"); - ctx->debug_fusion = val ? atoi(val) : 0; - } - - ctx->use_shared_buffers = ctx->mtl_device.hasUnifiedMemory; - - if (getenv("GGML_METAL_SHARED_BUFFERS_DISABLE") != NULL) { - ctx->use_shared_buffers = false; - } - - ctx->use_graph_optimize = true; - - if (getenv("GGML_METAL_GRAPH_OPTIMIZE_DISABLE") != NULL) { - ctx->use_graph_optimize = false; - } - - memset(ctx->fuse_cnt, 0, sizeof(ctx->fuse_cnt)); - - ctx->max_size = ctx->mtl_device.maxBufferLength; - - strncpy(ctx->name, [[ctx->mtl_device name] UTF8String], sizeof(ctx->name) - 1); - } - } - - ctx->mtl_device_ref_count++; - - return ctx->mtl_device; -} - -// release -static void ggml_backend_metal_device_rel(struct ggml_backend_metal_device_context * ctx) { - assert(ctx != NULL); - assert(ctx->mtl_device_ref_count > 0); - - ctx->mtl_device_ref_count--; - - if (ctx->mtl_device_ref_count == 0) { - if (ctx->debug_fusion > 0) { - fprintf(stderr, "%s: fusion stats:\n", __func__); - for (int i = 0; i < GGML_OP_COUNT; i++) { - if (ctx->fuse_cnt[i] == 0) { - continue; - } - - // note: cannot use ggml_log here - fprintf(stderr, "%s: - %s: %" PRIu64 "\n", __func__, ggml_op_name((enum ggml_op) i), ctx->fuse_cnt[i]); - } - } - - if (ctx->mtl_lock) { - [ctx->mtl_lock release]; - ctx->mtl_lock = nil; - } - - if (ctx->mtl_library) { - [ctx->mtl_library release]; - ctx->mtl_library = nil; - } - - if (ctx->mtl_queue) { - [ctx->mtl_queue release]; - ctx->mtl_queue = nil; - } - - if (ctx->mtl_device) { - [ctx->mtl_device release]; - ctx->mtl_device = nil; - } - } -} - -// kernels - -struct ggml_metal_kernel { - id pipeline; -}; - -@interface ggml_metal_kernel_wrapper : NSObject - -@property (nonatomic, assign) struct ggml_metal_kernel kernel; - -@end - -@implementation ggml_metal_kernel_wrapper -- (void) dealloc { - [_kernel.pipeline release]; - [super dealloc]; -} -@end - -enum ggml_metal_kernel_type { - GGML_METAL_KERNEL_TYPE_ADD_ID, - GGML_METAL_KERNEL_TYPE_REPEAT_F32, - GGML_METAL_KERNEL_TYPE_REPEAT_F16, - GGML_METAL_KERNEL_TYPE_REPEAT_I32, - GGML_METAL_KERNEL_TYPE_REPEAT_I16, - GGML_METAL_KERNEL_TYPE_SCALE, - GGML_METAL_KERNEL_TYPE_SCALE_4, - GGML_METAL_KERNEL_TYPE_CLAMP, - GGML_METAL_KERNEL_TYPE_TANH, - GGML_METAL_KERNEL_TYPE_RELU, - GGML_METAL_KERNEL_TYPE_SIGMOID, - GGML_METAL_KERNEL_TYPE_GELU, - GGML_METAL_KERNEL_TYPE_GELU_4, - GGML_METAL_KERNEL_TYPE_GELU_ERF, - GGML_METAL_KERNEL_TYPE_GELU_ERF_4, - GGML_METAL_KERNEL_TYPE_GELU_QUICK, - GGML_METAL_KERNEL_TYPE_GELU_QUICK_4, - GGML_METAL_KERNEL_TYPE_SILU, - GGML_METAL_KERNEL_TYPE_SILU_4, - GGML_METAL_KERNEL_TYPE_ELU, - GGML_METAL_KERNEL_TYPE_ABS, - GGML_METAL_KERNEL_TYPE_SGN, - GGML_METAL_KERNEL_TYPE_STEP, - GGML_METAL_KERNEL_TYPE_HARDSWISH, - GGML_METAL_KERNEL_TYPE_HARDSIGMOID, - GGML_METAL_KERNEL_TYPE_EXP, - GGML_METAL_KERNEL_TYPE_SOFT_MAX_F16, - GGML_METAL_KERNEL_TYPE_SOFT_MAX_F16_4, - GGML_METAL_KERNEL_TYPE_SOFT_MAX_F32, - GGML_METAL_KERNEL_TYPE_SOFT_MAX_F32_4, - GGML_METAL_KERNEL_TYPE_DIAG_MASK_INF, - GGML_METAL_KERNEL_TYPE_DIAG_MASK_INF_8, - GGML_METAL_KERNEL_TYPE_GET_ROWS_F32, - GGML_METAL_KERNEL_TYPE_GET_ROWS_F16, - GGML_METAL_KERNEL_TYPE_GET_ROWS_BF16, - GGML_METAL_KERNEL_TYPE_GET_ROWS_Q4_0, - GGML_METAL_KERNEL_TYPE_GET_ROWS_Q4_1, - GGML_METAL_KERNEL_TYPE_GET_ROWS_Q5_0, - GGML_METAL_KERNEL_TYPE_GET_ROWS_Q5_1, - GGML_METAL_KERNEL_TYPE_GET_ROWS_Q8_0, - GGML_METAL_KERNEL_TYPE_GET_ROWS_MXFP4, - GGML_METAL_KERNEL_TYPE_GET_ROWS_Q2_K, - GGML_METAL_KERNEL_TYPE_GET_ROWS_Q3_K, - GGML_METAL_KERNEL_TYPE_GET_ROWS_Q4_K, - GGML_METAL_KERNEL_TYPE_GET_ROWS_Q5_K, - GGML_METAL_KERNEL_TYPE_GET_ROWS_Q6_K, - GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ2_XXS, - GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ2_XS, - GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ3_XXS, - GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ3_S, - GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ2_S, - GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ1_S, - GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ1_M, - GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ4_NL, - GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ4_XS, - GGML_METAL_KERNEL_TYPE_GET_ROWS_I32, - GGML_METAL_KERNEL_TYPE_SET_ROWS_F32, - GGML_METAL_KERNEL_TYPE_SET_ROWS_F16, - GGML_METAL_KERNEL_TYPE_SET_ROWS_BF16, - GGML_METAL_KERNEL_TYPE_SET_ROWS_Q8_0, - GGML_METAL_KERNEL_TYPE_SET_ROWS_Q4_0, - GGML_METAL_KERNEL_TYPE_SET_ROWS_Q4_1, - GGML_METAL_KERNEL_TYPE_SET_ROWS_Q5_0, - GGML_METAL_KERNEL_TYPE_SET_ROWS_Q5_1, - GGML_METAL_KERNEL_TYPE_SET_ROWS_IQ4_NL, - GGML_METAL_KERNEL_TYPE_L2_NORM, - GGML_METAL_KERNEL_TYPE_GROUP_NORM, - GGML_METAL_KERNEL_TYPE_NORM, - GGML_METAL_KERNEL_TYPE_SSM_CONV_F32, - GGML_METAL_KERNEL_TYPE_SSM_SCAN_F32, - GGML_METAL_KERNEL_TYPE_SSM_SCAN_F32_GROUP, - GGML_METAL_KERNEL_TYPE_RWKV_WKV6_F32, - GGML_METAL_KERNEL_TYPE_RWKV_WKV7_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_F32_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_F32_F32_C4, - GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32_C4, - GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32_1ROW, - GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32_L4, - GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F16, - GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_F32_C4, - GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_F32_1ROW, - GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_F32_L4, - GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_BF16, - GGML_METAL_KERNEL_TYPE_MUL_MV_Q4_0_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_Q4_1_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_0_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_1_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_Q8_0_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_MXFP4_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F32_F32_R1_2, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F32_F32_R1_3, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F32_F32_R1_4, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F32_F32_R1_5, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F16_F32_R1_2, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F16_F32_R1_3, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F16_F32_R1_4, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F16_F32_R1_5, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_0_F32_R1_2, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_0_F32_R1_3, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_0_F32_R1_4, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_0_F32_R1_5, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_1_F32_R1_2, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_1_F32_R1_3, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_1_F32_R1_4, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_1_F32_R1_5, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_0_F32_R1_2, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_0_F32_R1_3, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_0_F32_R1_4, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_0_F32_R1_5, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_1_F32_R1_2, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_1_F32_R1_3, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_1_F32_R1_4, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_1_F32_R1_5, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q8_0_F32_R1_2, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q8_0_F32_R1_3, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q8_0_F32_R1_4, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q8_0_F32_R1_5, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_MXFP4_F32_R1_2, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_MXFP4_F32_R1_3, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_MXFP4_F32_R1_4, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_MXFP4_F32_R1_5, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_K_F32_R1_2, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_K_F32_R1_3, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_K_F32_R1_4, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_K_F32_R1_5, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_K_F32_R1_2, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_K_F32_R1_3, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_K_F32_R1_4, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_K_F32_R1_5, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q6_K_F32_R1_2, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q6_K_F32_R1_3, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q6_K_F32_R1_4, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q6_K_F32_R1_5, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_IQ4_NL_F32_R1_2, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_IQ4_NL_F32_R1_3, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_IQ4_NL_F32_R1_4, - GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_IQ4_NL_F32_R1_5, - GGML_METAL_KERNEL_TYPE_MUL_MV_Q2_K_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_Q3_K_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_Q4_K_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_K_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_Q6_K_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_IQ2_XXS_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_IQ2_XS_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_IQ3_XXS_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_IQ3_S_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_IQ2_S_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_IQ1_S_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_IQ1_M_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_IQ4_NL_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_IQ4_XS_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_F32_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_F16_F32, - //GGML_METAL_KERNEL_TYPE_MUL_MV_ID_F16_F32_1ROW, - //GGML_METAL_KERNEL_TYPE_MUL_MV_ID_F16_F32_L4, - //GGML_METAL_KERNEL_TYPE_MUL_MV_ID_F16_F16, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_BF16_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q4_0_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q4_1_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q5_0_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q5_1_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q8_0_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_MXFP4_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q2_K_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q3_K_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q4_K_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q5_K_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q6_K_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ2_XXS_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ2_XS_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ3_XXS_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ3_S_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ2_S_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ1_S_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ1_M_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ4_NL_F32, - GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ4_XS_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_F32_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_F16_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_BF16_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_Q4_0_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_Q4_1_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_0_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_1_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_Q8_0_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_MXFP4_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_Q2_K_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_Q3_K_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_Q4_K_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_K_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_Q6_K_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_IQ2_XXS_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_IQ2_XS_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_IQ3_XXS_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_IQ3_S_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_IQ2_S_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_IQ1_S_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_IQ1_M_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_IQ4_NL_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_IQ4_XS_F32, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_1, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_2, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_4, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_6, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_8, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_10, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_F32_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_F16_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_BF16_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q4_0_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q4_1_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q5_0_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q5_1_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q8_0_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MXFP4_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q2_K_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q3_K_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q4_K_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q5_K_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q6_K_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ2_XXS_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ2_XS_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ3_XXS_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ3_S_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ2_S_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ1_S_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ1_M_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ4_NL_F16, - GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ4_XS_F16, - GGML_METAL_KERNEL_TYPE_ROPE_NORM_F32, - GGML_METAL_KERNEL_TYPE_ROPE_NORM_F16, - GGML_METAL_KERNEL_TYPE_ROPE_MULTI_F32, - GGML_METAL_KERNEL_TYPE_ROPE_MULTI_F16, - GGML_METAL_KERNEL_TYPE_ROPE_VISION_F32, - GGML_METAL_KERNEL_TYPE_ROPE_VISION_F16, - GGML_METAL_KERNEL_TYPE_ROPE_NEOX_F32, - GGML_METAL_KERNEL_TYPE_ROPE_NEOX_F16, - GGML_METAL_KERNEL_TYPE_IM2COL_F16, - GGML_METAL_KERNEL_TYPE_IM2COL_F32, - GGML_METAL_KERNEL_TYPE_IM2COL_EXT_F16, - GGML_METAL_KERNEL_TYPE_IM2COL_EXT_F32, - GGML_METAL_KERNEL_TYPE_CONV_TRANSPOSE_1D_F32_F32, - GGML_METAL_KERNEL_TYPE_CONV_TRANSPOSE_1D_F16_F32, - GGML_METAL_KERNEL_TYPE_UPSCALE_F32, - GGML_METAL_KERNEL_TYPE_PAD_F32, - GGML_METAL_KERNEL_TYPE_PAD_REFLECT_1D_F32, - GGML_METAL_KERNEL_TYPE_ARANGE_F32, - GGML_METAL_KERNEL_TYPE_TIMESTEP_EMBEDDING_F32, - GGML_METAL_KERNEL_TYPE_ARGSORT_F32_I32_ASC, - GGML_METAL_KERNEL_TYPE_ARGSORT_F32_I32_DESC, - GGML_METAL_KERNEL_TYPE_LEAKY_RELU_F32, - GGML_METAL_KERNEL_TYPE_CPY_F32_F32, - GGML_METAL_KERNEL_TYPE_CPY_F32_F16, - GGML_METAL_KERNEL_TYPE_CPY_F32_BF16, - GGML_METAL_KERNEL_TYPE_CPY_F16_F16, - GGML_METAL_KERNEL_TYPE_CPY_F16_F32, - GGML_METAL_KERNEL_TYPE_CPY_BF16_F32, - GGML_METAL_KERNEL_TYPE_CPY_BF16_BF16, - GGML_METAL_KERNEL_TYPE_CPY_F32_I32, - GGML_METAL_KERNEL_TYPE_CPY_I32_F32, - GGML_METAL_KERNEL_TYPE_CPY_F32_Q8_0, - GGML_METAL_KERNEL_TYPE_CPY_F32_Q4_0, - GGML_METAL_KERNEL_TYPE_CPY_F32_Q4_1, - GGML_METAL_KERNEL_TYPE_CPY_F32_Q5_0, - GGML_METAL_KERNEL_TYPE_CPY_F32_Q5_1, - GGML_METAL_KERNEL_TYPE_CPY_F32_IQ4_NL, - GGML_METAL_KERNEL_TYPE_CPY_Q4_0_F32, - GGML_METAL_KERNEL_TYPE_CPY_Q4_0_F16, - GGML_METAL_KERNEL_TYPE_CPY_Q4_1_F32, - GGML_METAL_KERNEL_TYPE_CPY_Q4_1_F16, - GGML_METAL_KERNEL_TYPE_CPY_Q5_0_F32, - GGML_METAL_KERNEL_TYPE_CPY_Q5_0_F16, - GGML_METAL_KERNEL_TYPE_CPY_Q5_1_F32, - GGML_METAL_KERNEL_TYPE_CPY_Q5_1_F16, - GGML_METAL_KERNEL_TYPE_CPY_Q8_0_F32, - GGML_METAL_KERNEL_TYPE_CPY_Q8_0_F16, - GGML_METAL_KERNEL_TYPE_CONCAT, - GGML_METAL_KERNEL_TYPE_SQR, - GGML_METAL_KERNEL_TYPE_SQRT, - GGML_METAL_KERNEL_TYPE_SIN, - GGML_METAL_KERNEL_TYPE_COS, - GGML_METAL_KERNEL_TYPE_NEG, - GGML_METAL_KERNEL_TYPE_REGLU, - GGML_METAL_KERNEL_TYPE_GEGLU, - GGML_METAL_KERNEL_TYPE_SWIGLU, - GGML_METAL_KERNEL_TYPE_SWIGLU_OAI, - GGML_METAL_KERNEL_TYPE_GEGLU_ERF, - GGML_METAL_KERNEL_TYPE_GEGLU_QUICK, - GGML_METAL_KERNEL_TYPE_SUM_ROWS, - GGML_METAL_KERNEL_TYPE_MEAN, - GGML_METAL_KERNEL_TYPE_POOL_2D_AVG_F32, - GGML_METAL_KERNEL_TYPE_POOL_2D_MAX_F32, - GGML_METAL_KERNEL_TYPE_ARGMAX, - - GGML_METAL_KERNEL_TYPE_COUNT -}; - -struct ggml_metal_command_buffer { - id obj; - - // used to enable concurrent execution of ops in the command buffers - struct ggml_mem_ranges * mem_ranges; -}; - -struct ggml_backend_metal_context { - id device; - id queue; // currently a pointer to the device queue, but might become separate queue [TAG_QUEUE_PER_BACKEND] - - dispatch_queue_t d_queue; - - // the set of pre-compiled kernels for this context - struct ggml_metal_kernel kernels[GGML_METAL_KERNEL_TYPE_COUNT]; - - // additional, inference-time compiled kernels - NSMutableDictionary * kernels_ext; - - // capture state - bool capture_next_compute; - bool capture_started; - - id capture_scope; - - // command buffer state - int n_cb; // number of extra threads used to submit the command buffers - int n_nodes_0; // number of nodes submitted by the main thread - int n_nodes_1; // remaining number of nodes submitted by the n_cb threads - int n_nodes_per_cb; - - struct ggml_cgraph * gf; - - // the callback given to the thread pool - void (^encode_async)(size_t ith); - - // n_cb command buffers + 1 used by the main thread - struct ggml_metal_command_buffer cmd_bufs[GGML_METAL_MAX_COMMAND_BUFFERS + 1]; - - // extra command buffers for things like getting, setting and copying tensors - NSMutableArray * cmd_bufs_ext; - - // the last command buffer queued into the Metal queue with operations relevant to the current Metal backend - id cmd_buf_last; - - // abort ggml_metal_graph_compute if callback returns true - ggml_abort_callback abort_callback; - void * abort_callback_data; -}; - -// MSL code -// TODO: move the contents here when ready -// for now it is easier to work in a separate file -// static NSString * const msl_library_source = @"see metal.metal"; - -#if !GGML_METAL_EMBED_LIBRARY -// Here to assist with NSBundle Path Hack -@interface GGMLMetalClass : NSObject -@end -@implementation GGMLMetalClass -@end -#endif - -static void * ggml_metal_host_malloc(size_t n) { - void * data = NULL; - -#if TARGET_OS_OSX - kern_return_t err = vm_allocate((vm_map_t) mach_task_self(), (void *) &data, n, VM_FLAGS_ANYWHERE); - if (err != KERN_SUCCESS) { - GGML_LOG_ERROR("%s: error: vm_allocate failed\n", __func__); - return NULL; - } -#else - const int result = posix_memalign((void **) &data, sysconf(_SC_PAGESIZE), n); - if (result != 0) { - GGML_LOG_ERROR("%s: error: posix_memalign failed\n", __func__); - return NULL; - } -#endif - - return data; -} - -// load library -// -// - first check if the library is embedded -// - then check if the library is in the bundle -// - if not found, load the source and compile it -// - if that fails, return NULL -static id ggml_metal_load_library(id device, bool use_bfloat) { - const int64_t t_start = ggml_time_us(); - - id metal_library = nil; - NSError * error = nil; - NSString * src = nil; - -#if GGML_METAL_EMBED_LIBRARY - GGML_LOG_INFO("%s: using embedded metal library\n", __func__); - - extern const char ggml_metallib_start[]; - extern const char ggml_metallib_end[]; - - src = [[NSString alloc] initWithBytes:ggml_metallib_start length:(ggml_metallib_end-ggml_metallib_start) encoding:NSUTF8StringEncoding]; - -#else - -#ifdef SWIFT_PACKAGE - NSBundle * bundle = SWIFTPM_MODULE_BUNDLE; -#else - NSBundle * bundle = [NSBundle bundleForClass:[GGMLMetalClass class]]; -#endif - - NSString * path_lib = [bundle pathForResource:@"default" ofType:@"metallib"]; - if (path_lib == nil) { - // Try to find the resource in the directory where the current binary located. - NSString * current_binary = [[NSProcessInfo processInfo] arguments][0]; - NSString * bin_dir = [current_binary stringByDeletingLastPathComponent]; - NSString * default_metallib_path = [NSString pathWithComponents:@[bin_dir, @"default.metallib"]]; - if ([[NSFileManager defaultManager] isReadableFileAtPath:default_metallib_path]) { - GGML_LOG_INFO("%s: found '%s'\n", __func__, [default_metallib_path UTF8String]); - NSDictionary * atts = [[NSFileManager defaultManager] attributesOfItemAtPath:default_metallib_path error:&error]; - if (atts && atts[NSFileType] == NSFileTypeSymbolicLink) { - // Optionally, if this is a symlink, try to resolve it. - default_metallib_path = [[NSFileManager defaultManager] destinationOfSymbolicLinkAtPath:default_metallib_path error:&error]; - if (default_metallib_path && [default_metallib_path length] > 0 && ![[default_metallib_path substringToIndex:1] isEqualToString:@"/"]) { - // It is a relative path, adding the binary directory as directory prefix. - default_metallib_path = [NSString pathWithComponents:@[bin_dir, default_metallib_path]]; - } - if (!default_metallib_path || ![[NSFileManager defaultManager] isReadableFileAtPath:default_metallib_path]) { - // Link to the resource could not be resolved. - default_metallib_path = nil; - } else { - GGML_LOG_INFO("%s: symlink resolved '%s'\n", __func__, [default_metallib_path UTF8String]); - } - } - } else { - // The resource couldn't be found in the binary's directory. - default_metallib_path = nil; - } - path_lib = default_metallib_path; - } - - if (path_lib != nil) { - // pre-compiled library found - NSURL * libURL = [NSURL fileURLWithPath:path_lib]; - GGML_LOG_INFO("%s: loading '%s'\n", __func__, [path_lib UTF8String]); - - metal_library = [device newLibraryWithURL:libURL error:&error]; - if (error) { - GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]); - return NULL; - } - } else { - GGML_LOG_INFO("%s: default.metallib not found, loading from source\n", __func__); - - NSString * path_source; - NSString * path_resource = [[NSProcessInfo processInfo].environment objectForKey:@"GGML_METAL_PATH_RESOURCES"]; - - GGML_LOG_INFO("%s: GGML_METAL_PATH_RESOURCES = %s\n", __func__, path_resource ? [path_resource UTF8String] : "nil"); - - if (path_resource) { - path_source = [path_resource stringByAppendingPathComponent:@"ggml-metal.metal"]; - } else { - path_source = [bundle pathForResource:@"ggml-metal" ofType:@"metal"]; - } - - if (path_source == nil) { - GGML_LOG_WARN("%s: error: could not use bundle path to find ggml-metal.metal, falling back to trying cwd\n", __func__); - path_source = @"ggml-metal.metal"; - } - - GGML_LOG_INFO("%s: loading '%s'\n", __func__, [path_source UTF8String]); - - src = [NSString stringWithContentsOfFile:path_source encoding:NSUTF8StringEncoding error:&error]; - if (error) { - GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]); - return NULL; - } - } -#endif - - if (!metal_library) { - @autoreleasepool { - // dictionary of preprocessor macros - NSMutableDictionary * prep = [NSMutableDictionary dictionary]; - - if (use_bfloat) { - [prep setObject:@"1" forKey:@"GGML_METAL_USE_BF16"]; - } - -#if GGML_METAL_EMBED_LIBRARY - [prep setObject:@"1" forKey:@"GGML_METAL_EMBED_LIBRARY"]; -#endif - - MTLCompileOptions * options = [MTLCompileOptions new]; - options.preprocessorMacros = prep; - - //[options setFastMathEnabled:false]; - - metal_library = [device newLibraryWithSource:src options:options error:&error]; - if (error) { - GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]); - return NULL; - } - -#if !__has_feature(objc_arc) - [options release]; -#endif - } - } - -#if GGML_METAL_EMBED_LIBRARY - [src release]; -#endif // GGML_METAL_EMBED_LIBRARY - - GGML_LOG_INFO("%s: loaded in %.3f sec\n", __func__, (ggml_time_us() - t_start) / 1e6); - - return metal_library; -} - -static struct ggml_backend_metal_context * ggml_metal_init(ggml_backend_dev_t dev) { - GGML_LOG_INFO("%s: allocating\n", __func__); - -#if TARGET_OS_OSX && !GGML_METAL_NDEBUG - // Show all the Metal device instances in the system - NSArray * devices = MTLCopyAllDevices(); - for (id device in devices) { - GGML_LOG_INFO("%s: found device: %s\n", __func__, [[device name] UTF8String]); - } - [devices release]; // since it was created by a *Copy* C method -#endif - - // init context - struct ggml_backend_metal_context * ctx = calloc(1, sizeof(struct ggml_backend_metal_context)); - struct ggml_backend_metal_device_context * ctx_dev = dev->context; - - id device = ctx_dev->mtl_device; - - GGML_LOG_INFO("%s: picking default device: %s\n", __func__, [[device name] UTF8String]); - - ctx->device = device; - - // TODO: question - 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? - //ctx->queue = [device newCommandQueue]; [TAG_QUEUE_PER_BACKEND] - ctx->queue = ctx_dev->mtl_queue; - if (ctx->queue == nil) { - GGML_LOG_ERROR("%s: error: failed to create command queue\n", __func__); - return NULL; - } - - ctx->d_queue = dispatch_queue_create("ggml-metal", DISPATCH_QUEUE_CONCURRENT); - - // load library - { - [ctx_dev->mtl_lock lock]; - - if (ctx_dev->mtl_library == nil) { - ctx_dev->mtl_library = ggml_metal_load_library(device, ctx_dev->use_bfloat); - } - - [ctx_dev->mtl_lock unlock]; - } - - id metal_library = ctx_dev->mtl_library; - if (metal_library == nil) { - GGML_LOG_ERROR("%s: error: metal library is nil\n", __func__); - return NULL; - } - - // print MTL GPU family: - GGML_LOG_INFO("%s: GPU name: %s\n", __func__, [[device name] UTF8String]); - - // determine max supported GPU family - // https://developer.apple.com/metal/Metal-Shading-Language-Specification.pdf - // https://developer.apple.com/metal/Metal-Feature-Set-Tables.pdf - { - for (int i = MTLGPUFamilyApple1 + 20; i >= MTLGPUFamilyApple1; --i) { - if ([device supportsFamily:i]) { - GGML_LOG_INFO("%s: GPU family: MTLGPUFamilyApple%d (%d)\n", __func__, i - (int) MTLGPUFamilyApple1 + 1, i); - break; - } - } - - for (int i = MTLGPUFamilyCommon1 + 5; i >= MTLGPUFamilyCommon1; --i) { - if ([device supportsFamily:i]) { - GGML_LOG_INFO("%s: GPU family: MTLGPUFamilyCommon%d (%d)\n", __func__, i - (int) MTLGPUFamilyCommon1 + 1, i); - break; - } - } - - for (int i = MTLGPUFamilyMetal3_GGML + 5; i >= MTLGPUFamilyMetal3_GGML; --i) { - if ([device supportsFamily:i]) { - GGML_LOG_INFO("%s: GPU family: MTLGPUFamilyMetal%d (%d)\n", __func__, i - (int) MTLGPUFamilyMetal3_GGML + 3, i); - break; - } - } - } - - GGML_LOG_INFO("%s: simdgroup reduction = %s\n", __func__, ctx_dev->has_simdgroup_reduction ? "true" : "false"); - GGML_LOG_INFO("%s: simdgroup matrix mul. = %s\n", __func__, ctx_dev->has_simdgroup_mm ? "true" : "false"); - GGML_LOG_INFO("%s: has residency sets = %s\n", __func__, ctx_dev->has_residency_sets ? "true" : "false"); - GGML_LOG_INFO("%s: has bfloat = %s\n", __func__, ctx_dev->has_bfloat ? "true" : "false"); - GGML_LOG_INFO("%s: use bfloat = %s\n", __func__, ctx_dev->use_bfloat ? "true" : "false"); - GGML_LOG_INFO("%s: use fusion = %s\n", __func__, ctx_dev->use_fusion ? "true" : "false"); - GGML_LOG_INFO("%s: use concurrency = %s\n", __func__, ctx_dev->use_concurrency ? "true" : "false"); - GGML_LOG_INFO("%s: use shared buffers = %s\n", __func__, ctx_dev->use_shared_buffers ? "true" : "false"); - GGML_LOG_INFO("%s: use graph optimize = %s\n", __func__, ctx_dev->use_graph_optimize ? "true" : "false"); - GGML_LOG_INFO("%s: hasUnifiedMemory = %s\n", __func__, ctx_dev->mtl_device.hasUnifiedMemory ? "true" : "false"); - - ctx->capture_next_compute = false; - ctx->capture_started = false; - ctx->capture_scope = nil; - - ctx->gf = nil; - ctx->encode_async = nil; - for (int i = 0; i < GGML_METAL_MAX_COMMAND_BUFFERS; ++i) { - ctx->cmd_bufs[i].obj = nil; - - if (ctx_dev->use_concurrency) { - ctx->cmd_bufs[i].mem_ranges = ggml_mem_ranges_init(ctx_dev->debug_graph); - } - } - - ctx->cmd_bufs_ext = [[NSMutableArray alloc] init]; - - ctx->cmd_buf_last = nil; - -#if TARGET_OS_OSX || (TARGET_OS_IOS && __clang_major__ >= 15) - if (@available(macOS 10.12, iOS 16.0, *)) { - GGML_LOG_INFO("%s: recommendedMaxWorkingSetSize = %8.2f MB\n", __func__, device.recommendedMaxWorkingSetSize / 1e6); - } -#endif - - // load kernels - { - NSError * error = nil; - - for (int i = 0; i < GGML_METAL_KERNEL_TYPE_COUNT; ++i) { - ctx->kernels[i].pipeline = nil; - } - -#define GGML_METAL_ADD_KERNEL(e, name, supported) \ - if (supported) { \ - struct ggml_metal_kernel * kernel = &ctx->kernels[e]; \ - id metal_function = [metal_library newFunctionWithName:@"kernel_"#name]; \ - kernel->pipeline = [device newComputePipelineStateWithFunction:metal_function error:&error]; \ - GGML_LOG_DEBUG("%s: loaded %-40s %16p | th_max = %4d | th_width = %4d\n", __func__, "kernel_"#name, (void *) kernel->pipeline, \ - (int) kernel->pipeline.maxTotalThreadsPerThreadgroup, \ - (int) kernel->pipeline.threadExecutionWidth); \ - [metal_function release]; \ - if (error) { \ - GGML_LOG_ERROR("%s: error: load pipeline error: %s\n", __func__, [[error description] UTF8String]); \ - return NULL; \ - } \ - } else { \ - GGML_LOG_WARN("%s: skipping %-40s (not supported)\n", __func__, "kernel_"#name); \ - } - - const bool has_simdgroup_mm = ctx_dev->has_simdgroup_mm; - const bool has_simdgroup_reduction = ctx_dev->has_simdgroup_reduction; - const bool use_bfloat = ctx_dev->use_bfloat; - - // simd_sum and simd_max requires MTLGPUFamilyApple7 - - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ADD_ID, add_id, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_REPEAT_F32, repeat_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_REPEAT_F16, repeat_f16, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_REPEAT_I32, repeat_i32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_REPEAT_I16, repeat_i16, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SCALE, scale, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SCALE_4, scale_4, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CLAMP, clamp, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_TANH, tanh, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_RELU, relu, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SIGMOID, sigmoid, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GELU, gelu, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GELU_4, gelu_4, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GELU_ERF, gelu_erf, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GELU_ERF_4, gelu_erf_4, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GELU_QUICK, gelu_quick, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GELU_QUICK_4, gelu_quick_4, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SILU, silu, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SILU_4, silu_4, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ELU, elu, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ABS, abs, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SGN, sgn, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_STEP, step, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_HARDSWISH, hardswish, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_HARDSIGMOID, hardsigmoid, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_EXP, exp, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SOFT_MAX_F16, soft_max_f16, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SOFT_MAX_F16_4, soft_max_f16_4, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SOFT_MAX_F32, soft_max_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SOFT_MAX_F32_4, soft_max_f32_4, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_DIAG_MASK_INF, diag_mask_inf, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_DIAG_MASK_INF_8, diag_mask_inf_8, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_F32, get_rows_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_F16, get_rows_f16, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_BF16, get_rows_bf16, use_bfloat); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_Q4_0, get_rows_q4_0, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_Q4_1, get_rows_q4_1, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_Q5_0, get_rows_q5_0, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_Q5_1, get_rows_q5_1, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_Q8_0, get_rows_q8_0, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_MXFP4, get_rows_mxfp4, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_Q2_K, get_rows_q2_K, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_Q3_K, get_rows_q3_K, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_Q4_K, get_rows_q4_K, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_Q5_K, get_rows_q5_K, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_Q6_K, get_rows_q6_K, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ2_XXS, get_rows_iq2_xxs, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ2_XS, get_rows_iq2_xs, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ3_XXS, get_rows_iq3_xxs, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ3_S, get_rows_iq3_s, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ2_S, get_rows_iq2_s, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ1_S, get_rows_iq1_s, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ1_M, get_rows_iq1_m, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ4_NL, get_rows_iq4_nl, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ4_XS, get_rows_iq4_xs, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_I32, get_rows_i32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SET_ROWS_F32, set_rows_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SET_ROWS_F16, set_rows_f16, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SET_ROWS_BF16, set_rows_bf16, use_bfloat); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SET_ROWS_Q8_0, set_rows_q8_0, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SET_ROWS_Q4_0, set_rows_q4_0, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SET_ROWS_Q4_1, set_rows_q4_1, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SET_ROWS_Q5_0, set_rows_q5_0, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SET_ROWS_Q5_1, set_rows_q5_1, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SET_ROWS_IQ4_NL, set_rows_iq4_nl, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_L2_NORM, l2_norm, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GROUP_NORM, group_norm, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_NORM, norm, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SSM_CONV_F32, ssm_conv_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SSM_SCAN_F32, ssm_scan_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SSM_SCAN_F32_GROUP, ssm_scan_f32_group, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_RWKV_WKV6_F32, rwkv_wkv6_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_RWKV_WKV7_F32, rwkv_wkv7_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_F32_F32, mul_mv_f32_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_F32_F32_C4, mul_mv_f32_f32_c4, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_F32, mul_mv_bf16_f32, has_simdgroup_reduction && use_bfloat); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_F32_C4, mul_mv_bf16_f32_c4, use_bfloat); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_F32_1ROW, mul_mv_bf16_f32_1row, has_simdgroup_reduction && use_bfloat); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_F32_L4, mul_mv_bf16_f32_l4, has_simdgroup_reduction && use_bfloat); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_BF16, mul_mv_bf16_bf16, has_simdgroup_reduction && use_bfloat); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32, mul_mv_f16_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32_C4, mul_mv_f16_f32_c4, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32_1ROW, mul_mv_f16_f32_1row, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32_L4, mul_mv_f16_f32_l4, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F16, mul_mv_f16_f16, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_Q4_0_F32, mul_mv_q4_0_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_Q4_1_F32, mul_mv_q4_1_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_0_F32, mul_mv_q5_0_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_1_F32, mul_mv_q5_1_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_Q8_0_F32, mul_mv_q8_0_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_MXFP4_F32, mul_mv_mxfp4_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F32_F32_R1_2, mul_mv_ext_f32_f32_r1_2, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F32_F32_R1_3, mul_mv_ext_f32_f32_r1_3, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F32_F32_R1_4, mul_mv_ext_f32_f32_r1_4, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F32_F32_R1_5, mul_mv_ext_f32_f32_r1_5, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F16_F32_R1_2, mul_mv_ext_f16_f32_r1_2, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F16_F32_R1_3, mul_mv_ext_f16_f32_r1_3, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F16_F32_R1_4, mul_mv_ext_f16_f32_r1_4, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F16_F32_R1_5, mul_mv_ext_f16_f32_r1_5, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_0_F32_R1_2, mul_mv_ext_q4_0_f32_r1_2, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_0_F32_R1_3, mul_mv_ext_q4_0_f32_r1_3, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_0_F32_R1_4, mul_mv_ext_q4_0_f32_r1_4, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_0_F32_R1_5, mul_mv_ext_q4_0_f32_r1_5, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_1_F32_R1_2, mul_mv_ext_q4_1_f32_r1_2, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_1_F32_R1_3, mul_mv_ext_q4_1_f32_r1_3, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_1_F32_R1_4, mul_mv_ext_q4_1_f32_r1_4, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_1_F32_R1_5, mul_mv_ext_q4_1_f32_r1_5, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_0_F32_R1_2, mul_mv_ext_q5_0_f32_r1_2, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_0_F32_R1_3, mul_mv_ext_q5_0_f32_r1_3, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_0_F32_R1_4, mul_mv_ext_q5_0_f32_r1_4, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_0_F32_R1_5, mul_mv_ext_q5_0_f32_r1_5, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_1_F32_R1_2, mul_mv_ext_q5_1_f32_r1_2, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_1_F32_R1_3, mul_mv_ext_q5_1_f32_r1_3, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_1_F32_R1_4, mul_mv_ext_q5_1_f32_r1_4, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_1_F32_R1_5, mul_mv_ext_q5_1_f32_r1_5, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q8_0_F32_R1_2, mul_mv_ext_q8_0_f32_r1_2, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q8_0_F32_R1_3, mul_mv_ext_q8_0_f32_r1_3, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q8_0_F32_R1_4, mul_mv_ext_q8_0_f32_r1_4, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q8_0_F32_R1_5, mul_mv_ext_q8_0_f32_r1_5, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_MXFP4_F32_R1_2, mul_mv_ext_mxfp4_f32_r1_2, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_MXFP4_F32_R1_3, mul_mv_ext_mxfp4_f32_r1_3, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_MXFP4_F32_R1_4, mul_mv_ext_mxfp4_f32_r1_4, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_MXFP4_F32_R1_5, mul_mv_ext_mxfp4_f32_r1_5, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_K_F32_R1_2, mul_mv_ext_q4_K_f32_r1_2, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_K_F32_R1_3, mul_mv_ext_q4_K_f32_r1_3, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_K_F32_R1_4, mul_mv_ext_q4_K_f32_r1_4, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_K_F32_R1_5, mul_mv_ext_q4_K_f32_r1_5, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_K_F32_R1_2, mul_mv_ext_q5_K_f32_r1_2, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_K_F32_R1_3, mul_mv_ext_q5_K_f32_r1_3, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_K_F32_R1_4, mul_mv_ext_q5_K_f32_r1_4, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_K_F32_R1_5, mul_mv_ext_q5_K_f32_r1_5, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q6_K_F32_R1_2, mul_mv_ext_q6_K_f32_r1_2, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q6_K_F32_R1_3, mul_mv_ext_q6_K_f32_r1_3, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q6_K_F32_R1_4, mul_mv_ext_q6_K_f32_r1_4, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q6_K_F32_R1_5, mul_mv_ext_q6_K_f32_r1_5, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_IQ4_NL_F32_R1_2, mul_mv_ext_iq4_nl_f32_r1_2, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_IQ4_NL_F32_R1_3, mul_mv_ext_iq4_nl_f32_r1_3, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_IQ4_NL_F32_R1_4, mul_mv_ext_iq4_nl_f32_r1_4, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_IQ4_NL_F32_R1_5, mul_mv_ext_iq4_nl_f32_r1_5, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_Q2_K_F32, mul_mv_q2_K_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_Q3_K_F32, mul_mv_q3_K_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_Q4_K_F32, mul_mv_q4_K_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_K_F32, mul_mv_q5_K_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_Q6_K_F32, mul_mv_q6_K_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_IQ2_XXS_F32, mul_mv_iq2_xxs_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_IQ2_XS_F32, mul_mv_iq2_xs_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_IQ3_XXS_F32, mul_mv_iq3_xxs_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_IQ3_S_F32, mul_mv_iq3_s_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_IQ2_S_F32, mul_mv_iq2_s_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_IQ1_S_F32, mul_mv_iq1_s_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_IQ1_M_F32, mul_mv_iq1_m_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_IQ4_NL_F32, mul_mv_iq4_nl_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_IQ4_XS_F32, mul_mv_iq4_xs_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_F32_F32, mul_mv_id_f32_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_F16_F32, mul_mv_id_f16_f32, has_simdgroup_reduction); - //GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_F16_F32_1ROW, mul_mv_id_f16_f32_1row, has_simdgroup_reduction); - //GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_F16_F32_L4, mul_mv_id_f16_f32_l4, has_simdgroup_reduction); - //GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_F16_F16, mul_mv_id_f16_f16, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_BF16_F32, mul_mv_id_bf16_f32, has_simdgroup_reduction && use_bfloat); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q4_0_F32, mul_mv_id_q4_0_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q4_1_F32, mul_mv_id_q4_1_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q5_0_F32, mul_mv_id_q5_0_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q5_1_F32, mul_mv_id_q5_1_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q8_0_F32, mul_mv_id_q8_0_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_MXFP4_F32, mul_mv_id_mxfp4_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q2_K_F32, mul_mv_id_q2_K_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q3_K_F32, mul_mv_id_q3_K_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q4_K_F32, mul_mv_id_q4_K_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q5_K_F32, mul_mv_id_q5_K_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q6_K_F32, mul_mv_id_q6_K_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ2_XXS_F32, mul_mv_id_iq2_xxs_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ2_XS_F32, mul_mv_id_iq2_xs_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ3_XXS_F32, mul_mv_id_iq3_xxs_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ3_S_F32, mul_mv_id_iq3_s_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ2_S_F32, mul_mv_id_iq2_s_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ1_S_F32, mul_mv_id_iq1_s_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ1_M_F32, mul_mv_id_iq1_m_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ4_NL_F32, mul_mv_id_iq4_nl_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ4_XS_F32, mul_mv_id_iq4_xs_f32, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_F32_F32, mul_mm_f32_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_F16_F32, mul_mm_f16_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_BF16_F32, mul_mm_bf16_f32, has_simdgroup_mm && use_bfloat); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_Q4_0_F32, mul_mm_q4_0_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_Q4_1_F32, mul_mm_q4_1_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_0_F32, mul_mm_q5_0_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_1_F32, mul_mm_q5_1_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_Q8_0_F32, mul_mm_q8_0_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_MXFP4_F32, mul_mm_mxfp4_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_Q2_K_F32, mul_mm_q2_K_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_Q3_K_F32, mul_mm_q3_K_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_Q4_K_F32, mul_mm_q4_K_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_K_F32, mul_mm_q5_K_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_Q6_K_F32, mul_mm_q6_K_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_IQ2_XXS_F32, mul_mm_iq2_xxs_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_IQ2_XS_F32, mul_mm_iq2_xs_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_IQ3_XXS_F32, mul_mm_iq3_xxs_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_IQ3_S_F32, mul_mm_iq3_s_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_IQ2_S_F32, mul_mm_iq2_s_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_IQ1_S_F32, mul_mm_iq1_s_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_IQ1_M_F32, mul_mm_iq1_m_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_IQ4_NL_F32, mul_mm_iq4_nl_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_IQ4_XS_F32, mul_mm_iq4_xs_f32, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_1, mul_mm_id_map0_f16_ne20_1, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_2, mul_mm_id_map0_f16_ne20_2, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_4, mul_mm_id_map0_f16_ne20_4, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_6, mul_mm_id_map0_f16_ne20_6, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_8, mul_mm_id_map0_f16_ne20_8, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_10, mul_mm_id_map0_f16_ne20_10, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_16, mul_mm_id_map0_f16_ne20_16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_F32_F16, mul_mm_id_f32_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_F16_F16, mul_mm_id_f16_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_BF16_F16, mul_mm_id_bf16_f16, has_simdgroup_mm && use_bfloat); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q4_0_F16, mul_mm_id_q4_0_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q4_1_F16, mul_mm_id_q4_1_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q5_0_F16, mul_mm_id_q5_0_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q5_1_F16, mul_mm_id_q5_1_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q8_0_F16, mul_mm_id_q8_0_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MXFP4_F16, mul_mm_id_mxfp4_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q2_K_F16, mul_mm_id_q2_K_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q3_K_F16, mul_mm_id_q3_K_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q4_K_F16, mul_mm_id_q4_K_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q5_K_F16, mul_mm_id_q5_K_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q6_K_F16, mul_mm_id_q6_K_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ2_XXS_F16, mul_mm_id_iq2_xxs_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ2_XS_F16, mul_mm_id_iq2_xs_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ3_XXS_F16, mul_mm_id_iq3_xxs_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ3_S_F16, mul_mm_id_iq3_s_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ2_S_F16, mul_mm_id_iq2_s_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ1_S_F16, mul_mm_id_iq1_s_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ1_M_F16, mul_mm_id_iq1_m_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ4_NL_F16, mul_mm_id_iq4_nl_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ4_XS_F16, mul_mm_id_iq4_xs_f16, has_simdgroup_mm); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ROPE_NORM_F32, rope_norm_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ROPE_NORM_F16, rope_norm_f16, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ROPE_MULTI_F32, rope_multi_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ROPE_MULTI_F16, rope_multi_f16, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ROPE_VISION_F32, rope_vision_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ROPE_VISION_F16, rope_vision_f16, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ROPE_NEOX_F32, rope_neox_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ROPE_NEOX_F16, rope_neox_f16, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_IM2COL_F16, im2col_f16, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_IM2COL_F32, im2col_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_IM2COL_EXT_F16, im2col_ext_f16, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_IM2COL_EXT_F32, im2col_ext_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CONV_TRANSPOSE_1D_F32_F32, conv_transpose_1d_f32_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CONV_TRANSPOSE_1D_F16_F32, conv_transpose_1d_f16_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_UPSCALE_F32, upscale_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_PAD_F32, pad_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_PAD_REFLECT_1D_F32, pad_reflect_1d_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_TIMESTEP_EMBEDDING_F32, timestep_embedding_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ARANGE_F32, arange_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ARGSORT_F32_I32_ASC, argsort_f32_i32_asc, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ARGSORT_F32_I32_DESC, argsort_f32_i32_desc, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_LEAKY_RELU_F32, leaky_relu_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_F32, cpy_f32_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_F16, cpy_f32_f16, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_BF16, cpy_f32_bf16, use_bfloat); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F16_F32, cpy_f16_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F16_F16, cpy_f16_f16, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_BF16_F32, cpy_bf16_f32, use_bfloat); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_BF16_BF16, cpy_bf16_bf16, use_bfloat); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_I32, cpy_f32_i32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_I32_F32, cpy_i32_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_Q8_0, cpy_f32_q8_0, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_Q4_0, cpy_f32_q4_0, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_Q4_1, cpy_f32_q4_1, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_Q5_0, cpy_f32_q5_0, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_Q5_1, cpy_f32_q5_1, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_IQ4_NL, cpy_f32_iq4_nl, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_Q4_0_F32, cpy_q4_0_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_Q4_0_F16, cpy_q4_0_f16, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_Q4_1_F32, cpy_q4_1_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_Q4_1_F16, cpy_q4_1_f16, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_Q5_0_F32, cpy_q5_0_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_Q5_0_F16, cpy_q5_0_f16, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_Q5_1_F32, cpy_q5_1_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_Q5_1_F16, cpy_q5_1_f16, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_Q8_0_F32, cpy_q8_0_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_Q8_0_F16, cpy_q8_0_f16, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CONCAT, concat, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SQR, sqr, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SQRT, sqrt, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SIN, sin, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_COS, cos, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_NEG, neg, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_REGLU, reglu, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GEGLU, geglu, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SWIGLU, swiglu, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SWIGLU_OAI, swiglu_oai, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GEGLU_ERF, geglu_erf, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GEGLU_QUICK, geglu_quick, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SUM_ROWS, sum_rows, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MEAN, mean, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ARGMAX, argmax, has_simdgroup_reduction); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_POOL_2D_AVG_F32, pool_2d_avg_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_POOL_2D_MAX_F32, pool_2d_max_f32, true); - } - - ctx->kernels_ext = [[NSMutableDictionary alloc] init]; - - return ctx; -} - -static id ggml_metal_get_kernel(struct ggml_backend_metal_context * ctx, const char * name) { - NSString * key = [NSString stringWithUTF8String:name]; - - ggml_metal_kernel_wrapper * obj = [ctx->kernels_ext objectForKey:key]; - if (obj) { - return obj.kernel.pipeline; - } - - return nil; -} - -static id ggml_metal_compile_kernel(ggml_backend_t backend, const char * base, const char * name, MTLFunctionConstantValues * cv) { - struct ggml_backend_metal_context * ctx = backend->context; - struct ggml_backend_metal_device_context * ctx_dev = backend->device->context; - - id res = nil; - - @autoreleasepool { - NSError * error = nil; - - NSString * base_func = [NSString stringWithUTF8String:base]; - - GGML_LOG_DEBUG("%s: compiling kernel: base = '%s', name = '%s'\n", __func__, base, name); - - // TODO: make sure it is thread-safe to compile kernels in parallel - id metal_function = [ctx_dev->mtl_library newFunctionWithName:base_func constantValues:cv error:&error]; - if (!metal_function) { - GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]); - - return nil; - } - - struct ggml_metal_kernel kernel = { - /*.pipeline =*/ [ctx_dev->mtl_device newComputePipelineStateWithFunction:metal_function error:&error], - }; - - ggml_metal_kernel_wrapper * obj = [[ggml_metal_kernel_wrapper alloc] init]; - obj.kernel = kernel; - - res = obj.kernel.pipeline; - - NSString * key = [NSString stringWithUTF8String:name]; - [ctx->kernels_ext setObject:obj forKey:key]; - - [metal_function release]; - [obj release]; - - GGML_LOG_DEBUG("%s: loaded %-40s %16p | th_max = %4d | th_width = %4d\n", __func__, name, (void *) kernel.pipeline, - (int) kernel.pipeline.maxTotalThreadsPerThreadgroup, - (int) kernel.pipeline.threadExecutionWidth); - } - - return res; -} - -// tokens per expert -static size_t ggml_metal_mul_mat_id_extra_tpe(const struct ggml_tensor * op) { - assert(op->op == GGML_OP_MUL_MAT_ID); - - const int64_t ne02 = op->src[0]->ne[2]; // n_expert - - return ggml_type_size(GGML_TYPE_I32)*ne02; -} - -// id map [n_tokens, n_expert] -static size_t ggml_metal_mul_mat_id_extra_ids(const struct ggml_tensor * op) { - assert(op->op == GGML_OP_MUL_MAT_ID); - - const int64_t ne02 = op->src[0]->ne[2]; // n_expert - const int64_t ne21 = op->src[2]->ne[1]; // n_token - - return ggml_type_size(GGML_TYPE_I32)*ne02*ne21; -} - -// return true if we should use the FA vector kernel for this op -static bool ggml_metal_flash_attn_ext_use_vec(const struct ggml_tensor * op) { - assert(op->op == GGML_OP_FLASH_ATTN_EXT); - - const int64_t ne00 = op->src[0]->ne[0]; // head size - const int64_t ne01 = op->src[0]->ne[1]; // batch size - - // use vec kernel if the batch size is small and if the head size is supported - return (ne01 < 20) && (ne00 % 32 == 0); -} - -static size_t ggml_metal_flash_attn_ext_extra_tmp(const struct ggml_tensor * op) { - assert(op->op == GGML_OP_FLASH_ATTN_EXT); - - const int64_t nwg = 32; - - const int64_t ne01 = op->src[0]->ne[1]; - const int64_t ne02 = op->src[0]->ne[2]; - const int64_t ne03 = op->src[0]->ne[3]; - const int64_t ne20 = op->src[2]->ne[0]; - - // temp buffer for writing the results from each workgroup - // - ne20: the size of the Value head - // - + 2: the S and M values for each intermediate result - return ggml_type_size(GGML_TYPE_F32)*(ne01*ne02*ne03*nwg*(ne20 + 2)); -} - -static id ggml_metal_get_pipeline_flash_attn_ext( - ggml_backend_t backend, struct ggml_tensor * op, - bool has_mask, - bool has_sinks, - bool has_bias, - bool has_scap, - int32_t nsg) { - struct ggml_backend_metal_context * ctx = backend->context; - - char base[256]; - char name[256]; - - @autoreleasepool { - const int32_t dk = (int32_t) op->src[1]->ne[0]; - const int32_t dv = (int32_t) op->src[2]->ne[0]; - - const int32_t ns10 = op->src[1]->nb[1]/op->src[1]->nb[0]; - const int32_t ns20 = op->src[2]->nb[1]/op->src[2]->nb[0]; - - snprintf(base, 256, "kernel_%s_%s_dk%d_dv%d", - "flash_attn_ext", - ggml_type_name(op->src[1]->type), - dk, - dv); - - snprintf(name, 256, "kernel_%s_%s_dk%d_dv%d_mask=%d_sinks=%d_bias=%d_scap=%d_ns10=%d_ns20=%d_nsg=%d", - "flash_attn_ext", - ggml_type_name(op->src[1]->type), - dk, - dv, - has_mask, - has_sinks, - has_bias, - has_scap, - ns10, - ns20, - nsg); - - id res = ggml_metal_get_kernel(ctx, name); - if (res) { - // kernel found - return res; - } - - MTLFunctionConstantValues * cv = [[MTLFunctionConstantValues alloc] init]; - - [cv setConstantValue:&has_mask type:MTLDataTypeBool atIndex:FC_FLASH_ATTN_EXT + 0]; - [cv setConstantValue:&has_sinks type:MTLDataTypeBool atIndex:FC_FLASH_ATTN_EXT + 1]; - [cv setConstantValue:&has_bias type:MTLDataTypeBool atIndex:FC_FLASH_ATTN_EXT + 2]; - [cv setConstantValue:&has_scap type:MTLDataTypeBool atIndex:FC_FLASH_ATTN_EXT + 3]; - - [cv setConstantValue:&ns10 type:MTLDataTypeInt atIndex:FC_FLASH_ATTN_EXT + 20]; - [cv setConstantValue:&ns20 type:MTLDataTypeInt atIndex:FC_FLASH_ATTN_EXT + 21]; - [cv setConstantValue:&nsg type:MTLDataTypeInt atIndex:FC_FLASH_ATTN_EXT + 22]; - - res = ggml_metal_compile_kernel(backend, base, name, cv); - - [cv release]; - - return res; - } -} - -static id ggml_metal_get_pipeline_flash_attn_ext_vec( - ggml_backend_t backend, struct ggml_tensor * op, - bool has_mask, - bool has_sinks, - bool has_bias, - bool has_scap, - int32_t nsg, - int32_t nwg) { - struct ggml_backend_metal_context * ctx = backend->context; - - char base[256]; - char name[256]; - - @autoreleasepool { - const int32_t dk = (int32_t) op->src[1]->ne[0]; - const int32_t dv = (int32_t) op->src[2]->ne[0]; - - const int32_t ns10 = op->src[1]->nb[1]/op->src[1]->nb[0]; - const int32_t ns20 = op->src[2]->nb[1]/op->src[2]->nb[0]; - - snprintf(base, 256, "kernel_%s_%s_dk%d_dv%d", - "flash_attn_ext_vec", - ggml_type_name(op->src[1]->type), - dk, - dv); - - snprintf(name, 256, "kernel_%s_%s_dk%d_dv%d_mask=%d_sink=%d_bias=%d_softcap=%d_ns10=%d_ns20=%d_nsg=%d_nwg=%d", - "flash_attn_ext_vec", - ggml_type_name(op->src[1]->type), - dk, - dv, - has_mask, - has_sinks, - has_bias, - has_scap, - ns10, - ns20, - nsg, nwg); - - id res = ggml_metal_get_kernel(ctx, name); - if (res) { - // kernel found - return res; - } - - MTLFunctionConstantValues * cv = [[MTLFunctionConstantValues alloc] init]; - - [cv setConstantValue:&has_mask type:MTLDataTypeBool atIndex:FC_FLASH_ATTN_EXT_VEC + 0]; - [cv setConstantValue:&has_sinks type:MTLDataTypeBool atIndex:FC_FLASH_ATTN_EXT_VEC + 1]; - [cv setConstantValue:&has_bias type:MTLDataTypeBool atIndex:FC_FLASH_ATTN_EXT_VEC + 2]; - [cv setConstantValue:&has_scap type:MTLDataTypeBool atIndex:FC_FLASH_ATTN_EXT_VEC + 3]; - - [cv setConstantValue:&ns10 type:MTLDataTypeInt atIndex:FC_FLASH_ATTN_EXT_VEC + 20]; - [cv setConstantValue:&ns20 type:MTLDataTypeInt atIndex:FC_FLASH_ATTN_EXT_VEC + 21]; - [cv setConstantValue:&nsg type:MTLDataTypeInt atIndex:FC_FLASH_ATTN_EXT_VEC + 22]; - [cv setConstantValue:&nwg type:MTLDataTypeInt atIndex:FC_FLASH_ATTN_EXT_VEC + 23]; - - res = ggml_metal_compile_kernel(backend, base, name, cv); - - [cv release]; - - return res; - } -} - -static id ggml_metal_get_pipeline_flash_attn_ext_vec_reduce( - ggml_backend_t backend, struct ggml_tensor * op, - int32_t dv, - int32_t nwg) { - struct ggml_backend_metal_context * ctx = backend->context; - - char base[256]; - char name[256]; - - @autoreleasepool { - snprintf(base, 256, "kernel_flash_attn_ext_vec_reduce"); - snprintf(name, 256, "kernel_flash_attn_ext_vec_reduce_dv=%d_nwg=%d", dv, nwg); - - id res = ggml_metal_get_kernel(ctx, name); - if (res) { - // kernel found - return res; - } - - MTLFunctionConstantValues * cv = [[MTLFunctionConstantValues alloc] init]; - - [cv setConstantValue:&dv type:MTLDataTypeInt atIndex:FC_FLASH_ATTN_EXT_VEC_REDUCE + 0]; - [cv setConstantValue:&nwg type:MTLDataTypeInt atIndex:FC_FLASH_ATTN_EXT_VEC_REDUCE + 1]; - - res = ggml_metal_compile_kernel(backend, base, name, cv); - - [cv release]; - - return res; - } - - GGML_UNUSED(op); -} - -static id ggml_metal_get_pipeline_bin( - ggml_backend_t backend, enum ggml_op op, - int32_t n_fuse, - bool row) { - struct ggml_backend_metal_context * ctx = backend->context; - - char base[256]; - char name[256]; - - @autoreleasepool { - const char * op_str = "undefined"; - switch (op) { - case GGML_OP_ADD: op_str = "add"; break; - case GGML_OP_SUB: op_str = "sub"; break; - case GGML_OP_MUL: op_str = "mul"; break; - case GGML_OP_DIV: op_str = "div"; break; - default: GGML_ABORT("fatal error"); - }; - - if (row) { - snprintf(base, 256, "kernel_%s_row_c4_fuse_%d", op_str, n_fuse); - } else { - snprintf(base, 256, "kernel_%s_fuse_%d", op_str, n_fuse); - } - - snprintf(name, 256, "%s", base); - - id res = ggml_metal_get_kernel(ctx, name); - if (res) { - // kernel found - return res; - } - - return ggml_metal_compile_kernel(backend, base, name, nil); - } -} - -static id ggml_metal_get_pipeline_rms_norm( - ggml_backend_t backend, struct ggml_tensor * op, - int32_t n_fuse) { - struct ggml_backend_metal_context * ctx = backend->context; - - char base[256]; - char name[256]; - - @autoreleasepool { - switch (n_fuse) { - case 1: snprintf(base, 256, "kernel_rms_norm"); break; - case 2: snprintf(base, 256, "kernel_rms_norm_mul"); break; - case 3: snprintf(base, 256, "kernel_rms_norm_mul_add"); break; - default: GGML_ABORT("fatal error"); - } - - snprintf(name, 256, "%s", base); - - id res = ggml_metal_get_kernel(ctx, name); - if (res) { - // kernel found - return res; - } - - return ggml_metal_compile_kernel(backend, base, name, nil); - } - - GGML_UNUSED(op); -} - -static void ggml_metal_free(struct ggml_backend_metal_context * ctx) { - GGML_LOG_INFO("%s: deallocating\n", __func__); - - for (int i = 0; i < GGML_METAL_KERNEL_TYPE_COUNT; ++i) { - [ctx->kernels[i].pipeline release]; - } - - if (ctx->kernels_ext) { - [ctx->kernels_ext release]; - ctx->kernels_ext = nil; - } - - Block_release(ctx->encode_async); - - //[ctx->queue release]; // [TAG_QUEUE_PER_BACKEND] - - for (int i = 0; i < GGML_METAL_MAX_COMMAND_BUFFERS; ++i) { - if (ctx->cmd_bufs[i].obj) { - [ctx->cmd_bufs[i].obj release]; - } - - if (ctx->cmd_bufs[i].mem_ranges) { - ggml_mem_ranges_free(ctx->cmd_bufs[i].mem_ranges); - } - } - - [ctx->cmd_bufs_ext removeAllObjects]; - [ctx->cmd_bufs_ext release]; - - dispatch_release(ctx->d_queue); - - free(ctx); -} - -// temporarily defined here for compatibility between ggml-backend and the old API - -struct ggml_backend_metal_buffer { - void * data; - size_t size; - - id metal; -}; - -struct ggml_backend_metal_buffer_context { - void * all_data; - size_t all_size; - - // if false, the Metal buffer data is allocated in private GPU memory and is not shared with the host - bool is_shared; - - // multiple buffers are used only to avoid the maximum buffer size limitation when using mmap - int n_buffers; - struct ggml_backend_metal_buffer buffers[GGML_METAL_MAX_BUFFERS]; - - // optional MTLResidencySet - // 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; -}; - -// rset init -static bool ggml_backend_metal_buffer_rset_init( - struct ggml_backend_metal_buffer_context * ctx, - struct ggml_backend_metal_device_context * ctx_dev, - id device) { - ctx->rset = nil; - - if (!ctx_dev->has_residency_sets) { - return true; - } - -#if defined(GGML_METAL_HAS_RESIDENCY_SETS) - if (@available(macOS 15.0, iOS 18.0, tvOS 18.0, visionOS 2.0, *)) { - MTLResidencySetDescriptor * desc = [[MTLResidencySetDescriptor alloc] init]; - desc.label = @"ggml_backend_metal"; - desc.initialCapacity = ctx->n_buffers; - - NSError * error; - ctx->rset = [device newResidencySetWithDescriptor:desc error:&error]; - if (error) { - GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]); - [desc release]; - return false; - } - - [desc release]; - - for (int i = 0; i < ctx->n_buffers; i++) { - [ctx->rset addAllocation:ctx->buffers[i].metal]; - } - - [ctx->rset commit]; - [ctx->rset requestResidency]; - - return true; - } -#else - GGML_UNUSED(ctx_dev); - GGML_UNUSED(device); -#endif - - return true; -} - -// rset free -static void ggml_backend_metal_buffer_rset_free(struct ggml_backend_metal_buffer_context * ctx) { -#if defined(GGML_METAL_HAS_RESIDENCY_SETS) - if (@available(macOS 15.0, iOS 18.0, tvOS 18.0, visionOS 2.0, *)) { - if (ctx->rset) { - [ctx->rset endResidency]; - [ctx->rset removeAllAllocations]; - [ctx->rset release]; - } - } -#else - GGML_UNUSED(ctx); -#endif -} - -// finds the Metal buffer that contains the tensor data on the GPU device -// the assumption is that there is 1-to-1 mapping between the host and device memory buffers, so we can find the -// Metal buffer based on the host memory pointer -// -static id ggml_metal_get_buffer(const struct ggml_tensor * t, size_t * offs) { - //GGML_LOG_INFO("%s: data tensor '%16s', offs_data = %8ld, offs_eval = %8ld, offs_cach = %8ld\n", __func__, t->name, offs_data, offs_eval, offs_cach); - - const int64_t tsize = ggml_nbytes(t); - - ggml_backend_buffer_t buffer = t->view_src ? t->view_src->buffer : t->buffer; - - struct ggml_backend_metal_buffer_context * buf_ctx = (struct ggml_backend_metal_buffer_context *) buffer->context; - - // find the view that contains the tensor fully - for (int i = 0; i < buf_ctx->n_buffers; ++i) { - const int64_t ioffs = (int64_t) t->data - (int64_t) buf_ctx->buffers[i].data; - - //GGML_LOG_INFO("ioffs = %10ld, tsize = %10ld, sum = %10ld, buf_ctx->buffers[%d].size = %10ld\n", ioffs, tsize, ioffs + tsize, i, buf_ctx->buffers[i].size); - if (ioffs >= 0 && ioffs + tsize <= (int64_t) buf_ctx->buffers[i].size) { - *offs = (size_t) ioffs; - - //GGML_LOG_INFO("%s: tensor '%16s', offs = %8ld\n", __func__, t->name, *offs); - - return buf_ctx->buffers[i].metal; - } - } - - GGML_LOG_ERROR("%s: error: tensor '%s' buffer is nil\n", __func__, t->name); - - return nil; -} - -static bool ggml_metal_supports_op(const struct ggml_backend_metal_device_context * ctx_dev, const struct ggml_tensor * op) { - const bool has_simdgroup_mm = ctx_dev->has_simdgroup_mm; - const bool has_simdgroup_reduction = ctx_dev->has_simdgroup_reduction; - const bool use_bfloat = ctx_dev->use_bfloat; - - if (!use_bfloat) { - if (op->type == GGML_TYPE_BF16) { - return false; - } - - for (size_t i = 0, n = 3; i < n; ++i) { - if (op->src[i] != NULL && op->src[i]->type == GGML_TYPE_BF16) { - return false; - } - } - } - - switch (op->op) { - case GGML_OP_UNARY: - switch (ggml_get_unary_op(op)) { - case GGML_UNARY_OP_TANH: - case GGML_UNARY_OP_RELU: - case GGML_UNARY_OP_SIGMOID: - case GGML_UNARY_OP_GELU: - case GGML_UNARY_OP_GELU_ERF: - case GGML_UNARY_OP_GELU_QUICK: - case GGML_UNARY_OP_SILU: - case GGML_UNARY_OP_ELU: - case GGML_UNARY_OP_NEG: - case GGML_UNARY_OP_ABS: - case GGML_UNARY_OP_SGN: - case GGML_UNARY_OP_STEP: - case GGML_UNARY_OP_HARDSWISH: - case GGML_UNARY_OP_HARDSIGMOID: - case GGML_UNARY_OP_EXP: - return ggml_is_contiguous(op->src[0]) && op->src[0]->type == GGML_TYPE_F32; - default: - return false; - } - case GGML_OP_GLU: - switch (ggml_get_glu_op(op)) { - case GGML_GLU_OP_REGLU: - case GGML_GLU_OP_GEGLU: - case GGML_GLU_OP_SWIGLU: - case GGML_GLU_OP_SWIGLU_OAI: - case GGML_GLU_OP_GEGLU_ERF: - case GGML_GLU_OP_GEGLU_QUICK: - return ggml_is_contiguous_1(op->src[0]) && op->src[0]->type == GGML_TYPE_F32; - default: - return false; - } - case GGML_OP_NONE: - case GGML_OP_RESHAPE: - case GGML_OP_VIEW: - case GGML_OP_TRANSPOSE: - case GGML_OP_PERMUTE: - case GGML_OP_CONCAT: - return true; - case GGML_OP_ADD: - case GGML_OP_SUB: - case GGML_OP_MUL: - case GGML_OP_DIV: - case GGML_OP_ADD_ID: - return op->src[0]->type == GGML_TYPE_F32; - case GGML_OP_ACC: - case GGML_OP_REPEAT: - case GGML_OP_SCALE: - case GGML_OP_CONV_TRANSPOSE_1D: - return true; - case GGML_OP_CLAMP: - return op->src[0]->type == GGML_TYPE_F32; - case GGML_OP_SQR: - case GGML_OP_SQRT: - case GGML_OP_SIN: - case GGML_OP_COS: - return ggml_is_contiguous(op->src[0]) && op->src[0]->type == GGML_TYPE_F32; - case GGML_OP_LOG: - return false; // TODO: implement - case GGML_OP_SUM_ROWS: - case GGML_OP_MEAN: - case GGML_OP_SOFT_MAX: - case GGML_OP_GROUP_NORM: - return has_simdgroup_reduction && ggml_is_contiguous_rows(op->src[0]); - case GGML_OP_RMS_NORM: - case GGML_OP_L2_NORM: - return has_simdgroup_reduction && (op->ne[0] % 4 == 0 && ggml_is_contiguous_1(op->src[0])); - case GGML_OP_ARGMAX: - return has_simdgroup_reduction; - case GGML_OP_NORM: - return has_simdgroup_reduction && (op->ne[0] % 4 == 0 && ggml_is_contiguous_1(op->src[0])); - case GGML_OP_ROPE: - return true; - case GGML_OP_IM2COL: - return ggml_is_contiguous(op->src[1]) && op->src[1]->type == GGML_TYPE_F32 && (op->type == GGML_TYPE_F16 || op->type == GGML_TYPE_F32); - case GGML_OP_POOL_1D: - return false; - case GGML_OP_UPSCALE: - return op->src[0]->type == GGML_TYPE_F32 && op->op_params[0] == GGML_SCALE_MODE_NEAREST; - case GGML_OP_POOL_2D: - return op->src[0]->type == GGML_TYPE_F32; - case GGML_OP_PAD: - 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: - case GGML_OP_TIMESTEP_EMBEDDING: - case GGML_OP_ARGSORT: - case GGML_OP_LEAKY_RELU: - return op->src[0]->type == GGML_TYPE_F32; - case GGML_OP_ARANGE: - return true; - case GGML_OP_FLASH_ATTN_EXT: - // for new head sizes, add checks here - if (op->src[0]->ne[0] != 40 && - op->src[0]->ne[0] != 64 && - op->src[0]->ne[0] != 80 && - op->src[0]->ne[0] != 96 && - op->src[0]->ne[0] != 112 && - op->src[0]->ne[0] != 128 && - op->src[0]->ne[0] != 192 && - op->src[0]->ne[0] != 256) { - return false; - } - if (op->src[0]->ne[0] == 576) { - // DeepSeek sizes - // TODO: disabled for now, until optmized - return false; - } - if (op->src[1]->type != op->src[2]->type) { - return false; - } - return has_simdgroup_mm; // TODO: over-restricted for vec-kernels - case GGML_OP_SSM_CONV: - case GGML_OP_SSM_SCAN: - return has_simdgroup_reduction; - case GGML_OP_RWKV_WKV6: - case GGML_OP_RWKV_WKV7: - return true; - case GGML_OP_MUL_MAT: - case GGML_OP_MUL_MAT_ID: - return has_simdgroup_reduction && - (op->src[0]->type != GGML_TYPE_F32 || op->src[1]->type == GGML_TYPE_F32); - case GGML_OP_CPY: - case GGML_OP_DUP: - case GGML_OP_CONT: - { - switch (op->src[0]->type) { - case GGML_TYPE_F32: - switch (op->type) { - case GGML_TYPE_F32: - case GGML_TYPE_F16: - case GGML_TYPE_BF16: - case GGML_TYPE_Q8_0: - case GGML_TYPE_Q4_0: - case GGML_TYPE_Q4_1: - case GGML_TYPE_Q5_0: - case GGML_TYPE_Q5_1: - case GGML_TYPE_IQ4_NL: - case GGML_TYPE_I32: - return true; - default: - return false; - } - case GGML_TYPE_F16: - switch (op->type) { - case GGML_TYPE_F32: - case GGML_TYPE_F16: - return true; - default: - return false; - } - case GGML_TYPE_BF16: - switch (op->type) { - case GGML_TYPE_F32: - case GGML_TYPE_BF16: - return true; - default: - return false; - } - case GGML_TYPE_Q4_0: - case GGML_TYPE_Q4_1: - case GGML_TYPE_Q5_0: - case GGML_TYPE_Q5_1: - case GGML_TYPE_Q8_0: - switch (op->type) { - case GGML_TYPE_F32: - case GGML_TYPE_F16: - return true; - default: - return false; - } - case GGML_TYPE_I32: - return op->type == GGML_TYPE_F32; - default: - return false; - }; - } - case GGML_OP_DIAG_MASK_INF: - case GGML_OP_GET_ROWS: - { - return op->ne[3] == 1; - } - case GGML_OP_SET_ROWS: - { - if (op->src[0]->type != GGML_TYPE_F32) { - return false; - } - - switch (op->type) { - case GGML_TYPE_F32: - case GGML_TYPE_F16: - case GGML_TYPE_BF16: - case GGML_TYPE_Q8_0: - case GGML_TYPE_Q4_0: - case GGML_TYPE_Q4_1: - case GGML_TYPE_Q5_0: - case GGML_TYPE_Q5_1: - case GGML_TYPE_IQ4_NL: - return true; - default: - return false; - }; - } - default: - return false; - } -} - -struct ggml_metal_encode_context { - ggml_backend_t backend; - - id encoder; - - struct ggml_mem_ranges * mem_ranges; -}; - -static bool ggml_metal_encode_concurrency_reset(struct ggml_metal_encode_context * ctx) { - if (!ctx->mem_ranges) { - return true; - } - - [ctx->encoder memoryBarrierWithScope:MTLBarrierScopeBuffers]; - - ggml_mem_ranges_reset(ctx->mem_ranges); - - return true; -} - -static bool ggml_metal_encode_concurrency_check(struct ggml_metal_encode_context * ctx, const struct ggml_tensor * node) { - if (!ctx->mem_ranges) { - return false; - } - - return ggml_mem_ranges_check(ctx->mem_ranges, node); -} - -static bool ggml_metal_encode_concurrency_add(struct ggml_metal_encode_context * ctx, const struct ggml_tensor * node) { - if (!ctx->mem_ranges) { - return true; - } - - return ggml_mem_ranges_add(ctx->mem_ranges, node); -} - -static int ggml_metal_encode_node(struct ggml_metal_encode_context * ctx_enc, int idx, int idx_end) { - ggml_backend_t backend = ctx_enc->backend; - - id encoder = ctx_enc->encoder; - - struct ggml_backend_metal_context * ctx = backend->context; - struct ggml_backend_metal_device_context * ctx_dev = backend->device->context; - - struct ggml_cgraph * gf = ctx->gf; - - enum ggml_op ops[8]; - - struct ggml_tensor ** nodes = ggml_graph_nodes(gf) + idx; - struct ggml_tensor * node = nodes[0]; - - //GGML_LOG_INFO("%s: encoding node %3d, op = %8s\n", __func__, idx, ggml_op_name(node->op)); - - struct ggml_tensor * src0 = node->src[0]; - struct ggml_tensor * src1 = node->src[1]; - struct ggml_tensor * src2 = node->src[2]; - struct ggml_tensor * dst = node; - - if (ggml_is_empty(dst)) { - return 1; - } - - switch (dst->op) { - case GGML_OP_NONE: - case GGML_OP_RESHAPE: - case GGML_OP_VIEW: - case GGML_OP_TRANSPOSE: - case GGML_OP_PERMUTE: - { - // noop -> next node - } return 1; - default: - { - } break; - } - - if (!ggml_metal_supports_op(ctx_dev, dst)) { - GGML_LOG_ERROR("%s: error: unsupported op '%s'\n", __func__, ggml_op_desc(dst)); - GGML_ABORT("unsupported op"); - } - - const int64_t ne00 = src0 ? src0->ne[0] : 0; - const int64_t ne01 = src0 ? src0->ne[1] : 0; - const int64_t ne02 = src0 ? src0->ne[2] : 0; - const int64_t ne03 = src0 ? src0->ne[3] : 0; - - const uint64_t nb00 = src0 ? src0->nb[0] : 0; - const uint64_t nb01 = src0 ? src0->nb[1] : 0; - const uint64_t nb02 = src0 ? src0->nb[2] : 0; - const uint64_t nb03 = src0 ? src0->nb[3] : 0; - - const int64_t ne10 = src1 ? src1->ne[0] : 0; - const int64_t ne11 = src1 ? src1->ne[1] : 0; - const int64_t ne12 = src1 ? src1->ne[2] : 0; - const int64_t ne13 = src1 ? src1->ne[3] : 0; - - const uint64_t nb10 = src1 ? src1->nb[0] : 0; - const uint64_t nb11 = src1 ? src1->nb[1] : 0; - const uint64_t nb12 = src1 ? src1->nb[2] : 0; - const uint64_t nb13 = src1 ? src1->nb[3] : 0; - - const int64_t ne20 = src2 ? src2->ne[0] : 0; - const int64_t ne21 = src2 ? src2->ne[1] : 0; - const int64_t ne22 = src2 ? src2->ne[2] : 0; GGML_UNUSED(ne22); - const int64_t ne23 = src2 ? src2->ne[3] : 0; GGML_UNUSED(ne23); - - const uint64_t nb20 = src2 ? src2->nb[0] : 0; GGML_UNUSED(nb20); - const uint64_t nb21 = src2 ? src2->nb[1] : 0; - const uint64_t nb22 = src2 ? src2->nb[2] : 0; - const uint64_t nb23 = src2 ? src2->nb[3] : 0; GGML_UNUSED(nb23); - - const int64_t ne0 = dst ? dst->ne[0] : 0; - const int64_t ne1 = dst ? dst->ne[1] : 0; - const int64_t ne2 = dst ? dst->ne[2] : 0; - const int64_t ne3 = dst ? dst->ne[3] : 0; - - const uint64_t nb0 = dst ? dst->nb[0] : 0; - const uint64_t nb1 = dst ? dst->nb[1] : 0; - const uint64_t nb2 = dst ? dst->nb[2] : 0; - const uint64_t nb3 = dst ? dst->nb[3] : 0; - - size_t offs_src[GGML_MAX_SRC]; - - id id_src[GGML_MAX_SRC]; - - enum ggml_type srct[GGML_MAX_SRC]; - - for (int i = 0; i < GGML_MAX_SRC; i++) { - offs_src[i] = 0; - id_src[i] = node->src[i] ? ggml_metal_get_buffer(node->src[i], &offs_src[i]) : nil; - srct[i] = node->src[i] ? node->src[i]->type : GGML_TYPE_COUNT; - } - - // TODO: tmp shorthands - remove - size_t offs_src0 = offs_src[0]; - size_t offs_src1 = offs_src[1]; - size_t offs_src2 = offs_src[2]; - - id id_src0 = id_src[0]; - id id_src1 = id_src[1]; - id id_src2 = id_src[2]; - - const enum ggml_type src0t = src0 ? src0->type : GGML_TYPE_COUNT; - const enum ggml_type src1t = src1 ? src1->type : GGML_TYPE_COUNT; - const enum ggml_type src2t = src2 ? src2->type : GGML_TYPE_COUNT; - const enum ggml_type dstt = dst ? dst->type : GGML_TYPE_COUNT; - - size_t offs_dst = 0; - - id id_dst = dst ? ggml_metal_get_buffer(dst, &offs_dst) : nil; - - int n_fuse = 1; - - // check if the current node can run concurrently with other nodes before it - // the condition is that: - // - the current node cannot write to any previous src or dst ranges - // - the current node cannot read from any previous dst ranges - // - // if the condition is not satisfied, we put a memory barrier and clear all ranges - // otherwise, we add the new ranges to the encoding context and process the node concurrently - // - { - const bool is_concurrent = ggml_metal_encode_concurrency_check(ctx_enc, node); - - if (!is_concurrent) { - ggml_metal_encode_concurrency_reset(ctx_enc); - } - - if (ctx_dev->debug_graph > 0) { - GGML_LOG_DEBUG("%s: node[%5d] - %-12s %s\n", __func__, idx, ggml_op_name(dst->op), is_concurrent ? "(concurrent)" : ""); - } - if (ctx_dev->debug_graph > 1) { - if (src0) { - GGML_LOG_DEBUG("%s: src0 - %4s [%5lld, %5lld, %5lld, %5lld] [%5lld, %5lld, %5lld, %5lld], %d, %s\n", __func__, ggml_type_name(src0t), ne00, ne01, ne02, ne03, nb00, nb01, nb02, nb03, - ggml_is_contiguous(src0), src0->name); - } - if (src1) { - GGML_LOG_DEBUG("%s: src1 - %4s [%5lld, %5lld, %5lld, %5lld] [%5lld, %5lld, %5lld, %5lld], %d, %s\n", __func__, ggml_type_name(src1t), ne10, ne11, ne12, ne13, nb10, nb11, nb12, nb13, - ggml_is_contiguous(src1), src1->name); - } - if (dst) { - GGML_LOG_DEBUG("%s: dst - %4s [%5lld, %5lld, %5lld, %5lld] [%5lld, %5lld, %5lld, %5lld], 1, %s\n", __func__, ggml_type_name(dstt), ne0, ne1, ne2, ne3, nb0, nb1, nb2, nb3, - dst->name); - } - } - } - - id device = ctx_dev->mtl_device; - - switch (dst->op) { - case GGML_OP_CONCAT: - { - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CONCAT].pipeline; - - const int32_t dim = ((const int32_t *) dst->op_params)[0]; - - ggml_metal_kargs_concat args = { - /*.ne00 =*/ ne00, - /*.ne01 =*/ ne01, - /*.ne02 =*/ ne02, - /*.ne03 =*/ ne03, - /*.nb00 =*/ nb00, - /*.nb01 =*/ nb01, - /*.nb02 =*/ nb02, - /*.nb03 =*/ nb03, - /*.ne10 =*/ ne10, - /*.ne11 =*/ ne11, - /*.ne12 =*/ ne12, - /*.ne13 =*/ ne13, - /*.nb10 =*/ nb10, - /*.nb11 =*/ nb11, - /*.nb12 =*/ nb12, - /*.nb13 =*/ nb13, - /*.ne0 =*/ ne0, - /*.ne1 =*/ ne1, - /*.ne2 =*/ ne2, - /*.ne3 =*/ ne3, - /*.nb0 =*/ nb0, - /*.nb1 =*/ nb1, - /*.nb2 =*/ nb2, - /*.nb3 =*/ nb3, - /*.dim =*/ dim, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:2]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:3]; - - const int nth = MIN(1024, ne0); - - [encoder dispatchThreadgroups:MTLSizeMake(ne1, ne2, ne3) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } break; - case GGML_OP_ADD: - case GGML_OP_SUB: - case GGML_OP_MUL: - case GGML_OP_DIV: - { - GGML_ASSERT(src0t == GGML_TYPE_F32); - GGML_ASSERT(src1t == GGML_TYPE_F32); - - GGML_ASSERT(ggml_is_contiguous_rows(src0)); - GGML_ASSERT(ggml_is_contiguous_rows(src1)); - - const size_t offs = 0; - - bool bcast_row = false; - - ggml_metal_kargs_bin args = { - /*.ne00 =*/ ne00, - /*.ne01 =*/ ne01, - /*.ne02 =*/ ne02, - /*.ne03 =*/ ne03, - /*.nb00 =*/ nb00, - /*.nb01 =*/ nb01, - /*.nb02 =*/ nb02, - /*.nb03 =*/ nb03, - /*.ne10 =*/ ne10, - /*.ne11 =*/ ne11, - /*.ne12 =*/ ne12, - /*.ne13 =*/ ne13, - /*.nb10 =*/ nb10, - /*.nb11 =*/ nb11, - /*.nb12 =*/ nb12, - /*.nb13 =*/ nb13, - /*.ne0 =*/ ne0, - /*.ne1 =*/ ne1, - /*.ne2 =*/ ne2, - /*.ne3 =*/ ne3, - /*.nb0 =*/ nb0, - /*.nb1 =*/ nb1, - /*.nb2 =*/ nb2, - /*.nb3 =*/ nb3, - /*.offs =*/ offs, - /*.o1 =*/ { offs_src1 }, - }; - - // c[0] = add(a, b[0]) - // c[1] = add(c[0], b[1]) - // c[2] = add(c[1], b[2]) - // ... - if (ctx_dev->use_fusion) { - ops[0] = GGML_OP_ADD; - ops[1] = GGML_OP_ADD; - ops[2] = GGML_OP_ADD; - ops[3] = GGML_OP_ADD; - ops[4] = GGML_OP_ADD; - ops[5] = GGML_OP_ADD; - ops[6] = GGML_OP_ADD; - ops[7] = GGML_OP_ADD; - - size_t offs_fuse; - id id_fuse; - - // note: in metal, we sometimes encode the graph in parallel so we have to avoid fusing nodes - // across splits. idx_end indicates the last node in the current split - for (n_fuse = 0; n_fuse <= 6 && idx + n_fuse + 1 < idx_end; ++n_fuse) { - if (!ggml_can_fuse(gf, idx + n_fuse, ops + n_fuse, 2)) { - break; - } - - if (nodes[n_fuse] != nodes[n_fuse + 1]->src[0]) { - break; - } - - // b[0] === b[1] === ... - if (!ggml_are_same_layout(nodes[n_fuse]->src[1], nodes[n_fuse + 1]->src[1])) { - break; - } - - // only fuse nodes if src1 is in the same Metal buffer - id_fuse = ggml_metal_get_buffer(nodes[n_fuse + 1]->src[1], &offs_fuse); - if (id_fuse != id_src1) { - break; - } - - ctx_dev->fuse_cnt[nodes[n_fuse + 1]->op]++; - - args.o1[n_fuse + 1] = offs_fuse; - } - - ++n_fuse; - - if (ctx_dev->debug_fusion > 1 && n_fuse > 1) { - GGML_LOG_DEBUG("%s: fuse: ADD x %d\n", __func__, n_fuse); - } - } - - id pipeline = nil; - - if (ggml_nelements(src1) == ne10 && ggml_is_contiguous(src1) && ne00 % 4 == 0 && ne10 % 4 == 0) { - GGML_ASSERT(ggml_is_contiguous(src0)); - - // src1 is a row - GGML_ASSERT(ne11 == 1); - - pipeline = ggml_metal_get_pipeline_bin(backend, dst->op, n_fuse, true); - - bcast_row = true; - } else { - pipeline = ggml_metal_get_pipeline_bin(backend, dst->op, n_fuse, false); - } - - if (n_fuse > 1) { - id_dst = ggml_metal_get_buffer(nodes[n_fuse - 1], &offs_dst); - - for (int i = 1; i < n_fuse; ++i) { - if (!ggml_metal_encode_concurrency_check(ctx_enc, nodes[i])) { - ggml_metal_encode_concurrency_reset(ctx_enc); - - break; - } - } - } - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_src1 offset:0 atIndex:2]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:3]; - - if (bcast_row) { - const int64_t n = ggml_nelements(dst)/4; - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } else { - int nth = 32; - - while (16*nth < ne0 && nth < (int) pipeline.maxTotalThreadsPerThreadgroup) { - nth *= 2; - } - - [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } - } break; - case GGML_OP_ADD_ID: - { - GGML_ASSERT(src0t == GGML_TYPE_F32); - GGML_ASSERT(src1t == GGML_TYPE_F32); - GGML_ASSERT(src2t == GGML_TYPE_I32); - GGML_ASSERT(dstt == GGML_TYPE_F32); - - GGML_ASSERT(ggml_is_contiguous_rows(src0)); - - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_ADD_ID].pipeline; - - ggml_metal_kargs_add_id args = { - /*.ne0 =*/ ne0, - /*.ne1 =*/ ne1, - /*.nb01 =*/ nb01, - /*.nb02 =*/ nb02, - /*.nb11 =*/ nb11, - /*.nb21 =*/ nb21, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:2]; - [encoder setBuffer:id_src2 offset:offs_src2 atIndex:3]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:4]; - - const int nth = MIN((int) pipeline.maxTotalThreadsPerThreadgroup, ne00); - - [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, 1) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } break; - case GGML_OP_REPEAT: - { - id pipeline; - - switch (src0t) { - case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_REPEAT_F32].pipeline; break; - case GGML_TYPE_F16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_REPEAT_F16].pipeline; break; - case GGML_TYPE_I32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_REPEAT_I32].pipeline; break; - case GGML_TYPE_I16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_REPEAT_I16].pipeline; break; - default: GGML_ABORT("fatal error"); - } - - ggml_metal_kargs_repeat 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, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:2]; - - const int nth = MIN((int) pipeline.maxTotalThreadsPerThreadgroup, ne0); - - [encoder dispatchThreadgroups:MTLSizeMake(ne1, ne2, ne3) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } break; - case GGML_OP_ACC: - { - GGML_ASSERT(src0t == GGML_TYPE_F32); - GGML_ASSERT(src1t == GGML_TYPE_F32); - GGML_ASSERT(dstt == GGML_TYPE_F32); - - GGML_ASSERT(ggml_is_contiguous(src0)); - GGML_ASSERT(ggml_is_contiguous(src1)); - - const size_t pnb1 = ((const int32_t *) dst->op_params)[0]; - const size_t pnb2 = ((const int32_t *) dst->op_params)[1]; - const size_t pnb3 = ((const int32_t *) dst->op_params)[2]; - const size_t offs = ((const int32_t *) dst->op_params)[3]; - - const bool inplace = (bool) ((const int32_t *) dst->op_params)[4]; - - if (!inplace) { - // run a separete kernel to cpy src->dst - // not sure how to avoid this - // TODO: make a simpler cpy_bytes kernel - - const id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_F32].pipeline; - - ggml_metal_kargs_cpy 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, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:2]; - - const int nth = MIN((int) pipeline.maxTotalThreadsPerThreadgroup, ne00); - - [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - - ggml_metal_encode_concurrency_reset(ctx_enc); - } - - ggml_metal_kargs_bin args = { - /*.ne00 =*/ ne00, - /*.ne01 =*/ ne01, - /*.ne02 =*/ ne02, - /*.ne03 =*/ ne03, - /*.nb00 =*/ nb00, - /*.nb01 =*/ pnb1, - /*.nb02 =*/ pnb2, - /*.nb03 =*/ pnb3, - /*.ne10 =*/ ne10, - /*.ne11 =*/ ne11, - /*.ne12 =*/ ne12, - /*.ne13 =*/ ne13, - /*.nb10 =*/ nb10, - /*.nb11 =*/ nb11, - /*.nb12 =*/ nb12, - /*.nb13 =*/ nb13, - /*.ne0 =*/ ne0, - /*.ne1 =*/ ne1, - /*.ne2 =*/ ne2, - /*.ne3 =*/ ne3, - /*.nb0 =*/ nb0, - /*.nb1 =*/ pnb1, - /*.nb2 =*/ pnb2, - /*.nb3 =*/ pnb3, - /*.offs =*/ offs, - /*.o1 =*/ { offs_src1}, - }; - - //const id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_ADD].pipeline; - const id pipeline = ggml_metal_get_pipeline_bin(backend, GGML_OP_ADD, 1, false); - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_src1 offset:0 atIndex:2]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:3]; - - const int nth = MIN((int) pipeline.maxTotalThreadsPerThreadgroup, ne00); - - [encoder dispatchThreadgroups:MTLSizeMake(ne11, ne12, ne13) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } break; - case GGML_OP_SCALE: - { - GGML_ASSERT(ggml_is_contiguous(src0)); - - float scale; - float bias; - memcpy(&scale, ((const int32_t *) dst->op_params) + 0, sizeof(float)); - memcpy(&bias, ((const int32_t *) dst->op_params) + 1, sizeof(float)); - - int64_t n = ggml_nelements(dst); - - id pipeline = nil; - - if (n % 4 == 0) { - n /= 4; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SCALE_4].pipeline; - } else { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SCALE].pipeline; - } - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - [encoder setBytes:&scale length:sizeof(scale) atIndex:2]; - [encoder setBytes:&bias length:sizeof(bias) atIndex:3]; - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_OP_CLAMP: - { - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CLAMP].pipeline; - - float min; - float max; - memcpy(&min, ((const int32_t *) dst->op_params) + 0, sizeof(float)); - memcpy(&max, ((const int32_t *) dst->op_params) + 1, sizeof(float)); - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - [encoder setBytes:&min length:sizeof(min) atIndex:2]; - [encoder setBytes:&max length:sizeof(max) atIndex:3]; - - const int64_t n = ggml_nelements(dst); - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_OP_UNARY: - switch (ggml_get_unary_op(node)) { - // we are not taking into account the strides, so for now require contiguous tensors - GGML_ASSERT(ggml_is_contiguous(src0)); - - case GGML_UNARY_OP_TANH: - { - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_TANH].pipeline; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - - const int64_t n = ggml_nelements(dst); - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_UNARY_OP_RELU: - { - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_RELU].pipeline; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - - const int64_t n = ggml_nelements(dst); - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_UNARY_OP_SIGMOID: - { - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SIGMOID].pipeline; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - - const int64_t n = ggml_nelements(dst); - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_UNARY_OP_GELU: - { - int64_t n = ggml_nelements(dst); - - id pipeline = nil; - - if (n % 4 == 0) { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GELU_4].pipeline; - n /= 4; - } else { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GELU].pipeline; - } - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_UNARY_OP_GELU_ERF: - { - int64_t n = ggml_nelements(dst); - - id pipeline = nil; - - if (n % 4 == 0) { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GELU_ERF_4].pipeline; - n /= 4; - } else { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GELU_ERF].pipeline; - } - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_UNARY_OP_GELU_QUICK: - { - int64_t n = ggml_nelements(dst); - - id pipeline = nil; - - if (n % 4 == 0) { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GELU_QUICK_4].pipeline; - n /= 4; - } else { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GELU_QUICK].pipeline; - } - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_UNARY_OP_SILU: - { - int64_t n = ggml_nelements(dst); - - id pipeline = nil; - - if (n % 4 == 0) { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SILU_4].pipeline; - n /= 4; - } else { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SILU].pipeline; - } - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_UNARY_OP_ELU: - { - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_ELU].pipeline; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - - const int64_t n = ggml_nelements(dst); - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_UNARY_OP_NEG: - { - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_NEG].pipeline; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - - const int64_t n = ggml_nelements(dst); - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_UNARY_OP_ABS: - { - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_ABS].pipeline; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - - const int64_t n = ggml_nelements(dst); - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_UNARY_OP_SGN: - { - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SGN].pipeline; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - - const int64_t n = ggml_nelements(dst); - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_UNARY_OP_STEP: - { - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_STEP].pipeline; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - - const int64_t n = ggml_nelements(dst); - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_UNARY_OP_HARDSWISH: - { - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_HARDSWISH].pipeline; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - - const int64_t n = ggml_nelements(dst); - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_UNARY_OP_HARDSIGMOID: - { - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_HARDSIGMOID].pipeline; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - - const int64_t n = ggml_nelements(dst); - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_UNARY_OP_EXP: - { - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_EXP].pipeline; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - - const int64_t n = ggml_nelements(dst); - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - default: - { - GGML_LOG_WARN("%s: node %3d, op = %8s not implemented\n", __func__, idx, ggml_op_name(dst->op)); - GGML_ABORT("fatal error"); - } - } break; - case GGML_OP_GLU: - { - GGML_ASSERT(ggml_is_contiguous_1(src0)); - - if (src1) { - GGML_ASSERT(ggml_are_same_shape(src0, src1)); - } - - id pipeline = nil; - - switch (ggml_get_glu_op(node)) { - case GGML_GLU_OP_REGLU: - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_REGLU].pipeline; - break; - case GGML_GLU_OP_GEGLU: - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GEGLU].pipeline; - break; - case GGML_GLU_OP_SWIGLU: - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SWIGLU].pipeline; - break; - case GGML_GLU_OP_SWIGLU_OAI: - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SWIGLU_OAI].pipeline; - break; - case GGML_GLU_OP_GEGLU_ERF: - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GEGLU_ERF].pipeline; - break; - case GGML_GLU_OP_GEGLU_QUICK: - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GEGLU_QUICK].pipeline; - break; - default: - GGML_ABORT("fatal error"); - } - - const int32_t swp = ggml_get_op_params_i32(dst, 1); - const float alpha = ggml_get_op_params_f32(dst, 2); - const float limit = ggml_get_op_params_f32(dst, 3); - - const int32_t i00 = swp ? ne0 : 0; - const int32_t i10 = swp ? 0 : ne0; - - ggml_metal_kargs_glu args = { - /*.ne00 =*/ ne00, - /*.nb01 =*/ nb01, - /*.ne10 =*/ src1 ? ne10 : ne00, - /*.nb11 =*/ src1 ? nb11 : nb01, - /*.ne0 =*/ ne0, - /*.nb1 =*/ nb1, - /*.i00 =*/ src1 ? 0 : i00, - /*.i10 =*/ src1 ? 0 : i10, - /*.alpha=*/ alpha, - /*.limit=*/ limit - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - if (src1) { - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:1]; - } else { - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - } - [encoder setBuffer:id_dst offset:offs_dst atIndex:2]; - [encoder setBytes:&args length:sizeof(args) atIndex:3]; - - const int64_t nrows = ggml_nrows(src0); - - const int32_t nth = MIN((int) pipeline.maxTotalThreadsPerThreadgroup, ne00/2); - - [encoder dispatchThreadgroups:MTLSizeMake(nrows, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } break; - case GGML_OP_SQR: - { - GGML_ASSERT(ggml_is_contiguous(src0)); - - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SQR].pipeline; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - - const int64_t n = ggml_nelements(dst); - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_OP_SQRT: - { - GGML_ASSERT(ggml_is_contiguous(src0)); - - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SQRT].pipeline; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - - const int64_t n = ggml_nelements(dst); - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_OP_SIN: - { - GGML_ASSERT(ggml_is_contiguous(src0)); - - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SIN].pipeline; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - - const int64_t n = ggml_nelements(dst); - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_OP_COS: - { - GGML_ASSERT(ggml_is_contiguous(src0)); - - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_COS].pipeline; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - - const int64_t n = ggml_nelements(dst); - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_OP_SUM_ROWS: - case GGML_OP_MEAN: - { - GGML_ASSERT(src0->nb[0] == ggml_type_size(src0->type)); - - id pipeline = nil; - - switch (dst->op) { - case GGML_OP_SUM_ROWS: - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SUM_ROWS].pipeline; - break; - case GGML_OP_MEAN: - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MEAN].pipeline; - break; - default: - GGML_ABORT("fatal error"); - } - - int nth = 32; // SIMD width - - while (nth < ne00 && nth < (int) pipeline.maxTotalThreadsPerThreadgroup) { - nth *= 2; - } - - nth = MIN(nth, (int) pipeline.maxTotalThreadsPerThreadgroup); - nth = MIN(nth, ne00); - - ggml_metal_kargs_sum_rows args = { - /*.ne00 =*/ ne00, - /*.ne01 =*/ ne01, - /*.ne02 =*/ ne02, - /*.ne03 =*/ ne03, - /*.nb00 =*/ nb00, - /*.nb01 =*/ nb01, - /*.nb02 =*/ nb02, - /*.nb03 =*/ nb03, - /*.ne10 =*/ ne10, - /*.ne11 =*/ ne11, - /*.ne12 =*/ ne12, - /*.ne13 =*/ ne13, - /*.nb10 =*/ nb10, - /*.nb11 =*/ nb11, - /*.nb12 =*/ nb12, - /*.nb13 =*/ nb13, - /*.ne0 =*/ ne0, - /*.ne1 =*/ ne1, - /*.ne2 =*/ ne2, - /*.ne3 =*/ ne3, - /*.nb0 =*/ nb0, - /*.nb1 =*/ nb1, - /*.nb2 =*/ nb2, - /*.nb3 =*/ nb3, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:2]; - [encoder setThreadgroupMemoryLength:32*sizeof(float) atIndex:0]; - - [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } break; - case GGML_OP_SOFT_MAX: - { - GGML_ASSERT(!src1 || src1->type == GGML_TYPE_F16 || src1->type == GGML_TYPE_F32); - - int nth = 32; // SIMD width - - id pipeline = nil; - - const bool use_f16 = (src1 && src1->type == GGML_TYPE_F16); - - if (ne00%4 == 0) { - while (nth < ne00/4 && nth*ne01*ne02*ne03 < 256) { - nth *= 2; - } - if (use_f16) { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SOFT_MAX_F16_4].pipeline; - } else { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SOFT_MAX_F32_4].pipeline; - } - } else { - while (nth < ne00 && nth*ne01*ne02*ne03 < 256) { - nth *= 2; - } - if (use_f16) { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SOFT_MAX_F16].pipeline; - } else { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SOFT_MAX_F32].pipeline; - } - } - - float scale; - float max_bias; - - memcpy(&scale, ((const int32_t *) dst->op_params) + 0, sizeof(scale)); - memcpy(&max_bias, ((const int32_t *) dst->op_params) + 1, sizeof(max_bias)); - - const uint32_t n_head = src0->ne[2]; - const uint32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head)); - - const float m0 = powf(2.0f, -(max_bias ) / n_head_log2); - const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2); - - id h_src0 = id_src0; - - // softmax - - ggml_metal_kargs_soft_max args = { - /*.ne00 =*/ ne00, - /*.ne01 =*/ ne01, - /*.ne02 =*/ ne02, - /*.nb01 =*/ nb01, - /*.nb02 =*/ nb02, - /*.nb03 =*/ nb03, - /*.ne11 =*/ ne11, - /*.ne12 =*/ ne12, - /*.ne13 =*/ ne13, - /*.nb11 =*/ nb11, - /*.nb12 =*/ nb12, - /*.nb13 =*/ nb13, - /*.nb1 =*/ nb1, - /*.nb2 =*/ nb2, - /*.nb3 =*/ nb3, - /*.scale =*/ scale, - /*.max_bias =*/ max_bias, - /*.m0 =*/ m0, - /*.m1 =*/ m1, - /*.n_head_log2 =*/ n_head_log2, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:h_src0 offset:offs_src0 atIndex:0]; - if (id_src1) { - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:1]; - } else { - [encoder setBuffer:h_src0 offset:offs_src0 atIndex:1]; - } - if (id_src2) { - [encoder setBuffer:id_src2 offset:offs_src2 atIndex:2]; - } else { - [encoder setBuffer:h_src0 offset:offs_src0 atIndex:2]; - } - [encoder setBuffer:id_dst offset:offs_dst atIndex:3]; - [encoder setBytes:&args length:sizeof(args) atIndex:4]; - - [encoder setThreadgroupMemoryLength:32*sizeof(float) atIndex:0]; - - [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } break; - case GGML_OP_DIAG_MASK_INF: - { - const int n_past = ((const int32_t *)(dst->op_params))[0]; - - id pipeline = nil; - - if (ne00%8 == 0) { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_DIAG_MASK_INF_8].pipeline; - } else { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_DIAG_MASK_INF].pipeline; - } - - ggml_metal_kargs_diag_mask_inf args = { - /*.ne00 =*/ ne00, - /*.ne01 =*/ ne01, - /*.n_past =*/ n_past, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - [encoder setBytes:&args length:sizeof(args) atIndex:2]; - - if (ne00%8 == 0) { - [encoder dispatchThreadgroups:MTLSizeMake(ne00*ne01*ne02/8, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } - else { - [encoder dispatchThreadgroups:MTLSizeMake(ne00, ne01, ne02) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } - } break; - case GGML_OP_SSM_CONV: - { - GGML_ASSERT(src0t == GGML_TYPE_F32); - GGML_ASSERT(src1t == GGML_TYPE_F32); - - GGML_ASSERT(ggml_is_contiguous(src0)); - GGML_ASSERT(ggml_is_contiguous(src1)); - - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SSM_CONV_F32].pipeline; - - ggml_metal_kargs_ssm_conv args = { - /*.ne00 =*/ ne00, - /*.ne01 =*/ ne01, - /*.ne02 =*/ ne02, - /*.nb00 =*/ nb00, - /*.nb01 =*/ nb01, - /*.nb02 =*/ nb02, - /*.ne10 =*/ ne10, - /*.ne11 =*/ ne11, - /*.nb10 =*/ nb10, - /*.nb11 =*/ nb11, - /*.ne0 =*/ ne0, - /*.ne1 =*/ ne1, - /*.ne2 =*/ ne2, - /*.nb0 =*/ nb0, - /*.nb1 =*/ nb1, - /*.nb2 =*/ nb2, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:1]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:2]; - [encoder setBytes:&args length:sizeof(args) atIndex:3]; - - [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne1, ne02) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_OP_SSM_SCAN: - { - struct ggml_tensor * src3 = node->src[3]; - struct ggml_tensor * src4 = node->src[4]; - struct ggml_tensor * src5 = node->src[5]; - struct ggml_tensor * src6 = node->src[6]; - - GGML_ASSERT(src3); - GGML_ASSERT(src4); - GGML_ASSERT(src5); - GGML_ASSERT(src6); - - size_t offs_src3 = 0; - size_t offs_src4 = 0; - size_t offs_src5 = 0; - size_t offs_src6 = 0; - - id id_src3 = src3 ? ggml_metal_get_buffer(src3, &offs_src3) : nil; - id id_src4 = src4 ? ggml_metal_get_buffer(src4, &offs_src4) : nil; - id id_src5 = src5 ? ggml_metal_get_buffer(src5, &offs_src5) : nil; - id id_src6 = src6 ? ggml_metal_get_buffer(src6, &offs_src6) : nil; - - const int64_t ne30 = src3->ne[0]; - const int64_t ne31 = src3->ne[1]; GGML_UNUSED(ne31); - - const uint64_t nb30 = src3->nb[0]; GGML_UNUSED(nb30); - const uint64_t nb31 = src3->nb[1]; - - const int64_t ne40 = src4->ne[0]; GGML_UNUSED(ne40); - const int64_t ne41 = src4->ne[1]; - const int64_t ne42 = src4->ne[2]; GGML_UNUSED(ne42); - const int64_t ne43 = src4->ne[3]; GGML_UNUSED(ne43); - - const uint64_t nb40 = src4->nb[0]; GGML_UNUSED(nb40); - const uint64_t nb41 = src4->nb[1]; - const uint64_t nb42 = src4->nb[2]; - const uint64_t nb43 = src4->nb[3]; - - const int64_t ne50 = src5->ne[0]; GGML_UNUSED(ne50); - const int64_t ne51 = src5->ne[1]; GGML_UNUSED(ne51); - const int64_t ne52 = src5->ne[2]; GGML_UNUSED(ne52); - const int64_t ne53 = src5->ne[3]; GGML_UNUSED(ne53); - - const uint64_t nb50 = src5->nb[0]; GGML_UNUSED(nb50); - const uint64_t nb51 = src5->nb[1]; - const uint64_t nb52 = src5->nb[2]; - const uint64_t nb53 = src5->nb[3]; - - const int64_t ne60 = src6->ne[0]; GGML_UNUSED(ne60); - - const uint64_t nb60 = src6->nb[0]; GGML_UNUSED(nb60); - - const int64_t d_state = ne00; - const int64_t d_inner = ne01; - const int64_t n_head = ne02; - const int64_t n_group = ne41; - const int64_t n_seq_tokens = ne12; - const int64_t n_seqs = ne13; - - id pipeline = nil; - - if (ne30 == 1) { - // Mamba-2 - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SSM_SCAN_F32_GROUP].pipeline; - } else { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SSM_SCAN_F32].pipeline; - } - - ggml_metal_kargs_ssm_scan args = { - /*.d_state =*/ d_state, - /*.d_inner =*/ d_inner, - /*.n_head =*/ n_head, - /*.n_group =*/ n_group, - /*.n_seq_tokens =*/ n_seq_tokens, - /*.n_seqs =*/ n_seqs, - /*.s_off =*/ ggml_nelements(src1) * sizeof(float), - /*.nb01 =*/ nb01, - /*.nb02 =*/ nb02, - /*.nb03 =*/ nb03, - /*.nb11 =*/ nb11, - /*.nb12 =*/ nb12, - /*.nb13 =*/ nb13, - /*.nb21 =*/ nb21, - /*.nb22 =*/ nb22, - /*.nb31 =*/ nb31, - /*.nb41 =*/ nb41, - /*.nb42 =*/ nb42, - /*.nb43 =*/ nb43, - /*.nb51 =*/ nb51, - /*.nb52 =*/ nb52, - /*.nb53 =*/ nb53, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:1]; - [encoder setBuffer:id_src2 offset:offs_src2 atIndex:2]; - [encoder setBuffer:id_src3 offset:offs_src3 atIndex:3]; - [encoder setBuffer:id_src4 offset:offs_src4 atIndex:4]; - [encoder setBuffer:id_src5 offset:offs_src5 atIndex:5]; - [encoder setBuffer:id_src6 offset:offs_src6 atIndex:6]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:7]; - [encoder setBytes:&args length:sizeof(args) atIndex:8]; - - // One shared memory bucket for each simd group in the threadgroup - // NOTE: Metal kernels require the buffer size to be multiple of 16 bytes - // https://developer.apple.com/documentation/metal/mtlcomputecommandencoder/1443142-setthreadgroupmemorylength - if (d_state >= 32) { - GGML_ASSERT((int64_t)(d_state / 32) <= 32); - const int64_t shmem_size = 32; - GGML_ASSERT(d_state <= (int64_t)pipeline.maxTotalThreadsPerThreadgroup); - [encoder setThreadgroupMemoryLength:(shmem_size)*sizeof(float) atIndex:0]; - } - - if (ne30 == 1) { - // Mamba-2 - [encoder dispatchThreadgroups:MTLSizeMake(d_inner, n_head, n_seqs) threadsPerThreadgroup:MTLSizeMake(d_state, 1, 1)]; - } else { - GGML_ASSERT(d_inner == 1); - [encoder dispatchThreadgroups:MTLSizeMake(n_head, n_seqs, 1) threadsPerThreadgroup:MTLSizeMake(d_state, 1, 1)]; - } - } break; - case GGML_OP_RWKV_WKV6: - { - const int64_t B = dst->src[5]->ne[1]; - const int64_t T = dst->src[0]->ne[2]; - const int64_t C = dst->ne[0]; - const int64_t H = dst->src[0]->ne[1]; - - GGML_ASSERT(dst->src[5]->type == GGML_TYPE_F32); - GGML_ASSERT(C % H == 0); - GGML_ASSERT(C / H == 64); - - size_t offs_src3 = 0; - size_t offs_src4 = 0; - size_t offs_src5 = 0; - - id id_src3 = dst->src[3] ? ggml_metal_get_buffer(dst->src[3], &offs_src3) : nil; - id id_src4 = dst->src[4] ? ggml_metal_get_buffer(dst->src[4], &offs_src4) : nil; - id id_src5 = dst->src[5] ? ggml_metal_get_buffer(dst->src[5], &offs_src5) : nil; - - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_RWKV_WKV6_F32].pipeline; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:1]; - [encoder setBuffer:id_src2 offset:offs_src2 atIndex:2]; - [encoder setBuffer:id_src3 offset:offs_src3 atIndex:3]; - [encoder setBuffer:id_src4 offset:offs_src4 atIndex:4]; - [encoder setBuffer:id_src5 offset:offs_src5 atIndex:5]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:6]; - - [encoder setBytes:&B length:sizeof(B) atIndex:7]; - [encoder setBytes:&T length:sizeof(T) atIndex:8]; - [encoder setBytes:&C length:sizeof(C) atIndex:9]; - [encoder setBytes:&H length:sizeof(H) atIndex:10]; - - [encoder dispatchThreadgroups:MTLSizeMake(B * H, 1, 1) threadsPerThreadgroup:MTLSizeMake(C/ H, 1, 1)]; - } break; - case GGML_OP_RWKV_WKV7: - { - const int64_t B = dst->src[6]->ne[1]; - const int64_t T = dst->src[0]->ne[2]; - const int64_t C = dst->ne[0]; - const int64_t H = dst->src[0]->ne[1]; - - GGML_ASSERT(dst->src[6]->type == GGML_TYPE_F32); - GGML_ASSERT(C % H == 0); - GGML_ASSERT(C / H == 64); - - size_t offs_src3 = 0; - size_t offs_src4 = 0; - size_t offs_src5 = 0; - size_t offs_src6 = 0; - - id id_src3 = dst->src[3] ? ggml_metal_get_buffer(dst->src[3], &offs_src3) : nil; - id id_src4 = dst->src[4] ? ggml_metal_get_buffer(dst->src[4], &offs_src4) : nil; - id id_src5 = dst->src[5] ? ggml_metal_get_buffer(dst->src[5], &offs_src5) : nil; - id id_src6 = dst->src[6] ? ggml_metal_get_buffer(dst->src[6], &offs_src6) : nil; - - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_RWKV_WKV7_F32].pipeline; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:1]; - [encoder setBuffer:id_src2 offset:offs_src2 atIndex:2]; - [encoder setBuffer:id_src3 offset:offs_src3 atIndex:3]; - [encoder setBuffer:id_src4 offset:offs_src4 atIndex:4]; - [encoder setBuffer:id_src5 offset:offs_src5 atIndex:5]; - [encoder setBuffer:id_src6 offset:offs_src6 atIndex:6]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:7]; - - [encoder setBytes:&B length:sizeof(B) atIndex:8]; - [encoder setBytes:&T length:sizeof(T) atIndex:9]; - [encoder setBytes:&C length:sizeof(C) atIndex:10]; - [encoder setBytes:&H length:sizeof(H) atIndex:11]; - - [encoder dispatchThreadgroups:MTLSizeMake(B * H, 1, 1) threadsPerThreadgroup:MTLSizeMake(C/ H, 1, 1)]; - } break; - case GGML_OP_MUL_MAT: - { - GGML_ASSERT(ne00 == ne10); - - GGML_ASSERT(ne12 % ne02 == 0); - GGML_ASSERT(ne13 % ne03 == 0); - - const uint32_t r2 = ne12/ne02; - const uint32_t r3 = ne13/ne03; - - // find the break-even point where the matrix-matrix kernel becomes more efficient compared - // to the matrix-vector kernel - const int ne11_mm_min = 8; - - // first try to use small-batch mat-mv kernels - // these should be efficient for BS [2, ~8] - if (src1t == GGML_TYPE_F32 && (ne00%128 == 0) && - ( - ( - ( - src0t == GGML_TYPE_F32 || // TODO: helper function - src0t == GGML_TYPE_F16 || - src0t == GGML_TYPE_Q4_0 || - src0t == GGML_TYPE_Q4_1 || - src0t == GGML_TYPE_Q5_0 || - src0t == GGML_TYPE_Q5_1 || - src0t == GGML_TYPE_Q8_0 || - src0t == GGML_TYPE_MXFP4 || - src0t == GGML_TYPE_IQ4_NL || - false) && (ne11 >= 2 && ne11 <= 8) - ) || - ( - ( - src0t == GGML_TYPE_Q4_K || - src0t == GGML_TYPE_Q5_K || - src0t == GGML_TYPE_Q6_K || - false) && (ne11 >= 4 && ne11 <= 8) - ) - ) - ) { - // TODO: determine the optimal parameters based on grid utilization - // I still don't know why we should not always use the maximum available threads: - // - // nsg = pipeline.maxTotalThreadsPerThreadgroup / 32 - // - // my current hypothesis is that the work grid is not evenly divisible for different nsg - // values and there can be some tail effects when nsg is high. need to confirm this - // - const int nsg = 2; // num simdgroups per threadgroup - - // num threads along row per simdgroup - int nxpsg = 0; - if (ne00 % 256 == 0 && ne11 < 3) { - nxpsg = 16; - } else if (ne00 % 128 == 0) { - nxpsg = 8; - } else { - nxpsg = 4; - } - - const int nypsg = 32/nxpsg; // num threads along col per simdgroup (i.e. a simdgroup processes that many src0 rows at a time) - const int r0ptg = nypsg*nsg; // num src0 rows per threadgroup - int r1ptg = 4; // num src1 rows per threadgroup - - // note: not sure how optimal are those across all different hardware. there might be someting cleverer - switch (ne11) { - case 2: - r1ptg = 2; break; - case 3: - case 6: - r1ptg = 3; break; - case 4: - case 7: - case 8: - r1ptg = 4; break; - case 5: - r1ptg = 5; break; - }; - - id pipeline = nil; - - switch (src0->type) { - case GGML_TYPE_F32: - switch (r1ptg) { - case 2: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F32_F32_R1_2].pipeline; break; - case 3: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F32_F32_R1_3].pipeline; break; - case 4: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F32_F32_R1_4].pipeline; break; - case 5: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F32_F32_R1_5].pipeline; break; - default: GGML_ABORT("not implemented"); - } break; - case GGML_TYPE_F16: - switch (r1ptg) { - case 2: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F16_F32_R1_2].pipeline; break; - case 3: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F16_F32_R1_3].pipeline; break; - case 4: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F16_F32_R1_4].pipeline; break; - case 5: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_F16_F32_R1_5].pipeline; break; - default: GGML_ABORT("not implemented"); - } break; - case GGML_TYPE_Q4_0: - switch (r1ptg) { - case 2: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_0_F32_R1_2].pipeline; break; - case 3: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_0_F32_R1_3].pipeline; break; - case 4: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_0_F32_R1_4].pipeline; break; - case 5: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_0_F32_R1_5].pipeline; break; - default: GGML_ABORT("not implemented"); - } break; - case GGML_TYPE_Q4_1: - switch (r1ptg) { - case 2: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_1_F32_R1_2].pipeline; break; - case 3: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_1_F32_R1_3].pipeline; break; - case 4: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_1_F32_R1_4].pipeline; break; - case 5: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_1_F32_R1_5].pipeline; break; - default: GGML_ABORT("not implemented"); - } break; - case GGML_TYPE_Q5_0: - switch (r1ptg) { - case 2: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_0_F32_R1_2].pipeline; break; - case 3: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_0_F32_R1_3].pipeline; break; - case 4: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_0_F32_R1_4].pipeline; break; - case 5: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_0_F32_R1_5].pipeline; break; - default: GGML_ABORT("not implemented"); - } break; - case GGML_TYPE_Q5_1: - switch (r1ptg) { - case 2: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_1_F32_R1_2].pipeline; break; - case 3: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_1_F32_R1_3].pipeline; break; - case 4: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_1_F32_R1_4].pipeline; break; - case 5: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_1_F32_R1_5].pipeline; break; - default: GGML_ABORT("not implemented"); - } break; - case GGML_TYPE_Q8_0: - switch (r1ptg) { - case 2: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q8_0_F32_R1_2].pipeline; break; - case 3: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q8_0_F32_R1_3].pipeline; break; - case 4: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q8_0_F32_R1_4].pipeline; break; - case 5: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q8_0_F32_R1_5].pipeline; break; - default: GGML_ABORT("not implemented"); - } break; - case GGML_TYPE_MXFP4: - switch (r1ptg) { - case 2: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_MXFP4_F32_R1_2].pipeline; break; - case 3: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_MXFP4_F32_R1_3].pipeline; break; - case 4: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_MXFP4_F32_R1_4].pipeline; break; - case 5: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_MXFP4_F32_R1_5].pipeline; break; - default: GGML_ABORT("not implemented"); - } break; - case GGML_TYPE_Q4_K: - switch (r1ptg) { - case 2: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_K_F32_R1_2].pipeline; break; - case 3: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_K_F32_R1_3].pipeline; break; - case 4: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_K_F32_R1_4].pipeline; break; - case 5: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q4_K_F32_R1_5].pipeline; break; - default: GGML_ABORT("not implemented"); - } break; - case GGML_TYPE_Q5_K: - switch (r1ptg) { - case 2: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_K_F32_R1_2].pipeline; break; - case 3: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_K_F32_R1_3].pipeline; break; - case 4: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_K_F32_R1_4].pipeline; break; - case 5: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q5_K_F32_R1_5].pipeline; break; - default: GGML_ABORT("not implemented"); - } break; - case GGML_TYPE_Q6_K: - switch (r1ptg) { - case 2: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q6_K_F32_R1_2].pipeline; break; - case 3: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q6_K_F32_R1_3].pipeline; break; - case 4: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q6_K_F32_R1_4].pipeline; break; - case 5: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_Q6_K_F32_R1_5].pipeline; break; - default: GGML_ABORT("not implemented"); - } break; - case GGML_TYPE_IQ4_NL: - switch (r1ptg) { - case 2: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_IQ4_NL_F32_R1_2].pipeline; break; - case 3: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_IQ4_NL_F32_R1_3].pipeline; break; - case 4: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_IQ4_NL_F32_R1_4].pipeline; break; - case 5: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_EXT_IQ4_NL_F32_R1_5].pipeline; break; - default: GGML_ABORT("not implemented"); - } break; - default: GGML_ABORT("not implemented"); - } - - ggml_metal_kargs_mul_mv_ext args = { - /*.ne00 =*/ ne00, - /*.ne01 =*/ ne01, - /*.ne02 =*/ ne02, - /*.nb00 =*/ nb00, - /*.nb01 =*/ nb01, - /*.nb02 =*/ nb02, - /*.nb03 =*/ nb03, - /*.ne10 =*/ ne10, - /*.ne11 =*/ ne11, - /*.ne12 =*/ ne12, - /*.nb10 =*/ nb10, - /*.nb11 =*/ nb11, - /*.nb12 =*/ nb12, - /*.nb13 =*/ nb13, - /*.ne0 =*/ ne0, - /*.ne1 =*/ ne1, - /*.r2 =*/ r2, - /*.r3 =*/ r3, - /*.nsg =*/ nsg, - /*.nxpsg =*/ nxpsg, - /*.r1ptg =*/ r1ptg, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:2]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:3]; - - //printf("ne01 = %lld nr0ptg = %d\n", ne01, nr0ptg); - [encoder dispatchThreadgroups:MTLSizeMake((ne01 + r0ptg - 1)/r0ptg, (ne11 + r1ptg - 1)/r1ptg, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(32, nsg, 1)]; - } else - // for now the matrix-matrix multiplication kernel only works on A14+/M1+ SoCs - // AMD GPU and older A-chips will reuse matrix-vector multiplication kernel - if ([device supportsFamily:MTLGPUFamilyApple7] && - !ggml_is_transposed(src0) && - !ggml_is_transposed(src1) && - src1t == GGML_TYPE_F32 && - ne00 % 32 == 0 && ne00 >= 64 && - (ne11 > ne11_mm_min || (ggml_is_quantized(src0t) && ne12 > 1))) { - //printf("matrix: ne00 = %6d, ne01 = %6d, ne02 = %6d, ne11 = %6d, ne12 = %6d\n", ne00, ne01, ne02, ne11, ne12); - - // some Metal matrix data types require aligned pointers - // ref: https://developer.apple.com/metal/Metal-Shading-Language-Specification.pdf (Table 2.5) - switch (src0->type) { - case GGML_TYPE_F32: GGML_ASSERT(nb01 % 16 == 0); break; - case GGML_TYPE_F16: GGML_ASSERT(nb01 % 8 == 0); break; - case GGML_TYPE_BF16: GGML_ASSERT(nb01 % 8 == 0); break; - default: break; - } - - id pipeline = nil; - - switch (src0->type) { - case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_F32_F32 ].pipeline; break; - case GGML_TYPE_F16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_F16_F32 ].pipeline; break; - case GGML_TYPE_BF16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_BF16_F32 ].pipeline; break; - case GGML_TYPE_Q4_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q4_0_F32 ].pipeline; break; - case GGML_TYPE_Q4_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q4_1_F32 ].pipeline; break; - case GGML_TYPE_Q5_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_0_F32 ].pipeline; break; - case GGML_TYPE_Q5_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_1_F32 ].pipeline; break; - case GGML_TYPE_Q8_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q8_0_F32 ].pipeline; break; - case GGML_TYPE_MXFP4: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_MXFP4_F32 ].pipeline; break; - case GGML_TYPE_Q2_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q2_K_F32 ].pipeline; break; - case GGML_TYPE_Q3_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q3_K_F32 ].pipeline; break; - case GGML_TYPE_Q4_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q4_K_F32 ].pipeline; break; - case GGML_TYPE_Q5_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_K_F32 ].pipeline; break; - case GGML_TYPE_Q6_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q6_K_F32 ].pipeline; break; - case GGML_TYPE_IQ2_XXS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ2_XXS_F32].pipeline; break; - case GGML_TYPE_IQ2_XS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ2_XS_F32 ].pipeline; break; - case GGML_TYPE_IQ3_XXS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ3_XXS_F32].pipeline; break; - case GGML_TYPE_IQ3_S: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ3_S_F32 ].pipeline; break; - case GGML_TYPE_IQ2_S: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ2_S_F32 ].pipeline; break; - case GGML_TYPE_IQ1_S: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ1_S_F32 ].pipeline; break; - case GGML_TYPE_IQ1_M: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ1_M_F32 ].pipeline; break; - case GGML_TYPE_IQ4_NL: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ4_NL_F32 ].pipeline; break; - case GGML_TYPE_IQ4_XS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ4_XS_F32 ].pipeline; break; - default: GGML_ABORT("MUL MAT-MAT not implemented"); - } - - ggml_metal_kargs_mul_mm args = { - /*.ne00 =*/ ne00, - /*.ne02 =*/ ne02, - /*.nb01 =*/ nb01, - /*.nb02 =*/ nb02, - /*.nb03 =*/ nb03, - /*.ne12 =*/ ne12, - /*.nb10 =*/ nb10, - /*.nb11 =*/ nb11, - /*.nb12 =*/ nb12, - /*.nb13 =*/ nb13, - /*.ne0 =*/ ne0, - /*.ne1 =*/ ne1, - /*.r2 =*/ r2, - /*.r3 =*/ r3, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:2]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:3]; - - [encoder setThreadgroupMemoryLength:8192 atIndex:0]; - [encoder dispatchThreadgroups:MTLSizeMake((ne11 + 31)/32, (ne01 + 63)/64, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(128, 1, 1)]; - } else { - id pipeline = nil; - - int nsg = 0; // number of simdgroups - int nr0 = 0; // number of src0 rows per simdgroup - int nr1 = 1; // number of src1 rows per threadgroup - - size_t smem = 0; // shared memory - - // use custom matrix x vector kernel - switch (src0t) { - case GGML_TYPE_F32: - { - GGML_ASSERT(src1t == GGML_TYPE_F32); - nsg = 1; - nr0 = 1; - nr1 = 4; - if (ne00 == 4) { - nr0 = 32; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_F32_F32_C4].pipeline; - } else { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_F32_F32].pipeline; - } - } break; - case GGML_TYPE_F16: - { - nsg = 1; - nr0 = 1; - if (src1t == GGML_TYPE_F32) { - if (ne00 == 4) { - nr0 = 32; - nr1 = 4; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32_C4].pipeline; - } else if (ne11 * ne12 < 4) { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32_1ROW].pipeline; - } else if (ne00 >= 128 && ne01 >= 8 && ne00%4 == 0) { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32_L4].pipeline; - nr1 = ne11; - } else { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32].pipeline; - nr1 = 4; - } - } else { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F16].pipeline; - nr1 = 4; - } - } break; - case GGML_TYPE_BF16: - { - nsg = 1; - nr0 = 1; - if (src1t == GGML_TYPE_F32) { - if (ne00 == 4) { - nr0 = 32; - nr1 = 4; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_F32_C4].pipeline; - } else if (ne11 * ne12 < 4) { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_F32_1ROW].pipeline; - } else if (ne00 >= 128 && ne01 >= 8 && ne00%4 == 0) { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_F32_L4].pipeline; - nr1 = ne11; - } else { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_F32].pipeline; - nr1 = 4; - } - } else { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_BF16].pipeline; - nr1 = 4; - } - } break; - case GGML_TYPE_Q4_0: - { - nsg = N_SG_Q4_0; - nr0 = N_R0_Q4_0; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q4_0_F32].pipeline; - } break; - case GGML_TYPE_Q4_1: - { - nsg = N_SG_Q4_1; - nr0 = N_R0_Q4_1; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q4_1_F32].pipeline; - } break; - case GGML_TYPE_Q5_0: - { - nsg = N_SG_Q5_0; - nr0 = N_R0_Q5_0; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_0_F32].pipeline; - } break; - case GGML_TYPE_Q5_1: - { - nsg = N_SG_Q5_1; - nr0 = N_R0_Q5_1; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_1_F32].pipeline; - } break; - case GGML_TYPE_Q8_0: - { - nsg = N_SG_Q8_0; - nr0 = N_R0_Q8_0; - smem = 32*sizeof(float)*N_R0_Q8_0; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q8_0_F32].pipeline; - } break; - case GGML_TYPE_MXFP4: - { - nsg = N_SG_MXFP4; - nr0 = N_R0_MXFP4; - smem = 32*sizeof(float); - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_MXFP4_F32].pipeline; - } break; - case GGML_TYPE_Q2_K: - { - nsg = N_SG_Q2_K; - nr0 = N_R0_Q2_K; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q2_K_F32].pipeline; - } break; - case GGML_TYPE_Q3_K: - { - nsg = N_SG_Q3_K; - nr0 = N_R0_Q3_K; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q3_K_F32].pipeline; - } break; - case GGML_TYPE_Q4_K: - { - nsg = N_SG_Q4_K; - nr0 = N_R0_Q4_K; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q4_K_F32].pipeline; - } break; - case GGML_TYPE_Q5_K: - { - nsg = N_SG_Q5_K; - nr0 = N_R0_Q5_K; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_K_F32].pipeline; - } break; - case GGML_TYPE_Q6_K: - { - nsg = N_SG_Q6_K; - nr0 = N_R0_Q6_K; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q6_K_F32].pipeline; - } break; - case GGML_TYPE_IQ2_XXS: - { - nsg = N_SG_IQ2_XXS; - nr0 = N_R0_IQ2_XXS; - smem = 256*8+128; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ2_XXS_F32].pipeline; - } break; - case GGML_TYPE_IQ2_XS: - { - nsg = N_SG_IQ2_XS; - nr0 = N_R0_IQ2_XS; - smem = 512*8+128; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ2_XS_F32].pipeline; - } break; - case GGML_TYPE_IQ3_XXS: - { - nsg = N_SG_IQ3_XXS; - nr0 = N_R0_IQ3_XXS; - smem = 256*4+128; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ3_XXS_F32].pipeline; - } break; - case GGML_TYPE_IQ3_S: - { - nsg = N_SG_IQ3_S; - nr0 = N_R0_IQ3_S; - smem = 512*4; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ3_S_F32].pipeline; - } break; - case GGML_TYPE_IQ2_S: - { - nsg = N_SG_IQ2_S; - nr0 = N_R0_IQ2_S; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ2_S_F32].pipeline; - } break; - case GGML_TYPE_IQ1_S: - { - nsg = N_SG_IQ1_S; - nr0 = N_R0_IQ1_S; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ1_S_F32].pipeline; - } break; - case GGML_TYPE_IQ1_M: - { - nsg = N_SG_IQ1_M; - nr0 = N_R0_IQ1_M; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ1_M_F32].pipeline; - } break; - case GGML_TYPE_IQ4_NL: - { - nsg = N_SG_IQ4_NL; - nr0 = N_R0_IQ4_NL; - smem = 32*sizeof(float); - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ4_NL_F32].pipeline; - } break; - case GGML_TYPE_IQ4_XS: - { - nsg = N_SG_IQ4_XS; - nr0 = N_R0_IQ4_XS; - smem = 32*sizeof(float); - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ4_XS_F32].pipeline; - } break; - default: - { - GGML_LOG_ERROR("Asserting on type %d\n", (int)src0t); - GGML_ABORT("not implemented"); - } - }; - - ggml_metal_kargs_mul_mv args = { - /*.ne00 =*/ ne00, - /*.ne01 =*/ ne01, - /*.ne02 =*/ ne02, - /*.nb00 =*/ nb00, - /*.nb01 =*/ nb01, - /*.nb02 =*/ nb02, - /*.nb03 =*/ nb03, - /*.ne10 =*/ ne10, - /*.ne11 =*/ ne11, - /*.ne12 =*/ ne12, - /*.nb10 =*/ nb10, - /*.nb11 =*/ nb11, - /*.nb12 =*/ nb12, - /*.nb13 =*/ nb13, - /*.ne0 =*/ ne0, - /*.ne1 =*/ ne1, - /*.r2 =*/ r2, - /*.r3 =*/ r3, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:2]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:3]; - - if (smem > 0) { - [encoder setThreadgroupMemoryLength:smem atIndex:0]; - } - - if (src0t == GGML_TYPE_Q8_0) { - [encoder dispatchThreadgroups:MTLSizeMake((ne01 + nr0 - 1)/(nr0), (ne11 + nr1 - 1)/nr1, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(32, nsg, 1)]; - } else { - [encoder dispatchThreadgroups:MTLSizeMake((ne01 + nr0*nsg - 1)/(nr0*nsg), (ne11 + nr1 - 1)/nr1, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(32, nsg, 1)]; - } - } - } break; - case GGML_OP_MUL_MAT_ID: - { - // src2 = ids - GGML_ASSERT(src2t == GGML_TYPE_I32); - - GGML_ASSERT(!ggml_is_transposed(src0)); - GGML_ASSERT(!ggml_is_transposed(src1)); - - GGML_ASSERT(src1t == GGML_TYPE_F32); - - GGML_ASSERT(ne03 == 1); - GGML_ASSERT(ne13 == 1); - - const uint32_t r2 = 1; - const uint32_t r3 = 1; - - // find the break-even point where the matrix-matrix kernel becomes more efficient compared - // to the matrix-vector kernel - // ne20 = n_used_experts - // ne21 = n_rows (batch size) - const int ne21_mm_id_min = 32; - - // for now the matrix-matrix multiplication kernel only works on A14+/M1+ SoCs - // AMD GPU and older A-chips will reuse matrix-vector multiplication kernel - if ([device supportsFamily:MTLGPUFamilyApple7] && - ne00 % 32 == 0 && ne00 >= 64 && - (ne21 >= ne21_mm_id_min)) { - GGML_ASSERT(ne00 % 4 == 0); - - // some Metal matrix data types require aligned pointers - // ref: https://developer.apple.com/metal/Metal-Shading-Language-Specification.pdf (Table 2.5) - switch (src0->type) { - case GGML_TYPE_F32: GGML_ASSERT(nb01 % 16 == 0); break; - case GGML_TYPE_F16: GGML_ASSERT(nb01 % 8 == 0); break; - case GGML_TYPE_BF16: GGML_ASSERT(nb01 % 8 == 0); break; - default: break; - } - - // extra buffers for intermediate id mapping - size_t offs_tpe = offs_dst + ggml_nbytes(dst); - size_t offs_ids = offs_tpe + ggml_metal_mul_mat_id_extra_tpe(dst); - - { - ggml_metal_kargs_mul_mm_id_map0 args = { - ne02, - ne10, - ne11, // n_expert_used (bcast) - nb11, - nb12, - ne21, // n_tokens - ne20, // n_expert_used - nb21, - }; - - id pipeline = nil; - - pipeline = nil; - - switch (ne20) { - case 1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_1 ].pipeline; break; - case 2: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_2 ].pipeline; break; - case 4: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_4 ].pipeline; break; - case 6: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_6 ].pipeline; break; - case 8: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_8 ].pipeline; break; - case 10: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_10].pipeline; break; - case 16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MAP0_F16_NE20_16].pipeline; break; - default: GGML_ABORT("missing specialization for ne20 = %d", (int) ne20); - } - - GGML_ASSERT(ne02 <= (int) pipeline.maxTotalThreadsPerThreadgroup); - - const size_t smem = ne02*ne20*sizeof(uint16_t); - - GGML_ASSERT(smem <= device.maxThreadgroupMemoryLength); - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src2 offset:offs_src2 atIndex:1]; - [encoder setBuffer:id_dst offset:offs_tpe atIndex:2]; - [encoder setBuffer:id_dst offset:offs_ids atIndex:3]; - [encoder setThreadgroupMemoryLength:smem atIndex:0]; - - [encoder dispatchThreadgroups:MTLSizeMake(1, 1, 1) threadsPerThreadgroup:MTLSizeMake(ne02, 1, 1)]; - } - - // this barrier is always needed because the next kernel has to wait for the id maps to be computed - ggml_metal_encode_concurrency_reset(ctx_enc); - - { - id pipeline = nil; - - switch (src0->type) { - case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_F32_F16 ].pipeline; break; - case GGML_TYPE_F16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_F16_F16 ].pipeline; break; - case GGML_TYPE_BF16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_BF16_F16 ].pipeline; break; - case GGML_TYPE_Q4_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q4_0_F16 ].pipeline; break; - case GGML_TYPE_Q4_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q4_1_F16 ].pipeline; break; - case GGML_TYPE_Q5_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q5_0_F16 ].pipeline; break; - case GGML_TYPE_Q5_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q5_1_F16 ].pipeline; break; - case GGML_TYPE_Q8_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q8_0_F16 ].pipeline; break; - case GGML_TYPE_MXFP4: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_MXFP4_F16 ].pipeline; break; - case GGML_TYPE_Q2_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q2_K_F16 ].pipeline; break; - case GGML_TYPE_Q3_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q3_K_F16 ].pipeline; break; - case GGML_TYPE_Q4_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q4_K_F16 ].pipeline; break; - case GGML_TYPE_Q5_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q5_K_F16 ].pipeline; break; - case GGML_TYPE_Q6_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q6_K_F16 ].pipeline; break; - case GGML_TYPE_IQ2_XXS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ2_XXS_F16].pipeline; break; - case GGML_TYPE_IQ2_XS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ2_XS_F16 ].pipeline; break; - case GGML_TYPE_IQ3_XXS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ3_XXS_F16].pipeline; break; - case GGML_TYPE_IQ3_S: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ3_S_F16 ].pipeline; break; - case GGML_TYPE_IQ2_S: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ2_S_F16 ].pipeline; break; - case GGML_TYPE_IQ1_S: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ1_S_F16 ].pipeline; break; - case GGML_TYPE_IQ1_M: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ1_M_F16 ].pipeline; break; - case GGML_TYPE_IQ4_NL: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ4_NL_F16 ].pipeline; break; - case GGML_TYPE_IQ4_XS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ4_XS_F16 ].pipeline; break; - default: GGML_ABORT("MUL_MAT_ID not implemented"); - } - - ggml_metal_kargs_mul_mm_id args = { - /*.ne00 =*/ ne00, - /*.ne02 =*/ ne02, - /*.nb01 =*/ nb01, - /*.nb02 =*/ nb02, - /*.nb03 =*/ nb03, - /*.ne11 =*/ ne11, // n_expert_used (bcast) - /*.nb10 =*/ nb10, - /*.nb11 =*/ nb11, - /*.nb12 =*/ nb12, - /*.nb13 =*/ nb13, - /*.ne20 =*/ ne20, // n_expert_used - /*.ne21 =*/ ne21, // n_tokens - /*.ne0 =*/ ne0, - /*.ne1 =*/ ne1, - /*.r2 =*/ r2, - /*.r3 =*/ r3, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:2]; - [encoder setBuffer:id_dst offset:offs_tpe atIndex:3]; - [encoder setBuffer:id_dst offset:offs_ids atIndex:4]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:5]; - - [encoder setThreadgroupMemoryLength:8192 atIndex:0]; - [encoder dispatchThreadgroups:MTLSizeMake((ne21 + 31)/32, (ne01 + 63)/64, ne02) threadsPerThreadgroup:MTLSizeMake(128, 1, 1)]; - } - } else { - id pipeline = nil; - - int nsg = 0; // number of simdgroups - int nr0 = 0; // number of src0 rows per simdgroup - int nr1 = 1; // number of src1 rows per threadgroup - - size_t smem = 0; // shared memory - - // use custom matrix x vector kernel - switch (src0t) { - case GGML_TYPE_F32: - { - GGML_ASSERT(src1t == GGML_TYPE_F32); - nsg = 1; - nr0 = 1; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_F32_F32].pipeline; - } break; - case GGML_TYPE_F16: - { - GGML_ASSERT(src1t == GGML_TYPE_F32); - nsg = 1; - nr0 = 1; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_F16_F32].pipeline; - } break; - case GGML_TYPE_BF16: - { - GGML_ASSERT(src1t == GGML_TYPE_F32); - nsg = 1; - nr0 = 1; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_BF16_F32].pipeline; - } break; - case GGML_TYPE_Q4_0: - { - nsg = N_SG_Q4_0; - nr0 = N_R0_Q4_0; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q4_0_F32].pipeline; - } break; - case GGML_TYPE_Q4_1: - { - nsg = N_SG_Q4_1; - nr0 = N_R0_Q4_1; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q4_1_F32].pipeline; - } break; - case GGML_TYPE_Q5_0: - { - nsg = N_SG_Q5_0; - nr0 = N_R0_Q5_0; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q5_0_F32].pipeline; - } break; - case GGML_TYPE_Q5_1: - { - nsg = N_SG_Q5_1; - nr0 = N_R0_Q5_1; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q5_1_F32].pipeline; - } break; - case GGML_TYPE_Q8_0: - { - nsg = N_SG_Q8_0; - nr0 = N_R0_Q8_0; - smem = 32*sizeof(float)*N_R0_Q8_0; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q8_0_F32].pipeline; - } break; - case GGML_TYPE_MXFP4: - { - nsg = N_SG_MXFP4; - nr0 = N_R0_MXFP4; - smem = 32*sizeof(float); - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_MXFP4_F32].pipeline; - } break; - case GGML_TYPE_Q2_K: - { - nsg = N_SG_Q2_K; - nr0 = N_R0_Q2_K; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q2_K_F32].pipeline; - } break; - case GGML_TYPE_Q3_K: - { - nsg = N_SG_Q3_K; - nr0 = N_R0_Q3_K; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q3_K_F32].pipeline; - } break; - case GGML_TYPE_Q4_K: - { - nsg = N_SG_Q4_K; - nr0 = N_R0_Q4_K; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q4_K_F32].pipeline; - } break; - case GGML_TYPE_Q5_K: - { - nsg = N_SG_Q5_K; - nr0 = N_R0_Q5_K; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q5_K_F32].pipeline; - } break; - case GGML_TYPE_Q6_K: - { - nsg = N_SG_Q6_K; - nr0 = N_R0_Q6_K; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q6_K_F32].pipeline; - } break; - case GGML_TYPE_IQ2_XXS: - { - nsg = N_SG_IQ2_XXS; - nr0 = N_R0_IQ2_XXS; - smem = 256*8+128; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ2_XXS_F32].pipeline; - } break; - case GGML_TYPE_IQ2_XS: - { - nsg = N_SG_IQ2_XS; - nr0 = N_R0_IQ2_XS; - smem = 512*8+128; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ2_XS_F32].pipeline; - } break; - case GGML_TYPE_IQ3_XXS: - { - nsg = N_SG_IQ3_XXS; - nr0 = N_R0_IQ3_XXS; - smem = 256*4+128; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ3_XXS_F32].pipeline; - } break; - case GGML_TYPE_IQ3_S: - { - nsg = N_SG_IQ3_S; - nr0 = N_R0_IQ3_S; - smem = 512*4; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ3_S_F32].pipeline; - } break; - case GGML_TYPE_IQ2_S: - { - nsg = N_SG_IQ2_S; - nr0 = N_R0_IQ2_S; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ2_S_F32].pipeline; - } break; - case GGML_TYPE_IQ1_S: - { - nsg = N_SG_IQ1_S; - nr0 = N_R0_IQ1_S; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ1_S_F32].pipeline; - } break; - case GGML_TYPE_IQ1_M: - { - nsg = N_SG_IQ1_M; - nr0 = N_R0_IQ1_M; - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ1_M_F32].pipeline; - } break; - case GGML_TYPE_IQ4_NL: - { - nsg = N_SG_IQ4_NL; - nr0 = N_R0_IQ4_NL; - smem = 32*sizeof(float); - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ4_NL_F32].pipeline; - } break; - case GGML_TYPE_IQ4_XS: - { - nsg = N_SG_IQ4_XS; - nr0 = N_R0_IQ4_XS; - smem = 32*sizeof(float); - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ4_XS_F32].pipeline; - } break; - default: - { - GGML_LOG_ERROR("Asserting on type %d\n", (int)src2t); - GGML_ABORT("not implemented"); - } - }; - - if (ggml_is_quantized(src0t)) { - GGML_ASSERT(ne00 >= nsg*nr0); - } - - ggml_metal_kargs_mul_mv_id args = { - /*.nei0 =*/ ne20, - /*.nei1 =*/ ne21, - /*.nbi1 =*/ nb21, - /*.ne00 =*/ ne00, - /*.ne01 =*/ ne01, - /*.ne02 =*/ ne02, - /*.nb00 =*/ nb00, - /*.nb01 =*/ nb01, - /*.nb02 =*/ nb02, - /*.ne10 =*/ ne10, - /*.ne11 =*/ ne11, - /*.ne12 =*/ ne12, - /*.ne13 =*/ ne13, - /*.nb10 =*/ nb10, - /*.nb11 =*/ nb11, - /*.nb12 =*/ nb12, - /*.ne0 =*/ ne0, - /*.ne1 =*/ ne1, - /*.nb1 =*/ nb1, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:2]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:3]; - [encoder setBuffer:id_src2 offset:offs_src2 atIndex:4]; - - const int64_t _ne1 = 1; - const int64_t ne123 = ne20*ne21; - - if (smem > 0) { - [encoder setThreadgroupMemoryLength:smem atIndex:0]; - } - - if (src0t == GGML_TYPE_Q8_0) { - [encoder dispatchThreadgroups:MTLSizeMake((ne01 + nr0 - 1)/(nr0), (_ne1 + nr1 - 1)/nr1, ne123) threadsPerThreadgroup:MTLSizeMake(32, nsg, 1)]; - } else { - [encoder dispatchThreadgroups:MTLSizeMake((ne01 + nr0*nsg - 1)/(nr0*nsg), (_ne1 + nr1 - 1)/nr1, ne123) threadsPerThreadgroup:MTLSizeMake(32, nsg, 1)]; - } - } - } break; - case GGML_OP_GET_ROWS: - { - id pipeline = nil; - - switch (src0->type) { - case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_F32 ].pipeline; break; - case GGML_TYPE_F16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_F16 ].pipeline; break; - case GGML_TYPE_BF16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_BF16 ].pipeline; break; - case GGML_TYPE_Q4_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_Q4_0 ].pipeline; break; - case GGML_TYPE_Q4_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_Q4_1 ].pipeline; break; - case GGML_TYPE_Q5_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_Q5_0 ].pipeline; break; - case GGML_TYPE_Q5_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_Q5_1 ].pipeline; break; - case GGML_TYPE_Q8_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_Q8_0 ].pipeline; break; - case GGML_TYPE_MXFP4: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_MXFP4 ].pipeline; break; - case GGML_TYPE_Q2_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_Q2_K ].pipeline; break; - case GGML_TYPE_Q3_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_Q3_K ].pipeline; break; - case GGML_TYPE_Q4_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_Q4_K ].pipeline; break; - case GGML_TYPE_Q5_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_Q5_K ].pipeline; break; - case GGML_TYPE_Q6_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_Q6_K ].pipeline; break; - case GGML_TYPE_IQ2_XXS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ2_XXS].pipeline; break; - case GGML_TYPE_IQ2_XS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ2_XS ].pipeline; break; - case GGML_TYPE_IQ3_XXS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ3_XXS].pipeline; break; - case GGML_TYPE_IQ3_S: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ3_S ].pipeline; break; - case GGML_TYPE_IQ2_S: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ2_S ].pipeline; break; - case GGML_TYPE_IQ1_S: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ1_S ].pipeline; break; - case GGML_TYPE_IQ1_M: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ1_M ].pipeline; break; - case GGML_TYPE_IQ4_NL: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ4_NL ].pipeline; break; - case GGML_TYPE_IQ4_XS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_IQ4_XS ].pipeline; break; - case GGML_TYPE_I32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_I32 ].pipeline; break; - default: GGML_ABORT("not implemented"); - } - - ggml_metal_kargs_get_rows args = { - /*.ne00 =*/ ne00, - /*.nb01 =*/ nb01, - /*.nb02 =*/ nb02, - /*.ne10 =*/ ne10, - /*.nb10 =*/ nb10, - /*.nb11 =*/ nb11, - /*.nb1 =*/ nb1, - /*.nb2 =*/ nb2, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:2]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:3]; - - [encoder dispatchThreadgroups:MTLSizeMake(ne10, ne11, 1) threadsPerThreadgroup:MTLSizeMake(32, 1, 1)]; - } break; - case GGML_OP_SET_ROWS: - { - id pipeline = nil; - - switch (dst->type) { - case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SET_ROWS_F32 ].pipeline; break; - case GGML_TYPE_F16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SET_ROWS_F16 ].pipeline; break; - case GGML_TYPE_BF16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SET_ROWS_BF16 ].pipeline; break; - case GGML_TYPE_Q8_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SET_ROWS_Q8_0 ].pipeline; break; - case GGML_TYPE_Q4_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SET_ROWS_Q4_0 ].pipeline; break; - case GGML_TYPE_Q4_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SET_ROWS_Q4_1 ].pipeline; break; - case GGML_TYPE_Q5_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SET_ROWS_Q5_0 ].pipeline; break; - case GGML_TYPE_Q5_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SET_ROWS_Q5_1 ].pipeline; break; - case GGML_TYPE_IQ4_NL: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SET_ROWS_IQ4_NL].pipeline; break; - default: GGML_ABORT("not implemented"); - } - - const int32_t nk0 = ne0/ggml_blck_size(dst->type); - - int nth = 32; // SIMD width - - while (nth < nk0 && nth < (int) pipeline.maxTotalThreadsPerThreadgroup) { - nth *= 2; - } - - int nrptg = 1; - if (nth > nk0) { - nrptg = (nth + nk0 - 1)/nk0; - nth = nk0; - - if (nrptg*nth > (int) pipeline.maxTotalThreadsPerThreadgroup) { - nrptg--; - } - } - - nth = MIN(nth, nk0); - - ggml_metal_kargs_set_rows args = { - /*.nk0 =*/ nk0, - /*.ne01 =*/ ne01, - /*.nb01 =*/ nb01, - /*.nb02 =*/ nb02, - /*.nb03 =*/ nb03, - /*.ne11 =*/ ne11, - /*.ne12 =*/ ne12, - /*.nb10 =*/ nb10, - /*.nb11 =*/ nb11, - /*.nb12 =*/ nb12, - /*.nb1 =*/ nb1, - /*.nb2 =*/ nb2, - /*.nb3 =*/ nb3, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:2]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:3]; - - [encoder dispatchThreadgroups:MTLSizeMake((ne01 + nrptg - 1)/nrptg, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(nth, nrptg, 1)]; - } break; - case GGML_OP_RMS_NORM: - { - GGML_ASSERT(ne00 % 4 == 0); - GGML_ASSERT(ggml_is_contiguous_rows(src0)); - - float eps; - memcpy(&eps, dst->op_params, sizeof(float)); - - ggml_metal_kargs_rms_norm args = { - /*.ne00 =*/ ne00, - /*.ne00_4 =*/ ne00/4, - /*.nb1 =*/ nb1, - /*.nb2 =*/ nb2, - /*.nb3 =*/ nb3, - /*.eps =*/ eps, - /*.nef1 =*/ { ne01 }, - /*.nef2 =*/ { ne02 }, - /*.nef3 =*/ { ne03 }, - /*.nbf1 =*/ { nb01 }, - /*.nbf2 =*/ { nb02 }, - /*.nbf3 =*/ { nb03 }, - }; - - size_t offs_fuse[2] = { 0, 0 }; - id id_fuse[2] = { id_src0, id_src0 }; - - // d[0] = rms_norm(a) - // d[1] = mul(d[0], b) - // d[2] = add(d[1], c) - if (ctx_dev->use_fusion) { - ops[0] = GGML_OP_RMS_NORM; - ops[1] = GGML_OP_MUL; - ops[2] = GGML_OP_ADD; - - for (n_fuse = 0; n_fuse <= 1 && idx + n_fuse + 1 < idx_end; ++n_fuse) { - if (!ggml_can_fuse(gf, idx + n_fuse, ops + n_fuse, 2)) { - break; - } - - if (nodes[n_fuse] != nodes[n_fuse + 1]->src[0]) { - break; - } - - if (nodes[n_fuse + 1]->src[1]->ne[0] != node->ne[0]) { - break; - } - - if (!ggml_is_contiguous_rows(nodes[n_fuse + 1]->src[1])) { - break; - } - - if (nodes[n_fuse + 1]->type != GGML_TYPE_F32) { - break; - } - - ctx_dev->fuse_cnt[nodes[n_fuse + 1]->op]++; - - id_fuse[n_fuse] = ggml_metal_get_buffer(nodes[n_fuse + 1]->src[1], &offs_fuse[n_fuse]); - - args.nef1[n_fuse + 1] = nodes[n_fuse + 1]->src[1]->ne[1]; - args.nef2[n_fuse + 1] = nodes[n_fuse + 1]->src[1]->ne[2]; - args.nef3[n_fuse + 1] = nodes[n_fuse + 1]->src[1]->ne[3]; - - args.nbf1[n_fuse + 1] = nodes[n_fuse + 1]->src[1]->nb[1]; - args.nbf2[n_fuse + 1] = nodes[n_fuse + 1]->src[1]->nb[2]; - args.nbf3[n_fuse + 1] = nodes[n_fuse + 1]->src[1]->nb[3]; - } - - ++n_fuse; - - if (ctx_dev->debug_fusion > 1 && n_fuse > 1) { - if (n_fuse == 2) { - GGML_LOG_DEBUG("%s: fuse: RMS_NORM + MUL\n", __func__); - } - if (n_fuse == 3) { - GGML_LOG_DEBUG("%s: fuse: RMS_NORM + MUL + ADD\n", __func__); - } - } - } - - if (n_fuse > 1) { - id_dst = ggml_metal_get_buffer(nodes[n_fuse - 1], &offs_dst); - - for (int i = 1; i < n_fuse; ++i) { - if (!ggml_metal_encode_concurrency_check(ctx_enc, nodes[i])) { - ggml_metal_encode_concurrency_reset(ctx_enc); - - break; - } - } - } - - const id pipeline = ggml_metal_get_pipeline_rms_norm(backend, node, n_fuse); - - int nth = 32; // SIMD width - - while (nth < ne00/4 && nth < (int) pipeline.maxTotalThreadsPerThreadgroup) { - nth *= 2; - } - - nth = MIN(nth, (int) pipeline.maxTotalThreadsPerThreadgroup); - nth = MIN(nth, ne00/4); - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_fuse[0] offset:offs_fuse[0] atIndex:2]; - [encoder setBuffer:id_fuse[1] offset:offs_fuse[1] atIndex:3]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:4]; - - [encoder setThreadgroupMemoryLength:32*sizeof(float) atIndex:0]; - - [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } break; - case GGML_OP_L2_NORM: - { - GGML_ASSERT(ne00 % 4 == 0); - GGML_ASSERT(ggml_is_contiguous_1(src0)); - - float eps; - memcpy(&eps, dst->op_params, sizeof(float)); - - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_L2_NORM].pipeline; - - int nth = 32; // SIMD width - - while (nth < ne00/4 && nth < (int) pipeline.maxTotalThreadsPerThreadgroup) { - nth *= 2; - } - - nth = MIN(nth, (int) pipeline.maxTotalThreadsPerThreadgroup); - nth = MIN(nth, ne00/4); - - ggml_metal_kargs_l2_norm args = { - /*.ne00 =*/ ne00, - /*.ne00_4 =*/ ne00/4, - /*.nb01 =*/ nb01, - /*.eps =*/ eps, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:2]; - - [encoder setThreadgroupMemoryLength:32*sizeof(float) atIndex:0]; - - const int64_t nrows = ggml_nrows(src0); - - [encoder dispatchThreadgroups:MTLSizeMake(nrows, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } break; - case GGML_OP_GROUP_NORM: - { - GGML_ASSERT(ggml_is_contiguous(src0)); - - float eps; - memcpy(&eps, dst->op_params + 1, sizeof(float)); - - const int32_t n_groups = ((const int32_t *) dst->op_params)[0]; - - int nth = 32; // SIMD width - - //while (nth < ne00/4 && nth < 1024) { - // nth *= 2; - //} - - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GROUP_NORM].pipeline; - - ggml_metal_kargs_group_norm args = { - /*.ne00 =*/ ne00, - /*.ne01 =*/ ne01, - /*.ne02 =*/ ne02, - /*.nb00 =*/ nb00, - /*.nb01 =*/ nb01, - /*.nb02 =*/ nb02, - /*.n_groups =*/ n_groups, - /*.eps =*/ eps, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - [encoder setBytes:&args length:sizeof(args) atIndex:2]; - [encoder setThreadgroupMemoryLength:32*sizeof(float) atIndex:0]; - - [encoder dispatchThreadgroups:MTLSizeMake(n_groups, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } break; - case GGML_OP_NORM: - { - GGML_ASSERT(ne00 % 4 == 0); - GGML_ASSERT(ggml_is_contiguous_1(src0)); - - float eps; - memcpy(&eps, dst->op_params, sizeof(float)); - - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_NORM].pipeline; - - int nth = 32; // SIMD width - - while (nth < ne00/4 && nth < (int) pipeline.maxTotalThreadsPerThreadgroup) { - nth *= 2; - } - - nth = MIN(nth, (int) pipeline.maxTotalThreadsPerThreadgroup); - nth = MIN(nth, ne00/4); - - ggml_metal_kargs_norm args = { - /*.ne00 =*/ ne00, - /*.ne00_4 =*/ ne00/4, - /*.nb01 =*/ nb01, - /*.eps =*/ eps, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:2]; - - [encoder setThreadgroupMemoryLength:32*sizeof(float) atIndex:0]; - - const int64_t nrows = ggml_nrows(src0); - - [encoder dispatchThreadgroups:MTLSizeMake(nrows, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } break; - case GGML_OP_ROPE: - { - // make sure we have one or more position id(ne10) per token(ne02) - GGML_ASSERT(ne10 % ne02 == 0); - GGML_ASSERT(ne10 >= ne02); - - const int nth = MIN(1024, ne00); - - const int n_past = ((const int32_t *) dst->op_params)[0]; - const int n_dims = ((const int32_t *) dst->op_params)[1]; - const int mode = ((const int32_t *) dst->op_params)[2]; - // skip 3, n_ctx, used in GLM RoPE, unimplemented in metal - const int n_ctx_orig = ((const int32_t *) dst->op_params)[4]; - - float freq_base; - float freq_scale; - float ext_factor; - float attn_factor; - float beta_fast; - float beta_slow; - - memcpy(&freq_base, (const int32_t *) dst->op_params + 5, sizeof(float)); - memcpy(&freq_scale, (const int32_t *) dst->op_params + 6, sizeof(float)); - memcpy(&ext_factor, (const int32_t *) dst->op_params + 7, sizeof(float)); - memcpy(&attn_factor, (const int32_t *) dst->op_params + 8, sizeof(float)); - memcpy(&beta_fast, (const int32_t *) dst->op_params + 9, sizeof(float)); - memcpy(&beta_slow, (const int32_t *) dst->op_params + 10, sizeof(float)); - - const bool is_neox = mode & GGML_ROPE_TYPE_NEOX; - const bool is_mrope = mode & GGML_ROPE_TYPE_MROPE; - const bool is_vision = mode == GGML_ROPE_TYPE_VISION; - - // mrope - const int sect_0 = ((const int32_t *) dst->op_params)[11]; - const int sect_1 = ((const int32_t *) dst->op_params)[12]; - const int sect_2 = ((const int32_t *) dst->op_params)[13]; - const int sect_3 = ((const int32_t *) dst->op_params)[14]; - - id pipeline = nil; - - if (is_neox) { - switch (src0->type) { - case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_ROPE_NEOX_F32].pipeline; break; - case GGML_TYPE_F16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_ROPE_NEOX_F16].pipeline; break; - default: GGML_ABORT("fatal error"); - }; - } else if (is_mrope && !is_vision) { - GGML_ASSERT(ne10*4 >= ne02); // need at least 4 pos per token - switch (src0->type) { - case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_ROPE_MULTI_F32].pipeline; break; - case GGML_TYPE_F16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_ROPE_MULTI_F16].pipeline; break; - default: GGML_ABORT("fatal error"); - }; - } else if (is_vision) { - GGML_ASSERT(ne10*4 >= ne02); // need at least 4 pos per token - switch (src0->type) { - case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_ROPE_VISION_F32].pipeline; break; - case GGML_TYPE_F16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_ROPE_VISION_F16].pipeline; break; - default: GGML_ABORT("fatal error"); - }; - } else { - switch (src0->type) { - case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_ROPE_NORM_F32].pipeline; break; - case GGML_TYPE_F16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_ROPE_NORM_F16].pipeline; break; - default: GGML_ABORT("fatal error"); - }; - } - - ggml_metal_kargs_rope 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, - /*.n_past =*/ n_past, - /*.n_dims =*/ n_dims, - /*.n_ctx_orig =*/ n_ctx_orig, - /*.freq_base =*/ freq_base, - /*.freq_scale =*/ freq_scale, - /*.ext_factor =*/ ext_factor, - /*.attn_factor =*/ attn_factor, - /*.beta_fast =*/ beta_fast, - /*.beta_slow =*/ beta_slow, - /* sect_0 =*/ sect_0, - /* sect_1 =*/ sect_1, - /* sect_2 =*/ sect_2, - /* sect_3 =*/ sect_3, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:2]; - if (id_src2 != nil) { - [encoder setBuffer:id_src2 offset:offs_src2 atIndex:3]; - } else { - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:3]; - } - [encoder setBuffer:id_dst offset:offs_dst atIndex:4]; - - [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } break; - case GGML_OP_IM2COL: - { - GGML_ASSERT(ggml_is_contiguous(src1)); - GGML_ASSERT(src1->type == GGML_TYPE_F32); - GGML_ASSERT( dst->type == GGML_TYPE_F16 || dst->type == GGML_TYPE_F32); - - const int32_t s0 = ((const int32_t *)(dst->op_params))[0]; - const int32_t s1 = ((const int32_t *)(dst->op_params))[1]; - const int32_t p0 = ((const int32_t *)(dst->op_params))[2]; - const int32_t p1 = ((const int32_t *)(dst->op_params))[3]; - const int32_t d0 = ((const int32_t *)(dst->op_params))[4]; - const int32_t d1 = ((const int32_t *)(dst->op_params))[5]; - - const bool is_2D = ((const int32_t *)(dst->op_params))[6] == 1; - - const int32_t N = src1->ne[is_2D ? 3 : 2]; - const int32_t IC = src1->ne[is_2D ? 2 : 1]; - const int32_t IH = is_2D ? src1->ne[1] : 1; - const int32_t IW = src1->ne[0]; - - const int32_t KH = is_2D ? src0->ne[1] : 1; - const int32_t KW = src0->ne[0]; - - const int32_t OH = is_2D ? dst->ne[2] : 1; - const int32_t OW = dst->ne[1]; - - const int32_t CHW = IC * KH * KW; - - const uint64_t ofs0 = src1->nb[is_2D ? 3 : 2] / 4; - const uint64_t ofs1 = src1->nb[is_2D ? 2 : 1] / 4; - - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_IM2COL_F32].pipeline; - - const bool is_gt_mttpt = ((size_t)(N * KH * KW)) > pipeline.maxTotalThreadsPerThreadgroup; - - switch (dst->type) { - case GGML_TYPE_F32: { - pipeline = (is_gt_mttpt ? - ctx->kernels[GGML_METAL_KERNEL_TYPE_IM2COL_EXT_F32].pipeline - : - ctx->kernels[GGML_METAL_KERNEL_TYPE_IM2COL_F32].pipeline); - } break; - case GGML_TYPE_F16: { - pipeline = (is_gt_mttpt ? - ctx->kernels[GGML_METAL_KERNEL_TYPE_IM2COL_EXT_F16].pipeline - : - ctx->kernels[GGML_METAL_KERNEL_TYPE_IM2COL_F16].pipeline); - } break; - default: GGML_ABORT("fatal error"); - }; - - ggml_metal_kargs_im2col args = { - /*.ofs0 =*/ ofs0, - /*.ofs1 =*/ ofs1, - /*.IW =*/ IW, - /*.IH =*/ IH, - /*.CHW =*/ CHW, - /*.s0 =*/ s0, - /*.s1 =*/ s1, - /*.p0 =*/ p0, - /*.p1 =*/ p1, - /*.d0 =*/ d0, - /*.d1 =*/ d1, - /*.N =*/ N, - /*.KH =*/ KH, - /*.KW =*/ KW, - /*.KHW =*/ KH * KW, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - [encoder setBytes:&args length:sizeof(args) atIndex:2]; - - if (is_gt_mttpt) { - const uint64_t n_threads = MIN(pipeline.maxTotalThreadsPerThreadgroup, (uint64_t)N); - - const int64_t quotient = N / n_threads + (N % n_threads > 0 ? 1 : 0); - - [encoder dispatchThreadgroups:MTLSizeMake(quotient * CHW, OH, OW) threadsPerThreadgroup:MTLSizeMake(n_threads, 1, 1)]; - } else { - [encoder dispatchThreadgroups:MTLSizeMake(IC, OH, OW) threadsPerThreadgroup:MTLSizeMake(N, KH, KW)]; - } - } break; - case GGML_OP_CONV_TRANSPOSE_1D: - { - GGML_ASSERT(ggml_is_contiguous(src0)); - GGML_ASSERT(ggml_is_contiguous(src1)); - GGML_ASSERT(src0->type == GGML_TYPE_F16 || src0->type == GGML_TYPE_F32); - GGML_ASSERT(src1->type == GGML_TYPE_F32); - GGML_ASSERT( dst->type == GGML_TYPE_F32); - - const int32_t s0 = ((const int32_t *)(dst->op_params))[0]; - - const int32_t IC = src1->ne[1]; - const int32_t IL = src1->ne[0]; - - const int32_t K = src0->ne[0]; - - const int32_t OL = dst->ne[0]; - const int32_t OC = dst->ne[1]; - - id pipeline; - - switch (src0->type) { - case GGML_TYPE_F32: { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CONV_TRANSPOSE_1D_F32_F32].pipeline; - } break; - case GGML_TYPE_F16: { - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CONV_TRANSPOSE_1D_F16_F32].pipeline; - } break; - default: GGML_ABORT("fatal error"); - }; - - ggml_metal_kargs_conv_transpose_1d args = { - /*.IC =*/ IC, - /*.IL =*/ IL, - /*.K =*/ K, - /*.s0 =*/ s0, - /*.nb0 =*/ nb0, - /*.nb1 =*/ nb1, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:1]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:2]; - [encoder setBytes:&args length:sizeof(args) atIndex:3]; - - [encoder dispatchThreadgroups:MTLSizeMake(OL, OC, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_OP_UPSCALE: - { - GGML_ASSERT(src0->type == GGML_TYPE_F32); - - const float sf0 = (float)ne0/src0->ne[0]; - const float sf1 = (float)ne1/src0->ne[1]; - const float sf2 = (float)ne2/src0->ne[2]; - const float sf3 = (float)ne3/src0->ne[3]; - - const id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_UPSCALE_F32].pipeline; - - ggml_metal_kargs_upscale 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, - /*.sf0 =*/ sf0, - /*.sf1 =*/ sf1, - /*.sf2 =*/ sf2, - /*.sf3 =*/ sf3 - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - [encoder setBytes:&args length:sizeof(args) atIndex:2]; - - const int nth = MIN((int) pipeline.maxTotalThreadsPerThreadgroup, ne0); - - [encoder dispatchThreadgroups:MTLSizeMake(ne1, ne2, ne3) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } break; - case GGML_OP_PAD: - { - GGML_ASSERT(src0->type == GGML_TYPE_F32); - - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_PAD_F32].pipeline; - - ggml_metal_kargs_pad 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 - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - [encoder setBytes:&args length:sizeof(args) atIndex:2]; - - const int nth = MIN(1024, ne0); - - [encoder dispatchThreadgroups:MTLSizeMake(ne1, ne2, ne3) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } break; - case GGML_OP_PAD_REFLECT_1D: - { - GGML_ASSERT(src0->type == GGML_TYPE_F32); - - const int32_t p0 = ((const int32_t *)(dst->op_params))[0]; - const int32_t p1 = ((const int32_t *)(dst->op_params))[1]; - - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_PAD_REFLECT_1D_F32].pipeline; - - ggml_metal_kargs_pad_reflect_1d 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, - /*.p0 =*/ p0, - /*.p1 =*/ p1 - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - [encoder setBytes:&args length:sizeof(args) atIndex:2]; - - const int nth = MIN(1024, ne0); - - [encoder dispatchThreadgroups:MTLSizeMake(ne1, ne2, ne3) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } break; - case GGML_OP_ARANGE: - { - GGML_ASSERT(dst->type == GGML_TYPE_F32); - - float start; - float step; - - memcpy(&start, ((const int32_t *) dst->op_params) + 0, sizeof(float)); - memcpy(&step, ((const int32_t *) dst->op_params) + 2, sizeof(float)); - - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_ARANGE_F32].pipeline; - - ggml_metal_kargs_arange args = { - /*.ne0 =*/ ne0, - /*.start =*/ start, - /*.step =*/ step - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:0]; - [encoder setBytes:&args length:sizeof(args) atIndex:1]; - - const int nth = MIN(1024, ne0); - - [encoder dispatchThreadgroups:MTLSizeMake(1, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } break; - case GGML_OP_TIMESTEP_EMBEDDING: - { - GGML_ASSERT(src0->type == GGML_TYPE_F32); - - const int dim = dst->op_params[0]; - const int max_period = dst->op_params[1]; - - const int half = dim / 2; - - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_TIMESTEP_EMBEDDING_F32].pipeline; - - ggml_metal_kargs_timestep_embedding args = { - /*.nb1 =*/ nb1, - /*.dim =*/ dim, - /*.max_period =*/ max_period - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - [encoder setBytes:&args length:sizeof(args) atIndex:2]; - - const int nth = MIN(1024, half); - - [encoder dispatchThreadgroups:MTLSizeMake(ne00, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } break; - case GGML_OP_ARGSORT: - { - GGML_ASSERT(src0->type == GGML_TYPE_F32); - GGML_ASSERT( dst->type == GGML_TYPE_I32); - - const int nrows = ggml_nrows(src0); - - enum ggml_sort_order order = (enum ggml_sort_order) dst->op_params[0]; - - // bitonic sort requires the number of elements to be power of 2 - int64_t ne00_padded = 1; - while (ne00_padded < ne00) { - ne00_padded *= 2; - } - - // Metal kernels require the buffer size to be multiple of 16 bytes - // https://developer.apple.com/documentation/metal/mtlcomputecommandencoder/1443142-setthreadgroupmemorylength - const int mem_size = GGML_PAD(ne00_padded*sizeof(int32_t), 16); - - id pipeline = nil; - - switch (order) { - case GGML_SORT_ORDER_ASC: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_ARGSORT_F32_I32_ASC].pipeline; break; - case GGML_SORT_ORDER_DESC: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_ARGSORT_F32_I32_DESC].pipeline; break; - default: GGML_ABORT("fatal error"); - }; - - ggml_metal_kargs_argsort args = { - /*.ncols =*/ ne00, - /*.ncols_pad =*/ ne00_padded - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - [encoder setBytes:&args length:sizeof(args) atIndex:2]; - [encoder setThreadgroupMemoryLength:mem_size atIndex:0]; - - [encoder dispatchThreadgroups:MTLSizeMake(1, nrows, 1) threadsPerThreadgroup:MTLSizeMake(ne00_padded, 1, 1)]; - } break; - case GGML_OP_LEAKY_RELU: - { - GGML_ASSERT(src0->type == GGML_TYPE_F32); - - float slope; - memcpy(&slope, dst->op_params, sizeof(float)); - - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_LEAKY_RELU_F32].pipeline; - - ggml_metal_kargs_leaky_relu args = { - /*.slope =*/ slope - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - [encoder setBytes:&args length:sizeof(args) atIndex:2]; - - const int64_t n = ggml_nelements(dst); - - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; - case GGML_OP_FLASH_ATTN_EXT: - { - GGML_ASSERT(ne00 % 4 == 0); - GGML_ASSERT(ne11 % 32 == 0); - - GGML_ASSERT(src0->type == GGML_TYPE_F32); - GGML_ASSERT(src1->type == src2->type); - - //GGML_ASSERT(ggml_are_same_shape (src1, src2)); - GGML_ASSERT(ne11 == ne21); - GGML_ASSERT(ne12 == ne22); - - struct ggml_tensor * src3 = node->src[3]; // mask - struct ggml_tensor * src4 = node->src[4]; // sinks - - size_t offs_src3 = 0; - size_t offs_src4 = 0; - - id id_src3 = src3 ? ggml_metal_get_buffer(src3, &offs_src3) : nil; - id id_src4 = src4 ? ggml_metal_get_buffer(src4, &offs_src4) : nil; - - GGML_ASSERT(!src3 || src3->type == GGML_TYPE_F16); - GGML_ASSERT(!src3 || src3->ne[1] >= GGML_PAD(src0->ne[1], 8) && - "the Flash-Attention Metal kernel requires the mask to be padded to 8 and at least n_queries big"); - - const int64_t ne30 = src3 ? src3->ne[0] : 0; GGML_UNUSED(ne30); - //const int64_t ne31 = src3 ? src3->ne[1] : 0; - const int64_t ne32 = src3 ? src3->ne[2] : 0; GGML_UNUSED(ne32); - const int64_t ne33 = src3 ? src3->ne[3] : 0; GGML_UNUSED(ne33); - - const uint64_t nb30 = src3 ? src3->nb[0] : 0; GGML_UNUSED(nb30); - const uint64_t nb31 = src3 ? src3->nb[1] : 0; - const uint64_t nb32 = src3 ? src3->nb[2] : 0; GGML_UNUSED(nb32); - const uint64_t nb33 = src3 ? src3->nb[3] : 0; GGML_UNUSED(nb33); - - float scale; - float max_bias; - float logit_softcap; - - memcpy(&scale, ((const int32_t *) dst->op_params) + 0, sizeof(scale)); - memcpy(&max_bias, ((const int32_t *) dst->op_params) + 1, sizeof(max_bias)); - memcpy(&logit_softcap, ((const int32_t *) dst->op_params) + 2, sizeof(logit_softcap)); - - if (logit_softcap != 0.0f) { - scale /= logit_softcap; - } - - const bool has_mask = src3 != NULL; - const bool has_sinks = src4 != NULL; - const bool has_bias = max_bias != 0.0f; - const bool has_scap = logit_softcap != 0.0f; - - const uint32_t n_head = src0->ne[2]; - const uint32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head)); - - const float m0 = powf(2.0f, -(max_bias ) / n_head_log2); - const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2); - - GGML_ASSERT(ne01 < 65536); - - if (!ggml_metal_flash_attn_ext_use_vec(dst)) { - // half8x8 kernel - const int64_t nqptg = 8; // queries per threadgroup !! sync with kernel template arguments !! - const int64_t ncpsg = 64; // cache values per simdgroup !! sync with kernel template arguments !! - - GGML_ASSERT(nqptg <= 32); - GGML_ASSERT(nqptg % 8 == 0); - GGML_ASSERT(ncpsg % 32 == 0); - - const int is_q = ggml_is_quantized(src1->type) ? 1 : 0; - - // 2*(2*ncpsg) - // ncpsg soft_max values + ncpsg mask values - // - // 16*32*(nsg) - // the shared memory needed for the simdgroups to load the KV cache - // each thread loads (dequantizes) 16 head elements, there are 32 threads in th SG - // -#define FATTN_SMEM(nsg) (GGML_PAD((nqptg*(ne00 + 2*GGML_PAD(ne20, 64) + 2*(2*ncpsg)) + is_q*(16*32*(nsg)))*(sizeof(float)/2), 16)) - - //int64_t nsgmax = 4; - // - //if (is_q) { - // nsgmax = 2; - // while (true) { - // const size_t smem = FATTN_SMEM(nsgmax); - // if (smem > device.maxThreadgroupMemoryLength/2) { - // break; - // } - // nsgmax *= 2; - // } - // nsgmax /= 2; - //} - - // simdgroups per threadgroup (a.k.a. warps) - //nsg = ne01 <= nqptg ? MAX(4, MIN(nsgmax, MIN(ne11/ncpsg, (int64_t) pipeline.maxTotalThreadsPerThreadgroup/32))) : 4; - int32_t nsg = 4; - - const size_t smem = FATTN_SMEM(nsg); - - ggml_metal_kargs_flash_attn_ext args = { - /*.ne01 =*/ ne01, - /*.ne02 =*/ ne02, - /*.ne03 =*/ ne03, - /*.nb01 =*/ nb01, - /*.nb02 =*/ nb02, - /*.nb03 =*/ nb03, - /*.ne11 =*/ ne11, - /*.ne_12_2 =*/ ne12, - /*.ne_12_3 =*/ ne13, - /*.ns10 =*/ nb11/nb10, - /*.nb11 =*/ nb11, - /*.nb12 =*/ nb12, - /*.nb13 =*/ nb13, - /*.ns20 =*/ nb21/nb20, - /*.nb21 =*/ nb21, - /*.nb22 =*/ nb22, - /*.nb23 =*/ nb23, - /*.ne32 =*/ ne32, - /*.ne33 =*/ ne33, - /*.nb31 =*/ nb31, - /*.nb32 =*/ nb32, - /*.nb33 =*/ nb33, - /*.ne1 =*/ ne1, - /*.ne2 =*/ ne2, - /*.ne3 =*/ ne3, - /*.scale =*/ scale, - /*.max_bias =*/ max_bias, - /*.m0 =*/ m0, - /*.m1 =*/ m1, - /*.n_head_log2 =*/ n_head_log2, - /*.logit_softcap =*/ logit_softcap, - }; - - id pipeline = ggml_metal_get_pipeline_flash_attn_ext(backend, node, has_mask, has_sinks, has_bias, has_scap, nsg); - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:2]; - [encoder setBuffer:id_src2 offset:offs_src2 atIndex:3]; - if (id_src3) { - [encoder setBuffer:id_src3 offset:offs_src3 atIndex:4]; - } else { - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:4]; - } - if (id_src4) { - [encoder setBuffer:id_src4 offset:offs_src4 atIndex:5]; - } else { - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:5]; - } - - [encoder setBuffer:id_dst offset:offs_dst atIndex:6]; - - //printf("smem: %zu, max: %zu, nsg = %d, ne02 = %d, ne12 = %d\n", smem, device.maxThreadgroupMemoryLength, (int) nsg, ne02, ne12); - GGML_ASSERT(smem <= device.maxThreadgroupMemoryLength); - [encoder setThreadgroupMemoryLength:smem atIndex:0]; - [encoder dispatchThreadgroups:MTLSizeMake((ne01 + nqptg - 1)/nqptg, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(32, nsg, 1)]; -#undef FATTN_SMEM - } else { - // half4x4 kernel - const int64_t nqptg = 1; // queries per threadgroup !! sync with kernel template arguments !! - const int64_t ncpsg = 32; // cache values per simdgroup !! sync with kernel template arguments !! - const int64_t nkpsg = 1*ncpsg; - - GGML_ASSERT(nqptg <= 32); - GGML_ASSERT(nqptg % 1 == 0); - GGML_ASSERT(ncpsg % 32 == 0); - - // ne00 + 2*ncpsg*(nsg) - // for each query, we load it as f16 in shared memory (ne00) - // and store the soft_max values and the mask - // - // ne20*(nsg) - // each simdgroup has a full f32 head vector in shared mem to accumulate results - // -#define FATTN_SMEM(nsg) (GGML_PAD((nqptg*(GGML_PAD(ne00, 128) + 4*ncpsg*(nsg)) + 2*GGML_PAD(ne20, 128)*(nsg))*(sizeof(float)/2), 16)) - - int64_t nsgmax = 2; - while (true) { - const size_t smem = FATTN_SMEM(nsgmax); - // avoid using more than half of the threadgroup memory - can cause slow downs especially for large head sizes - if (smem > device.maxThreadgroupMemoryLength/2) { - break; - } - nsgmax *= 2; - } - nsgmax /= 2; - - // simdgroups per threadgroup (a.k.a. warps) - //const int64_t nsgt = MAX(2, MIN(nsgmax, MIN((ne11 + nkpsg - 1)/(nkpsg), (int64_t) pipeline.maxTotalThreadsPerThreadgroup/32))); - const int64_t nsgt = MAX(2, MIN(nsgmax, MIN((ne11 + nkpsg - 1)/(nkpsg), (int64_t) 1024/32))); - - int64_t nsg = 1; - while (nsg <= nsgt) { - nsg *= 2; - } - nsg /= 2; - - // workgroups - // each workgroup handles nsg*nkpsg cache values - int32_t nwg = 1; - if (false) { - // for small KV caches, we could launch a single workgroup and write the results directly to dst/ - // however, this does not lead to significant improvement, so disabled - nwg = 1; - nsg = 4; - } else { - nwg = 32; - nsg = 1; - while (2*nwg*nsg*nkpsg < ne11 && nsg < 4) { - nsg *= 2; - } - } - - ggml_metal_kargs_flash_attn_ext_vec args = { - /*.ne01 =*/ ne01, - /*.ne02 =*/ ne02, - /*.ne03 =*/ ne03, - /*.nb01 =*/ nb01, - /*.nb02 =*/ nb02, - /*.nb03 =*/ nb03, - /*.ne11 =*/ ne11, - /*.ne_12_2 =*/ ne12, - /*.ne_12_3 =*/ ne13, - /*.ns10 =*/ nb11/nb10, - /*.nb11 =*/ nb11, - /*.nb12 =*/ nb12, - /*.nb13 =*/ nb13, - /*.ns20 =*/ nb21/nb20, - /*.nb21 =*/ nb21, - /*.nb22 =*/ nb22, - /*.nb23 =*/ nb23, - /*.ne32 =*/ ne32, - /*.ne33 =*/ ne33, - /*.nb31 =*/ nb31, - /*.nb32 =*/ nb32, - /*.nb33 =*/ nb33, - /*.ne1 =*/ ne1, - /*.ne2 =*/ ne2, - /*.ne3 =*/ ne3, - /*.scale =*/ scale, - /*.max_bias =*/ max_bias, - /*.m0 =*/ m0, - /*.m1 =*/ m1, - /*.n_head_log2 =*/ n_head_log2, - /*.logit_softcap =*/ logit_softcap, - }; - - id pipeline = ggml_metal_get_pipeline_flash_attn_ext_vec(backend, node, has_mask, has_sinks, has_bias, has_scap, nsg, nwg); - - GGML_ASSERT(nsg*32 <= (int) pipeline.maxTotalThreadsPerThreadgroup); - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:2]; - [encoder setBuffer:id_src2 offset:offs_src2 atIndex:3]; - if (id_src3) { - [encoder setBuffer:id_src3 offset:offs_src3 atIndex:4]; - } else { - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:4]; - } - if (id_src4) { - [encoder setBuffer:id_src4 offset:offs_src4 atIndex:5]; - } else { - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:5]; - } - - const size_t smem = FATTN_SMEM(nsg); - - //printf("smem: %zu, max: %zu, nsg = %d, nsgmax = %d\n", smem, device.maxThreadgroupMemoryLength, (int) nsg, (int) nsgmax); - GGML_ASSERT(smem <= device.maxThreadgroupMemoryLength); - - if (nwg == 1) { - // using 1 workgroup -> write the result directly into dst - [encoder setBuffer:id_dst offset:offs_dst atIndex:6]; - - [encoder setThreadgroupMemoryLength:smem atIndex:0]; - [encoder dispatchThreadgroups:MTLSizeMake((ne01 + nqptg - 1)/nqptg, ne02, ne03*nwg) threadsPerThreadgroup:MTLSizeMake(32, nsg, 1)]; - } else { - // sanity checks - GGML_ASSERT(ne01*ne02*ne03 == ne1*ne2*ne3); - GGML_ASSERT(ne1*ne2*ne3 <= (1u << 31)); - - // write the results from each workgroup into a temp buffer - const size_t offs_tmp = offs_dst + ggml_nbytes(dst); - [encoder setBuffer:id_dst offset:offs_tmp atIndex:6]; - - [encoder setThreadgroupMemoryLength:smem atIndex:0]; - [encoder dispatchThreadgroups:MTLSizeMake((ne01 + nqptg - 1)/nqptg, ne02, ne03*nwg) threadsPerThreadgroup:MTLSizeMake(32, nsg, 1)]; - - // sync the 2 kernels - ggml_metal_encode_concurrency_reset(ctx_enc); - - // reduce the results from the workgroups - { - const int32_t nrows = ne1*ne2*ne3; - - ggml_metal_kargs_flash_attn_ext_vec_reduce args0 = { - nrows, - }; - - id pipeline0 = ggml_metal_get_pipeline_flash_attn_ext_vec_reduce(backend, node, ne20, nwg); - - [encoder setComputePipelineState:pipeline0]; - [encoder setBytes:&args0 length:sizeof(args0) atIndex:0]; - [encoder setBuffer:id_dst offset:offs_tmp atIndex:1]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:2]; - - //printf("ne1 = %d, ne2 = %d, ne3 = %d, ne20 = %d\n", ne1, ne2, ne3, ne20); - [encoder dispatchThreadgroups:MTLSizeMake(nrows, 1, 1) threadsPerThreadgroup:MTLSizeMake(32*nwg, 1, 1)]; - } - } -#undef FATTN_SMEM - } - } break; - case GGML_OP_DUP: - case GGML_OP_CPY: - case GGML_OP_CONT: - { - id pipeline = nil; - - switch (src0t) { - case GGML_TYPE_F32: - { - GGML_ASSERT(ne0 % ggml_blck_size(dst->type) == 0); - - switch (dstt) { - case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_F32].pipeline; break; - case GGML_TYPE_I32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_I32].pipeline; break; - case GGML_TYPE_F16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_F16].pipeline; break; - case GGML_TYPE_BF16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_BF16].pipeline; break; - case GGML_TYPE_Q8_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_Q8_0].pipeline; break; - case GGML_TYPE_Q4_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_Q4_0].pipeline; break; - case GGML_TYPE_Q4_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_Q4_1].pipeline; break; - case GGML_TYPE_Q5_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_Q5_0].pipeline; break; - case GGML_TYPE_Q5_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_Q5_1].pipeline; break; - case GGML_TYPE_IQ4_NL: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_IQ4_NL].pipeline; break; - default: GGML_ABORT("not implemented"); - }; - } break; - case GGML_TYPE_I32: - { - switch (dstt) { - case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_I32_F32].pipeline; break; - default: GGML_ABORT("not implemented"); - }; - } break; - case GGML_TYPE_F16: - { - switch (dstt) { - case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F16_F32].pipeline; break; - case GGML_TYPE_F16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F16_F16].pipeline; break; - default: GGML_ABORT("not implemented"); - }; - } break; - case GGML_TYPE_BF16: - { - switch (dstt) { - case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_BF16_F32].pipeline; break; - case GGML_TYPE_BF16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_BF16_BF16].pipeline; break; - default: GGML_ABORT("not implemented"); - }; - } break; - case GGML_TYPE_Q4_0: - { - switch (dstt) { - case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_Q4_0_F32].pipeline; break; - case GGML_TYPE_F16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_Q4_0_F16].pipeline; break; - default: GGML_ABORT("not implemented"); - }; - } break; - case GGML_TYPE_Q4_1: - { - switch (dstt) { - case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_Q4_1_F32].pipeline; break; - case GGML_TYPE_F16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_Q4_1_F16].pipeline; break; - default: GGML_ABORT("not implemented"); - }; - } break; - case GGML_TYPE_Q5_0: - { - switch (dstt) { - case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_Q5_0_F32].pipeline; break; - case GGML_TYPE_F16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_Q5_0_F16].pipeline; break; - default: GGML_ABORT("not implemented"); - }; - } break; - case GGML_TYPE_Q5_1: - { - switch (dstt) { - case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_Q5_1_F32].pipeline; break; - case GGML_TYPE_F16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_Q5_1_F16].pipeline; break; - default: GGML_ABORT("not implemented"); - }; - } break; - case GGML_TYPE_Q8_0: - { - switch (dstt) { - case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_Q8_0_F32].pipeline; break; - case GGML_TYPE_F16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_Q8_0_F16].pipeline; break; - default: GGML_ABORT("not implemented"); - }; - } break; - default: GGML_ABORT("not implemented"); - } - - GGML_ASSERT(ne00 % ggml_blck_size(src0->type) == 0); - - // TODO: support - //const int32_t nk00 = ne00/ggml_blck_size(dst->type); - const int32_t nk00 = ne00; - - int nth = 32; // SIMD width - - while (nth < nk00 && nth < (int) pipeline.maxTotalThreadsPerThreadgroup) { - nth *= 2; - } - - nth = MIN(nth, (int) pipeline.maxTotalThreadsPerThreadgroup); - - // when rows are small, we can batch them together in a single threadgroup - int nrptg = 1; - - // TODO: relax this constraint in the future - if (ggml_blck_size(src0->type) == 1 && ggml_blck_size(dst->type) == 1) { - if (nth > nk00) { - nrptg = (nth + nk00 - 1)/nk00; - nth = nk00; - - if (nrptg*nth > (int) pipeline.maxTotalThreadsPerThreadgroup) { - nrptg--; - } - } - } - - nth = MIN(nth, nk00); - - ggml_metal_kargs_cpy args = { - /*.ne00 =*/ nk00, - /*.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, - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBytes:&args length:sizeof(args) atIndex:0]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:2]; - - [encoder dispatchThreadgroups:MTLSizeMake((ne01 + nrptg - 1)/nrptg, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(nth, nrptg, 1)]; - } break; - case GGML_OP_POOL_2D: - { - GGML_ASSERT(ggml_is_contiguous(src0)); - GGML_ASSERT(src0t == GGML_TYPE_F32 && src0t == dstt); - - const int32_t * opts = dst->op_params; - enum ggml_op_pool op = opts[0]; - - id pipeline = nil; - switch (src0t) { - case GGML_TYPE_F32: { - switch(op) { - case GGML_OP_POOL_AVG: - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_POOL_2D_AVG_F32].pipeline; break; - case GGML_OP_POOL_MAX: - pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_POOL_2D_MAX_F32].pipeline; break; - default: GGML_ASSERT(false && "not implemented"); - } - } break; - default: GGML_ASSERT(false && "not implemented"); - } - - const int32_t k0 = opts[1]; - const int32_t k1 = opts[2]; - const int32_t s0 = opts[3]; - const int32_t s1 = opts[4]; - const int32_t p0 = opts[5]; - const int32_t p1 = opts[6]; - - const int64_t IH = src0->ne[1]; - const int64_t IW = src0->ne[0]; - - const int64_t N = dst->ne[3]; - const int64_t OC = dst->ne[2]; - const int64_t OH = dst->ne[1]; - const int64_t OW = dst->ne[0]; - - const int64_t parallel_elements = N * OC * OH * OW; - const int64_t n_threads = MIN((int64_t)[pipeline maxTotalThreadsPerThreadgroup], parallel_elements); - const int64_t n_tg = (parallel_elements + n_threads - 1) / n_threads; - - ggml_metal_kargs_pool_2d args_pool_2d = { - /* .k0 = */ k0, - /* .k1 = */ k1, - /* .s0 = */ s0, - /* .s1 = */ s1, - /* .p0 = */ p0, - /* .p1 = */ p1, - /* .IH = */ IH, - /* .IW = */ IW, - /* .OH = */ OH, - /* .OW = */ OW, - /* .parallel_elements = */ parallel_elements - }; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - [encoder setBytes:&args_pool_2d length:sizeof(args_pool_2d) atIndex:2]; - - [encoder dispatchThreadgroups:MTLSizeMake(n_tg, 1, 1) threadsPerThreadgroup:MTLSizeMake(n_threads, 1, 1)]; - } break; - case GGML_OP_ARGMAX: - { - GGML_ASSERT(src0->type == GGML_TYPE_F32); - GGML_ASSERT(ggml_is_contiguous_1(src0)); - GGML_ASSERT(nb00 == ggml_type_size(src0->type)); - - const int64_t nrows = ggml_nrows(src0); - - int nth = 32; // SIMD width - while (nth < ne00 && nth*ne01*ne02*ne03 < 256) { - nth *= 2; - } - - id pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_ARGMAX].pipeline; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - [encoder setBytes:&ne00 length:sizeof( int64_t) atIndex:2]; - [encoder setBytes:&nb01 length:sizeof(uint64_t) atIndex:3]; - [encoder setThreadgroupMemoryLength:32*sizeof(float) atIndex:0]; - [encoder setThreadgroupMemoryLength:32*sizeof(int32_t) atIndex:1]; - - [encoder dispatchThreadgroups:MTLSizeMake(nrows, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } break; - default: - { - GGML_LOG_ERROR("%s: error: node %3d, op = %8s not implemented\n", __func__, idx, ggml_op_name(dst->op)); - GGML_ABORT("fatal error"); - } - } - - if (ctx_dev->debug_graph > 0) { - if (n_fuse > 1) { - GGML_LOG_DEBUG("%s: fuse %d ops\n", __func__, n_fuse); - } - } - - // update the mem ranges in the encoding context - for (int i = 0; i < n_fuse; ++i) { - if (!ggml_metal_encode_concurrency_add(ctx_enc, nodes[i])) { - ggml_metal_encode_concurrency_reset(ctx_enc); - } - } - - return n_fuse; -} - -static enum ggml_status ggml_metal_graph_compute( - ggml_backend_t backend, - struct ggml_cgraph * gf) { - struct ggml_backend_metal_context * ctx = backend->context; - struct ggml_backend_metal_device_context * ctx_dev = backend->device->context; - - // number of nodes encoded by the main thread (empirically determined) - const int n_main = 64; - - // number of threads in addition to the main thread - const int n_cb = ctx->n_cb; - - // 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 - // each thread creates it's own command buffer and enqueues the ops in parallel - // - // tests on M1 Pro and M2 Ultra using LLaMA models, show that optimal values for n_cb are 1 or 2 - - @autoreleasepool { - ctx->gf = gf; - - ctx->n_nodes_0 = MIN(n_main, gf->n_nodes); - ctx->n_nodes_1 = gf->n_nodes - ctx->n_nodes_0; - - ctx->n_nodes_per_cb = (ctx->n_nodes_1 + ctx->n_cb - 1) / ctx->n_cb; - - const bool should_capture = ctx->capture_next_compute; - if (should_capture) { - ctx->capture_next_compute = false; - - // make sure all previous computations have finished before starting the capture - if (ctx->cmd_buf_last) { - [ctx->cmd_buf_last waitUntilCompleted]; - ctx->cmd_buf_last = nil; - } - - if (!ctx->capture_started) { - // create capture scope - ctx->capture_scope = [[MTLCaptureManager sharedCaptureManager] newCaptureScopeWithDevice:ctx_dev->mtl_device]; - - MTLCaptureDescriptor * descriptor = [MTLCaptureDescriptor new]; - descriptor.captureObject = ctx->capture_scope; - descriptor.destination = MTLCaptureDestinationGPUTraceDocument; - descriptor.outputURL = [NSURL fileURLWithPath:[NSString stringWithFormat:@"/tmp/perf-metal.gputrace"]]; - - NSError * error = nil; - if (![[MTLCaptureManager sharedCaptureManager] startCaptureWithDescriptor:descriptor error:&error]) { - GGML_LOG_ERROR("%s: error: unable to start capture '%s'\n", __func__, [[error localizedDescription] UTF8String]); - } else { - [ctx->capture_scope beginScope]; - ctx->capture_started = true; - } - } - } - - // the main thread commits the first few commands immediately - // cmd_buf[n_cb] - { - id cmd_buf = [ctx->queue commandBufferWithUnretainedReferences]; - [cmd_buf retain]; - - if (ctx->cmd_bufs[n_cb].obj) { - [ctx->cmd_bufs[n_cb].obj release]; - } - ctx->cmd_bufs[n_cb].obj = cmd_buf; - - [cmd_buf enqueue]; - - ctx->encode_async(n_cb); - } - - // remember the command buffer for the next iteration - ctx->cmd_buf_last = ctx->cmd_bufs[n_cb].obj; - - // 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]; - [cmd_buf retain]; - - if (ctx->cmd_bufs[cb_idx].obj) { - [ctx->cmd_bufs[cb_idx].obj release]; - } - ctx->cmd_bufs[cb_idx].obj = cmd_buf; - - // always enqueue the first two command buffers - // enqueue all of the command buffers if we don't need to abort - if (cb_idx < 2 || ctx->abort_callback == NULL) { - [cmd_buf enqueue]; - - // update the pointer to the last queued command buffer - // this is needed to implement synchronize() - ctx->cmd_buf_last = cmd_buf; - } - } - - dispatch_apply(n_cb, ctx->d_queue, ctx->encode_async); - - // for debugging: block until graph is computed - //[ctx->cmd_buf_last waitUntilCompleted]; - - // enter here only when capturing in order to wait for all computation to finish - // otherwise, we leave the graph to compute asynchronously - if (!should_capture && ctx->capture_started) { - // wait for completion and check status of each command buffer - // needed to detect if the device ran out-of-memory for example (#1881) - { - id cmd_buf = ctx->cmd_bufs[n_cb].obj; - [cmd_buf waitUntilCompleted]; - - MTLCommandBufferStatus status = [cmd_buf status]; - if (status != MTLCommandBufferStatusCompleted) { - GGML_LOG_INFO("%s: command buffer %d failed with status %lu\n", __func__, n_cb, status); - if (status == MTLCommandBufferStatusError) { - GGML_LOG_INFO("error: %s\n", [[cmd_buf error].localizedDescription UTF8String]); - } - - return GGML_STATUS_FAILED; - } - } - - for (int i = 0; i < n_cb; ++i) { - id cmd_buf = ctx->cmd_bufs[i].obj; - [cmd_buf waitUntilCompleted]; - - MTLCommandBufferStatus status = [cmd_buf status]; - if (status != MTLCommandBufferStatusCompleted) { - GGML_LOG_INFO("%s: command buffer %d failed with status %lu\n", __func__, i, status); - if (status == MTLCommandBufferStatusError) { - GGML_LOG_INFO("error: %s\n", [[cmd_buf error].localizedDescription UTF8String]); - } - - return GGML_STATUS_FAILED; - } - - id next_buffer = (i + 1 < n_cb ? ctx->cmd_bufs[i + 1].obj : nil); - if (!next_buffer) { - continue; - } - - const bool next_queued = ([next_buffer status] != MTLCommandBufferStatusNotEnqueued); - if (next_queued) { - continue; - } - - if (ctx->abort_callback && ctx->abort_callback(ctx->abort_callback_data)) { - GGML_LOG_INFO("%s: command buffer %d aborted", __func__, i); - return GGML_STATUS_ABORTED; - } - - [next_buffer commit]; - } - - [ctx->capture_scope endScope]; - [[MTLCaptureManager sharedCaptureManager] stopCapture]; - } - } - - return GGML_STATUS_SUCCESS; -} - -//////////////////////////////////////////////////////////////////////////////// -// backend interface -//////////////////////////////////////////////////////////////////////////////// - -// shared buffer - -static void ggml_backend_metal_buffer_shared_free_buffer(ggml_backend_buffer_t buffer) { - struct ggml_backend_metal_buffer_context * ctx = (struct ggml_backend_metal_buffer_context *)buffer->context; - - for (int i = 0; i < ctx->n_buffers; i++) { - [ctx->buffers[i].metal release]; - } - - ggml_backend_metal_buffer_rset_free(ctx); - - GGML_ASSERT(ctx->is_shared); - - { -#if TARGET_OS_OSX - vm_deallocate((vm_map_t)mach_task_self(), (vm_address_t)ctx->all_data, ctx->all_size); -#else - free(ctx->all_data); -#endif - } - - free(ctx); -} - -static void * ggml_backend_metal_buffer_shared_get_base(ggml_backend_buffer_t buffer) { - struct ggml_backend_metal_buffer_context * ctx = (struct ggml_backend_metal_buffer_context *)buffer->context; - - return ctx->all_data; -} - -static void ggml_backend_metal_buffer_shared_memset_tensor(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, uint8_t value, size_t offset, size_t size) { - struct ggml_backend_metal_buffer_context * ctx = (struct ggml_backend_metal_buffer_context *)buffer->context; - - GGML_ASSERT(ctx->is_shared); - - memset((char *)tensor->data + offset, value, size); -} - -static void ggml_backend_metal_buffer_shared_set_tensor(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size) { - struct ggml_backend_metal_buffer_context * ctx = (struct ggml_backend_metal_buffer_context *)buffer->context; - - GGML_ASSERT(ctx->is_shared); - - memcpy((char *)tensor->data + offset, data, size); -} - -static void ggml_backend_metal_buffer_shared_get_tensor(ggml_backend_buffer_t buffer, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size) { - struct ggml_backend_metal_buffer_context * ctx = (struct ggml_backend_metal_buffer_context *)buffer->context; - - GGML_ASSERT(ctx->is_shared); - - memcpy(data, (const char *)tensor->data + offset, size); -} - -static bool ggml_backend_metal_buffer_shared_cpy_tensor(ggml_backend_buffer_t buffer, const struct ggml_tensor * src, struct ggml_tensor * dst) { - GGML_UNUSED(buffer); - GGML_UNUSED(src); - GGML_UNUSED(dst); - - return false; -} - -static void ggml_backend_metal_buffer_shared_clear(ggml_backend_buffer_t buffer, uint8_t value) { - struct ggml_backend_metal_buffer_context * ctx = (struct ggml_backend_metal_buffer_context *)buffer->context; - - GGML_ASSERT(ctx->is_shared); - - memset(ctx->all_data, value, ctx->all_size); -} - -static struct ggml_backend_buffer_i ggml_backend_metal_buffer_shared_i = { - /* .free_buffer = */ ggml_backend_metal_buffer_shared_free_buffer, - /* .get_base = */ ggml_backend_metal_buffer_shared_get_base, - /* .init_tensor = */ NULL, - /* .memset_tensor = */ ggml_backend_metal_buffer_shared_memset_tensor, - /* .set_tensor = */ ggml_backend_metal_buffer_shared_set_tensor, - /* .get_tensor = */ ggml_backend_metal_buffer_shared_get_tensor, - /* .cpy_tensor = */ ggml_backend_metal_buffer_shared_cpy_tensor, - /* .clear = */ ggml_backend_metal_buffer_shared_clear, - /* .reset = */ NULL, -}; - -// private buffer - -static void ggml_backend_metal_buffer_private_free_buffer(ggml_backend_buffer_t buffer) { - struct ggml_backend_metal_buffer_context * ctx = (struct ggml_backend_metal_buffer_context *)buffer->context; - - for (int i = 0; i < ctx->n_buffers; i++) { - [ctx->buffers[i].metal release]; - } - - ggml_backend_metal_buffer_rset_free(ctx); - - GGML_ASSERT(!ctx->is_shared); - - free(ctx); -} - -static void * ggml_backend_metal_buffer_private_get_base(ggml_backend_buffer_t buffer) { - struct ggml_backend_metal_buffer_context * ctx = (struct ggml_backend_metal_buffer_context *)buffer->context; - - return ctx->all_data; -} - -static void ggml_backend_metal_buffer_private_memset_tensor(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, uint8_t value, size_t offset, size_t size) { - struct ggml_backend_metal_buffer_context * ctx = (struct ggml_backend_metal_buffer_context *)buffer->context; - - GGML_ASSERT(!ctx->is_shared); - - @autoreleasepool { - // dst - size_t buf_dst_offset = 0; - id buf_dst = ggml_metal_get_buffer(tensor, &buf_dst_offset); - - buf_dst_offset += offset; - - id queue = ctx->queue; - id cmd_buf = [queue commandBufferWithUnretainedReferences]; - - { - id encoder = [cmd_buf blitCommandEncoder]; - - [encoder fillBuffer:buf_dst - range:NSMakeRange(buf_dst_offset, buf_dst_offset + size) - value:value]; - - [encoder endEncoding]; - } - - [cmd_buf commit]; - [cmd_buf waitUntilCompleted]; - } -} - -static void ggml_backend_metal_buffer_private_set_tensor(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size) { - struct ggml_backend_metal_buffer_context * ctx = (struct ggml_backend_metal_buffer_context *)buffer->context; - - GGML_ASSERT(!ctx->is_shared); - - @autoreleasepool { - // src - void * data_ptr = (void *)(uintptr_t) data; // "const cast" the src data - id buf_src = [ctx->device newBufferWithBytesNoCopy:data_ptr - length:size - options:MTLResourceStorageModeShared - deallocator:nil]; - - // dst - size_t buf_dst_offset = 0; - id buf_dst = ggml_metal_get_buffer(tensor, &buf_dst_offset); - - buf_dst_offset += offset; - - // note: for experimentation purposes, here we use a semaphore to wait for the copy to complete - // 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 = ctx->queue; - id cmd_buf = [queue commandBufferWithUnretainedReferences]; - - { - id encoder = [cmd_buf blitCommandEncoder]; - - [encoder copyFromBuffer:buf_src - sourceOffset:0 - toBuffer:buf_dst - destinationOffset:buf_dst_offset - size:size]; - - [encoder endEncoding]; - } - - [cmd_buf addCompletedHandler:^(id cb) { - // TODO: can check for errors here - GGML_UNUSED(cb); - - dispatch_semaphore_signal(completion_semaphore); - }]; - - [cmd_buf commit]; - - dispatch_semaphore_wait(completion_semaphore, DISPATCH_TIME_FOREVER); - //[cmd_buf waitUntilCompleted]; - } -} - -static void ggml_backend_metal_buffer_private_get_tensor(ggml_backend_buffer_t buffer, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size) { - struct ggml_backend_metal_buffer_context * ctx = (struct ggml_backend_metal_buffer_context *)buffer->context; - - GGML_ASSERT(!ctx->is_shared); - - @autoreleasepool { - // src - size_t buf_src_offset = 0; - id buf_src = ggml_metal_get_buffer(tensor, &buf_src_offset); - - buf_src_offset += offset; - - // dst - id buf_dst = [ctx->device newBufferWithBytesNoCopy:data - length:size - options:MTLResourceStorageModeShared - deallocator:nil]; - - id queue = ctx->queue; - id cmd_buf = [queue commandBufferWithUnretainedReferences]; - - { - id encoder = [cmd_buf blitCommandEncoder]; - - [encoder copyFromBuffer:buf_src - sourceOffset:buf_src_offset - toBuffer:buf_dst - destinationOffset:0 - size:size]; - - [encoder endEncoding]; - } - - [cmd_buf commit]; - [cmd_buf waitUntilCompleted]; - } -} - -static bool ggml_backend_metal_buffer_private_cpy_tensor(ggml_backend_buffer_t buffer, const struct ggml_tensor * src, struct ggml_tensor * dst) { - GGML_UNUSED(buffer); - GGML_UNUSED(src); - GGML_UNUSED(dst); - - return false; -} - -static void ggml_backend_metal_buffer_private_clear(ggml_backend_buffer_t buffer, uint8_t value) { - struct ggml_backend_metal_buffer_context * ctx = (struct ggml_backend_metal_buffer_context *)buffer->context; - - GGML_ASSERT(!ctx->is_shared); - - @autoreleasepool { - id queue = ctx->queue; - id cmd_buf = [queue commandBufferWithUnretainedReferences]; - - { - id encoder = [cmd_buf blitCommandEncoder]; - - [encoder fillBuffer:ctx->buffers[0].metal - range:NSMakeRange(0, ctx->buffers[0].size) - value:value]; - - [encoder endEncoding]; - } - - [cmd_buf commit]; - [cmd_buf waitUntilCompleted]; - } -} - -static struct ggml_backend_buffer_i ggml_backend_metal_buffer_private_i = { - /* .free_buffer = */ ggml_backend_metal_buffer_private_free_buffer, - /* .get_base = */ ggml_backend_metal_buffer_private_get_base, - /* .init_tensor = */ NULL, - /* .memset_tensor = */ ggml_backend_metal_buffer_private_memset_tensor, - /* .set_tensor = */ ggml_backend_metal_buffer_private_set_tensor, - /* .get_tensor = */ ggml_backend_metal_buffer_private_get_tensor, - /* .cpy_tensor = */ ggml_backend_metal_buffer_private_cpy_tensor, - /* .clear = */ ggml_backend_metal_buffer_private_clear, - /* .reset = */ NULL, -}; - -// -// buffer types -// - -static void ggml_backend_metal_log_allocated_size(id device, size_t size_aligned) { -#ifndef GGML_METAL_NDEBUG -#if TARGET_OS_OSX || (TARGET_OS_IOS && __clang_major__ >= 15) - if (@available(macOS 10.12, iOS 16.0, *)) { - GGML_LOG_DEBUG("%s: allocated buffer, size = %8.2f MiB, (%8.2f / %8.2f)\n", - __func__, - size_aligned / 1024.0 / 1024.0, - device.currentAllocatedSize / 1024.0 / 1024.0, - device.recommendedMaxWorkingSetSize / 1024.0 / 1024.0); - - if (device.currentAllocatedSize > device.recommendedMaxWorkingSetSize) { - GGML_LOG_WARN("%s: warning: current allocated size is greater than the recommended max working set size\n", __func__); - } - } else { - GGML_LOG_INFO("%s: allocated buffer, size = %8.2f MiB, (%8.2f)\n", - __func__, - size_aligned / 1024.0 / 1024.0, - device.currentAllocatedSize / 1024.0 / 1024.0); - } -#endif -#endif - GGML_UNUSED(device); - GGML_UNUSED(size_aligned); -} - -// common method for allocating shread or private Metal buffers -static ggml_backend_buffer_t ggml_backend_metal_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size, bool shared) { - struct ggml_backend_metal_buffer_context * ctx = calloc(1, sizeof(struct ggml_backend_metal_buffer_context)); - - const size_t size_page = sysconf(_SC_PAGESIZE); - - size_t size_aligned = size; - if ((size_aligned % size_page) != 0) { - size_aligned += (size_page - (size_aligned % size_page)); - } - - struct ggml_backend_metal_device_context * ctx_dev = (struct ggml_backend_metal_device_context *)buft->device->context; - - GGML_ASSERT(ctx_dev->mtl_device != nil); - - id device = ctx_dev->mtl_device; - - // allocate shared buffer if the device supports it and it is required by the buffer type - if (ctx_dev->use_shared_buffers && shared) { - ctx->all_data = ggml_metal_host_malloc(size_aligned); - ctx->is_shared = true; - } else { - // dummy, non-NULL value - we'll populate this after creating the Metal buffer below - ctx->all_data = (void *) 0x000000400ULL; - ctx->is_shared = false; - } - ctx->all_size = size_aligned; - - ctx->device = device; - ctx->queue = ctx_dev->mtl_queue; - - ctx->n_buffers = 1; - - if (ctx->all_data != NULL) { - ctx->buffers[0].size = size; - ctx->buffers[0].metal = nil; - - if (size_aligned > 0) { - if (ctx_dev->use_shared_buffers) { - ctx->buffers[0].metal = [device newBufferWithBytesNoCopy:ctx->all_data - length:size_aligned - options:MTLResourceStorageModeShared - deallocator:nil]; - } else { - ctx->buffers[0].metal = [device newBufferWithLength:size_aligned options:MTLResourceStorageModePrivate]; - - ctx->all_data = (void *) (ctx->buffers[0].metal.gpuAddress); - } - } - - ctx->buffers[0].data = ctx->all_data; - } - - if (size_aligned > 0 && (ctx->all_data == NULL || ctx->buffers[0].metal == nil)) { - GGML_LOG_ERROR("%s: error: failed to allocate buffer, size = %8.2f MiB\n", __func__, size_aligned / 1024.0 / 1024.0); - free(ctx); - return NULL; - } - - if (!ggml_backend_metal_buffer_rset_init(ctx, ctx_dev, device)) { - GGML_LOG_ERROR("%s: error: failed to initialize residency set\n", __func__); - free(ctx); - return NULL; - } - - //ggml_backend_metal_log_allocated_size(device, size_aligned); - - struct ggml_backend_buffer_i buf_i = ctx->is_shared ? ggml_backend_metal_buffer_shared_i : ggml_backend_metal_buffer_private_i; - - return ggml_backend_buffer_init(buft, buf_i, ctx, size); -} - -static size_t ggml_backend_metal_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const struct ggml_tensor * tensor) { - size_t res = ggml_nbytes(tensor); - - // some operations require additional memory for fleeting data: - switch (tensor->op) { - case GGML_OP_MUL_MAT_ID: - { - res += ggml_metal_mul_mat_id_extra_tpe(tensor); - res += ggml_metal_mul_mat_id_extra_ids(tensor); - } break; - case GGML_OP_FLASH_ATTN_EXT: - { - if (ggml_metal_flash_attn_ext_use_vec(tensor)) { - res += ggml_metal_flash_attn_ext_extra_tmp(tensor); - } - } break; - default: - break; - } - - return res; - - GGML_UNUSED(buft); -} - -// default (shared) buffer type - -static const char * ggml_backend_metal_buffer_type_shared_get_name(ggml_backend_buffer_type_t buft) { - return "Metal"; - - GGML_UNUSED(buft); -} - -static ggml_backend_buffer_t ggml_backend_metal_buffer_type_shared_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) { - return ggml_backend_metal_buffer_type_alloc_buffer(buft, size, true); -} - -static size_t ggml_backend_metal_buffer_type_shared_get_alignment(ggml_backend_buffer_type_t buft) { - return 32; - - GGML_UNUSED(buft); -} - -static size_t ggml_backend_metal_buffer_type_shared_get_max_size(ggml_backend_buffer_type_t buft) { - const size_t max_size = ((struct ggml_backend_metal_device_context *)buft->device->context)->max_size; - - return max_size; -} - -static size_t ggml_backend_metal_buffer_type_shared_get_alloc_size(ggml_backend_buffer_type_t buft, const struct ggml_tensor * tensor) { - return ggml_backend_metal_buffer_type_get_alloc_size(buft, tensor); -} - -static bool ggml_backend_metal_buffer_type_shared_is_host(ggml_backend_buffer_type_t buft) { - return false; - - GGML_UNUSED(buft); -} - -static ggml_backend_buffer_type_t ggml_backend_metal_buffer_type_shared(void) { - static struct ggml_backend_buffer_type ggml_backend_buffer_type_metal = { - /* .iface = */ { - /* .get_name = */ ggml_backend_metal_buffer_type_shared_get_name, - /* .alloc_buffer = */ ggml_backend_metal_buffer_type_shared_alloc_buffer, - /* .get_alignment = */ ggml_backend_metal_buffer_type_shared_get_alignment, - /* .get_max_size = */ ggml_backend_metal_buffer_type_shared_get_max_size, - /* .get_alloc_size = */ ggml_backend_metal_buffer_type_shared_get_alloc_size, - /* .is_host = */ ggml_backend_metal_buffer_type_shared_is_host, - }, - /* .device = */ &g_ggml_backend_metal_device, - /* .context = */ NULL, - }; - - return &ggml_backend_buffer_type_metal; -} - -// default (private) buffer type - -static const char * ggml_backend_metal_buffer_type_private_get_name(ggml_backend_buffer_type_t buft) { - return "Metal_Private"; - - GGML_UNUSED(buft); -} - -static ggml_backend_buffer_t ggml_backend_metal_buffer_type_private_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) { - return ggml_backend_metal_buffer_type_alloc_buffer(buft, size, false); -} - -static size_t ggml_backend_metal_buffer_type_private_get_alignment(ggml_backend_buffer_type_t buft) { - return 32; - - GGML_UNUSED(buft); -} - -static size_t ggml_backend_metal_buffer_type_private_get_max_size(ggml_backend_buffer_type_t buft) { - const size_t max_size = ((struct ggml_backend_metal_device_context *)buft->device->context)->max_size; - - return max_size; -} - -static size_t ggml_backend_metal_buffer_type_private_get_alloc_size(ggml_backend_buffer_type_t buft, const struct ggml_tensor * tensor) { - return ggml_backend_metal_buffer_type_get_alloc_size(buft, tensor); -} - -static bool ggml_backend_metal_buffer_type_private_is_host(ggml_backend_buffer_type_t buft) { - return false; - - GGML_UNUSED(buft); -} - -static ggml_backend_buffer_type_t ggml_backend_metal_buffer_type_private(void) { - static struct ggml_backend_buffer_type ggml_backend_buffer_type_metal = { - /* .iface = */ { - /* .get_name = */ ggml_backend_metal_buffer_type_private_get_name, - /* .alloc_buffer = */ ggml_backend_metal_buffer_type_private_alloc_buffer, - /* .get_alignment = */ ggml_backend_metal_buffer_type_private_get_alignment, - /* .get_max_size = */ ggml_backend_metal_buffer_type_private_get_max_size, - /* .get_alloc_size = */ ggml_backend_metal_buffer_type_private_get_alloc_size, - /* .is_host = */ ggml_backend_metal_buffer_type_private_is_host, - }, - /* .device = */ &g_ggml_backend_metal_device, - /* .context = */ NULL, - }; - - return &ggml_backend_buffer_type_metal; -} - -// mapped buffer type - -static const char * ggml_backend_metal_buffer_type_mapped_get_name(ggml_backend_buffer_type_t buft) { - return "Metal_Mapped"; - - GGML_UNUSED(buft); -} - -static ggml_backend_buffer_t ggml_backend_metal_buffer_type_mapped_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) { - // for mapped buffers, prefer shared memory - return ggml_backend_metal_buffer_type_alloc_buffer(buft, size, true); -} - -static size_t ggml_backend_metal_buffer_type_mapped_get_alignment(ggml_backend_buffer_type_t buft) { - return 32; - - GGML_UNUSED(buft); -} - -static size_t ggml_backend_metal_buffer_type_mapped_get_max_size(ggml_backend_buffer_type_t buft) { - const size_t max_size = ((struct ggml_backend_metal_device_context *)buft->device->context)->max_size; - - return max_size; -} - -static size_t ggml_backend_metal_buffer_type_mapped_get_alloc_size(ggml_backend_buffer_type_t buft, const struct ggml_tensor * tensor) { - return ggml_backend_metal_buffer_type_get_alloc_size(buft, tensor); -} - -static bool ggml_backend_metal_buffer_type_mapped_is_host(ggml_backend_buffer_type_t buft) { - return false; - - GGML_UNUSED(buft); -} - -static ggml_backend_buffer_type_t ggml_backend_metal_buffer_type_mapped(void) { - // note: not obvious, but this buffer type still needs to implement .alloc_buffer: - // https://github.com/ggml-org/llama.cpp/pull/15832#discussion_r2333177099 - static struct ggml_backend_buffer_type ggml_backend_buffer_type_mapped_metal = { - /* .iface = */ { - /* .get_name = */ ggml_backend_metal_buffer_type_mapped_get_name, - /* .alloc_buffer = */ ggml_backend_metal_buffer_type_mapped_alloc_buffer, - /* .get_alignment = */ ggml_backend_metal_buffer_type_mapped_get_alignment, - /* .get_max_size = */ ggml_backend_metal_buffer_type_mapped_get_max_size, - /* .get_alloc_size = */ ggml_backend_metal_buffer_type_mapped_get_alloc_size, - /* .is_host = */ ggml_backend_metal_buffer_type_mapped_is_host, - }, - /* .device = */ &g_ggml_backend_metal_device, - /* .context = */ NULL, - }; - - return &ggml_backend_buffer_type_mapped_metal; -} - -// backend - -static const char * ggml_backend_metal_name(ggml_backend_t backend) { - return "Metal"; - - GGML_UNUSED(backend); -} - -static void ggml_backend_metal_free(ggml_backend_t backend) { - struct ggml_backend_metal_context * ctx = backend->context; - - ggml_metal_free(ctx); - - free(backend); -} - -static void ggml_backend_metal_synchronize(ggml_backend_t backend) { - struct ggml_backend_metal_context * ctx = backend->context; - - // wait for any backend operations to finish - if (ctx->cmd_buf_last) { - [ctx->cmd_buf_last waitUntilCompleted]; - ctx->cmd_buf_last = nil; - } - - // release any completed command buffers - if (ctx->cmd_bufs_ext.count > 0) { - for (size_t i = 0; i < ctx->cmd_bufs_ext.count; ++i) { - id cmd_buf = ctx->cmd_bufs_ext[i]; - - MTLCommandBufferStatus status = [cmd_buf status]; - if (status != MTLCommandBufferStatusCompleted) { - GGML_LOG_ERROR("%s: error: command buffer %d failed with status %d\n", __func__, (int) i, (int) status); - if (status == MTLCommandBufferStatusError) { - GGML_LOG_ERROR("error: %s\n", [[cmd_buf error].localizedDescription UTF8String]); - } - GGML_ABORT("fatal error"); - } - - [cmd_buf release]; - } - - [ctx->cmd_bufs_ext removeAllObjects]; - } -} - -static void ggml_backend_metal_set_tensor_async(ggml_backend_t backend, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size) { - struct ggml_backend_metal_context * ctx = backend->context; - struct ggml_backend_metal_device_context * ctx_dev = backend->device->context; - - @autoreleasepool { - id device = ctx_dev->mtl_device; - - // wrap the source data into a Metal buffer - id buf_src = [device newBufferWithBytes:data - length:size - options:MTLResourceStorageModeShared]; - - size_t buf_dst_offset = 0; - id buf_dst = ggml_metal_get_buffer(tensor, &buf_dst_offset); - - if (buf_dst == nil) { - GGML_ABORT("%s: failed to find buffer for tensor '%s'\n", __func__, tensor->name); - } - - buf_dst_offset += offset; - - // 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 commandBufferWithUnretainedReferences]; - id encoder = [cmd_buf blitCommandEncoder]; - - [encoder copyFromBuffer:buf_src - sourceOffset:0 - toBuffer:buf_dst - destinationOffset:buf_dst_offset - size:size]; - - [encoder endEncoding]; - [cmd_buf commit]; - - // do not wait here for completion - //[cmd_buf waitUntilCompleted]; - - // instead, remember a reference to the command buffer and wait for it later if needed - [ctx->cmd_bufs_ext addObject:cmd_buf]; - ctx->cmd_buf_last = cmd_buf; - - [cmd_buf retain]; - } -} - -static void ggml_backend_metal_get_tensor_async(ggml_backend_t backend, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size) { - struct ggml_backend_metal_context * ctx = backend->context; - struct ggml_backend_metal_device_context * ctx_dev = backend->device->context; - - @autoreleasepool { - id device = ctx_dev->mtl_device; - - id buf_dst = [device newBufferWithBytesNoCopy:data - length:size - options:MTLResourceStorageModeShared - deallocator:nil]; - - size_t buf_src_offset = 0; - id buf_src = ggml_metal_get_buffer(tensor, &buf_src_offset); - - if (buf_src == nil) { - GGML_ABORT("%s: failed to find buffer for tensor '%s'\n", __func__, tensor->name); - } - - buf_src_offset += offset; - - // 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 commandBufferWithUnretainedReferences]; - id encoder = [cmd_buf blitCommandEncoder]; - - [encoder copyFromBuffer:buf_src - sourceOffset:buf_src_offset - toBuffer:buf_dst - destinationOffset:0 - size:size]; - - [encoder endEncoding]; - [cmd_buf commit]; - - // do not wait here for completion - //[cmd_buf waitUntilCompleted]; - - // instead, remember a reference to the command buffer and wait for it later if needed - [ctx->cmd_bufs_ext addObject:cmd_buf]; - ctx->cmd_buf_last = cmd_buf; - - [cmd_buf retain]; - } -} - -static bool ggml_backend_metal_cpy_tensor_async(ggml_backend_t backend_src, ggml_backend_t backend_dst, const struct ggml_tensor * src, struct ggml_tensor * dst) { - return false; - - GGML_UNUSED(backend_src); - GGML_UNUSED(backend_dst); - GGML_UNUSED(src); - GGML_UNUSED(dst); -} - -static enum ggml_status ggml_backend_metal_graph_compute(ggml_backend_t backend, struct ggml_cgraph * cgraph) { - return ggml_metal_graph_compute(backend, cgraph); -} - -static void ggml_backend_metal_graph_optimize(ggml_backend_t backend, struct ggml_cgraph * cgraph) { - struct ggml_backend_metal_device_context * ctx_dev = backend->device->context; - - //const int64_t t_start = ggml_time_us(); - - if (ctx_dev->use_graph_optimize) { - ggml_metal_graph_optimize(cgraph); - } - - //printf("%s: graph optimize took %.3f ms\n", __func__, (ggml_time_us() - t_start) / 1000.0); -} - -static void ggml_backend_metal_set_n_cb(ggml_backend_t backend, int n_cb) { - GGML_ASSERT(ggml_backend_is_metal(backend)); - - struct ggml_backend_metal_context * ctx = (struct ggml_backend_metal_context *)backend->context; - - if (ctx->n_cb != n_cb) { - ctx->n_cb = MIN(n_cb, GGML_METAL_MAX_COMMAND_BUFFERS); - - if (ctx->n_cb > 2) { - GGML_LOG_WARN("%s: n_cb = %d, using n_cb > 2 is not recommended and can degrade the performance in some cases\n", __func__, n_cb); - } - } - - if (ctx->encode_async) { - Block_release(ctx->encode_async); - } - - ctx->encode_async = Block_copy(^(size_t iter) { - const int cb_idx = iter; - const int n_cb_l = ctx->n_cb; - - const int n_nodes_0 = ctx->n_nodes_0; - const int n_nodes_1 = ctx->n_nodes_1; - - const int n_nodes_per_cb = ctx->n_nodes_per_cb; - - id cmd_buf = ctx->cmd_bufs[cb_idx].obj; - struct ggml_mem_ranges * mem_ranges = ctx->cmd_bufs[cb_idx].mem_ranges; - - if (mem_ranges) { - ggml_mem_ranges_reset(mem_ranges); - } - - id encoder; - - struct ggml_backend_metal_device_context * ctx_dev = backend->device->context; - - if (ctx_dev->use_concurrency) { - encoder = [cmd_buf computeCommandEncoderWithDispatchType: MTLDispatchTypeConcurrent]; - } else { - encoder = [cmd_buf computeCommandEncoder]; - } - - int node_start = 0; - int node_end = n_nodes_0; - - if (cb_idx < n_cb_l) { - node_start = n_nodes_0 + ( (cb_idx + 0) * n_nodes_per_cb); - node_end = n_nodes_0 + (MIN((cb_idx == n_cb_l - 1) ? n_nodes_1 : (cb_idx + 1) * n_nodes_per_cb, n_nodes_1)); - } - - const bool should_capture = ctx->capture_next_compute; - - struct ggml_metal_encode_context ctx_enc = { - /*.backend =*/ backend, - /*.encoder =*/ encoder, - /*.mem_ranges =*/ mem_ranges, - }; - - for (int idx = node_start; idx < node_end;) { - if (should_capture) { - [encoder pushDebugGroup:[NSString stringWithCString:ggml_op_desc(ggml_graph_node(ctx->gf, idx)) encoding:NSUTF8StringEncoding]]; - } - - const int res = ggml_metal_encode_node(&ctx_enc, idx, node_end); - if (idx + res > node_end) { - GGML_ABORT("fusion error: nodes spanning multiple encoders have been fused. this indicates a bug in the fusion logic %s", - "https://github.com/ggml-org/llama.cpp/pull/14849"); - } - - if (should_capture) { - [encoder popDebugGroup]; - } - - if (res == 0) { - break; - } - - idx += res; - } - - [encoder endEncoding]; - - if (cb_idx < 2 || ctx->abort_callback == NULL) { - [cmd_buf commit]; - } - }); -} - -static struct ggml_backend_i ggml_backend_metal_i = { - /* .get_name = */ ggml_backend_metal_name, - /* .free = */ ggml_backend_metal_free, - /* .set_tensor_async = */ ggml_backend_metal_set_tensor_async, - /* .get_tensor_async = */ ggml_backend_metal_get_tensor_async, - /* .cpy_tensor_async = */ ggml_backend_metal_cpy_tensor_async, // only needed for multi-GPU setups - /* .synchronize = */ ggml_backend_metal_synchronize, - /* .graph_plan_create = */ NULL, - /* .graph_plan_free = */ NULL, - /* .graph_plan_update = */ NULL, - /* .graph_plan_compute = */ NULL, - /* .graph_compute = */ ggml_backend_metal_graph_compute, - - // the events API is needed only for multi-GPU setups, so likely no need to implement it for Metal - // in any case, these docs seem relevant if we ever decide to implement it: - // https://developer.apple.com/documentation/metal/mtlcommandbuffer#Synchronizing-Passes-with-Events - /* .event_record = */ NULL, - /* .event_wait = */ NULL, - /* .optimize_graph = */ ggml_backend_metal_graph_optimize, -}; - -static ggml_guid_t ggml_backend_metal_guid(void) { - static ggml_guid guid = { 0x81, 0xa1, 0x8b, 0x1e, 0x71, 0xec, 0x79, 0xed, 0x2b, 0x85, 0xdc, 0x8a, 0x61, 0x98, 0x30, 0xe6 }; - return &guid; -} - -// TODO: remove in the future -ggml_backend_t ggml_backend_metal_init(void) { - ggml_backend_dev_t dev = ggml_backend_reg_dev_get(ggml_backend_metal_reg(), 0); - - struct ggml_backend_metal_context * ctx = ggml_metal_init(dev); - if (ctx == NULL) { - GGML_LOG_ERROR("%s: error: failed to allocate context\n", __func__); - return NULL; - } - - ggml_backend_t backend = malloc(sizeof(struct ggml_backend)); - - *backend = (struct ggml_backend) { - /* .guid = */ ggml_backend_metal_guid(), - /* .interface = */ ggml_backend_metal_i, - /* .device = */ dev, - /* .context = */ ctx, - }; - - ggml_backend_metal_set_n_cb(backend, 1); - - return backend; -} - -bool ggml_backend_is_metal(ggml_backend_t backend) { - return backend != NULL && ggml_guid_matches(backend->guid, ggml_backend_metal_guid()); -} - -void ggml_backend_metal_set_abort_callback(ggml_backend_t backend, ggml_abort_callback abort_callback, void * user_data) { - GGML_ASSERT(ggml_backend_is_metal(backend)); - - struct ggml_backend_metal_context * ctx = (struct ggml_backend_metal_context *)backend->context; - - ctx->abort_callback = abort_callback; - ctx->abort_callback_data = user_data; -} - -bool ggml_backend_metal_supports_family(ggml_backend_t backend, int family) { - GGML_ASSERT(ggml_backend_is_metal(backend)); - - struct ggml_backend_metal_device_context * ctx_dev = backend->device->context; - - GGML_ASSERT(ctx_dev->mtl_device != nil); - - return [ctx_dev->mtl_device supportsFamily:(MTLGPUFamilyApple1 + family - 1)]; -} - -void ggml_backend_metal_capture_next_compute(ggml_backend_t backend) { - GGML_ASSERT(ggml_backend_is_metal(backend)); - - struct ggml_backend_metal_context * ctx = (struct ggml_backend_metal_context *)backend->context; - ctx->capture_next_compute = true; -} - -// backend device - -static const char * ggml_backend_metal_device_get_name(ggml_backend_dev_t dev) { - return "Metal"; - - GGML_UNUSED(dev); -} - -static const char * ggml_backend_metal_device_get_description(ggml_backend_dev_t dev) { - struct ggml_backend_metal_device_context * ctx_dev = (struct ggml_backend_metal_device_context *)dev->context; - - return ctx_dev->name; -} - -static void ggml_backend_metal_device_get_memory(ggml_backend_dev_t dev, size_t * free, size_t * total) { - if (@available(macOS 10.12, iOS 16.0, *)) { - struct ggml_backend_metal_device_context * ctx_dev = (struct ggml_backend_metal_device_context *)dev->context; - id device = ctx_dev->mtl_device; - - *total = device.recommendedMaxWorkingSetSize; - *free = *total - device.currentAllocatedSize; - } else { - *free = 1; - *total = 1; - } -} - -static enum ggml_backend_dev_type ggml_backend_metal_device_get_type(ggml_backend_dev_t dev) { - return GGML_BACKEND_DEVICE_TYPE_GPU; - - GGML_UNUSED(dev); -} - -static void ggml_backend_metal_device_get_props(ggml_backend_dev_t dev, struct ggml_backend_dev_props * props) { - props->name = ggml_backend_metal_device_get_name(dev); - props->description = ggml_backend_metal_device_get_description(dev); - props->type = ggml_backend_metal_device_get_type(dev); - ggml_backend_metal_device_get_memory(dev, &props->memory_free, &props->memory_total); - props->caps = (struct ggml_backend_dev_caps) { - /* .async = */ true, - /* .host_buffer = */ false, - /* .buffer_from_host_ptr = */ true, - /* .events = */ false, - }; -} - -static ggml_backend_t ggml_backend_metal_device_init(ggml_backend_dev_t dev, const char * params) { - struct ggml_backend_metal_context * ctx = ggml_metal_init(dev); - if (ctx == NULL) { - GGML_LOG_ERROR("%s: error: failed to allocate context\n", __func__); - return NULL; - } - - ggml_backend_t backend = malloc(sizeof(struct ggml_backend)); - - *backend = (struct ggml_backend) { - /* .guid = */ ggml_backend_metal_guid(), - /* .interface = */ ggml_backend_metal_i, - /* .device = */ dev, - /* .context = */ ctx, - }; - - ggml_backend_metal_set_n_cb(backend, 1); - - return backend; - - GGML_UNUSED(params); -} - -static ggml_backend_buffer_type_t ggml_backend_metal_device_get_buffer_type(ggml_backend_dev_t dev) { - struct ggml_backend_metal_device_context * ctx_dev = dev->context; - - return ctx_dev->use_shared_buffers ? ggml_backend_metal_buffer_type_shared() : ggml_backend_metal_buffer_type_private(); -} - -static ggml_backend_buffer_t ggml_backend_metal_device_buffer_mapped(ggml_backend_dev_t dev, void * ptr, size_t size, size_t max_tensor_size) { - struct ggml_backend_metal_buffer_context * ctx = calloc(1, sizeof(struct ggml_backend_metal_buffer_context)); - - ctx->all_data = ptr; - ctx->all_size = size; - - ctx->is_shared = true; - - ctx->n_buffers = 0; - - const size_t size_page = sysconf(_SC_PAGESIZE); - - // page-align the data ptr - { - const uintptr_t offs = (uintptr_t) ptr % size_page; - ptr = (void *) ((char *) ptr - offs); - size += offs; - } - - size_t size_aligned = size; - if ((size_aligned % size_page) != 0) { - size_aligned += (size_page - (size_aligned % size_page)); - } - - struct ggml_backend_metal_device_context * ctx_dev = (struct ggml_backend_metal_device_context *)dev->context; - - GGML_ASSERT(ctx_dev->mtl_device != nil); - - id device = ctx_dev->mtl_device; - - ctx->device = device; - ctx->queue = ctx_dev->mtl_queue; - - // the buffer fits into the max buffer size allowed by the device - if (size_aligned <= device.maxBufferLength) { - ctx->buffers[ctx->n_buffers].data = ptr; - ctx->buffers[ctx->n_buffers].size = size; - ctx->buffers[ctx->n_buffers].metal = nil; - - if (size_aligned > 0) { - ctx->buffers[ctx->n_buffers].metal = [device newBufferWithBytesNoCopy:ptr length:size_aligned options:MTLResourceStorageModeShared deallocator:nil]; - - if (ctx->buffers[ctx->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); - return false; - } - } - - ggml_backend_metal_log_allocated_size(device, size_aligned); - - ++ctx->n_buffers; - } else { - // this overlap between the views will guarantee that the tensor with the maximum size will fully fit into - // one of the views - const size_t size_ovlp = ((max_tensor_size + size_page - 1) / size_page + 1) * size_page; // round-up 2 pages just in case - const size_t size_step = device.maxBufferLength - size_ovlp; - const size_t size_view = device.maxBufferLength; - - for (size_t i = 0; i < size; i += size_step) { - const size_t size_step_aligned = (i + size_view <= size) ? size_view : (size_aligned - i); - - ctx->buffers[ctx->n_buffers].data = (void *) ((uint8_t *) ptr + i); - ctx->buffers[ctx->n_buffers].size = size_step_aligned; - ctx->buffers[ctx->n_buffers].metal = nil; - - if (size_step_aligned > 0) { - ctx->buffers[ctx->n_buffers].metal = [device newBufferWithBytesNoCopy:(void *) ((uint8_t *) ptr + i) length:size_step_aligned options:MTLResourceStorageModeShared deallocator:nil]; - - if (ctx->buffers[ctx->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); - return false; - } - } - - ggml_backend_metal_log_allocated_size(device, size_step_aligned); - - if (i + size_step < size) { - GGML_LOG_INFO("\n"); - } - - ++ctx->n_buffers; - } - } - - if (!ggml_backend_metal_buffer_rset_init(ctx, ctx_dev, device)) { - GGML_LOG_ERROR("%s: error: failed to initialize residency set\n", __func__); - free(ctx); - return NULL; - } - - return ggml_backend_buffer_init(ggml_backend_metal_buffer_type_mapped(), ggml_backend_metal_buffer_shared_i, ctx, size); -} - -static bool ggml_backend_metal_device_supports_op(ggml_backend_dev_t dev, const struct ggml_tensor * op) { - struct ggml_backend_metal_device_context * ctx_dev = dev->context; - - return ggml_metal_supports_op(ctx_dev, op); -} - -static bool ggml_backend_metal_device_supports_buft(ggml_backend_dev_t dev, ggml_backend_buffer_type_t buft) { - return - buft->iface.get_name == ggml_backend_metal_buffer_type_shared_get_name || - buft->iface.get_name == ggml_backend_metal_buffer_type_private_get_name || - buft->iface.get_name == ggml_backend_metal_buffer_type_mapped_get_name; - - GGML_UNUSED(dev); -} - -static int64_t get_op_batch_size(const struct ggml_tensor * op) { - switch (op->op) { - case GGML_OP_MUL_MAT: - return op->ne[1]; - case GGML_OP_MUL_MAT_ID: - return op->ne[2]; - default: - return ggml_nrows(op); - } -} - -static bool ggml_backend_metal_device_offload_op(ggml_backend_dev_t dev, const struct ggml_tensor * op) { - const int min_batch_size = 32; - - return (op->op == GGML_OP_MUL_MAT || - op->op == GGML_OP_MUL_MAT_ID) && - get_op_batch_size(op) >= min_batch_size; - - GGML_UNUSED(dev); - GGML_UNUSED(op); -} - -static struct ggml_backend_device_i ggml_backend_metal_device_i = { - /* .get_name = */ ggml_backend_metal_device_get_name, - /* .get_description = */ ggml_backend_metal_device_get_description, - /* .get_memory = */ ggml_backend_metal_device_get_memory, - /* .get_type = */ ggml_backend_metal_device_get_type, - /* .get_props = */ ggml_backend_metal_device_get_props, - /* .init_backend = */ ggml_backend_metal_device_init, - /* .get_buffer_type = */ ggml_backend_metal_device_get_buffer_type, - /* .get_host_buffer_type = */ NULL, - /* .buffer_from_host_ptr = */ ggml_backend_metal_device_buffer_mapped, - /* .supports_op = */ ggml_backend_metal_device_supports_op, - /* .supports_buft = */ ggml_backend_metal_device_supports_buft, - /* .offload_op = */ ggml_backend_metal_device_offload_op, - /* .event_new = */ NULL, - /* .event_free = */ NULL, - /* .event_synchronize = */ NULL, -}; - -// backend registry - -static const char * ggml_backend_metal_reg_get_name(ggml_backend_reg_t reg) { - return "Metal"; - - GGML_UNUSED(reg); -} - -static size_t ggml_backend_metal_reg_device_count(ggml_backend_reg_t reg) { - return 1; - - GGML_UNUSED(reg); -} - -static ggml_backend_dev_t ggml_backend_metal_reg_device_get(ggml_backend_reg_t reg, size_t index) { - GGML_ASSERT(index == 0); - - return &g_ggml_backend_metal_device; - - GGML_UNUSED(reg); - GGML_UNUSED(index); -} - -static struct ggml_backend_feature g_ggml_backend_metal_features[] = { -#if defined(GGML_METAL_EMBED_LIBRARY) - { "EMBED_LIBRARY", "1" }, -#endif -#if defined(GGML_METAL_USE_BF16) - { "BF16", "1" }, -#endif - { nil, nil }, -}; - -static struct ggml_backend_feature * ggml_backend_metal_get_features(ggml_backend_reg_t reg) { - return g_ggml_backend_metal_features; - - GGML_UNUSED(reg); -} - -static void * ggml_backend_metal_get_proc_address(ggml_backend_reg_t reg, const char * name) { - if (strcmp(name, "ggml_backend_get_features") == 0) { - return (void *)ggml_backend_metal_get_features; - } - - return NULL; - - GGML_UNUSED(reg); -} -static struct ggml_backend_reg_i ggml_backend_metal_reg_i = { - /* .get_name = */ ggml_backend_metal_reg_get_name, - /* .device_count = */ ggml_backend_metal_reg_device_count, - /* .device_get = */ ggml_backend_metal_reg_device_get, - /* .get_proc_address = */ ggml_backend_metal_get_proc_address, -}; - -// called upon program exit -static void ggml_metal_cleanup(void) { - ggml_backend_metal_device_rel(&g_ggml_ctx_dev_main); -} - -// TODO: make thread-safe -ggml_backend_reg_t ggml_backend_metal_reg(void) { - ggml_backend_metal_device_acq(&g_ggml_ctx_dev_main); - - // register cleanup callback - // TODO: not ideal, but not sure if there is a better way to do this in Objective-C - atexit(ggml_metal_cleanup); - - { - g_ggml_backend_metal_reg = (struct ggml_backend_reg) { - /* .api_version = */ GGML_BACKEND_API_VERSION, - /* .iface = */ ggml_backend_metal_reg_i, - /* .context = */ NULL, - }; - - g_ggml_backend_metal_device = (struct ggml_backend_device) { - /* .iface = */ ggml_backend_metal_device_i, - /* .reg = */ &g_ggml_backend_metal_reg, - /* .context = */ &g_ggml_ctx_dev_main, - }; - } - - return &g_ggml_backend_metal_reg; -} - -GGML_BACKEND_DL_IMPL(ggml_backend_metal_reg) diff --git a/ggml/src/ggml-metal/ggml-metal.metal b/ggml/src/ggml-metal/ggml-metal.metal index 5057e264f6..f34b89e590 100644 --- a/ggml/src/ggml-metal/ggml-metal.metal +++ b/ggml/src/ggml-metal/ggml-metal.metal @@ -27,11 +27,11 @@ using namespace metal; // .../usr/bin/metal -dM -E -c ggml/src/ggml-metal/ggml-metal.metal // .../usr/bin/metal -dM -E -c -target air64-apple-ios14.0 ggml/src/ggml-metal/ggml-metal.metal // -#if __METAL_VERSION__ < 310 && defined(GGML_METAL_USE_BF16) -#undef GGML_METAL_USE_BF16 +#if __METAL_VERSION__ < 310 && defined(GGML_METAL_HAS_BF16) +#undef GGML_METAL_HAS_BF16 #endif -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) typedef matrix bfloat4x4; #endif @@ -87,7 +87,7 @@ void dequantize_f16_t4(device const half4 * src, short il, thread type4 & reg) { reg = (type4)(*(src)); } -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template void dequantize_bf16(device const bfloat4x4 * src, short il, thread type4x4 & reg) { reg = (type4x4)(*src); @@ -1222,53 +1222,78 @@ typedef decltype(kernel_div_row_c4_fuse_impl<1>) kernel_div_row_c4_fuse_t; template [[host_name("kernel_div_row_c4_fuse_1")]] kernel kernel_div_row_c4_fuse_t kernel_div_row_c4_fuse_impl<1>; -kernel void kernel_scale( +kernel void kernel_scale_f32( + constant ggml_metal_kargs_scale & args, device const float * src0, device float * dst, - constant float & scale, - constant float & bias, uint tpig[[thread_position_in_grid]]) { - dst[tpig] = src0[tpig] * scale + bias; + dst[tpig] = src0[tpig] * args.scale + args.bias; } -kernel void kernel_scale_4( +kernel void kernel_scale_f32_4( + constant ggml_metal_kargs_scale & args, device const float4 * src0, device float4 * dst, - constant float & scale, - constant float & bias, uint tpig[[thread_position_in_grid]]) { - dst[tpig] = src0[tpig] * scale + bias; + dst[tpig] = src0[tpig] * args.scale + args.bias; } -kernel void kernel_clamp( +kernel void kernel_clamp_f32( + constant ggml_metal_kargs_clamp & args, device const float * src0, device float * dst, - constant float & min, - constant float & max, uint tpig[[thread_position_in_grid]]) { - dst[tpig] = src0[tpig] < min ? min : (src0[tpig] > max ? max : src0[tpig]); + dst[tpig] = clamp(src0[tpig], args.min, args.max); } -kernel void kernel_relu( +kernel void kernel_clamp_f32_4( + constant ggml_metal_kargs_clamp & args, + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + dst[tpig] = clamp(src0[tpig], args.min, args.max); +} + +kernel void kernel_relu_f32( device const float * src0, device float * dst, uint tpig[[thread_position_in_grid]]) { dst[tpig] = max(0.0f, src0[tpig]); } -kernel void kernel_sigmoid( +kernel void kernel_relu_f32_4( + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + dst[tpig] = max(0.0f, src0[tpig]); +} + +kernel void kernel_sigmoid_f32( device const float * src0, device float * dst, uint tpig[[thread_position_in_grid]]) { dst[tpig] = 1.0f / (1.0f + exp(-src0[tpig])); } -kernel void kernel_tanh( +kernel void kernel_sigmoid_f32_4( + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + dst[tpig] = 1.0f / (1.0f + exp(-src0[tpig])); +} + +kernel void kernel_tanh_f32( device const float * src0, device float * dst, uint tpig[[thread_position_in_grid]]) { - device const float & x = src0[tpig]; - dst[tpig] = precise::tanh(x); + dst[tpig] = precise::tanh(src0[tpig]); +} + +kernel void kernel_tanh_f32_4( + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + dst[tpig] = precise::tanh(src0[tpig]); } constant float GELU_COEF_A = 0.044715f; @@ -1276,7 +1301,7 @@ constant float GELU_QUICK_COEF = -1.702f; constant float SQRT_2_OVER_PI = 0.79788456080286535587989211986876f; constant float SQRT_2_INV = 0.70710678118654752440084436210484f; -kernel void kernel_gelu( +kernel void kernel_gelu_f32( device const float * src0, device float * dst, uint tpig[[thread_position_in_grid]]) { @@ -1285,7 +1310,7 @@ kernel void kernel_gelu( dst[tpig] = 0.5f*x*(1.0f + precise::tanh(SQRT_2_OVER_PI*x*(1.0f + GELU_COEF_A*x*x))); } -kernel void kernel_gelu_4( +kernel void kernel_gelu_f32_4( device const float4 * src0, device float4 * dst, uint tpig[[thread_position_in_grid]]) { @@ -1298,7 +1323,7 @@ kernel void kernel_gelu_4( dst[tpig] = 0.5f*x*(1.0f + precise::tanh(SQRT_2_OVER_PI*x*(1.0f + GELU_COEF_A*x*x))); } -kernel void kernel_gelu_quick( +kernel void kernel_gelu_quick_f32( device const float * src0, device float * dst, uint tpig[[thread_position_in_grid]]) { @@ -1307,7 +1332,7 @@ kernel void kernel_gelu_quick( dst[tpig] = x*(1.0f/(1.0f+exp(GELU_QUICK_COEF*x))); } -kernel void kernel_gelu_quick_4( +kernel void kernel_gelu_quick_f32_4( device const float4 * src0, device float4 * dst, uint tpig[[thread_position_in_grid]]) { @@ -1334,7 +1359,7 @@ T erf_approx(T x) { return sign_x * y; } -kernel void kernel_gelu_erf( +kernel void kernel_gelu_erf_f32( device const float * src0, device float * dst, uint tpig[[thread_position_in_grid]]) { @@ -1343,7 +1368,7 @@ kernel void kernel_gelu_erf( dst[tpig] = 0.5f*x*(1.0f+erf_approx(x*SQRT_2_INV)); } -kernel void kernel_gelu_erf_4( +kernel void kernel_gelu_erf_f32_4( device const float4 * src0, device float4 * dst, uint tpig[[thread_position_in_grid]]) { @@ -1352,7 +1377,7 @@ kernel void kernel_gelu_erf_4( dst[tpig] = 0.5f*x*(1.0f+erf_approx(x*SQRT_2_INV)); } -kernel void kernel_silu( +kernel void kernel_silu_f32( device const float * src0, device float * dst, uint tpig[[thread_position_in_grid]]) { @@ -1360,7 +1385,7 @@ kernel void kernel_silu( dst[tpig] = x / (1.0f + exp(-x)); } -kernel void kernel_silu_4( +kernel void kernel_silu_f32_4( device const float4 * src0, device float4 * dst, uint tpig[[thread_position_in_grid]]) { @@ -1368,99 +1393,202 @@ kernel void kernel_silu_4( dst[tpig] = x / (1.0f + exp(-x)); } -kernel void kernel_elu( +kernel void kernel_elu_f32( device const float * src0, device float * dst, uint tpig[[thread_position_in_grid]]) { - device const float & x = src0[tpig]; + const float x = src0[tpig]; dst[tpig] = (x > 0.0f) ? x : (exp(x) - 1.0f); } -kernel void kernel_sqr( +kernel void kernel_elu_f32_4( + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + const float4 x = src0[tpig]; + dst[tpig][0] = (x[0] > 0.0f) ? x[0] : (exp(x[0]) - 1.0f); + dst[tpig][1] = (x[1] > 0.0f) ? x[1] : (exp(x[1]) - 1.0f); + dst[tpig][2] = (x[2] > 0.0f) ? x[2] : (exp(x[2]) - 1.0f); + dst[tpig][3] = (x[3] > 0.0f) ? x[3] : (exp(x[3]) - 1.0f); +} + +kernel void kernel_sqr_f32( device const float * src0, device float * dst, uint tpig[[thread_position_in_grid]]) { dst[tpig] = src0[tpig] * src0[tpig]; } -kernel void kernel_sqrt( +kernel void kernel_sqr_f32_4( + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + dst[tpig] = src0[tpig] * src0[tpig]; +} + +kernel void kernel_sqrt_f32( device const float * src0, device float * dst, uint tpig[[thread_position_in_grid]]) { dst[tpig] = sqrt(src0[tpig]); } -kernel void kernel_sin( +kernel void kernel_sqrt_f32_4( + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + dst[tpig] = sqrt(src0[tpig]); +} + +kernel void kernel_sin_f32( device const float * src0, device float * dst, uint tpig[[thread_position_in_grid]]) { dst[tpig] = sin(src0[tpig]); } -kernel void kernel_cos( +kernel void kernel_sin_f32_4( + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + dst[tpig] = sin(src0[tpig]); +} + +kernel void kernel_cos_f32( device const float * src0, device float * dst, uint tpig[[thread_position_in_grid]]) { dst[tpig] = cos(src0[tpig]); } -kernel void kernel_neg( +kernel void kernel_cos_f32_4( + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + dst[tpig] = cos(src0[tpig]); +} + +kernel void kernel_log_f32( + device const float * src0, + device float * dst, + uint tpig[[thread_position_in_grid]]) { + dst[tpig] = log(src0[tpig]); +} + +kernel void kernel_log_f32_4( + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + dst[tpig] = log(src0[tpig]); +} + +kernel void kernel_neg_f32( device const float * src0, device float * dst, uint tpig[[thread_position_in_grid]]) { dst[tpig] = -src0[tpig]; } -kernel void kernel_abs( +kernel void kernel_neg_f32_4( + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + dst[tpig] = -src0[tpig]; +} + +kernel void kernel_abs_f32( device const float * src0, device float * dst, uint tpig[[thread_position_in_grid]]) { dst[tpig] = fabs(src0[tpig]); } -kernel void kernel_sgn( - device const float * src0, - device float * dst, +kernel void kernel_abs_f32_4( + device const float4 * src0, + device float4 * dst, uint tpig[[thread_position_in_grid]]) { - device const float & x = src0[tpig]; - dst[tpig] = (x > 0.0f) ? 1.0f : ((x < 0.0f) ? -1.0f : 0.0f); + dst[tpig] = fabs(src0[tpig]); } -kernel void kernel_step( +kernel void kernel_sgn_f32( device const float * src0, device float * dst, uint tpig[[thread_position_in_grid]]) { - dst[tpig] = src0[tpig] > 0.0f ? 1.0f : 0.0f; + dst[tpig] = sign(src0[tpig]); } -kernel void kernel_hardswish( +kernel void kernel_sgn_f32_4( + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + dst[tpig] = sign(src0[tpig]); +} + +kernel void kernel_step_f32( device const float * src0, device float * dst, uint tpig[[thread_position_in_grid]]) { - device const float & x = src0[tpig]; + dst[tpig] = step(0.0f, src0[tpig]); +} + +kernel void kernel_step_f32_4( + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + dst[tpig] = step(0.0f, src0[tpig]); +} + +kernel void kernel_hardswish_f32( + device const float * src0, + device float * dst, + uint tpig[[thread_position_in_grid]]) { + const float x = src0[tpig]; dst[tpig] = x * fmin(1.0f, fmax(0.0f, (x + 3.0f) / 6.0f)); } -kernel void kernel_hardsigmoid( +kernel void kernel_hardswish_f32_4( + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + const float4 x = src0[tpig]; + dst[tpig] = x * fmin(1.0f, fmax(0.0f, (x + 3.0f) / 6.0f)); +} + +kernel void kernel_hardsigmoid_f32( device const float * src0, device float * dst, uint tpig[[thread_position_in_grid]]) { - device const float & x = src0[tpig]; + const float x = src0[tpig]; dst[tpig] = fmin(1.0f, fmax(0.0f, (x + 3.0f) / 6.0f)); } -kernel void kernel_exp( +kernel void kernel_hardsigmoid_f32_4( + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + const float4 x = src0[tpig]; + dst[tpig] = fmin(1.0f, fmax(0.0f, (x + 3.0f) / 6.0f)); +} + +kernel void kernel_exp_f32( device const float * src0, device float * dst, uint tpig[[thread_position_in_grid]]) { dst[tpig] = exp(src0[tpig]); } -kernel void kernel_reglu( +kernel void kernel_exp_f32_4( + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + dst[tpig] = exp(src0[tpig]); +} + +kernel void kernel_reglu_f32( + constant ggml_metal_kargs_glu & args, device const char * src0, device const char * src1, device char * dst, - constant ggml_metal_kargs_glu & args, uint tgpig[[threadgroup_position_in_grid]], uint tpitg[[thread_position_in_threadgroup]], uint ntg[[threads_per_threadgroup]]) { @@ -1476,11 +1604,11 @@ kernel void kernel_reglu( } } -kernel void kernel_geglu( +kernel void kernel_geglu_f32( + constant ggml_metal_kargs_glu & args, device const char * src0, device const char * src1, device char * dst, - constant ggml_metal_kargs_glu & args, uint tgpig[[threadgroup_position_in_grid]], uint tpitg[[thread_position_in_threadgroup]], uint ntg[[threads_per_threadgroup]]) { @@ -1498,11 +1626,11 @@ kernel void kernel_geglu( } } -kernel void kernel_swiglu( +kernel void kernel_swiglu_f32( + constant ggml_metal_kargs_glu & args, device const char * src0, device const char * src1, device char * dst, - constant ggml_metal_kargs_glu & args, uint tgpig[[threadgroup_position_in_grid]], uint tpitg[[thread_position_in_threadgroup]], uint ntg[[threads_per_threadgroup]]) { @@ -1520,11 +1648,11 @@ kernel void kernel_swiglu( } } -kernel void kernel_swiglu_oai( +kernel void kernel_swiglu_oai_f32( + constant ggml_metal_kargs_glu & args, device const char * src0, device const char * src1, device char * dst, - constant ggml_metal_kargs_glu & args, uint tgpig[[threadgroup_position_in_grid]], uint tpitg[[thread_position_in_threadgroup]], uint ntg[[threads_per_threadgroup]]) { @@ -1546,11 +1674,11 @@ kernel void kernel_swiglu_oai( } } -kernel void kernel_geglu_erf( +kernel void kernel_geglu_erf_f32( + constant ggml_metal_kargs_glu & args, device const char * src0, device const char * src1, device char * dst, - constant ggml_metal_kargs_glu & args, uint tgpig[[threadgroup_position_in_grid]], uint tpitg[[thread_position_in_threadgroup]], uint ntg[[threads_per_threadgroup]]) { @@ -1568,11 +1696,11 @@ kernel void kernel_geglu_erf( } } -kernel void kernel_geglu_quick( +kernel void kernel_geglu_quick_f32( + constant ggml_metal_kargs_glu & args, device const char * src0, device const char * src1, device char * dst, - constant ggml_metal_kargs_glu & args, uint tgpig[[threadgroup_position_in_grid]], uint tpitg[[thread_position_in_threadgroup]], uint ntg[[threads_per_threadgroup]]) { @@ -1642,16 +1770,16 @@ kernel void kernel_sum_rows( typedef decltype(kernel_sum_rows) kernel_sum_rows_t; -template [[host_name("kernel_sum_rows")]] kernel kernel_sum_rows_t kernel_sum_rows; -template [[host_name("kernel_mean")]] kernel kernel_sum_rows_t kernel_sum_rows; +template [[host_name("kernel_sum_rows_f32")]] kernel kernel_sum_rows_t kernel_sum_rows; +template [[host_name("kernel_mean_f32")]] kernel kernel_sum_rows_t kernel_sum_rows; template kernel void kernel_soft_max( + constant ggml_metal_kargs_soft_max & args, device const char * src0, device const char * src1, device const char * src2, device char * dst, - constant ggml_metal_kargs_soft_max & args, threadgroup float * buf [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], @@ -1753,11 +1881,11 @@ kernel void kernel_soft_max( template kernel void kernel_soft_max_4( + constant ggml_metal_kargs_soft_max & args, device const char * src0, device const char * src1, device const char * src2, device char * dst, - constant ggml_metal_kargs_soft_max & args, threadgroup float * buf [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], @@ -1867,53 +1995,12 @@ template [[host_name("kernel_soft_max_f32")]] kernel kernel_soft_max_t kerne template [[host_name("kernel_soft_max_f16_4")]] kernel kernel_soft_max_4_t kernel_soft_max_4; template [[host_name("kernel_soft_max_f32_4")]] kernel kernel_soft_max_4_t kernel_soft_max_4; -kernel void kernel_diag_mask_inf( - device const float * src0, - device float * dst, - constant ggml_metal_kargs_diag_mask_inf & args, - uint3 tpig[[thread_position_in_grid]]) { - const int64_t i02 = tpig[2]; - const int64_t i01 = tpig[1]; - const int64_t i00 = tpig[0]; - - if (i00 > args.n_past + i01) { - dst[i02*args.ne01*args.ne00 + i01*args.ne00 + i00] = -INFINITY; - } else { - dst[i02*args.ne01*args.ne00 + i01*args.ne00 + i00] = src0[i02*args.ne01*args.ne00 + i01*args.ne00 + i00]; - } -} - -kernel void kernel_diag_mask_inf_8( - device const float4 * src0, - device float4 * dst, - constant ggml_metal_kargs_diag_mask_inf & args, - uint3 tpig[[thread_position_in_grid]]) { - - const int64_t i = 2*tpig[0]; - - dst[i+0] = src0[i+0]; - dst[i+1] = src0[i+1]; - int64_t i4 = 4*i; - const int64_t i02 = i4/(args.ne00*args.ne01); i4 -= i02*args.ne00*args.ne01; - const int64_t i01 = i4/(args.ne00); i4 -= i01*args.ne00; - const int64_t i00 = i4; - for (int k = 3; k >= 0; --k) { - if (i00 + 4 + k <= args.n_past + i01) { - break; - } - dst[i+1][k] = -INFINITY; - if (i00 + k > args.n_past + i01) { - dst[i][k] = -INFINITY; - } - } -} - // ref: ggml.c:ggml_compute_forward_ssm_conv_f32 -kernel void kernel_ssm_conv_f32( +kernel void kernel_ssm_conv_f32_f32( + constant ggml_metal_kargs_ssm_conv & args, device const void * src0, device const void * src1, device float * dst, - constant ggml_metal_kargs_ssm_conv & args, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], uint3 ntg[[threads_per_threadgroup]]) { @@ -1942,6 +2029,7 @@ kernel void kernel_ssm_conv_f32( // ref: ggml.c:ggml_compute_forward_ssm_scan_f32, Mamba-1 part kernel void kernel_ssm_scan_f32( + constant ggml_metal_kargs_ssm_scan & args, device const void * src0, device const void * src1, device const void * src2, @@ -1951,7 +2039,6 @@ kernel void kernel_ssm_scan_f32( device const void * src6, device float * dst, threadgroup float * shared [[threadgroup(0)]], - constant ggml_metal_kargs_ssm_scan & args, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]], @@ -2057,7 +2144,8 @@ kernel void kernel_ssm_scan_f32( } // ref: ggml.c:ggml_compute_forward_ssm_scan_f32, Mamba-2 part -kernel void kernel_ssm_scan_f32_group( +kernel void kernel_ssm_scan_group_f32( + constant ggml_metal_kargs_ssm_scan & args, device const void * src0, device const void * src1, device const void * src2, @@ -2067,7 +2155,6 @@ kernel void kernel_ssm_scan_f32_group( device const void * src6, device float * dst, threadgroup float * shared [[threadgroup(0)]], - constant ggml_metal_kargs_ssm_scan & args, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]], @@ -2346,24 +2433,22 @@ kernel void kernel_rwkv_wkv7_f32( } } -kernel void kernel_argmax( - device const void * x, - device int32_t * dst, - constant int64_t & ncols, - constant uint64_t & nb01, - threadgroup float * shared_maxval [[threadgroup(0)]], - threadgroup int32_t * shared_argmax [[threadgroup(1)]], +kernel void kernel_argmax_f32( + constant ggml_metal_kargs_argmax & args, + device const char * src0, + device char * dst, + threadgroup char * shmem [[threadgroup(0)]], uint tgpig[[threadgroup_position_in_grid]], uint tpitg[[thread_position_in_threadgroup]], uint sgitg[[simdgroup_index_in_threadgroup]], uint tiisg[[thread_index_in_simdgroup]], uint ntg[[threads_per_threadgroup]]) { - device const float * x_row = (device const float *) ((device const char *) x + tgpig * nb01); + device const float * x_row = (device const float *) ((device const char *) src0 + tgpig * args.nb01); float lmax = -INFINITY; int32_t larg = -1; - for (int i00 = tpitg; i00 < ncols; i00 += ntg) { + for (int i00 = tpitg; i00 < args.ne00; i00 += ntg) { if (x_row[i00] > lmax) { lmax = x_row[i00]; larg = i00; @@ -2374,6 +2459,11 @@ kernel void kernel_argmax( float max_val = simd_max(lmax); int32_t arg_val = simd_max(select(-1, larg, lmax == max_val)); + device int32_t * dst_i32 = (device int32_t *) dst; + + threadgroup float * shared_maxval = (threadgroup float *) shmem; + threadgroup int32_t * shared_argmax = (threadgroup int32_t *) shmem + N_SIMDWIDTH; + if (ntg > N_SIMDWIDTH) { if (sgitg == 0) { shared_maxval[tiisg] = -INFINITY; @@ -2395,15 +2485,15 @@ kernel void kernel_argmax( float max_val_reduced = simd_max(max_val); int32_t arg_val_reduced = simd_max(select(-1, arg_val, max_val == max_val_reduced)); - dst[tgpig] = arg_val_reduced; + dst_i32[tgpig] = arg_val_reduced; return; } - dst[tgpig] = arg_val; + dst_i32[tgpig] = arg_val; } -kernel void kernel_norm( +kernel void kernel_norm_f32( constant ggml_metal_kargs_norm & args, device const char * src0, device char * dst, @@ -2537,11 +2627,11 @@ kernel void kernel_rms_norm_fuse_impl( typedef decltype(kernel_rms_norm_fuse_impl<1>) kernel_rms_norm_fuse_t; -template [[host_name("kernel_rms_norm")]] kernel kernel_rms_norm_fuse_t kernel_rms_norm_fuse_impl<1>; -template [[host_name("kernel_rms_norm_mul")]] kernel kernel_rms_norm_fuse_t kernel_rms_norm_fuse_impl<2>; -template [[host_name("kernel_rms_norm_mul_add")]] kernel kernel_rms_norm_fuse_t kernel_rms_norm_fuse_impl<3>; +template [[host_name("kernel_rms_norm_f32")]] kernel kernel_rms_norm_fuse_t kernel_rms_norm_fuse_impl<1>; +template [[host_name("kernel_rms_norm_mul_f32")]] kernel kernel_rms_norm_fuse_t kernel_rms_norm_fuse_impl<2>; +template [[host_name("kernel_rms_norm_mul_add_f32")]] kernel kernel_rms_norm_fuse_t kernel_rms_norm_fuse_impl<3>; -kernel void kernel_l2_norm( +kernel void kernel_l2_norm_f32( constant ggml_metal_kargs_l2_norm & args, device const char * src0, device char * dst, @@ -2584,10 +2674,10 @@ kernel void kernel_l2_norm( } } -kernel void kernel_group_norm( +kernel void kernel_group_norm_f32( + constant ggml_metal_kargs_group_norm & args, device const float * src0, device float * dst, - constant ggml_metal_kargs_group_norm & args, threadgroup float * buf [[threadgroup(0)]], uint tgpig[[threadgroup_position_in_grid]], uint tpitg[[thread_position_in_threadgroup]], @@ -2595,7 +2685,7 @@ kernel void kernel_group_norm( uint tiisg[[thread_index_in_simdgroup]], uint ntg[[threads_per_threadgroup]]) { const int64_t ne = args.ne00*args.ne01*args.ne02; - const int64_t gs = args.ne00*args.ne01*((args.ne02 + args.n_groups - 1) / args.n_groups); + const int64_t gs = args.ne00*args.ne01*((args.ne02 + args.ngrp - 1) / args.ngrp); int start = tgpig * gs; int end = start + gs; @@ -3407,7 +3497,7 @@ typedef decltype(kernel_mul_mv) mul_mv_t; template [[host_name("kernel_mul_mv_f32_f32")]] kernel mul_mv_t kernel_mul_mv; template [[host_name("kernel_mul_mv_f16_f32")]] kernel mul_mv_t kernel_mul_mv; template [[host_name("kernel_mul_mv_f16_f16")]] kernel mul_mv_t kernel_mul_mv; -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template [[host_name("kernel_mul_mv_bf16_f32")]] kernel mul_mv_t kernel_mul_mv; template [[host_name("kernel_mul_mv_bf16_bf16")]] kernel mul_mv_t kernel_mul_mv; #endif @@ -3472,7 +3562,7 @@ typedef decltype(kernel_mul_mv_c4) mul_mv_c4_t; template [[host_name("kernel_mul_mv_f32_f32_c4")]] kernel mul_mv_c4_t kernel_mul_mv_c4; template [[host_name("kernel_mul_mv_f16_f32_c4")]] kernel mul_mv_c4_t kernel_mul_mv_c4; -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template [[host_name("kernel_mul_mv_bf16_f32_c4")]] kernel mul_mv_c4_t kernel_mul_mv_c4; #endif @@ -3529,7 +3619,7 @@ kernel void kernel_mul_mv_1row( typedef decltype(kernel_mul_mv_1row) mul_mv_1row_t; template [[host_name("kernel_mul_mv_f16_f32_1row")]] kernel mul_mv_1row_t kernel_mul_mv_1row; -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template [[host_name("kernel_mul_mv_bf16_f32_1row")]] kernel mul_mv_1row_t kernel_mul_mv_1row; #endif @@ -3576,7 +3666,7 @@ kernel void kernel_mul_mv_l4( typedef decltype(kernel_mul_mv_l4) mul_mv_l4_t; template [[host_name("kernel_mul_mv_f16_f32_l4")]] kernel mul_mv_l4_t kernel_mul_mv_l4; -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template [[host_name("kernel_mul_mv_bf16_f32_l4")]] kernel mul_mv_l4_t kernel_mul_mv_l4; #endif @@ -3879,62 +3969,63 @@ template [[host_name("kernel_rope_multi_f16")]] kernel kernel_rope_multi_t kerne template [[host_name("kernel_rope_vision_f32")]] kernel kernel_rope_vision_t kernel_rope_vision; template [[host_name("kernel_rope_vision_f16")]] kernel kernel_rope_vision_t kernel_rope_vision; -typedef void (im2col_t)( - device const float * x, - device char * dst, - constant ggml_metal_kargs_im2col & args, - uint3 tgpig[[threadgroup_position_in_grid]], - uint3 tgpg[[threadgroups_per_grid]], - uint3 tpitg[[thread_position_in_threadgroup]], - uint3 ntg[[threads_per_threadgroup]]); - -template -kernel void kernel_im2col( - device const float * x, - device char * dst, - constant ggml_metal_kargs_im2col & args, - uint3 tgpig[[threadgroup_position_in_grid]], - uint3 tgpg[[threadgroups_per_grid]], - uint3 tpitg[[thread_position_in_threadgroup]], - uint3 ntg[[threads_per_threadgroup]]) { -// const int64_t IC = tgpg[0]; - const int64_t OH = tgpg[1]; - const int64_t OW = tgpg[2]; - -// const int64_t N = ntg[0]; - const int64_t KH = ntg[1]; - const int64_t KW = ntg[2]; - - const int64_t in = tpitg[0]; - const int64_t ikh = tpitg[1]; - const int64_t ikw = tpitg[2]; - - const int64_t iic = tgpig[0]; - const int64_t ioh = tgpig[1]; - const int64_t iow = tgpig[2]; - - const int64_t iiw = iow*args.s0 + ikw*args.d0 - args.p0; - const int64_t iih = ioh*args.s1 + ikh*args.d1 - args.p1; - - const int64_t offset_dst = (in*OH*OW + ioh*OW + iow)*args.CHW + (iic*(KH*KW) + ikh*KW + ikw); - - device T * pdst = (device T *) (dst); - - if (iih < 0 || iih >= args.IH || iiw < 0 || iiw >= args.IW) { - pdst[offset_dst] = 0.0f; - } else { - const int64_t offset_src = in*args.ofs0 + iic*args.ofs1 + iih*args.IW + iiw; - pdst[offset_dst] = x[offset_src]; - } -} - -template [[host_name("kernel_im2col_f32")]] kernel im2col_t kernel_im2col; -template [[host_name("kernel_im2col_f16")]] kernel im2col_t kernel_im2col; +// TODO: obolete -- remove +//typedef void (im2col_t)( +// constant ggml_metal_kargs_im2col & args, +// device const float * x, +// device char * dst, +// uint3 tgpig[[threadgroup_position_in_grid]], +// uint3 tgpg[[threadgroups_per_grid]], +// uint3 tpitg[[thread_position_in_threadgroup]], +// uint3 ntg[[threads_per_threadgroup]]); +// +//template +//kernel void kernel_im2col( +// constant ggml_metal_kargs_im2col & args, +// device const float * x, +// device char * dst, +// uint3 tgpig[[threadgroup_position_in_grid]], +// uint3 tgpg[[threadgroups_per_grid]], +// uint3 tpitg[[thread_position_in_threadgroup]], +// uint3 ntg[[threads_per_threadgroup]]) { +//// const int64_t IC = tgpg[0]; +// const int64_t OH = tgpg[1]; +// const int64_t OW = tgpg[2]; +// +//// const int64_t N = ntg[0]; +// const int64_t KH = ntg[1]; +// const int64_t KW = ntg[2]; +// +// const int64_t in = tpitg[0]; +// const int64_t ikh = tpitg[1]; +// const int64_t ikw = tpitg[2]; +// +// const int64_t iic = tgpig[0]; +// const int64_t ioh = tgpig[1]; +// const int64_t iow = tgpig[2]; +// +// const int64_t iiw = iow*args.s0 + ikw*args.d0 - args.p0; +// const int64_t iih = ioh*args.s1 + ikh*args.d1 - args.p1; +// +// const int64_t offset_dst = (in*OH*OW + ioh*OW + iow)*args.CHW + (iic*(KH*KW) + ikh*KW + ikw); +// +// device T * pdst = (device T *) (dst); +// +// if (iih < 0 || iih >= args.IH || iiw < 0 || iiw >= args.IW) { +// pdst[offset_dst] = 0.0f; +// } else { +// const int64_t offset_src = in*args.ofs0 + iic*args.ofs1 + iih*args.IW + iiw; +// pdst[offset_dst] = x[offset_src]; +// } +//} +// +//template [[host_name("kernel_im2col_f32")]] kernel im2col_t kernel_im2col; +//template [[host_name("kernel_im2col_f16")]] kernel im2col_t kernel_im2col; typedef void (im2col_ext_t)( + constant ggml_metal_kargs_im2col & args, device const float * x, device char * dst, - constant ggml_metal_kargs_im2col & args, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tgpg[[threadgroups_per_grid]], uint3 tpitg[[thread_position_in_threadgroup]], @@ -3942,16 +4033,16 @@ typedef void (im2col_ext_t)( template kernel void kernel_im2col_ext( + constant ggml_metal_kargs_im2col & args, device const float * x, device char * dst, - constant ggml_metal_kargs_im2col & args, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tgpg[[threadgroups_per_grid]], // tgpg[0] = D x IC x KH x KW, CHW = IC x KH x KW uint3 tpitg[[thread_position_in_threadgroup]], uint3 ntg[[threads_per_threadgroup]]) { // [M, 1, 1] const int64_t KHW = (int64_t)args.KHW; - const int64_t d = tgpig[0] / args.CHW; + const int64_t d = tgpig[0] / args.CHW; const int64_t chw = tgpig[0] % args.CHW; const int64_t tgpig_0 = chw / KHW; // 0 ~ (IC - 1) const int64_t HW = tgpig[0] % KHW; @@ -3985,19 +4076,19 @@ template [[host_name("kernel_im2col_ext_f32")]] kernel im2col_ext_t kernel_im2co template [[host_name("kernel_im2col_ext_f16")]] kernel im2col_ext_t kernel_im2col_ext; typedef void (conv_transpose_1d_t)( + constant ggml_metal_kargs_conv_transpose_1d & args, device const float * src0, device const float * src1, device char * dst, - constant ggml_metal_kargs_conv_transpose_1d & args, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tgpg[[threadgroups_per_grid]]); template kernel void kernel_conv_transpose_1d( + constant ggml_metal_kargs_conv_transpose_1d & args, device const T * src0, device const float * src1, device char * dst, - constant ggml_metal_kargs_conv_transpose_1d & args, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tgpg[[threadgroups_per_grid]]) { @@ -4021,26 +4112,26 @@ kernel void kernel_conv_transpose_1d( template [[host_name("kernel_conv_transpose_1d_f32_f32")]] kernel void kernel_conv_transpose_1d( + constant ggml_metal_kargs_conv_transpose_1d & args, device const float * src0, device const float * src1, device char * dst, - constant ggml_metal_kargs_conv_transpose_1d & args, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tgpg[[threadgroups_per_grid]]); template [[host_name("kernel_conv_transpose_1d_f16_f32")]] kernel void kernel_conv_transpose_1d( + constant ggml_metal_kargs_conv_transpose_1d & args, device const half * src0, device const float * src1, device char * dst, - constant ggml_metal_kargs_conv_transpose_1d & args, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tgpg[[threadgroups_per_grid]]); kernel void kernel_upscale_f32( + constant ggml_metal_kargs_upscale & args, device const char * src0, device char * dst, - constant ggml_metal_kargs_upscale & args, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], uint3 ntg[[threads_per_threadgroup]]) { @@ -4064,9 +4155,9 @@ kernel void kernel_upscale_f32( } kernel void kernel_pad_f32( + constant ggml_metal_kargs_pad & args, device const char * src0, device char * dst, - constant ggml_metal_kargs_pad & args, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], uint3 ntg[[threads_per_threadgroup]]) { @@ -4100,9 +4191,9 @@ kernel void kernel_pad_f32( } kernel void kernel_pad_reflect_1d_f32( + constant ggml_metal_kargs_pad_reflect_1d & args, device const char * src0, device char * dst, - constant ggml_metal_kargs_pad_reflect_1d & args, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tgpg[[threadgroups_per_grid]], uint3 tpitg[[thread_position_in_threadgroup]], @@ -4133,8 +4224,8 @@ kernel void kernel_pad_reflect_1d_f32( } kernel void kernel_arange_f32( - device char * dst, constant ggml_metal_kargs_arange & args, + device char * dst, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], uint3 ntg[[threads_per_threadgroup]]) { @@ -4147,9 +4238,9 @@ kernel void kernel_arange_f32( } kernel void kernel_timestep_embedding_f32( + constant ggml_metal_kargs_timestep_embedding & args, device const char * src0, device char * dst, - constant ggml_metal_kargs_timestep_embedding & args, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], uint3 ntg[[threads_per_threadgroup]]) { @@ -4173,19 +4264,19 @@ kernel void kernel_timestep_embedding_f32( // bitonic sort implementation following the CUDA kernels as reference typedef void (argsort_t)( - device const float * x, - device int32_t * dst, constant ggml_metal_kargs_argsort & args, + device const float * x, + device int32_t * dst, threadgroup int32_t * shared_values [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]]); template kernel void kernel_argsort_f32_i32( - device const float * x, - device int32_t * dst, constant ggml_metal_kargs_argsort & args, - threadgroup int32_t * shared_values [[threadgroup(0)]], + device const float * x, + device int32_t * dst, + threadgroup int32_t * shared_values [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]]) { // bitonic sort @@ -4238,11 +4329,21 @@ template [[host_name("kernel_argsort_f32_i32_asc")]] kernel argsort_t kernel_ar template [[host_name("kernel_argsort_f32_i32_desc")]] kernel argsort_t kernel_argsort_f32_i32; kernel void kernel_leaky_relu_f32( + constant ggml_metal_kargs_leaky_relu & args, device const float * src0, device float * dst, - constant ggml_metal_kargs_leaky_relu & args, uint tpig[[thread_position_in_grid]]) { - dst[tpig] = src0[tpig] > 0.0f ? src0[tpig] : src0[tpig] * args.slope; + const float x = src0[tpig]; + dst[tpig] = x > 0.0f ? x : x * args.slope; +} + +kernel void kernel_leaky_relu_f32_4( + constant ggml_metal_kargs_leaky_relu & args, + device const float4 * src0, + device float4 * dst, + uint tpig[[thread_position_in_grid]]) { + const float4 x = src0[tpig]; + dst[tpig] = float4(x > 0.0f)*x + float4(x <= 0.0f)*(x * args.slope); } constant bool FC_flash_attn_ext_has_mask [[function_constant(FC_FLASH_ATTN_EXT + 0)]]; @@ -4884,7 +4985,7 @@ template [[host_name("kernel_flash_attn_ext_f16_dk192_dv128")]] kernel flash_at template [[host_name("kernel_flash_attn_ext_f16_dk256_dv256")]] kernel flash_attn_ext_t kernel_flash_attn_ext; template [[host_name("kernel_flash_attn_ext_f16_dk576_dv512")]] kernel flash_attn_ext_t kernel_flash_attn_ext; -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template [[host_name("kernel_flash_attn_ext_bf16_dk40_dv40" )]] kernel flash_attn_ext_t kernel_flash_attn_ext; template [[host_name("kernel_flash_attn_ext_bf16_dk64_dv64" )]] kernel flash_attn_ext_t kernel_flash_attn_ext; template [[host_name("kernel_flash_attn_ext_bf16_dk80_dv80" )]] kernel flash_attn_ext_t kernel_flash_attn_ext; @@ -5450,7 +5551,7 @@ kernel void kernel_flash_attn_ext_vec( typedef decltype(kernel_flash_attn_ext_vec) flash_attn_ext_vec_t; template [[host_name("kernel_flash_attn_ext_vec_f16_dk64_dv64")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template [[host_name("kernel_flash_attn_ext_vec_bf16_dk64_dv64")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; #endif template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk64_dv64")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; @@ -5460,7 +5561,7 @@ template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk64_dv64")]] kernel flas template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk64_dv64")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; template [[host_name("kernel_flash_attn_ext_vec_f16_dk96_dv96")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template [[host_name("kernel_flash_attn_ext_vec_bf16_dk96_dv96")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; #endif template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk96_dv96")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; @@ -5470,7 +5571,7 @@ template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk96_dv96")]] kernel flas template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk96_dv96")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; template [[host_name("kernel_flash_attn_ext_vec_f16_dk128_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template [[host_name("kernel_flash_attn_ext_vec_bf16_dk128_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; #endif template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk128_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; @@ -5480,7 +5581,7 @@ template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk128_dv128")]] kernel flas template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk128_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; template [[host_name("kernel_flash_attn_ext_vec_f16_dk192_dv192")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template [[host_name("kernel_flash_attn_ext_vec_bf16_dk192_dv192")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; #endif template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk192_dv192")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; @@ -5490,7 +5591,7 @@ template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk192_dv192")]] kernel flas template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk192_dv192")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; template [[host_name("kernel_flash_attn_ext_vec_f16_dk192_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template [[host_name("kernel_flash_attn_ext_vec_bf16_dk192_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; #endif template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk192_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; @@ -5500,7 +5601,7 @@ template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk192_dv128")]] kernel flas template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk192_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; template [[host_name("kernel_flash_attn_ext_vec_f16_dk256_dv256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template [[host_name("kernel_flash_attn_ext_vec_bf16_dk256_dv256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; #endif template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk256_dv256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; @@ -5510,7 +5611,7 @@ template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk256_dv256")]] kernel flas template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk256_dv256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; template [[host_name("kernel_flash_attn_ext_vec_f16_dk576_dv512")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template [[host_name("kernel_flash_attn_ext_vec_bf16_dk576_dv512")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; #endif template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk576_dv512")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec; @@ -5603,12 +5704,12 @@ template [[host_name("kernel_cpy_f32_f32")]] kernel kernel_cpy_t kernel_cpy; template [[host_name("kernel_cpy_f32_i32")]] kernel kernel_cpy_t kernel_cpy; template [[host_name("kernel_cpy_i32_f32")]] kernel kernel_cpy_t kernel_cpy; -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template [[host_name("kernel_cpy_f32_bf16")]] kernel kernel_cpy_t kernel_cpy; #endif template [[host_name("kernel_cpy_f16_f32")]] kernel kernel_cpy_t kernel_cpy; template [[host_name("kernel_cpy_f16_f16")]] kernel kernel_cpy_t kernel_cpy; -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template [[host_name("kernel_cpy_bf16_f32")]] kernel kernel_cpy_t kernel_cpy; template [[host_name("kernel_cpy_bf16_bf16")]] kernel kernel_cpy_t kernel_cpy; #endif @@ -7880,13 +7981,13 @@ kernel void kernel_mul_mm_id_map0( typedef decltype(kernel_mul_mm_id_map0<1>) kernel_mul_mm_id_map0_t; -template [[host_name("kernel_mul_mm_id_map0_f16_ne20_1" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<1>; -template [[host_name("kernel_mul_mm_id_map0_f16_ne20_2" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<2>; -template [[host_name("kernel_mul_mm_id_map0_f16_ne20_4" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<4>; -template [[host_name("kernel_mul_mm_id_map0_f16_ne20_6" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<6>; -template [[host_name("kernel_mul_mm_id_map0_f16_ne20_8" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<8>; -template [[host_name("kernel_mul_mm_id_map0_f16_ne20_10")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<10>; -template [[host_name("kernel_mul_mm_id_map0_f16_ne20_16")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<16>; +template [[host_name("kernel_mul_mm_id_map0_ne20_1" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<1>; +template [[host_name("kernel_mul_mm_id_map0_ne20_2" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<2>; +template [[host_name("kernel_mul_mm_id_map0_ne20_4" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<4>; +template [[host_name("kernel_mul_mm_id_map0_ne20_6" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<6>; +template [[host_name("kernel_mul_mm_id_map0_ne20_8" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<8>; +template [[host_name("kernel_mul_mm_id_map0_ne20_10")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<10>; +template [[host_name("kernel_mul_mm_id_map0_ne20_16")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<16>; template kernel void kernel_mul_mm_id( @@ -8050,7 +8151,7 @@ typedef decltype(kernel_get_rows_f) get_rows_f_t; template [[host_name("kernel_get_rows_f32")]] kernel get_rows_f_t kernel_get_rows_f; template [[host_name("kernel_get_rows_f16")]] kernel get_rows_f_t kernel_get_rows_f; -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template [[host_name("kernel_get_rows_bf16")]] kernel get_rows_f_t kernel_get_rows_f; #endif @@ -8085,7 +8186,7 @@ typedef decltype(kernel_set_rows_f) set_rows_f_t; template [[host_name("kernel_set_rows_f32")]] kernel set_rows_f_t kernel_set_rows_f; template [[host_name("kernel_set_rows_f16")]] kernel set_rows_f_t kernel_set_rows_f; -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template [[host_name("kernel_set_rows_bf16")]] kernel set_rows_f_t kernel_set_rows_f; #endif @@ -8106,7 +8207,7 @@ typedef decltype(kernel_mul_mm; template [[host_name("kernel_mul_mm_f16_f32")]] kernel mul_mm_t kernel_mul_mm; -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template [[host_name("kernel_mul_mm_bf16_f32")]] kernel mul_mm_t kernel_mul_mm; #endif template [[host_name("kernel_mul_mm_q4_0_f32")]] kernel mul_mm_t kernel_mul_mm; @@ -8138,7 +8239,7 @@ typedef decltype(kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_f16_f16")]] kernel mul_mm_id kernel_mul_mm_id; -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template [[host_name("kernel_mul_mm_id_bf16_f16")]] kernel mul_mm_id kernel_mul_mm_id; #endif template [[host_name("kernel_mul_mm_id_q4_0_f16")]] kernel mul_mm_id kernel_mul_mm_id; @@ -8282,7 +8383,7 @@ typedef decltype(kernel_mul_mv_id>>; template [[host_name("kernel_mul_mv_id_f16_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -#if defined(GGML_METAL_USE_BF16) +#if defined(GGML_METAL_HAS_BF16) template [[host_name("kernel_mul_mv_id_bf16_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; #endif template [[host_name("kernel_mul_mv_id_q8_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; @@ -8310,12 +8411,12 @@ template [[host_name("kernel_mul_mv_id_iq4_nl_f32")]] kernel kernel_mul_mv_id_t template [[host_name("kernel_mul_mv_id_iq4_xs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; kernel void kernel_pool_2d_max_f32( + constant ggml_metal_kargs_pool_2d & args, device const float * src0, device float * dst, - constant ggml_metal_kargs_pool_2d & args, uint gid[[thread_position_in_grid]]) { - if (gid >= args.parallel_elements) { + if (gid >= args.np) { return; } @@ -8348,12 +8449,12 @@ kernel void kernel_pool_2d_max_f32( } kernel void kernel_pool_2d_avg_f32( + constant ggml_metal_kargs_pool_2d & args, device const float * src0, device float * dst, - constant ggml_metal_kargs_pool_2d & args, uint gid[[thread_position_in_grid]]) { - if (gid >= args.parallel_elements) { + if (gid >= args.np) { return; } diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp index b54a1a4e82..ce4a88761c 100644 --- a/tests/test-backend-ops.cpp +++ b/tests/test-backend-ops.cpp @@ -6325,12 +6325,20 @@ static std::vector> make_test_cases_eval() { } for (ggml_type type : {GGML_TYPE_F16, GGML_TYPE_F32}) { - test_cases.emplace_back(new test_sqr(type)); - test_cases.emplace_back(new test_sqrt(type)); - test_cases.emplace_back(new test_log(type)); - test_cases.emplace_back(new test_sin(type)); - test_cases.emplace_back(new test_cos(type)); - test_cases.emplace_back(new test_clamp(type)); + test_cases.emplace_back(new test_sqr (type)); + test_cases.emplace_back(new test_sqrt (type)); + test_cases.emplace_back(new test_log (type)); + test_cases.emplace_back(new test_sin (type)); + test_cases.emplace_back(new test_cos (type)); + test_cases.emplace_back(new test_clamp (type)); + test_cases.emplace_back(new test_leaky_relu(type)); + test_cases.emplace_back(new test_sqr (type, {7, 1, 5, 3})); + test_cases.emplace_back(new test_sqrt (type, {7, 1, 5, 3})); + test_cases.emplace_back(new test_log (type, {7, 1, 5, 3})); + test_cases.emplace_back(new test_sin (type, {7, 1, 5, 3})); + test_cases.emplace_back(new test_cos (type, {7, 1, 5, 3})); + test_cases.emplace_back(new test_clamp (type, {7, 1, 5, 3})); + test_cases.emplace_back(new test_leaky_relu(type, {7, 1, 5, 3})); } test_cases.emplace_back(new test_diag_mask_inf(GGML_TYPE_F32, {10, 10, 1, 1}, 5)); From d304f459d8619399eb232b1e3689379306f439d3 Mon Sep 17 00:00:00 2001 From: Reese Levine Date: Wed, 17 Sep 2025 13:09:40 -0700 Subject: [PATCH 27/52] GGML WebGPU: Support for ADD, MUL, RMS_NORM, GET_ROWS operators (#16018) * Add paramater buffer pool, batching of submissions, refactor command building/submission * Add header for linux builds * Free staged parameter buffers at once * Format with clang-format * Fix thread-safe implementation * Use device implicit synchronization * Update workflow to use custom release * Remove testing branch workflow * some f32 tests passing * Disable set_rows until it's implemented * f32 add all tests passing * Begin work on set_rows * Work on set rows * Add error buffers for reporting unsupported SET_ROWS indices * Remove extra comments * Add templated addition, clean up code * Get addition and multiplication working * Implement rms_norm * Add get_rows implementation * Add new get_rows files * Refactor use of wg size entry * Fix compilation * Try manually unrolled q4_0 quant * Revert "Try manually unrolled q4_0 quant" This reverts commit 77f8b96515f7e640ae4b0e44f066321fbc4a6166. * Move to constant max wg size * Check for tensor size in supports_op * Vectorize f32 and change default workgroup size * Move f32 get_rows from < 4 to % 4 != 0 * fix linter errors * Add in-place tests --------- Co-authored-by: Neha Abbas --- ggml/src/ggml-webgpu/ggml-webgpu.cpp | 707 ++++++++----- .../ggml-webgpu/wgsl-shaders/add.tmpl.wgsl | 44 + .../wgsl-shaders/add_in_place.tmpl.wgsl | 41 + .../ggml-webgpu/wgsl-shaders/binary_head.tmpl | 45 + .../wgsl-shaders/common_decls.tmpl | 930 ++++++++++++++++++ .../ggml-webgpu/wgsl-shaders/embed_wgsl.py | 53 +- .../wgsl-shaders/get_rows.tmpl.wgsl | 874 ++++++++++++++++ .../ggml-webgpu/wgsl-shaders/mul.tmpl.wgsl | 44 + .../wgsl-shaders/mul_in_place.tmpl.wgsl | 41 + .../wgsl-shaders/mul_mat.tmpl.wgsl | 925 +---------------- .../ggml-webgpu/wgsl-shaders/rms_norm.wgsl | 57 ++ .../wgsl-shaders/rms_norm_in_place.wgsl | 48 + .../ggml-webgpu/wgsl-shaders/set_rows.wgsl | 1 - tests/test-backend-ops.cpp | 4 + 14 files changed, 2673 insertions(+), 1141 deletions(-) create mode 100644 ggml/src/ggml-webgpu/wgsl-shaders/add.tmpl.wgsl create mode 100644 ggml/src/ggml-webgpu/wgsl-shaders/add_in_place.tmpl.wgsl create mode 100644 ggml/src/ggml-webgpu/wgsl-shaders/binary_head.tmpl create mode 100644 ggml/src/ggml-webgpu/wgsl-shaders/common_decls.tmpl create mode 100644 ggml/src/ggml-webgpu/wgsl-shaders/get_rows.tmpl.wgsl create mode 100644 ggml/src/ggml-webgpu/wgsl-shaders/mul.tmpl.wgsl create mode 100644 ggml/src/ggml-webgpu/wgsl-shaders/mul_in_place.tmpl.wgsl create mode 100644 ggml/src/ggml-webgpu/wgsl-shaders/rms_norm.wgsl create mode 100644 ggml/src/ggml-webgpu/wgsl-shaders/rms_norm_in_place.wgsl diff --git a/ggml/src/ggml-webgpu/ggml-webgpu.cpp b/ggml/src/ggml-webgpu/ggml-webgpu.cpp index df6a3ed95a..8e7b986df8 100644 --- a/ggml/src/ggml-webgpu/ggml-webgpu.cpp +++ b/ggml/src/ggml-webgpu/ggml-webgpu.cpp @@ -116,6 +116,10 @@ struct webgpu_context_struct { wgpu::Queue queue; wgpu::Limits limits; + // 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; + std::recursive_mutex mutex; webgpu_buf_pool param_buf_pool; @@ -124,7 +128,15 @@ struct webgpu_context_struct { wgpu::ComputePipeline memset_pipeline; wgpu::ComputePipeline mul_mat_pipeline[30][2]; wgpu::ComputePipeline set_rows_pipeline; + wgpu::ComputePipeline get_rows_pipeline[30]; + wgpu::ComputePipeline get_rows_f32_no_vec_pipeline; wgpu::ComputePipeline cpy_pipeline; + wgpu::ComputePipeline add_pipeline[2]; + wgpu::ComputePipeline add_ip_pipeline[2]; + wgpu::ComputePipeline mul_pipeline[2]; + wgpu::ComputePipeline mul_ip_pipeline[2]; + wgpu::ComputePipeline rms_norm_pipeline; + wgpu::ComputePipeline rms_norm_ip_pipeline; size_t memset_bytes_per_thread; @@ -232,14 +244,15 @@ static void ggml_backend_webgpu_wait_on_submission(webgpu_context & ctx) { std::lock_guard lock(ctx->mutex); if (ctx->callback_futures.empty()) { // no existing callbacks, wait on queue submission - ctx->instance.WaitAny(ctx->queue.OnSubmittedWorkDone( - wgpu::CallbackMode::AllowSpontaneous, - [](wgpu::QueueWorkDoneStatus status, wgpu::StringView message) { - if (status != wgpu::QueueWorkDoneStatus::Success) { - GGML_LOG_ERROR("ggml_webgpu: Failed to submit commands: %s\n", std::string(message).c_str()); - } - }), - UINT64_MAX); + ctx->instance.WaitAny( + ctx->queue.OnSubmittedWorkDone(wgpu::CallbackMode::AllowSpontaneous, + [](wgpu::QueueWorkDoneStatus status, wgpu::StringView message) { + if (status != wgpu::QueueWorkDoneStatus::Success) { + GGML_LOG_ERROR("ggml_webgpu: Failed to submit commands: %s\n", + std::string(message).c_str()); + } + }), + UINT64_MAX); } else { // existing callbacks, wait on them ctx->instance.WaitAny(ctx->callback_futures.size(), ctx->callback_futures.data(), UINT64_MAX); @@ -286,10 +299,7 @@ static void ggml_backend_webgpu_submit_queue(webgpu_context & ctx) { // Check for errrors in SET_ROWS operations for (auto & error_bufs : staged_set_row_error_bufs) { wgpu::Future f = error_bufs.host_buf.MapAsync( - wgpu::MapMode::Read, - 0, - error_bufs.host_buf.GetSize(), - wgpu::CallbackMode::AllowSpontaneous, + wgpu::MapMode::Read, 0, error_bufs.host_buf.GetSize(), wgpu::CallbackMode::AllowSpontaneous, [ctx, error_bufs](wgpu::MapAsyncStatus status, wgpu::StringView message) { if (status != wgpu::MapAsyncStatus::Success) { GGML_LOG_ERROR("ggml_webgpu: Failed to map error buffer: %s\n", std::string(message).c_str()); @@ -311,10 +321,7 @@ static void ggml_backend_webgpu_map_buffer(webgpu_context & ctx, wgpu::MapMode mode, size_t offset, size_t size) { - ctx->instance.WaitAny(buffer.MapAsync(mode, - offset, - size, - wgpu::CallbackMode::AllowSpontaneous, + ctx->instance.WaitAny(buffer.MapAsync(mode, offset, size, wgpu::CallbackMode::AllowSpontaneous, [](wgpu::MapAsyncStatus status, wgpu::StringView message) { if (status != wgpu::MapAsyncStatus::Success) { GGML_LOG_ERROR("ggml_webgpu: Failed to map buffer: %s\n", @@ -351,7 +358,8 @@ static void ggml_backend_webgpu_build_and_enqueue(webgpu_context & std::vector params, std::vector bind_group_entries, uint32_t wg_x, - bool submit_and_wait = false) { + const char * bind_group_label = nullptr, + bool submit_and_wait = false) { webgpu_pool_bufs params_bufs = ctx->param_buf_pool.alloc_bufs(); ggml_backend_webgpu_map_buffer(ctx, params_bufs.host_buf, wgpu::MapMode::Write, 0, params_bufs.host_buf.GetSize()); @@ -372,6 +380,9 @@ static void ggml_backend_webgpu_build_and_enqueue(webgpu_context & bind_group_desc.layout = pipeline.GetBindGroupLayout(0); bind_group_desc.entryCount = bind_group_entries.size(); bind_group_desc.entries = bind_group_entries.data(); + if (bind_group_label) { + bind_group_desc.label = bind_group_label; + } wgpu::BindGroup bind_group = ctx->device.CreateBindGroup(&bind_group_desc); wgpu::CommandEncoder encoder = ctx->device.CreateCommandEncoder(); @@ -415,9 +426,9 @@ 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->limits.maxComputeWorkgroupSizeX * ctx->memset_bytes_per_thread; + 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; - ggml_backend_webgpu_build_and_enqueue(ctx, ctx->memset_pipeline, params, entries, wg_x, true); + ggml_backend_webgpu_build_and_enqueue(ctx, ctx->memset_pipeline, params, entries, wg_x, "MEMSET", true); } /** End WebGPU Actions */ @@ -461,26 +472,26 @@ static size_t ggml_webgpu_tensor_binding_size(webgpu_context & ctx, ggml_tensor ~(WEBGPU_STORAGE_BUF_BINDING_MULT - 1); } +// Used to determine if two tensors are the same for in-place operations +static bool ggml_webgpu_tensor_equal(ggml_tensor * a, ggml_tensor * b) { + return (ggml_webgpu_tensor_buf(a).Get() == ggml_webgpu_tensor_buf(b).Get()) && + (ggml_webgpu_tensor_offset(a) == ggml_webgpu_tensor_offset(b)); +} + static void ggml_webgpu_cpy(webgpu_context & ctx, ggml_tensor * src, ggml_tensor * dst) { uint32_t ne = (uint32_t) ggml_nelements(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 shape — same for both tensors even if permuted - (uint32_t) src->ne[0], - (uint32_t) src->ne[1], - (uint32_t) src->ne[2], - (uint32_t) src->ne[3] }; + 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 shape — same for both tensors even if permuted + (uint32_t) src->ne[0], (uint32_t) src->ne[1], (uint32_t) src->ne[2], (uint32_t) src->ne[3] + }; std::vector entries = { { .binding = 0, @@ -493,9 +504,9 @@ static void ggml_webgpu_cpy(webgpu_context & ctx, ggml_tensor * src, ggml_tensor .size = ggml_webgpu_tensor_binding_size(ctx, dst) } }; - size_t max_wg_size = ctx->limits.maxComputeWorkgroupSizeX; + size_t max_wg_size = ctx->max_wg_size_x; uint32_t wg_x = (ne + max_wg_size - 1) / max_wg_size; - ggml_backend_webgpu_build_and_enqueue(ctx, ctx->cpy_pipeline, params, entries, wg_x); + ggml_backend_webgpu_build_and_enqueue(ctx, ctx->cpy_pipeline, params, entries, wg_x, ggml_op_name(dst->op)); } static void ggml_webgpu_set_rows(webgpu_context & ctx, ggml_tensor * src, ggml_tensor * idx, ggml_tensor * dst) { @@ -509,27 +520,21 @@ static void ggml_webgpu_set_rows(webgpu_context & ctx, ggml_tensor * src, ggml_t error_bufs.host_buf.Unmap(); } - std::vector params = { (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, src) / ggml_type_size(src->type)), - (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, idx) / ggml_type_size(idx->type)), - (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, dst) / ggml_type_size(dst->type)), - // Convert byte-strides to element-strides - (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) (idx->nb[0] / ggml_type_size(idx->type)), - (uint32_t) (idx->nb[1] / ggml_type_size(idx->type)), - (uint32_t) (idx->nb[2] / ggml_type_size(idx->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)), - // Shape of src - (uint32_t) src->ne[0], - (uint32_t) src->ne[1], - (uint32_t) src->ne[2], - (uint32_t) src->ne[3], - // Shape of idx - (uint32_t) (idx->ne[1]), - (uint32_t) (idx->ne[2]) }; + std::vector params = { + (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, src) / ggml_type_size(src->type)), + (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, idx) / ggml_type_size(idx->type)), + (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, dst) / ggml_type_size(dst->type)), + // Convert byte-strides to element-strides + (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) (idx->nb[0] / ggml_type_size(idx->type)), + (uint32_t) (idx->nb[1] / ggml_type_size(idx->type)), (uint32_t) (idx->nb[2] / ggml_type_size(idx->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)), + // Shape of src + (uint32_t) src->ne[0], (uint32_t) src->ne[1], (uint32_t) src->ne[2], (uint32_t) src->ne[3], + // Shape of idx + (uint32_t) (idx->ne[1]), (uint32_t) (idx->ne[2]) + }; std::vector entries = { { .binding = 0, @@ -547,13 +552,55 @@ static void ggml_webgpu_set_rows(webgpu_context & ctx, ggml_tensor * src, ggml_t { .binding = 3, .buffer = error_bufs.dev_buf, .offset = 0, .size = error_bufs.dev_buf.GetSize() } }; - size_t max_wg_size = ctx->limits.maxComputeWorkgroupSizeX; + size_t max_wg_size = ctx->max_wg_size_x; uint32_t wg_x = (src->ne[1] * src->ne[2] * src->ne[3] + max_wg_size - 1) / max_wg_size; std::lock_guard lock(ctx->mutex); ctx->staged_set_row_error_bufs.push_back(error_bufs); - ggml_backend_webgpu_build_and_enqueue(ctx, ctx->set_rows_pipeline, params, entries, wg_x); + ggml_backend_webgpu_build_and_enqueue(ctx, ctx->set_rows_pipeline, params, entries, wg_x, ggml_op_name(dst->op)); +} + +static void ggml_webgpu_get_rows(webgpu_context & ctx, ggml_tensor * src, ggml_tensor * idx, ggml_tensor * dst) { + std::vector params = { + (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, src) / ggml_type_size(src->type)), + (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, idx) / ggml_type_size(idx->type)), + (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, dst) / ggml_type_size(dst->type)), + // Convert byte-strides to element-strides + (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) (idx->nb[0] / ggml_type_size(idx->type)), + (uint32_t) (idx->nb[1] / ggml_type_size(idx->type)), (uint32_t) (idx->nb[2] / ggml_type_size(idx->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)), + // Shape of dst + (uint32_t) dst->ne[0], (uint32_t) dst->ne[1], (uint32_t) dst->ne[2], (uint32_t) dst->ne[3], + // Shape of idx + (uint32_t) (idx->ne[1]), (uint32_t) (idx->ne[2]) + }; + + 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) }, + { .binding = 1, + .buffer = ggml_webgpu_tensor_buf(idx), + .offset = ggml_webgpu_tensor_align_offset(ctx, idx), + .size = ggml_webgpu_tensor_binding_size(ctx, idx) }, + { .binding = 2, + .buffer = ggml_webgpu_tensor_buf(dst), + .offset = ggml_webgpu_tensor_align_offset(ctx, dst), + .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; + + wgpu::ComputePipeline 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; + } + ggml_backend_webgpu_build_and_enqueue(ctx, pipeline, params, entries, wg_x, ggml_op_name(dst->op)); } static void ggml_webgpu_mul_mat(webgpu_context & ctx, ggml_tensor * src0, ggml_tensor * src1, ggml_tensor * dst) { @@ -593,7 +640,104 @@ static void ggml_webgpu_mul_mat(webgpu_context & ctx, ggml_tensor * src0, ggml_t 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; - ggml_backend_webgpu_build_and_enqueue(ctx, ctx->mul_mat_pipeline[src0->type][src1->type], params, entries, wg_x); + ggml_backend_webgpu_build_and_enqueue(ctx, ctx->mul_mat_pipeline[src0->type][src1->type], params, entries, wg_x, + ggml_op_name(dst->op)); +} + +static void ggml_webgpu_binary_op(webgpu_context & ctx, + ggml_tensor * src0, + ggml_tensor * src1, + ggml_tensor * dst, + wgpu::ComputePipeline & pipeline, + bool in_place) { + std::vector params = { + (uint32_t) ggml_nelements(dst), + (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, src0) / ggml_type_size(src0->type)), + (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, src1) / ggml_type_size(src1->type)), + (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, dst) / ggml_type_size(dst->type)), + (uint32_t) (src1->nb[0] / ggml_type_size(src1->type)), + (uint32_t) (src1->nb[1] / ggml_type_size(src1->type)), + (uint32_t) (src1->nb[2] / ggml_type_size(src1->type)), + (uint32_t) (src1->nb[3] / ggml_type_size(src1->type)), + (uint32_t) src0->ne[0], + (uint32_t) src0->ne[1], + (uint32_t) src0->ne[2], + (uint32_t) src1->ne[0], + (uint32_t) src1->ne[1], + (uint32_t) src1->ne[2], + (uint32_t) src1->ne[3], + }; + + std::vector entries = { + { .binding = 0, + .buffer = ggml_webgpu_tensor_buf(src0), + .offset = ggml_webgpu_tensor_align_offset(ctx, src0), + .size = ggml_webgpu_tensor_binding_size(ctx, src0) }, + { .binding = 1, + .buffer = ggml_webgpu_tensor_buf(src1), + .offset = ggml_webgpu_tensor_align_offset(ctx, src1), + .size = ggml_webgpu_tensor_binding_size(ctx, src1) } + }; + if (!in_place) { + entries.push_back({ .binding = 2, + .buffer = ggml_webgpu_tensor_buf(dst), + .offset = ggml_webgpu_tensor_align_offset(ctx, dst), + .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; + ggml_backend_webgpu_build_and_enqueue(ctx, pipeline, params, entries, wg_x, ggml_op_name(dst->op)); +} + +static void ggml_webgpu_rms_norm(webgpu_context & ctx, ggml_tensor * src, ggml_tensor * dst) { + bool in_place = ggml_webgpu_tensor_equal(src, dst); + + uint32_t eps; + memcpy(&eps, dst->op_params, sizeof(float)); + + std::vector params = { + (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, src) / ggml_type_size(src->type)), + }; + if (!in_place) { + params.push_back((uint32_t) (ggml_webgpu_tensor_misalignment(ctx, dst) / ggml_type_size(dst->type))); + } + params.push_back((uint32_t) (src->nb[1] / ggml_type_size(src->type))); + params.push_back((uint32_t) (src->nb[2] / ggml_type_size(src->type))); + params.push_back((uint32_t) (src->nb[3] / ggml_type_size(src->type))); + if (!in_place) { + params.push_back((uint32_t) (dst->nb[1] / ggml_type_size(dst->type))); + params.push_back((uint32_t) (dst->nb[2] / ggml_type_size(dst->type))); + params.push_back((uint32_t) (dst->nb[3] / ggml_type_size(dst->type))); + } + params.push_back((uint32_t) src->ne[0]); + params.push_back((uint32_t) src->ne[1]); + params.push_back((uint32_t) src->ne[2]); + params.push_back((uint32_t) src->ne[3]); + params.push_back(eps); // epsilon, will be bitcast to float in shader + + 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 (!in_place) { + 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) }); + } + + wgpu::ComputePipeline pipeline; + if (in_place) { + pipeline = ctx->rms_norm_ip_pipeline; + } else { + pipeline = ctx->rms_norm_pipeline; + } + size_t max_wg_size = ctx->max_wg_size_x; + uint32_t wg_x = (src->ne[1] * src->ne[2] * src->ne[3] + max_wg_size - 1) / max_wg_size; + ggml_backend_webgpu_build_and_enqueue(ctx, pipeline, params, entries, wg_x, ggml_op_name(dst->op)); } // Returns true if node has enqueued work into the queue, false otherwise @@ -615,20 +759,34 @@ static bool ggml_webgpu_encode_node(webgpu_context ctx, ggml_tensor * node) { case GGML_OP_RESHAPE: return false; case GGML_OP_CPY: - { - ggml_webgpu_cpy(ctx, src0, node); - break; - } + ggml_webgpu_cpy(ctx, src0, node); + break; case GGML_OP_SET_ROWS: - { - ggml_webgpu_set_rows(ctx, src0, src1, node); - break; - } + ggml_webgpu_set_rows(ctx, src0, src1, node); + break; + case GGML_OP_GET_ROWS: + ggml_webgpu_get_rows(ctx, src0, src1, node); + break; case GGML_OP_MUL_MAT: - { - ggml_webgpu_mul_mat(ctx, src0, src1, node); - break; + ggml_webgpu_mul_mat(ctx, src0, src1, node); + break; + case GGML_OP_ADD: + if (ggml_webgpu_tensor_equal(src0, node)) { + ggml_webgpu_binary_op(ctx, src0, src1, node, ctx->add_ip_pipeline[node->type], true); + } else { + ggml_webgpu_binary_op(ctx, src0, src1, node, ctx->add_pipeline[node->type], false); } + break; + case GGML_OP_MUL: + if (ggml_webgpu_tensor_equal(src0, node)) { + ggml_webgpu_binary_op(ctx, src0, src1, node, ctx->mul_ip_pipeline[node->type], true); + } else { + ggml_webgpu_binary_op(ctx, src0, src1, node, ctx->mul_pipeline[node->type], false); + } + break; + case GGML_OP_RMS_NORM: + ggml_webgpu_rms_norm(ctx, src0, node); + break; default: return false; } @@ -731,8 +889,8 @@ static void ggml_backend_webgpu_buffer_set_tensor(ggml_backend_buffer_t buffer, ((uint8_t *) &val32)[i] = ((const uint8_t *) data)[size - remaining_size + i]; } // memset the remaining bytes - ggml_backend_webgpu_buffer_memset( - webgpu_ctx, buf_ctx->buffer, val32, total_offset + (size - remaining_size), remaining_size); + ggml_backend_webgpu_buffer_memset(webgpu_ctx, buf_ctx->buffer, val32, total_offset + (size - remaining_size), + remaining_size); } else { // wait for WriteBuffer to complete ggml_backend_webgpu_wait_on_submission(webgpu_ctx); @@ -766,11 +924,8 @@ static void ggml_backend_webgpu_buffer_get_tensor(ggml_backend_buffer_t buffer, if (webgpu_ctx->get_tensor_staging_buf) { webgpu_ctx->get_tensor_staging_buf.Destroy(); } - ggml_webgpu_create_buffer(device, - webgpu_ctx->get_tensor_staging_buf, - final_size, - wgpu::BufferUsage::CopyDst | wgpu::BufferUsage::MapRead, - "get_tensor_staging_buf"); + ggml_webgpu_create_buffer(device, webgpu_ctx->get_tensor_staging_buf, final_size, + wgpu::BufferUsage::CopyDst | wgpu::BufferUsage::MapRead, "get_tensor_staging_buf"); } // Copy the data from the buffer to the staging buffer @@ -824,8 +979,7 @@ 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, + ggml_webgpu_create_buffer(ctx->webgpu_ctx->device, buf, (size + WEBGPU_STORAGE_BUF_BINDING_MULT - 1) & ~(WEBGPU_STORAGE_BUF_BINDING_MULT - 1), wgpu::BufferUsage::Storage | wgpu::BufferUsage::CopySrc | wgpu::BufferUsage::CopyDst, "allocated_buffer"); @@ -890,9 +1044,17 @@ static ggml_guid_t ggml_backend_webgpu_guid(void) { return reinterpret_cast((void *) guid_str); } +// The max workgroup size is a common constant +static std::vector ggml_webgpu_max_wg_size_entry(webgpu_context & webgpu_ctx) { + std::vector constants(1); + constants[0].key = "wg_size"; + constants[0].value = webgpu_ctx->max_wg_size_x; + return constants; +} + 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->limits.maxComputeWorkgroupSizeX; + size_t max_wg_size = webgpu_ctx->max_wg_size_x; size_t max_threads = 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 = @@ -906,109 +1068,142 @@ static void ggml_webgpu_init_memset_pipeline(webgpu_context & webgpu_ctx) { } 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_F32][GGML_TYPE_F32], - wgsl_mul_mat_f32_f32, - "mul_mat_f32_f32"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, - webgpu_ctx->mul_mat_pipeline[GGML_TYPE_F16][GGML_TYPE_F16], - wgsl_mul_mat_f16_f16, - "mul_mat_f16_f16"); - ggml_webgpu_create_pipeline(webgpu_ctx->device, - webgpu_ctx->mul_mat_pipeline[GGML_TYPE_F16][GGML_TYPE_F32], - wgsl_mul_mat_f16_f32, - "mul_mat_f16_f32"); - 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"); + ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_F32][GGML_TYPE_F32], + wgsl_mul_mat_f32_f32, "mul_mat_f32_f32"); + ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_F16][GGML_TYPE_F16], + wgsl_mul_mat_f16_f16, "mul_mat_f16_f16"); + ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_mat_pipeline[GGML_TYPE_F16][GGML_TYPE_F32], + wgsl_mul_mat_f16_f32, "mul_mat_f16_f32"); + 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"); } static void ggml_webgpu_init_set_rows_pipeline(webgpu_context & webgpu_ctx) { - std::vector constants(1); - constants[0].key = "wg_size"; - constants[0].value = webgpu_ctx->limits.maxComputeWorkgroupSizeX; - ggml_webgpu_create_pipeline( - webgpu_ctx->device, webgpu_ctx->set_rows_pipeline, wgsl_set_rows, "set_rows", constants); + ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->set_rows_pipeline, wgsl_set_rows, "set_rows", + ggml_webgpu_max_wg_size_entry(webgpu_ctx)); +} + +static void ggml_webgpu_init_get_rows_pipeline(webgpu_context & webgpu_ctx) { + std::vector constants = ggml_webgpu_max_wg_size_entry(webgpu_ctx); + 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); } static void ggml_webgpu_init_cpy_pipeline(webgpu_context & webgpu_ctx) { - std::vector constants(1); - constants[0].key = "wg_size"; - constants[0].value = webgpu_ctx->limits.maxComputeWorkgroupSizeX; - ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->cpy_pipeline, wgsl_cpy, "cpy", constants); + ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->cpy_pipeline, wgsl_cpy, "cpy", + ggml_webgpu_max_wg_size_entry(webgpu_ctx)); +} + +static void ggml_webgpu_init_add_pipeline(webgpu_context & webgpu_ctx) { + std::vector constants = ggml_webgpu_max_wg_size_entry(webgpu_ctx); + ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->add_pipeline[GGML_TYPE_F32], wgsl_add_f32, "add_f32", + constants); + ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->add_pipeline[GGML_TYPE_F16], wgsl_add_f16, "add_f16", + constants); + ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->add_ip_pipeline[GGML_TYPE_F32], wgsl_add_in_place_f32, + "add_in_place_f32", constants); + ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->add_ip_pipeline[GGML_TYPE_F16], wgsl_add_in_place_f16, + "add_in_place_f16", constants); +} + +static void ggml_webgpu_init_mul_pipeline(webgpu_context & webgpu_ctx) { + std::vector constants = ggml_webgpu_max_wg_size_entry(webgpu_ctx); + ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_pipeline[GGML_TYPE_F32], wgsl_mul_f32, "mul_f32", + constants); + ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_pipeline[GGML_TYPE_F16], wgsl_mul_f16, "mul_f16", + constants); + ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_ip_pipeline[GGML_TYPE_F32], wgsl_mul_in_place_f32, + "mul_in_place_f32", constants); + ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_ip_pipeline[GGML_TYPE_F16], wgsl_mul_in_place_f16, + "mul_in_place_f16", constants); +} + +static void ggml_webgpu_init_rms_norm_pipeline(webgpu_context & webgpu_ctx) { + std::vector constants = ggml_webgpu_max_wg_size_entry(webgpu_ctx); + ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->rms_norm_pipeline, wgsl_rms_norm, "rms_norm", + constants); + ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->rms_norm_ip_pipeline, wgsl_rms_norm_in_place, + "rms_norm_in_place", constants); } static ggml_backend_t ggml_backend_webgpu_device_init(ggml_backend_dev_t dev, const char * params) { @@ -1058,24 +1253,77 @@ static bool ggml_backend_webgpu_device_supports_buft(ggml_backend_dev_t dev, ggm return buft->iface.get_name == ggml_backend_webgpu_buffer_type_get_name; } -static bool ggml_backend_webgpu_device_supports_op(ggml_backend_dev_t dev, const ggml_tensor * op) { - GGML_UNUSED(dev); +static bool ggml_webgpu_supported_qtype(ggml_type type) { + switch (type) { + case GGML_TYPE_Q4_0: + case GGML_TYPE_Q4_1: + case GGML_TYPE_Q5_0: + case GGML_TYPE_Q5_1: + case GGML_TYPE_Q8_0: + case GGML_TYPE_Q2_K: + case GGML_TYPE_Q3_K: + case GGML_TYPE_Q4_K: + case GGML_TYPE_Q5_K: + case GGML_TYPE_Q6_K: + case GGML_TYPE_IQ2_XXS: + case GGML_TYPE_IQ2_XS: + case GGML_TYPE_IQ2_S: + case GGML_TYPE_IQ3_XXS: + case GGML_TYPE_IQ3_S: + case GGML_TYPE_IQ1_S: + case GGML_TYPE_IQ1_M: + case GGML_TYPE_IQ4_NL: + case GGML_TYPE_IQ4_XS: + return true; + default: + return false; + } +} +static bool ggml_backend_webgpu_device_supports_op(ggml_backend_dev_t dev, const ggml_tensor * op) { + ggml_backend_webgpu_device_context * ctx = static_cast(dev->context); + + webgpu_context webgpu_ctx = ctx->webgpu_ctx; + + ggml_tensor * src0 = op->src[0]; + ggml_tensor * src1 = op->src[1]; + // on smaller devices (or CI), tensors may be larger than the max storage buffer size + if (ggml_nbytes(op) > webgpu_ctx->limits.maxStorageBufferBindingSize || + (src0 != nullptr && ggml_nbytes(src0) > webgpu_ctx->limits.maxStorageBufferBindingSize) || + (src1 != nullptr && ggml_nbytes(src1) > webgpu_ctx->limits.maxStorageBufferBindingSize)) { + return false; + } + + bool supports_op = false; switch (op->op) { case GGML_OP_NONE: case GGML_OP_VIEW: case GGML_OP_PERMUTE: case GGML_OP_TRANSPOSE: case GGML_OP_RESHAPE: - return true; + supports_op = true; + break; + case GGML_OP_ADD: + case GGML_OP_MUL: + supports_op = (op->type == GGML_TYPE_F32 || op->type == GGML_TYPE_F16) && (op->src[0]->type == op->type) && + (op->src[1]->type == op->type); + break; case GGML_OP_CPY: case GGML_OP_SET_ROWS: - return op->type == GGML_TYPE_F16 && op->src[0]->type == GGML_TYPE_F32; + supports_op = (op->type == GGML_TYPE_F16 && op->src[0]->type == GGML_TYPE_F32); + break; + case GGML_OP_GET_ROWS: + if (op->src[0]->type == GGML_TYPE_F32 || op->src[0]->type == GGML_TYPE_F16 || + op->src[0]->type == GGML_TYPE_I32 || ggml_webgpu_supported_qtype(op->src[0]->type)) { + supports_op = (op->type == GGML_TYPE_F32); + } + break; case GGML_OP_MUL_MAT: { switch (op->src[1]->type) { case GGML_TYPE_F16: - return op->src[0]->type == GGML_TYPE_F16; + supports_op = (op->src[0]->type == GGML_TYPE_F16); + break; case GGML_TYPE_F32: switch (op->src[0]->type) { case GGML_TYPE_F32: @@ -1099,17 +1347,30 @@ static bool ggml_backend_webgpu_device_supports_op(ggml_backend_dev_t dev, const case GGML_TYPE_IQ1_M: case GGML_TYPE_IQ4_NL: case GGML_TYPE_IQ4_XS: - return true; + supports_op = true; + break; default: - return false; + break; } default: - return false; + break; } + break; } + case GGML_OP_RMS_NORM: + supports_op = op->type == GGML_TYPE_F32 && op->src[0]->type == GGML_TYPE_F32; + break; default: - return false; + break; } +#ifdef GGML_WEBGPU_DEBUG + if (!supports_op) { + WEBGPU_LOG_DEBUG("not supported: " << ggml_op_name(op->op) << " with types dst: " << ggml_type_name(op->type) + << ", src0: " << (op->src[0] ? ggml_type_name(op->src[0]->type) : "null") + << ", src1: " << (op->src[1] ? ggml_type_name(op->src[1]->type) : "null")); + } +#endif + return supports_op; } static struct ggml_backend_device_i ggml_backend_webgpu_device_i = { @@ -1155,18 +1416,20 @@ 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 = {}; - ctx->instance.WaitAny( - ctx->instance.RequestAdapter(&options, wgpu::CallbackMode::AllowSpontaneous, - [&ctx](wgpu::RequestAdapterStatus status, wgpu::Adapter adapter, const char * message) { - if (status != wgpu::RequestAdapterStatus::Success) { - GGML_LOG_ERROR("ggml_webgpu: Failed to get an adapter: %s\n", message); - return; - } - ctx->adapter = std::move(adapter); - }), UINT64_MAX); + ctx->instance.WaitAny(ctx->instance.RequestAdapter( + &options, wgpu::CallbackMode::AllowSpontaneous, + [&ctx](wgpu::RequestAdapterStatus status, wgpu::Adapter adapter, const char * message) { + if (status != wgpu::RequestAdapterStatus::Success) { + GGML_LOG_ERROR("ggml_webgpu: Failed to get an adapter: %s\n", message); + return; + } + ctx->adapter = std::move(adapter); + }), + UINT64_MAX); GGML_ASSERT(ctx->adapter != nullptr); ctx->adapter.GetLimits(&ctx->limits); + ctx->max_wg_size_x = 288; // default value wgpu::AdapterInfo info{}; ctx->adapter.GetInfo(&info); @@ -1182,21 +1445,21 @@ static ggml_backend_dev_t ggml_backend_webgpu_reg_get_device(ggml_backend_reg_t wgpu::CallbackMode::AllowSpontaneous, [](const wgpu::Device & device, wgpu::DeviceLostReason reason, wgpu::StringView message) { GGML_UNUSED(device); - GGML_LOG_ERROR( - "ggml_webgpu: Device lost! Reason: %d, Message: %s\n", static_cast(reason), std::string(message).c_str()); + GGML_LOG_ERROR("ggml_webgpu: Device lost! Reason: %d, Message: %s\n", static_cast(reason), + std::string(message).c_str()); }); dev_desc.SetUncapturedErrorCallback( [](const wgpu::Device & device, wgpu::ErrorType reason, wgpu::StringView message) { GGML_UNUSED(device); - GGML_LOG_ERROR( - "ggml_webgpu: Device error! Reason: %d, Message: %s\n", static_cast(reason), std::string(message).c_str()); + GGML_LOG_ERROR("ggml_webgpu: Device error! Reason: %d, Message: %s\n", static_cast(reason), + std::string(message).c_str()); }); ctx->instance.WaitAny(ctx->adapter.RequestDevice( - &dev_desc, - wgpu::CallbackMode::AllowSpontaneous, + &dev_desc, wgpu::CallbackMode::AllowSpontaneous, [ctx](wgpu::RequestDeviceStatus status, wgpu::Device device, wgpu::StringView message) { if (status != wgpu::RequestDeviceStatus::Success) { - GGML_LOG_ERROR("ggml_webgpu: Failed to get a device: %s\n", std::string(message).c_str()); + GGML_LOG_ERROR("ggml_webgpu: Failed to get a device: %s\n", + std::string(message).c_str()); return; } ctx->device = std::move(device); @@ -1208,34 +1471,28 @@ static ggml_backend_dev_t ggml_backend_webgpu_reg_get_device(ggml_backend_reg_t ctx->queue = ctx->device.GetQueue(); // Create buffer pool for shader parameters - ctx->param_buf_pool.init(ctx->device, - WEBGPU_NUM_PARAM_BUFS, - WEBGPU_PARAMS_BUF_SIZE_BYTES, + ctx->param_buf_pool.init(ctx->device, WEBGPU_NUM_PARAM_BUFS, WEBGPU_PARAMS_BUF_SIZE_BYTES, wgpu::BufferUsage::CopyDst | wgpu::BufferUsage::Uniform, wgpu::BufferUsage::CopySrc | wgpu::BufferUsage::MapWrite); - ctx->set_rows_error_buf_pool.init(ctx->device, - WEBGPU_NUM_SET_ROWS_ERROR_BUFS, - WEBGPU_SET_ROWS_ERROR_BUF_SIZE_BYTES, + ctx->set_rows_error_buf_pool.init(ctx->device, WEBGPU_NUM_SET_ROWS_ERROR_BUFS, WEBGPU_SET_ROWS_ERROR_BUF_SIZE_BYTES, wgpu::BufferUsage::CopySrc | wgpu::BufferUsage::Storage, wgpu::BufferUsage::CopyDst | wgpu::BufferUsage::MapRead); ggml_webgpu_init_memset_pipeline(ctx); ggml_webgpu_init_mul_mat_pipeline(ctx); ggml_webgpu_init_set_rows_pipeline(ctx); + ggml_webgpu_init_get_rows_pipeline(ctx); ggml_webgpu_init_cpy_pipeline(ctx); + ggml_webgpu_init_add_pipeline(ctx); + ggml_webgpu_init_mul_pipeline(ctx); + ggml_webgpu_init_rms_norm_pipeline(ctx); #ifdef GGML_WEBGPU_DEBUG // Initialize debug buffers - ggml_webgpu_create_buffer(ctx->device, - ctx->debug_host_buf, - WEBGPU_DEBUG_BUF_ELEMS * sizeof(uint32_t), - wgpu::BufferUsage::CopyDst | wgpu::BufferUsage::MapRead, - "debug_host_buf"); - ggml_webgpu_create_buffer(ctx->device, - ctx->debug_dev_buf, - WEBGPU_DEBUG_BUF_ELEMS * sizeof(uint32_t), - wgpu::BufferUsage::Storage | wgpu::BufferUsage::CopySrc, - "debug_dev_buf"); + ggml_webgpu_create_buffer(ctx->device, ctx->debug_host_buf, WEBGPU_DEBUG_BUF_ELEMS * sizeof(uint32_t), + wgpu::BufferUsage::CopyDst | wgpu::BufferUsage::MapRead, "debug_host_buf"); + ggml_webgpu_create_buffer(ctx->device, ctx->debug_dev_buf, WEBGPU_DEBUG_BUF_ELEMS * sizeof(uint32_t), + wgpu::BufferUsage::Storage | wgpu::BufferUsage::CopySrc, "debug_dev_buf"); #endif static ggml_backend_webgpu_device_context device_ctx; @@ -1246,12 +1503,8 @@ static ggml_backend_dev_t ggml_backend_webgpu_reg_get_device(ggml_backend_reg_t GGML_LOG_INFO( "ggml_webgpu: adapter_info: vendor_id: %u | vendor: %s | architecture: %s | device_id: %u | name: %s | " "device_desc: %s\n", - info.vendorID, - std::string(info.vendor).c_str(), - std::string(info.architecture).c_str(), - info.deviceID, - std::string(info.device).c_str(), - std::string(info.description).c_str()); + info.vendorID, std::string(info.vendor).c_str(), std::string(info.architecture).c_str(), info.deviceID, + std::string(info.device).c_str(), std::string(info.description).c_str()); // See GGML Backend Device Interface section static ggml_backend_device device = { diff --git a/ggml/src/ggml-webgpu/wgsl-shaders/add.tmpl.wgsl b/ggml/src/ggml-webgpu/wgsl-shaders/add.tmpl.wgsl new file mode 100644 index 0000000000..f261cbb553 --- /dev/null +++ b/ggml/src/ggml-webgpu/wgsl-shaders/add.tmpl.wgsl @@ -0,0 +1,44 @@ +#define(VARIANTS) + +[ + { + "REPLS": { + "TYPE" : "f32", + } + }, + { + "REPLS": { + "TYPE" : "f16", + } + } +] + +#end(VARIANTS) + +#define(SHADER) + +enable f16; + +#include "binary_head.tmpl" + +@group(0) @binding(0) +var src0: array<{{TYPE}}>; + +@group(0) @binding(1) +var src1: array<{{TYPE}}>; + +@group(0) @binding(2) +var dst: array<{{TYPE}}>; + +@group(0) @binding(3) +var params: Params; + +override wg_size: u32; +@compute @workgroup_size(wg_size) +fn main(@builtin(global_invocation_id) gid: vec3) { + if (gid.x < params.ne) { + dst[params.offset_dst + gid.x] = src0[params.offset_src0 + gid.x] + src1[params.offset_src1 + src1_index(gid.x)]; + } +} + +#end(SHADER) diff --git a/ggml/src/ggml-webgpu/wgsl-shaders/add_in_place.tmpl.wgsl b/ggml/src/ggml-webgpu/wgsl-shaders/add_in_place.tmpl.wgsl new file mode 100644 index 0000000000..903f7bdbcc --- /dev/null +++ b/ggml/src/ggml-webgpu/wgsl-shaders/add_in_place.tmpl.wgsl @@ -0,0 +1,41 @@ +#define(VARIANTS) + +[ + { + "REPLS": { + "TYPE" : "f32", + } + }, + { + "REPLS": { + "TYPE" : "f16", + } + } +] + +#end(VARIANTS) + +#define(SHADER) + +enable f16; + +#include "binary_head.tmpl" + +@group(0) @binding(0) +var src0: array<{{TYPE}}>; + +@group(0) @binding(1) +var src1: array<{{TYPE}}>; + +@group(0) @binding(2) +var params: Params; + +override wg_size: u32; +@compute @workgroup_size(wg_size) +fn main(@builtin(global_invocation_id) gid: vec3) { + if (gid.x < params.ne) { + src0[params.offset_dst + gid.x] = src0[params.offset_src0 + gid.x] + src1[params.offset_src1 + src1_index(gid.x)]; + } +} + +#end(SHADER) diff --git a/ggml/src/ggml-webgpu/wgsl-shaders/binary_head.tmpl b/ggml/src/ggml-webgpu/wgsl-shaders/binary_head.tmpl new file mode 100644 index 0000000000..4b254f468d --- /dev/null +++ b/ggml/src/ggml-webgpu/wgsl-shaders/binary_head.tmpl @@ -0,0 +1,45 @@ +struct Params { + ne: u32, + + // offsets in elements + offset_src0: u32, + offset_src1: u32, + offset_dst: u32, + + stride_src1_0: u32, + stride_src1_1: u32, + stride_src1_2: u32, + stride_src1_3: u32, + + a_ne0: u32, + a_ne1: u32, + a_ne2: u32, + + b_ne0: u32, + b_ne1: u32, + b_ne2: u32, + b_ne3: u32, +}; + +fn src1_index(_i: u32) -> u32 { + var i = _i; + let a_i3 = i / (params.a_ne2 * params.a_ne1 * params.a_ne0); + i = i % (params.a_ne2 * params.a_ne1 * params.a_ne0); + let a_i2 = i / (params.a_ne1 * params.a_ne0); + i = i % (params.a_ne1 * params.a_ne0); + let a_i1 = i / params.a_ne0; + let a_i0 = i % params.a_ne0; + + // handle repetition of b + // index loops back to the beginning and repeats after elements are exhausted = modulo + let b_i0 = a_i0 % params.b_ne0; + let b_i1 = a_i1 % params.b_ne1; + let b_i2 = a_i2 % params.b_ne2; + let b_i3 = a_i3 % params.b_ne3; + + // compute index for position in b's flat array + return b_i0 * params.stride_src1_0 + + b_i1 * params.stride_src1_1 + + b_i2 * params.stride_src1_2 + + b_i3 * params.stride_src1_3; +} diff --git a/ggml/src/ggml-webgpu/wgsl-shaders/common_decls.tmpl b/ggml/src/ggml-webgpu/wgsl-shaders/common_decls.tmpl new file mode 100644 index 0000000000..389c97bb51 --- /dev/null +++ b/ggml/src/ggml-webgpu/wgsl-shaders/common_decls.tmpl @@ -0,0 +1,930 @@ +#decl(BYTE_HELPERS) + +fn get_byte(value: u32, index: u32) -> u32 { + return (value >> (index * 8)) & 0xFF; +} + +fn get_byte_i32(value: u32, index: u32) -> i32 { + return bitcast(((value >> (index * 8)) & 0xFF) << 24) >> 24; +} + +#enddecl(BYTE_HELPERS) + +#decl(Q4_0_T) +struct q4_0 { + d: f16, + qs: array +}; +#enddecl(Q4_0_T) + +#decl(Q4_1_T) +struct q4_1 { + d: f16, + m: f16, + qs: array +}; +#enddecl(Q4_1_T) + +#decl(Q5_0_T) +struct q5_0 { + d: f16, + qh: array, + qs: array +}; +#enddecl(Q5_0_T) + +#decl(Q5_1_T) +struct q5_1 { + d: f16, + m: f16, + qh: u32, + qs: array +}; +#enddecl(Q5_1_T) + +#decl(Q8_0_T) +struct q8_0 { + d: f16, + qs: array +}; +#enddecl(Q8_0_T) + +#decl(Q8_1_T) +struct q8_1 { + d: f16, + m: f16, + qs: array +}; +#enddecl(Q8_1_T) + +#decl(Q2_K_T) +struct q2_k { + scales: array, + qs: array, + d: f16, + dmin: f16 +}; +#enddecl(Q2_K_T) + +#decl(Q3_K_T) +struct q3_k { + hmask: array, + qs: array, + scales: array, + d: f16 +}; +#enddecl(Q3_K_T) + +#decl(Q45_K_SCALE_MIN) + +fn get_scale_min(is: u32, scales: array) -> vec2 { + if (is < 4) { + let sc_byte = get_byte(scales[is / 4], is % 4); + let min_byte = get_byte(scales[(is + 4) / 4], is % 4); + return vec2(f32(sc_byte & 63), f32(min_byte & 63)); + } else { + let sc_min_lo = get_byte(scales[(is + 4) / 4], (is + 4) % 4); + let sc_hi = get_byte(scales[(is - 4) / 4], (is - 4) % 4); + let min_hi = get_byte(scales[is / 4], is % 4); + let sc = (sc_min_lo & 0xF) | ((sc_hi >> 6) << 4); + let m = (sc_min_lo >> 4) | ((min_hi >> 6) << 4); + return vec2(f32(sc), f32(m)); + } +} + +#enddecl(Q45_K_SCALE_MIN) + +#decl(Q4_K_T) +struct q4_k { + d: f16, + dmin: f16, + scales: array, + qs: array +}; +#enddecl(Q4_K_T) + +#decl(Q5_K_T) +struct q5_k { + d: f16, + dmin: f16, + scales: array, + qh: array, + qs: array +}; +#enddecl(Q5_K_T) + +#decl(Q6_K_T) +struct q6_k { + ql: array, + qh: array, + scales: array, + d: f16 +}; +#enddecl(Q6_K_T) + +#decl(IQ2_XXS_T) +struct iq2_xxs { + d: f16, + qs: array +}; +#enddecl(IQ2_XXS_T) + +#decl(IQ2_XS_T) +struct iq2_xs { + d: f16, + qs: array, + scales: array +}; +#enddecl(IQ2_XS_T) + +#decl(IQ2_S_T) +struct iq2_s { + d: f16, + qs: array, + qh: array, + scales: array +}; +#enddecl(IQ2_S_T) + +#decl(IQ3_XSS_T) +struct iq3_xxs { + d: f16, + qs: array +}; +#enddecl(IQ3_XSS_T) + +#decl(IQ3_S_T) +struct iq3_s { + d: f16, + qs: array, + qh: array, + signs: array, + scales: array +}; +#enddecl(IQ3_S_T) + +#decl(IQ1_S_T) +struct iq1_s { + d: f16, + qs: array, + qh: array +}; +#enddecl(IQ1_S_T) + +#decl(IQ1_M_T) +struct iq1_m { + qs: array, + qh: array, + scales: array +}; +#enddecl(IQ1_M_T) + +#decl(IQ4_NL_T) +struct iq4_nl { + d: f16, + qs: array, +}; +#enddecl(IQ4_NL_T) + +#decl(IQ4_XS_T) +struct iq4_xs { + d: f16, + scales_h: f16, + scales_l: u32, + qs: array +}; +#enddecl(IQ4_XS_T) + +#decl(IQ23_TABLES) +const kmask_iq2xs : array = array( + 0x08040201u, // 1, 2, 4, 8 + 0x80402010u // 16, 32, 64, 128 +); + +const ksigns_iq2xs: array = array( + 0x03828100,0x87060584,0x8b0a0988,0x0f8e8d0c, + 0x93121190,0x17969514,0x1b9a9918,0x9f1e1d9c, + 0xa32221a0,0x27a6a524,0x2baaa928,0xaf2e2dac, + 0x33b2b130,0xb73635b4,0xbb3a39b8,0x3fbebd3c, + 0xc34241c0,0x47c6c544,0x4bcac948,0xcf4e4dcc, + 0x53d2d150,0xd75655d4,0xdb5a59d8,0x5fdedd5c, + 0x63e2e160,0xe76665e4,0xeb6a69e8,0x6feeed6c, + 0xf37271f0,0x77f6f574,0x7bfaf978,0xff7e7dfc +); +#enddecl(IQ23_TABLES) + +#decl(IQ2_XXS_GRID) +const iq2xxs_grid = array( + 0x08080808, 0x08080808, 0x0808082b, 0x08080808, 0x08081919, 0x08080808, 0x08082b08, 0x08080808, + 0x08082b2b, 0x08080808, 0x08190819, 0x08080808, 0x08191908, 0x08080808, 0x082b0808, 0x08080808, + 0x082b082b, 0x08080808, 0x082b2b08, 0x08080808, 0x082b2b2b, 0x08080808, 0x19080819, 0x08080808, + 0x19081908, 0x08080808, 0x19190808, 0x08080808, 0x19192b08, 0x08080808, 0x192b0819, 0x08080808, + 0x192b1908, 0x08080808, 0x2b080808, 0x08080808, 0x2b08082b, 0x08080808, 0x2b082b2b, 0x08080808, + 0x2b2b082b, 0x08080808, 0x08080819, 0x08080819, 0x08081908, 0x08080819, 0x08190808, 0x08080819, + 0x08191919, 0x08080819, 0x19080808, 0x08080819, 0x2b081908, 0x08080819, 0x2b192b08, 0x08080819, + 0x08080808, 0x0808082b, 0x0808082b, 0x0808082b, 0x082b082b, 0x0808082b, 0x2b08082b, 0x0808082b, + 0x08080819, 0x08081908, 0x08081908, 0x08081908, 0x08190808, 0x08081908, 0x082b0819, 0x08081908, + 0x082b1908, 0x08081908, 0x19080808, 0x08081908, 0x1908082b, 0x08081908, 0x19082b08, 0x08081908, + 0x192b0808, 0x08081908, 0x2b080819, 0x08081908, 0x2b081908, 0x08081908, 0x2b190808, 0x08081908, + 0x2b2b1908, 0x08081908, 0x08080808, 0x08081919, 0x0808082b, 0x08081919, 0x08082b08, 0x08081919, + 0x082b0808, 0x08081919, 0x1908192b, 0x08081919, 0x192b2b19, 0x08081919, 0x2b080808, 0x08081919, + 0x2b190819, 0x08081919, 0x08082b19, 0x0808192b, 0x08190808, 0x0808192b, 0x19080808, 0x0808192b, + 0x2b081908, 0x0808192b, 0x2b2b1908, 0x0808192b, 0x08080808, 0x08082b08, 0x08081919, 0x08082b08, + 0x08082b08, 0x08082b08, 0x08191908, 0x08082b08, 0x082b2b08, 0x08082b08, 0x19080819, 0x08082b08, + 0x19081908, 0x08082b08, 0x19190808, 0x08082b08, 0x1919082b, 0x08082b08, 0x2b082b08, 0x08082b08, + 0x08081908, 0x08082b19, 0x19080808, 0x08082b19, 0x0808082b, 0x08082b2b, 0x08191908, 0x08082b2b, + 0x08080819, 0x08190808, 0x08081908, 0x08190808, 0x08190808, 0x08190808, 0x082b0819, 0x08190808, + 0x19080808, 0x08190808, 0x192b0808, 0x08190808, 0x2b081908, 0x08190808, 0x2b190808, 0x08190808, + 0x2b191919, 0x08190808, 0x08080808, 0x08190819, 0x08082b08, 0x08190819, 0x082b0808, 0x08190819, + 0x19190808, 0x08190819, 0x19192b2b, 0x08190819, 0x2b080808, 0x08190819, 0x082b1908, 0x0819082b, + 0x19081919, 0x0819082b, 0x08080808, 0x08191908, 0x08082b08, 0x08191908, 0x082b0808, 0x08191908, + 0x082b1919, 0x08191908, 0x19082b19, 0x08191908, 0x2b080808, 0x08191908, 0x08192b08, 0x08191919, + 0x192b082b, 0x08191919, 0x08080808, 0x0819192b, 0x0819192b, 0x0819192b, 0x08080819, 0x08192b08, + 0x08081908, 0x08192b08, 0x08190808, 0x08192b08, 0x19080808, 0x08192b08, 0x2b080819, 0x08192b08, + 0x08080808, 0x08192b19, 0x08081919, 0x08192b19, 0x2b2b0808, 0x08192b19, 0x19190819, 0x08192b2b, + 0x08080808, 0x082b0808, 0x0808082b, 0x082b0808, 0x08082b2b, 0x082b0808, 0x19081908, 0x082b0808, + 0x192b0819, 0x082b0808, 0x2b080808, 0x082b0808, 0x2b08082b, 0x082b0808, 0x082b2b19, 0x082b0819, + 0x19082b08, 0x082b0819, 0x08080808, 0x082b082b, 0x0808082b, 0x082b082b, 0x08080819, 0x082b1908, + 0x08081908, 0x082b1908, 0x08190808, 0x082b1908, 0x19080808, 0x082b1908, 0x1919192b, 0x082b1908, + 0x08080808, 0x082b1919, 0x19080819, 0x082b1919, 0x192b1908, 0x082b1919, 0x2b190808, 0x082b192b, + 0x08082b08, 0x082b2b08, 0x082b0808, 0x082b2b08, 0x2b191908, 0x082b2b08, 0x19081908, 0x082b2b2b, + 0x08080819, 0x19080808, 0x08081908, 0x19080808, 0x08190808, 0x19080808, 0x08192b08, 0x19080808, + 0x082b0819, 0x19080808, 0x082b1908, 0x19080808, 0x19080808, 0x19080808, 0x19082b08, 0x19080808, + 0x1919192b, 0x19080808, 0x192b0808, 0x19080808, 0x2b080819, 0x19080808, 0x2b081908, 0x19080808, + 0x2b190808, 0x19080808, 0x08080808, 0x19080819, 0x082b0808, 0x19080819, 0x192b0819, 0x19080819, + 0x2b080808, 0x19080819, 0x2b081919, 0x19080819, 0x08080819, 0x1908082b, 0x08190808, 0x1908082b, + 0x19082b08, 0x1908082b, 0x1919192b, 0x1908082b, 0x192b2b08, 0x1908082b, 0x08080808, 0x19081908, + 0x08082b08, 0x19081908, 0x082b0808, 0x19081908, 0x2b080808, 0x19081908, 0x2b192b19, 0x19081908, + 0x0819082b, 0x19081919, 0x082b1908, 0x19081919, 0x08080808, 0x1908192b, 0x08080819, 0x19082b08, + 0x08081908, 0x19082b08, 0x08190808, 0x19082b08, 0x19080808, 0x19082b08, 0x19081919, 0x19082b08, + 0x08080808, 0x19082b19, 0x19192b08, 0x19082b19, 0x192b0819, 0x19082b19, 0x2b08082b, 0x19082b19, + 0x19081919, 0x19082b2b, 0x2b190808, 0x19082b2b, 0x08080808, 0x19190808, 0x08082b08, 0x19190808, + 0x08190819, 0x19190808, 0x08192b19, 0x19190808, 0x082b0808, 0x19190808, 0x2b080808, 0x19190808, + 0x2b082b08, 0x19190808, 0x08081908, 0x19190819, 0x1908082b, 0x19190819, 0x2b2b1908, 0x19190819, + 0x2b190819, 0x1919082b, 0x2b190808, 0x19191908, 0x2b19082b, 0x19191908, 0x08082b2b, 0x19191919, + 0x08080819, 0x1919192b, 0x19191908, 0x1919192b, 0x08080808, 0x19192b08, 0x08190819, 0x19192b08, + 0x08192b19, 0x19192b08, 0x192b1908, 0x19192b08, 0x19080808, 0x19192b19, 0x08082b08, 0x19192b2b, + 0x08081908, 0x192b0808, 0x08190808, 0x192b0808, 0x19080808, 0x192b0808, 0x192b2b08, 0x192b0808, + 0x08080808, 0x192b0819, 0x19191919, 0x192b0819, 0x08192b08, 0x192b082b, 0x192b0808, 0x192b082b, + 0x08080808, 0x192b1908, 0x08081919, 0x192b1908, 0x08190808, 0x192b1919, 0x0819082b, 0x192b1919, + 0x2b081908, 0x192b1919, 0x1908082b, 0x192b2b08, 0x08080808, 0x2b080808, 0x0808082b, 0x2b080808, + 0x08082b2b, 0x2b080808, 0x19080819, 0x2b080808, 0x2b08082b, 0x2b080808, 0x08081908, 0x2b080819, + 0x08192b08, 0x2b080819, 0x19080808, 0x2b080819, 0x08190819, 0x2b08082b, 0x08080819, 0x2b081908, + 0x08081908, 0x2b081908, 0x08190808, 0x2b081908, 0x08191919, 0x2b081908, 0x19080808, 0x2b081908, + 0x192b0808, 0x2b081908, 0x08080808, 0x2b081919, 0x1908192b, 0x2b081919, 0x2b191908, 0x2b081919, + 0x08082b19, 0x2b08192b, 0x19080808, 0x2b08192b, 0x192b0808, 0x2b08192b, 0x0808082b, 0x2b082b08, + 0x08081908, 0x2b082b19, 0x08190819, 0x2b082b2b, 0x08081908, 0x2b190808, 0x08190808, 0x2b190808, + 0x082b1908, 0x2b190808, 0x19080808, 0x2b190808, 0x2b2b0819, 0x2b190808, 0x0819192b, 0x2b190819, + 0x2b080808, 0x2b190819, 0x19081919, 0x2b19082b, 0x08080808, 0x2b191908, 0x082b082b, 0x2b191908, + 0x19081908, 0x2b191908, 0x19190819, 0x2b191919, 0x2b080819, 0x2b192b08, 0x082b0808, 0x2b192b19, + 0x0808082b, 0x2b2b0808, 0x19190808, 0x2b2b0808, 0x2b081919, 0x2b2b0808, 0x08082b19, 0x2b2b0819, + 0x08080808, 0x2b2b082b, 0x08192b08, 0x2b2b1908, 0x19190808, 0x2b2b2b08, 0x08081908, 0x2b2b2b19 +); +#enddecl(IQ2_XXS_GRID) + +#decl(IQ2_XS_GRID) +const iq2xs_grid = array( + 0x08080808, 0x08080808, 0x0808082b, 0x08080808, 0x08081919, 0x08080808, 0x08082b08, 0x08080808, + 0x08082b2b, 0x08080808, 0x08190819, 0x08080808, 0x08191908, 0x08080808, 0x0819192b, 0x08080808, + 0x08192b19, 0x08080808, 0x082b0808, 0x08080808, 0x082b082b, 0x08080808, 0x082b1919, 0x08080808, + 0x082b2b08, 0x08080808, 0x19080819, 0x08080808, 0x19081908, 0x08080808, 0x1908192b, 0x08080808, + 0x19082b19, 0x08080808, 0x19190808, 0x08080808, 0x1919082b, 0x08080808, 0x19191919, 0x08080808, + 0x19192b08, 0x08080808, 0x192b0819, 0x08080808, 0x192b1908, 0x08080808, 0x2b080808, 0x08080808, + 0x2b08082b, 0x08080808, 0x2b081919, 0x08080808, 0x2b082b08, 0x08080808, 0x2b190819, 0x08080808, + 0x2b191908, 0x08080808, 0x2b192b19, 0x08080808, 0x2b2b0808, 0x08080808, 0x08080819, 0x08080819, + 0x08081908, 0x08080819, 0x0808192b, 0x08080819, 0x08082b19, 0x08080819, 0x08190808, 0x08080819, + 0x0819082b, 0x08080819, 0x08191919, 0x08080819, 0x08192b08, 0x08080819, 0x08192b2b, 0x08080819, + 0x082b0819, 0x08080819, 0x082b1908, 0x08080819, 0x19080808, 0x08080819, 0x1908082b, 0x08080819, + 0x19081919, 0x08080819, 0x19082b08, 0x08080819, 0x19190819, 0x08080819, 0x19191908, 0x08080819, + 0x192b0808, 0x08080819, 0x192b2b08, 0x08080819, 0x2b080819, 0x08080819, 0x2b081908, 0x08080819, + 0x2b190808, 0x08080819, 0x08080808, 0x0808082b, 0x0808082b, 0x0808082b, 0x08081919, 0x0808082b, + 0x08082b08, 0x0808082b, 0x08190819, 0x0808082b, 0x08191908, 0x0808082b, 0x082b0808, 0x0808082b, + 0x19080819, 0x0808082b, 0x19081908, 0x0808082b, 0x19190808, 0x0808082b, 0x19191919, 0x0808082b, + 0x2b080808, 0x0808082b, 0x2b082b2b, 0x0808082b, 0x08080819, 0x08081908, 0x08081908, 0x08081908, + 0x0808192b, 0x08081908, 0x08082b19, 0x08081908, 0x08190808, 0x08081908, 0x0819082b, 0x08081908, + 0x08191919, 0x08081908, 0x08192b08, 0x08081908, 0x082b0819, 0x08081908, 0x082b1908, 0x08081908, + 0x19080808, 0x08081908, 0x1908082b, 0x08081908, 0x19081919, 0x08081908, 0x19082b08, 0x08081908, + 0x19190819, 0x08081908, 0x19191908, 0x08081908, 0x1919192b, 0x08081908, 0x192b0808, 0x08081908, + 0x2b080819, 0x08081908, 0x2b081908, 0x08081908, 0x2b190808, 0x08081908, 0x08080808, 0x08081919, + 0x0808082b, 0x08081919, 0x08081919, 0x08081919, 0x08082b08, 0x08081919, 0x08190819, 0x08081919, + 0x08191908, 0x08081919, 0x082b0808, 0x08081919, 0x19080819, 0x08081919, 0x19081908, 0x08081919, + 0x19190808, 0x08081919, 0x192b0819, 0x08081919, 0x2b080808, 0x08081919, 0x08080819, 0x0808192b, + 0x08081908, 0x0808192b, 0x08190808, 0x0808192b, 0x082b192b, 0x0808192b, 0x19080808, 0x0808192b, + 0x1908082b, 0x0808192b, 0x2b081908, 0x0808192b, 0x08080808, 0x08082b08, 0x0808082b, 0x08082b08, + 0x08081919, 0x08082b08, 0x08082b08, 0x08082b08, 0x08082b2b, 0x08082b08, 0x08190819, 0x08082b08, + 0x08191908, 0x08082b08, 0x082b0808, 0x08082b08, 0x082b1919, 0x08082b08, 0x19080819, 0x08082b08, + 0x19081908, 0x08082b08, 0x19190808, 0x08082b08, 0x19192b08, 0x08082b08, 0x2b080808, 0x08082b08, + 0x2b2b0808, 0x08082b08, 0x2b2b2b2b, 0x08082b08, 0x08080819, 0x08082b19, 0x08081908, 0x08082b19, + 0x08190808, 0x08082b19, 0x19080808, 0x08082b19, 0x2b080819, 0x08082b19, 0x2b082b19, 0x08082b19, + 0x08080808, 0x08082b2b, 0x082b0808, 0x08082b2b, 0x082b2b08, 0x08082b2b, 0x2b19192b, 0x08082b2b, + 0x2b2b0808, 0x08082b2b, 0x08080819, 0x08190808, 0x08081908, 0x08190808, 0x0808192b, 0x08190808, + 0x08082b19, 0x08190808, 0x08190808, 0x08190808, 0x0819082b, 0x08190808, 0x08191919, 0x08190808, + 0x08192b08, 0x08190808, 0x082b0819, 0x08190808, 0x082b1908, 0x08190808, 0x19080808, 0x08190808, + 0x1908082b, 0x08190808, 0x19081919, 0x08190808, 0x19082b08, 0x08190808, 0x19190819, 0x08190808, + 0x19191908, 0x08190808, 0x192b0808, 0x08190808, 0x192b2b2b, 0x08190808, 0x2b080819, 0x08190808, + 0x2b081908, 0x08190808, 0x2b190808, 0x08190808, 0x08080808, 0x08190819, 0x0808082b, 0x08190819, + 0x08081919, 0x08190819, 0x08082b08, 0x08190819, 0x08190819, 0x08190819, 0x08191908, 0x08190819, + 0x082b0808, 0x08190819, 0x19080819, 0x08190819, 0x19081908, 0x08190819, 0x19190808, 0x08190819, + 0x2b080808, 0x08190819, 0x2b191908, 0x08190819, 0x2b19192b, 0x08190819, 0x08080819, 0x0819082b, + 0x08081908, 0x0819082b, 0x0808192b, 0x0819082b, 0x08190808, 0x0819082b, 0x19080808, 0x0819082b, + 0x192b0808, 0x0819082b, 0x08080808, 0x08191908, 0x0808082b, 0x08191908, 0x08081919, 0x08191908, + 0x08082b08, 0x08191908, 0x08190819, 0x08191908, 0x08191908, 0x08191908, 0x082b0808, 0x08191908, + 0x19080819, 0x08191908, 0x19081908, 0x08191908, 0x19082b19, 0x08191908, 0x19190808, 0x08191908, + 0x192b1908, 0x08191908, 0x2b080808, 0x08191908, 0x08080819, 0x08191919, 0x08081908, 0x08191919, + 0x08190808, 0x08191919, 0x19080808, 0x08191919, 0x08080808, 0x0819192b, 0x08191908, 0x0819192b, + 0x19082b19, 0x0819192b, 0x08080819, 0x08192b08, 0x08081908, 0x08192b08, 0x08190808, 0x08192b08, + 0x0819082b, 0x08192b08, 0x19080808, 0x08192b08, 0x19191908, 0x08192b08, 0x2b08192b, 0x08192b08, + 0x08080808, 0x08192b19, 0x08081919, 0x08192b19, 0x192b192b, 0x08192b19, 0x19190819, 0x08192b2b, + 0x2b2b2b19, 0x08192b2b, 0x08080808, 0x082b0808, 0x0808082b, 0x082b0808, 0x08081919, 0x082b0808, + 0x08082b08, 0x082b0808, 0x08082b2b, 0x082b0808, 0x08190819, 0x082b0808, 0x08191908, 0x082b0808, + 0x082b0808, 0x082b0808, 0x19080819, 0x082b0808, 0x19081908, 0x082b0808, 0x19190808, 0x082b0808, + 0x2b080808, 0x082b0808, 0x2b2b0808, 0x082b0808, 0x08080819, 0x082b0819, 0x08081908, 0x082b0819, + 0x08190808, 0x082b0819, 0x19080808, 0x082b0819, 0x19082b08, 0x082b0819, 0x192b1919, 0x082b0819, + 0x08080808, 0x082b082b, 0x082b082b, 0x082b082b, 0x2b080808, 0x082b082b, 0x2b2b2b08, 0x082b082b, + 0x08080819, 0x082b1908, 0x08081908, 0x082b1908, 0x08190808, 0x082b1908, 0x082b2b19, 0x082b1908, + 0x19080808, 0x082b1908, 0x08080808, 0x082b1919, 0x19080819, 0x082b1919, 0x1919082b, 0x082b1919, + 0x2b192b19, 0x082b1919, 0x08080819, 0x082b192b, 0x08192b2b, 0x082b192b, 0x2b2b192b, 0x082b192b, + 0x08080808, 0x082b2b08, 0x08082b08, 0x082b2b08, 0x08082b2b, 0x082b2b08, 0x082b0808, 0x082b2b08, + 0x19191919, 0x082b2b08, 0x2b082b08, 0x082b2b08, 0x2b2b082b, 0x082b2b08, 0x192b2b08, 0x082b2b19, + 0x2b190808, 0x082b2b19, 0x08082b08, 0x082b2b2b, 0x082b0808, 0x082b2b2b, 0x2b08082b, 0x082b2b2b, + 0x2b082b08, 0x082b2b2b, 0x2b082b2b, 0x082b2b2b, 0x08080819, 0x19080808, 0x08081908, 0x19080808, + 0x0808192b, 0x19080808, 0x08082b19, 0x19080808, 0x08190808, 0x19080808, 0x0819082b, 0x19080808, + 0x08191919, 0x19080808, 0x08192b08, 0x19080808, 0x082b0819, 0x19080808, 0x082b1908, 0x19080808, + 0x19080808, 0x19080808, 0x1908082b, 0x19080808, 0x19081919, 0x19080808, 0x19082b08, 0x19080808, + 0x19082b2b, 0x19080808, 0x19190819, 0x19080808, 0x19191908, 0x19080808, 0x192b0808, 0x19080808, + 0x192b1919, 0x19080808, 0x2b080819, 0x19080808, 0x2b081908, 0x19080808, 0x2b190808, 0x19080808, + 0x08080808, 0x19080819, 0x0808082b, 0x19080819, 0x08081919, 0x19080819, 0x08082b08, 0x19080819, + 0x08190819, 0x19080819, 0x08191908, 0x19080819, 0x082b0808, 0x19080819, 0x19080819, 0x19080819, + 0x19081908, 0x19080819, 0x19190808, 0x19080819, 0x2b080808, 0x19080819, 0x2b081919, 0x19080819, + 0x2b2b082b, 0x19080819, 0x08080819, 0x1908082b, 0x08081908, 0x1908082b, 0x08190808, 0x1908082b, + 0x0819082b, 0x1908082b, 0x082b2b19, 0x1908082b, 0x19080808, 0x1908082b, 0x08080808, 0x19081908, + 0x0808082b, 0x19081908, 0x08081919, 0x19081908, 0x08082b08, 0x19081908, 0x08190819, 0x19081908, + 0x08191908, 0x19081908, 0x08192b19, 0x19081908, 0x082b0808, 0x19081908, 0x19080819, 0x19081908, + 0x19081908, 0x19081908, 0x19190808, 0x19081908, 0x2b080808, 0x19081908, 0x2b191908, 0x19081908, + 0x08080819, 0x19081919, 0x08081908, 0x19081919, 0x08190808, 0x19081919, 0x082b1908, 0x19081919, + 0x19080808, 0x19081919, 0x2b192b2b, 0x19081919, 0x08080808, 0x1908192b, 0x08082b2b, 0x1908192b, + 0x19081908, 0x1908192b, 0x19190808, 0x1908192b, 0x08080819, 0x19082b08, 0x08081908, 0x19082b08, + 0x08190808, 0x19082b08, 0x19080808, 0x19082b08, 0x19081919, 0x19082b08, 0x19191908, 0x19082b08, + 0x192b082b, 0x19082b08, 0x08080808, 0x19082b19, 0x08190819, 0x19082b19, 0x19081908, 0x19082b19, + 0x19190808, 0x19082b19, 0x192b2b19, 0x19082b19, 0x08081908, 0x19082b2b, 0x08080808, 0x19190808, + 0x0808082b, 0x19190808, 0x08081919, 0x19190808, 0x08082b08, 0x19190808, 0x08190819, 0x19190808, + 0x08191908, 0x19190808, 0x082b0808, 0x19190808, 0x082b2b08, 0x19190808, 0x19080819, 0x19190808, + 0x19081908, 0x19190808, 0x19190808, 0x19190808, 0x2b080808, 0x19190808, 0x08080819, 0x19190819, + 0x08081908, 0x19190819, 0x08190808, 0x19190819, 0x08191919, 0x19190819, 0x19080808, 0x19190819, + 0x1908082b, 0x19190819, 0x08080808, 0x1919082b, 0x19081908, 0x1919082b, 0x2b2b2b2b, 0x1919082b, + 0x08080819, 0x19191908, 0x08081908, 0x19191908, 0x08190808, 0x19191908, 0x082b0819, 0x19191908, + 0x19080808, 0x19191908, 0x192b0808, 0x19191908, 0x2b080819, 0x19191908, 0x2b2b0819, 0x19191908, + 0x08080808, 0x19191919, 0x08082b08, 0x19191919, 0x2b080808, 0x19191919, 0x2b082b08, 0x19191919, + 0x082b0819, 0x1919192b, 0x192b2b08, 0x1919192b, 0x2b2b0819, 0x1919192b, 0x08080808, 0x19192b08, + 0x08191908, 0x19192b08, 0x19080819, 0x19192b08, 0x19190808, 0x19192b08, 0x2b192b19, 0x19192b08, + 0x08192b2b, 0x19192b19, 0x19080808, 0x19192b19, 0x1908082b, 0x19192b19, 0x2b081919, 0x19192b2b, + 0x08080819, 0x192b0808, 0x08081908, 0x192b0808, 0x08190808, 0x192b0808, 0x19080808, 0x192b0808, + 0x19191908, 0x192b0808, 0x192b082b, 0x192b0808, 0x2b08192b, 0x192b0808, 0x2b2b2b19, 0x192b0808, + 0x08080808, 0x192b0819, 0x082b1908, 0x192b082b, 0x19082b2b, 0x192b082b, 0x2b19082b, 0x192b082b, + 0x08080808, 0x192b1908, 0x0819192b, 0x192b1908, 0x08190808, 0x192b1919, 0x19080808, 0x192b1919, + 0x19081919, 0x192b1919, 0x2b2b1908, 0x192b1919, 0x08080819, 0x192b2b08, 0x192b2b2b, 0x192b2b08, + 0x082b1919, 0x192b2b19, 0x0808192b, 0x192b2b2b, 0x19191908, 0x192b2b2b, 0x192b082b, 0x192b2b2b, + 0x08080808, 0x2b080808, 0x0808082b, 0x2b080808, 0x08081919, 0x2b080808, 0x08082b08, 0x2b080808, + 0x08190819, 0x2b080808, 0x08191908, 0x2b080808, 0x082b0808, 0x2b080808, 0x082b2b2b, 0x2b080808, + 0x19080819, 0x2b080808, 0x19081908, 0x2b080808, 0x19190808, 0x2b080808, 0x2b080808, 0x2b080808, + 0x2b08082b, 0x2b080808, 0x2b2b2b08, 0x2b080808, 0x2b2b2b2b, 0x2b080808, 0x08080819, 0x2b080819, + 0x08081908, 0x2b080819, 0x0808192b, 0x2b080819, 0x08190808, 0x2b080819, 0x19080808, 0x2b080819, + 0x19190819, 0x2b080819, 0x19192b19, 0x2b080819, 0x08080808, 0x2b08082b, 0x082b0808, 0x2b08082b, + 0x2b080808, 0x2b08082b, 0x2b08082b, 0x2b08082b, 0x2b2b0808, 0x2b08082b, 0x2b2b2b08, 0x2b08082b, + 0x08080819, 0x2b081908, 0x08081908, 0x2b081908, 0x08190808, 0x2b081908, 0x0819082b, 0x2b081908, + 0x08191919, 0x2b081908, 0x19080808, 0x2b081908, 0x192b0808, 0x2b081908, 0x2b082b19, 0x2b081908, + 0x08080808, 0x2b081919, 0x19081908, 0x2b081919, 0x2b2b1919, 0x2b081919, 0x08192b08, 0x2b08192b, + 0x192b2b2b, 0x2b08192b, 0x08080808, 0x2b082b08, 0x08082b08, 0x2b082b08, 0x082b1919, 0x2b082b08, + 0x19192b2b, 0x2b082b08, 0x2b080808, 0x2b082b08, 0x2b08082b, 0x2b082b08, 0x2b2b2b08, 0x2b082b08, + 0x0808192b, 0x2b082b19, 0x082b082b, 0x2b082b2b, 0x2b080808, 0x2b082b2b, 0x2b082b08, 0x2b082b2b, + 0x2b19192b, 0x2b082b2b, 0x2b2b2b08, 0x2b082b2b, 0x08080819, 0x2b190808, 0x08081908, 0x2b190808, + 0x08190808, 0x2b190808, 0x19080808, 0x2b190808, 0x1919192b, 0x2b190808, 0x2b081908, 0x2b190808, + 0x08080808, 0x2b190819, 0x082b082b, 0x2b190819, 0x192b1908, 0x2b190819, 0x1919192b, 0x2b19082b, + 0x2b082b19, 0x2b19082b, 0x08080808, 0x2b191908, 0x08081919, 0x2b191908, 0x19081908, 0x2b191908, + 0x19190808, 0x2b191908, 0x19192b08, 0x2b191908, 0x082b2b19, 0x2b191919, 0x2b190808, 0x2b191919, + 0x2b19082b, 0x2b191919, 0x19080819, 0x2b19192b, 0x19190819, 0x2b192b08, 0x2b2b192b, 0x2b192b08, + 0x19082b19, 0x2b192b19, 0x08191919, 0x2b192b2b, 0x192b0808, 0x2b192b2b, 0x08080808, 0x2b2b0808, + 0x0808082b, 0x2b2b0808, 0x08082b08, 0x2b2b0808, 0x08082b2b, 0x2b2b0808, 0x082b0808, 0x2b2b0808, + 0x082b2b2b, 0x2b2b0808, 0x2b2b0808, 0x2b2b0808, 0x19190819, 0x2b2b0819, 0x19192b19, 0x2b2b0819, + 0x2b2b192b, 0x2b2b0819, 0x08080808, 0x2b2b082b, 0x0808082b, 0x2b2b082b, 0x08082b08, 0x2b2b082b, + 0x082b2b2b, 0x2b2b082b, 0x2b080808, 0x2b2b082b, 0x2b2b0808, 0x2b2b082b, 0x19080808, 0x2b2b1908, + 0x2b191919, 0x2b2b1908, 0x192b1919, 0x2b2b192b, 0x2b192b08, 0x2b2b192b, 0x08082b2b, 0x2b2b2b08, + 0x082b0808, 0x2b2b2b08, 0x082b082b, 0x2b2b2b08, 0x082b2b08, 0x2b2b2b08, 0x2b2b0808, 0x2b2b2b08, + 0x2b2b2b08, 0x2b2b2b08, 0x08081908, 0x2b2b2b19, 0x2b081908, 0x2b2b2b19, 0x2b08192b, 0x2b2b2b19, + 0x082b2b08, 0x2b2b2b2b, 0x082b2b2b, 0x2b2b2b2b, 0x2b190819, 0x2b2b2b2b, 0x2b2b2b2b, 0x2b2b2b2b +); +#enddecl(IQ2_XS_GRID) + +#decl(IQ2_S_GRID) +const iq2s_grid = array( + 0x08080808, 0x08080808, 0x0808082b, 0x08080808, 0x08081919, 0x08080808, 0x08082b08, 0x08080808, + 0x08082b2b, 0x08080808, 0x08190819, 0x08080808, 0x08191908, 0x08080808, 0x0819192b, 0x08080808, + 0x08192b19, 0x08080808, 0x082b0808, 0x08080808, 0x082b082b, 0x08080808, 0x082b1919, 0x08080808, + 0x082b2b08, 0x08080808, 0x19080819, 0x08080808, 0x19081908, 0x08080808, 0x1908192b, 0x08080808, + 0x19082b19, 0x08080808, 0x19190808, 0x08080808, 0x1919082b, 0x08080808, 0x19191919, 0x08080808, + 0x19192b08, 0x08080808, 0x192b0819, 0x08080808, 0x192b1908, 0x08080808, 0x192b192b, 0x08080808, + 0x192b2b19, 0x08080808, 0x2b080808, 0x08080808, 0x2b08082b, 0x08080808, 0x2b081919, 0x08080808, + 0x2b082b08, 0x08080808, 0x2b190819, 0x08080808, 0x2b191908, 0x08080808, 0x2b2b0808, 0x08080808, + 0x2b2b1919, 0x08080808, 0x2b2b2b2b, 0x08080808, 0x08080819, 0x08080819, 0x08081908, 0x08080819, + 0x0808192b, 0x08080819, 0x08082b19, 0x08080819, 0x08190808, 0x08080819, 0x0819082b, 0x08080819, + 0x08191919, 0x08080819, 0x08192b08, 0x08080819, 0x082b0819, 0x08080819, 0x082b1908, 0x08080819, + 0x19080808, 0x08080819, 0x1908082b, 0x08080819, 0x19081919, 0x08080819, 0x19082b08, 0x08080819, + 0x19190819, 0x08080819, 0x19191908, 0x08080819, 0x1919192b, 0x08080819, 0x19192b19, 0x08080819, + 0x192b0808, 0x08080819, 0x192b1919, 0x08080819, 0x192b2b08, 0x08080819, 0x2b080819, 0x08080819, + 0x2b081908, 0x08080819, 0x2b190808, 0x08080819, 0x2b19082b, 0x08080819, 0x2b191919, 0x08080819, + 0x2b2b0819, 0x08080819, 0x2b2b1908, 0x08080819, 0x08080808, 0x0808082b, 0x0808082b, 0x0808082b, + 0x08081919, 0x0808082b, 0x08082b08, 0x0808082b, 0x08190819, 0x0808082b, 0x08191908, 0x0808082b, + 0x082b0808, 0x0808082b, 0x082b2b2b, 0x0808082b, 0x19080819, 0x0808082b, 0x19081908, 0x0808082b, + 0x1908192b, 0x0808082b, 0x19082b19, 0x0808082b, 0x19190808, 0x0808082b, 0x19191919, 0x0808082b, + 0x2b080808, 0x0808082b, 0x2b081919, 0x0808082b, 0x2b082b2b, 0x0808082b, 0x2b191908, 0x0808082b, + 0x2b2b082b, 0x0808082b, 0x08080819, 0x08081908, 0x08081908, 0x08081908, 0x0808192b, 0x08081908, + 0x08082b19, 0x08081908, 0x08190808, 0x08081908, 0x0819082b, 0x08081908, 0x08191919, 0x08081908, + 0x08192b08, 0x08081908, 0x082b0819, 0x08081908, 0x082b1908, 0x08081908, 0x082b192b, 0x08081908, + 0x082b2b19, 0x08081908, 0x19080808, 0x08081908, 0x1908082b, 0x08081908, 0x19081919, 0x08081908, + 0x19082b08, 0x08081908, 0x19082b2b, 0x08081908, 0x19190819, 0x08081908, 0x19191908, 0x08081908, + 0x1919192b, 0x08081908, 0x19192b19, 0x08081908, 0x192b0808, 0x08081908, 0x192b082b, 0x08081908, + 0x192b1919, 0x08081908, 0x2b080819, 0x08081908, 0x2b081908, 0x08081908, 0x2b08192b, 0x08081908, + 0x2b082b19, 0x08081908, 0x2b190808, 0x08081908, 0x2b191919, 0x08081908, 0x2b192b08, 0x08081908, + 0x2b2b0819, 0x08081908, 0x2b2b1908, 0x08081908, 0x08080808, 0x08081919, 0x0808082b, 0x08081919, + 0x08081919, 0x08081919, 0x08082b08, 0x08081919, 0x08082b2b, 0x08081919, 0x08190819, 0x08081919, + 0x08191908, 0x08081919, 0x0819192b, 0x08081919, 0x08192b19, 0x08081919, 0x082b0808, 0x08081919, + 0x082b1919, 0x08081919, 0x082b2b08, 0x08081919, 0x19080819, 0x08081919, 0x19081908, 0x08081919, + 0x1908192b, 0x08081919, 0x19082b19, 0x08081919, 0x19190808, 0x08081919, 0x1919082b, 0x08081919, + 0x19191919, 0x08081919, 0x19192b08, 0x08081919, 0x192b0819, 0x08081919, 0x192b1908, 0x08081919, + 0x2b080808, 0x08081919, 0x2b08082b, 0x08081919, 0x2b081919, 0x08081919, 0x2b082b08, 0x08081919, + 0x2b190819, 0x08081919, 0x2b191908, 0x08081919, 0x2b2b0808, 0x08081919, 0x08080819, 0x0808192b, + 0x08081908, 0x0808192b, 0x0808192b, 0x0808192b, 0x08082b19, 0x0808192b, 0x08190808, 0x0808192b, + 0x08191919, 0x0808192b, 0x19080808, 0x0808192b, 0x19081919, 0x0808192b, 0x19082b08, 0x0808192b, + 0x19190819, 0x0808192b, 0x19191908, 0x0808192b, 0x192b0808, 0x0808192b, 0x2b080819, 0x0808192b, + 0x2b081908, 0x0808192b, 0x2b190808, 0x0808192b, 0x08080808, 0x08082b08, 0x0808082b, 0x08082b08, + 0x08081919, 0x08082b08, 0x08082b08, 0x08082b08, 0x08190819, 0x08082b08, 0x08191908, 0x08082b08, + 0x0819192b, 0x08082b08, 0x08192b19, 0x08082b08, 0x082b0808, 0x08082b08, 0x082b1919, 0x08082b08, + 0x082b2b2b, 0x08082b08, 0x19080819, 0x08082b08, 0x19081908, 0x08082b08, 0x1908192b, 0x08082b08, + 0x19082b19, 0x08082b08, 0x19190808, 0x08082b08, 0x1919082b, 0x08082b08, 0x19191919, 0x08082b08, + 0x19192b08, 0x08082b08, 0x192b0819, 0x08082b08, 0x192b1908, 0x08082b08, 0x2b080808, 0x08082b08, + 0x2b081919, 0x08082b08, 0x2b191908, 0x08082b08, 0x2b2b2b2b, 0x08082b08, 0x08080819, 0x08082b19, + 0x08081908, 0x08082b19, 0x08190808, 0x08082b19, 0x0819082b, 0x08082b19, 0x08191919, 0x08082b19, + 0x08192b08, 0x08082b19, 0x082b0819, 0x08082b19, 0x19080808, 0x08082b19, 0x19081919, 0x08082b19, + 0x19082b08, 0x08082b19, 0x19190819, 0x08082b19, 0x19191908, 0x08082b19, 0x192b0808, 0x08082b19, + 0x2b080819, 0x08082b19, 0x2b190808, 0x08082b19, 0x08080808, 0x08082b2b, 0x08190819, 0x08082b2b, + 0x08191908, 0x08082b2b, 0x082b082b, 0x08082b2b, 0x082b2b08, 0x08082b2b, 0x082b2b2b, 0x08082b2b, + 0x19190808, 0x08082b2b, 0x2b192b19, 0x08082b2b, 0x08080819, 0x08190808, 0x08081908, 0x08190808, + 0x0808192b, 0x08190808, 0x08082b19, 0x08190808, 0x08190808, 0x08190808, 0x0819082b, 0x08190808, + 0x08191919, 0x08190808, 0x08192b08, 0x08190808, 0x082b0819, 0x08190808, 0x082b1908, 0x08190808, + 0x082b192b, 0x08190808, 0x19080808, 0x08190808, 0x1908082b, 0x08190808, 0x19081919, 0x08190808, + 0x19082b08, 0x08190808, 0x19190819, 0x08190808, 0x19191908, 0x08190808, 0x1919192b, 0x08190808, + 0x19192b19, 0x08190808, 0x192b0808, 0x08190808, 0x192b082b, 0x08190808, 0x192b1919, 0x08190808, + 0x192b2b08, 0x08190808, 0x2b080819, 0x08190808, 0x2b081908, 0x08190808, 0x2b08192b, 0x08190808, + 0x2b190808, 0x08190808, 0x2b191919, 0x08190808, 0x2b192b08, 0x08190808, 0x2b2b0819, 0x08190808, + 0x2b2b1908, 0x08190808, 0x08080808, 0x08190819, 0x0808082b, 0x08190819, 0x08081919, 0x08190819, + 0x08082b08, 0x08190819, 0x08082b2b, 0x08190819, 0x08190819, 0x08190819, 0x08191908, 0x08190819, + 0x0819192b, 0x08190819, 0x08192b19, 0x08190819, 0x082b0808, 0x08190819, 0x082b082b, 0x08190819, + 0x082b1919, 0x08190819, 0x082b2b08, 0x08190819, 0x19080819, 0x08190819, 0x19081908, 0x08190819, + 0x1908192b, 0x08190819, 0x19082b19, 0x08190819, 0x19190808, 0x08190819, 0x1919082b, 0x08190819, + 0x19191919, 0x08190819, 0x19192b08, 0x08190819, 0x192b0819, 0x08190819, 0x192b1908, 0x08190819, + 0x2b080808, 0x08190819, 0x2b08082b, 0x08190819, 0x2b081919, 0x08190819, 0x2b082b08, 0x08190819, + 0x2b190819, 0x08190819, 0x2b191908, 0x08190819, 0x08080819, 0x0819082b, 0x08081908, 0x0819082b, + 0x08082b19, 0x0819082b, 0x08190808, 0x0819082b, 0x08191919, 0x0819082b, 0x082b0819, 0x0819082b, + 0x082b1908, 0x0819082b, 0x19080808, 0x0819082b, 0x19081919, 0x0819082b, 0x19190819, 0x0819082b, + 0x19191908, 0x0819082b, 0x2b080819, 0x0819082b, 0x2b081908, 0x0819082b, 0x2b190808, 0x0819082b, + 0x08080808, 0x08191908, 0x0808082b, 0x08191908, 0x08081919, 0x08191908, 0x08082b08, 0x08191908, + 0x08190819, 0x08191908, 0x08191908, 0x08191908, 0x0819192b, 0x08191908, 0x08192b19, 0x08191908, + 0x082b0808, 0x08191908, 0x082b1919, 0x08191908, 0x082b2b08, 0x08191908, 0x19080819, 0x08191908, + 0x19081908, 0x08191908, 0x1908192b, 0x08191908, 0x19082b19, 0x08191908, 0x19190808, 0x08191908, + 0x1919082b, 0x08191908, 0x19191919, 0x08191908, 0x19192b08, 0x08191908, 0x192b0819, 0x08191908, + 0x192b1908, 0x08191908, 0x2b080808, 0x08191908, 0x2b08082b, 0x08191908, 0x2b081919, 0x08191908, + 0x2b082b08, 0x08191908, 0x2b190819, 0x08191908, 0x2b191908, 0x08191908, 0x2b2b0808, 0x08191908, + 0x08080819, 0x08191919, 0x08081908, 0x08191919, 0x0808192b, 0x08191919, 0x08082b19, 0x08191919, + 0x08190808, 0x08191919, 0x0819082b, 0x08191919, 0x08191919, 0x08191919, 0x08192b08, 0x08191919, + 0x082b0819, 0x08191919, 0x082b1908, 0x08191919, 0x19080808, 0x08191919, 0x1908082b, 0x08191919, + 0x19081919, 0x08191919, 0x19082b08, 0x08191919, 0x19190819, 0x08191919, 0x19191908, 0x08191919, + 0x192b0808, 0x08191919, 0x2b080819, 0x08191919, 0x2b081908, 0x08191919, 0x2b190808, 0x08191919, + 0x08080808, 0x0819192b, 0x08081919, 0x0819192b, 0x08082b08, 0x0819192b, 0x08190819, 0x0819192b, + 0x08191908, 0x0819192b, 0x082b0808, 0x0819192b, 0x19080819, 0x0819192b, 0x19081908, 0x0819192b, + 0x19190808, 0x0819192b, 0x2b080808, 0x0819192b, 0x2b2b2b2b, 0x0819192b, 0x08080819, 0x08192b08, + 0x08081908, 0x08192b08, 0x0808192b, 0x08192b08, 0x08082b19, 0x08192b08, 0x08190808, 0x08192b08, + 0x08191919, 0x08192b08, 0x08192b08, 0x08192b08, 0x082b0819, 0x08192b08, 0x19080808, 0x08192b08, + 0x1908082b, 0x08192b08, 0x19081919, 0x08192b08, 0x19082b08, 0x08192b08, 0x19190819, 0x08192b08, + 0x19191908, 0x08192b08, 0x192b0808, 0x08192b08, 0x2b080819, 0x08192b08, 0x2b081908, 0x08192b08, + 0x08080808, 0x08192b19, 0x0808082b, 0x08192b19, 0x08081919, 0x08192b19, 0x08082b08, 0x08192b19, + 0x08190819, 0x08192b19, 0x08191908, 0x08192b19, 0x082b0808, 0x08192b19, 0x19080819, 0x08192b19, + 0x19081908, 0x08192b19, 0x19190808, 0x08192b19, 0x192b2b19, 0x08192b19, 0x2b2b082b, 0x08192b19, + 0x08081908, 0x08192b2b, 0x08190808, 0x08192b2b, 0x19080808, 0x08192b2b, 0x1919192b, 0x08192b2b, + 0x08080808, 0x082b0808, 0x0808082b, 0x082b0808, 0x08081919, 0x082b0808, 0x08082b08, 0x082b0808, + 0x08190819, 0x082b0808, 0x08191908, 0x082b0808, 0x0819192b, 0x082b0808, 0x08192b19, 0x082b0808, + 0x082b0808, 0x082b0808, 0x082b1919, 0x082b0808, 0x082b2b2b, 0x082b0808, 0x19080819, 0x082b0808, + 0x19081908, 0x082b0808, 0x19190808, 0x082b0808, 0x1919082b, 0x082b0808, 0x19191919, 0x082b0808, + 0x192b1908, 0x082b0808, 0x2b080808, 0x082b0808, 0x2b082b2b, 0x082b0808, 0x2b191908, 0x082b0808, + 0x2b2b2b2b, 0x082b0808, 0x08080819, 0x082b0819, 0x08081908, 0x082b0819, 0x08190808, 0x082b0819, + 0x0819082b, 0x082b0819, 0x08191919, 0x082b0819, 0x082b0819, 0x082b0819, 0x19080808, 0x082b0819, + 0x1908082b, 0x082b0819, 0x19081919, 0x082b0819, 0x19190819, 0x082b0819, 0x19191908, 0x082b0819, + 0x192b0808, 0x082b0819, 0x2b080819, 0x082b0819, 0x2b081908, 0x082b0819, 0x2b190808, 0x082b0819, + 0x08080808, 0x082b082b, 0x08082b2b, 0x082b082b, 0x082b082b, 0x082b082b, 0x082b2b08, 0x082b082b, + 0x082b2b2b, 0x082b082b, 0x19081908, 0x082b082b, 0x19190808, 0x082b082b, 0x2b082b08, 0x082b082b, + 0x2b082b2b, 0x082b082b, 0x2b2b2b08, 0x082b082b, 0x08080819, 0x082b1908, 0x08081908, 0x082b1908, + 0x0808192b, 0x082b1908, 0x08082b19, 0x082b1908, 0x08190808, 0x082b1908, 0x08191919, 0x082b1908, + 0x08192b08, 0x082b1908, 0x082b0819, 0x082b1908, 0x082b1908, 0x082b1908, 0x19080808, 0x082b1908, + 0x1908082b, 0x082b1908, 0x19081919, 0x082b1908, 0x19082b08, 0x082b1908, 0x19190819, 0x082b1908, + 0x19191908, 0x082b1908, 0x192b0808, 0x082b1908, 0x2b080819, 0x082b1908, 0x2b081908, 0x082b1908, + 0x2b190808, 0x082b1908, 0x08080808, 0x082b1919, 0x08081919, 0x082b1919, 0x08082b08, 0x082b1919, + 0x08190819, 0x082b1919, 0x08191908, 0x082b1919, 0x082b0808, 0x082b1919, 0x19080819, 0x082b1919, + 0x19081908, 0x082b1919, 0x19190808, 0x082b1919, 0x192b192b, 0x082b1919, 0x2b080808, 0x082b1919, + 0x08080819, 0x082b192b, 0x08081908, 0x082b192b, 0x08190808, 0x082b192b, 0x19080808, 0x082b192b, + 0x19192b19, 0x082b192b, 0x08080808, 0x082b2b08, 0x08081919, 0x082b2b08, 0x08190819, 0x082b2b08, + 0x08191908, 0x082b2b08, 0x19080819, 0x082b2b08, 0x19081908, 0x082b2b08, 0x19190808, 0x082b2b08, + 0x2b082b2b, 0x082b2b08, 0x2b2b2b2b, 0x082b2b08, 0x08080819, 0x082b2b19, 0x08081908, 0x082b2b19, + 0x08190808, 0x082b2b19, 0x2b191919, 0x082b2b19, 0x08082b2b, 0x082b2b2b, 0x082b082b, 0x082b2b2b, + 0x192b1908, 0x082b2b2b, 0x2b082b08, 0x082b2b2b, 0x2b082b2b, 0x082b2b2b, 0x08080819, 0x19080808, + 0x08081908, 0x19080808, 0x0808192b, 0x19080808, 0x08082b19, 0x19080808, 0x08190808, 0x19080808, + 0x0819082b, 0x19080808, 0x08191919, 0x19080808, 0x08192b08, 0x19080808, 0x08192b2b, 0x19080808, + 0x082b0819, 0x19080808, 0x082b1908, 0x19080808, 0x082b192b, 0x19080808, 0x19080808, 0x19080808, + 0x1908082b, 0x19080808, 0x19081919, 0x19080808, 0x19082b08, 0x19080808, 0x19082b2b, 0x19080808, + 0x19190819, 0x19080808, 0x19191908, 0x19080808, 0x1919192b, 0x19080808, 0x19192b19, 0x19080808, + 0x192b0808, 0x19080808, 0x192b082b, 0x19080808, 0x192b1919, 0x19080808, 0x2b080819, 0x19080808, + 0x2b081908, 0x19080808, 0x2b190808, 0x19080808, 0x2b191919, 0x19080808, 0x2b192b08, 0x19080808, + 0x2b2b0819, 0x19080808, 0x2b2b1908, 0x19080808, 0x08080808, 0x19080819, 0x0808082b, 0x19080819, + 0x08081919, 0x19080819, 0x08082b08, 0x19080819, 0x08190819, 0x19080819, 0x08191908, 0x19080819, + 0x0819192b, 0x19080819, 0x08192b19, 0x19080819, 0x082b0808, 0x19080819, 0x082b082b, 0x19080819, + 0x082b1919, 0x19080819, 0x19080819, 0x19080819, 0x19081908, 0x19080819, 0x1908192b, 0x19080819, + 0x19082b19, 0x19080819, 0x19190808, 0x19080819, 0x1919082b, 0x19080819, 0x19191919, 0x19080819, + 0x19192b08, 0x19080819, 0x192b0819, 0x19080819, 0x192b1908, 0x19080819, 0x2b080808, 0x19080819, + 0x2b08082b, 0x19080819, 0x2b081919, 0x19080819, 0x2b082b08, 0x19080819, 0x2b190819, 0x19080819, + 0x2b191908, 0x19080819, 0x2b2b0808, 0x19080819, 0x08080819, 0x1908082b, 0x08081908, 0x1908082b, + 0x08190808, 0x1908082b, 0x0819082b, 0x1908082b, 0x08191919, 0x1908082b, 0x08192b08, 0x1908082b, + 0x082b1908, 0x1908082b, 0x19080808, 0x1908082b, 0x19081919, 0x1908082b, 0x19082b08, 0x1908082b, + 0x19190819, 0x1908082b, 0x19191908, 0x1908082b, 0x192b0808, 0x1908082b, 0x2b080819, 0x1908082b, + 0x2b081908, 0x1908082b, 0x08080808, 0x19081908, 0x0808082b, 0x19081908, 0x08081919, 0x19081908, + 0x08082b08, 0x19081908, 0x08082b2b, 0x19081908, 0x08190819, 0x19081908, 0x08191908, 0x19081908, + 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0x2b082b2b, 0x2b08082b, 0x2b082b2b, 0x2b2b082b, 0x2b082b2b, 0x08080819, 0x2b190808, + 0x08081908, 0x2b190808, 0x08082b19, 0x2b190808, 0x08190808, 0x2b190808, 0x0819082b, 0x2b190808, + 0x08191919, 0x2b190808, 0x08192b08, 0x2b190808, 0x082b1908, 0x2b190808, 0x19080808, 0x2b190808, + 0x1908082b, 0x2b190808, 0x19081919, 0x2b190808, 0x19082b08, 0x2b190808, 0x19190819, 0x2b190808, + 0x19191908, 0x2b190808, 0x192b0808, 0x2b190808, 0x2b080819, 0x2b190808, 0x2b081908, 0x2b190808, + 0x2b190808, 0x2b190808, 0x08080808, 0x2b190819, 0x08081919, 0x2b190819, 0x08190819, 0x2b190819, + 0x08191908, 0x2b190819, 0x19080819, 0x2b190819, 0x19081908, 0x2b190819, 0x19190808, 0x2b190819, + 0x19192b2b, 0x2b190819, 0x08080819, 0x2b19082b, 0x08081908, 0x2b19082b, 0x08190808, 0x2b19082b, + 0x19080808, 0x2b19082b, 0x2b2b192b, 0x2b19082b, 0x08080808, 0x2b191908, 0x0808082b, 0x2b191908, + 0x08081919, 0x2b191908, 0x08082b08, 0x2b191908, 0x08190819, 0x2b191908, 0x08191908, 0x2b191908, + 0x082b0808, 0x2b191908, 0x19080819, 0x2b191908, 0x19081908, 0x2b191908, 0x19190808, 0x2b191908, + 0x2b080808, 0x2b191908, 0x2b19192b, 0x2b191908, 0x08080819, 0x2b191919, 0x08081908, 0x2b191919, + 0x08190808, 0x2b191919, 0x19080808, 0x2b191919, 0x2b192b08, 0x2b191919, 0x2b2b0819, 0x2b191919, + 0x08080808, 0x2b19192b, 0x1908192b, 0x2b19192b, 0x192b1908, 0x2b19192b, 0x08080819, 0x2b192b08, + 0x08081908, 0x2b192b08, 0x08190808, 0x2b192b08, 0x082b192b, 0x2b192b08, 0x19080808, 0x2b192b08, + 0x2b2b2b19, 0x2b192b08, 0x08080808, 0x2b192b19, 0x19082b19, 0x2b192b19, 0x1919082b, 0x2b192b19, + 0x2b190808, 0x2b192b2b, 0x08080808, 0x2b2b0808, 0x08081919, 0x2b2b0808, 0x08082b2b, 0x2b2b0808, + 0x08191908, 0x2b2b0808, 0x082b082b, 0x2b2b0808, 0x082b2b2b, 0x2b2b0808, 0x19080819, 0x2b2b0808, + 0x19081908, 0x2b2b0808, 0x19190808, 0x2b2b0808, 0x2b2b082b, 0x2b2b0808, 0x2b2b2b2b, 0x2b2b0808, + 0x19080808, 0x2b2b0819, 0x192b1919, 0x2b2b0819, 0x0808082b, 0x2b2b082b, 0x08082b2b, 0x2b2b082b, + 0x082b082b, 0x2b2b082b, 0x082b2b08, 0x2b2b082b, 0x082b2b2b, 0x2b2b082b, 0x2b08082b, 0x2b2b082b, + 0x2b082b08, 0x2b2b082b, 0x2b082b2b, 0x2b2b082b, 0x2b2b2b08, 0x2b2b082b, 0x08080819, 0x2b2b1908, + 0x08081908, 0x2b2b1908, 0x08190808, 0x2b2b1908, 0x19080808, 0x2b2b1908, 0x2b082b19, 0x2b2b1908, + 0x2b2b1908, 0x2b2b1908, 0x08080808, 0x2b2b1919, 0x08192b19, 0x2b2b1919, 0x19190819, 0x2b2b192b, + 0x08082b2b, 0x2b2b2b08, 0x082b2b08, 0x2b2b2b08, 0x2b2b082b, 0x2b2b2b08, 0x19191908, 0x2b2b2b19, + 0x2b08192b, 0x2b2b2b19, 0x08082b08, 0x2b2b2b2b, 0x08082b2b, 0x2b2b2b2b, 0x082b0808, 0x2b2b2b2b, + 0x082b082b, 0x2b2b2b2b, 0x082b2b08, 0x2b2b2b2b, 0x2b082b08, 0x2b2b2b2b, 0x2b2b2b2b, 0x2b2b2b2b +); +#enddecl(IQ2_S_GRID) + +#decl(IQ3_XSS_GRID) + +const iq3xxs_grid = array( + 0x04040404, 0x04040414, 0x04040424, 0x04040c0c, 0x04040c1c, 0x04040c3e, 0x04041404, 0x04041414, + 0x04041c0c, 0x04042414, 0x04043e1c, 0x04043e2c, 0x040c040c, 0x040c041c, 0x040c0c04, 0x040c0c14, + 0x040c140c, 0x040c142c, 0x040c1c04, 0x040c1c14, 0x040c240c, 0x040c2c24, 0x040c3e04, 0x04140404, + 0x04140414, 0x04140424, 0x04140c0c, 0x04141404, 0x04141414, 0x04141c0c, 0x04141c1c, 0x04141c3e, + 0x04142c0c, 0x04142c3e, 0x04143e2c, 0x041c040c, 0x041c043e, 0x041c0c04, 0x041c0c14, 0x041c142c, + 0x041c3e04, 0x04240c1c, 0x04241c3e, 0x04242424, 0x04242c3e, 0x04243e1c, 0x04243e2c, 0x042c040c, + 0x042c043e, 0x042c1c14, 0x042c2c14, 0x04341c2c, 0x04343424, 0x043e0c04, 0x043e0c24, 0x043e0c34, + 0x043e241c, 0x043e340c, 0x0c04040c, 0x0c04041c, 0x0c040c04, 0x0c040c14, 0x0c04140c, 0x0c04141c, + 0x0c041c04, 0x0c041c14, 0x0c041c24, 0x0c04243e, 0x0c042c04, 0x0c0c0404, 0x0c0c0414, 0x0c0c0c0c, + 0x0c0c1404, 0x0c0c1414, 0x0c14040c, 0x0c14041c, 0x0c140c04, 0x0c140c14, 0x0c14140c, 0x0c141c04, + 0x0c143e14, 0x0c1c0404, 0x0c1c0414, 0x0c1c1404, 0x0c1c1c0c, 0x0c1c2434, 0x0c1c3434, 0x0c24040c, + 0x0c24042c, 0x0c242c04, 0x0c2c1404, 0x0c2c1424, 0x0c2c2434, 0x0c2c3e0c, 0x0c34042c, 0x0c3e1414, + 0x0c3e2404, 0x14040404, 0x14040414, 0x14040c0c, 0x14040c1c, 0x14041404, 0x14041414, 0x14041434, + 0x14041c0c, 0x14042414, 0x140c040c, 0x140c041c, 0x140c042c, 0x140c0c04, 0x140c0c14, 0x140c140c, + 0x140c1c04, 0x140c341c, 0x140c343e, 0x140c3e04, 0x14140404, 0x14140414, 0x14140c0c, 0x14140c3e, + 0x14141404, 0x14141414, 0x14141c3e, 0x14142404, 0x14142c2c, 0x141c040c, 0x141c0c04, 0x141c0c24, + 0x141c3e04, 0x141c3e24, 0x14241c2c, 0x14242c1c, 0x142c041c, 0x142c143e, 0x142c240c, 0x142c3e24, + 0x143e040c, 0x143e041c, 0x143e0c34, 0x143e242c, 0x1c04040c, 0x1c040c04, 0x1c040c14, 0x1c04140c, + 0x1c04141c, 0x1c042c04, 0x1c04342c, 0x1c043e14, 0x1c0c0404, 0x1c0c0414, 0x1c0c1404, 0x1c0c1c0c, + 0x1c0c2424, 0x1c0c2434, 0x1c14040c, 0x1c14041c, 0x1c140c04, 0x1c14142c, 0x1c142c14, 0x1c143e14, + 0x1c1c0c0c, 0x1c1c1c1c, 0x1c241c04, 0x1c24243e, 0x1c243e14, 0x1c2c0404, 0x1c2c0434, 0x1c2c1414, + 0x1c2c2c2c, 0x1c340c24, 0x1c341c34, 0x1c34341c, 0x1c3e1c1c, 0x1c3e3404, 0x24040424, 0x24040c3e, + 0x24041c2c, 0x24041c3e, 0x24042c1c, 0x24042c3e, 0x240c3e24, 0x24141404, 0x24141c3e, 0x24142404, + 0x24143404, 0x24143434, 0x241c043e, 0x241c242c, 0x24240424, 0x24242c0c, 0x24243424, 0x242c142c, + 0x242c241c, 0x242c3e04, 0x243e042c, 0x243e0c04, 0x243e0c14, 0x243e1c04, 0x2c040c14, 0x2c04240c, + 0x2c043e04, 0x2c0c0404, 0x2c0c0434, 0x2c0c1434, 0x2c0c2c2c, 0x2c140c24, 0x2c141c14, 0x2c143e14, + 0x2c1c0414, 0x2c1c2c1c, 0x2c240c04, 0x2c24141c, 0x2c24143e, 0x2c243e14, 0x2c2c0414, 0x2c2c1c0c, + 0x2c342c04, 0x2c3e1424, 0x2c3e2414, 0x34041424, 0x34042424, 0x34042434, 0x34043424, 0x340c140c, + 0x340c340c, 0x34140c3e, 0x34143424, 0x341c1c04, 0x341c1c34, 0x34242424, 0x342c042c, 0x342c2c14, + 0x34341c1c, 0x343e041c, 0x343e140c, 0x3e04041c, 0x3e04042c, 0x3e04043e, 0x3e040c04, 0x3e041c14, + 0x3e042c14, 0x3e0c1434, 0x3e0c2404, 0x3e140c14, 0x3e14242c, 0x3e142c14, 0x3e1c0404, 0x3e1c0c2c, + 0x3e1c1c1c, 0x3e1c3404, 0x3e24140c, 0x3e24240c, 0x3e2c0404, 0x3e2c0414, 0x3e2c1424, 0x3e341c04 +); +#enddecl(IQ3_XSS_GRID) + +#decl(IQ3_S_GRID) + +const iq3s_grid = array( + 0x01010101, 0x01010103, 0x01010105, 0x0101010b, 0x0101010f, 0x01010301, 0x01010303, 0x01010305, + 0x01010309, 0x0101030d, 0x01010501, 0x01010503, 0x0101050b, 0x01010707, 0x01010901, 0x01010905, + 0x0101090b, 0x0101090f, 0x01010b03, 0x01010b07, 0x01010d01, 0x01010d05, 0x01010f03, 0x01010f09, + 0x01010f0f, 0x01030101, 0x01030103, 0x01030105, 0x01030109, 0x01030301, 0x01030303, 0x0103030b, + 0x01030501, 0x01030507, 0x0103050f, 0x01030703, 0x0103070b, 0x01030909, 0x01030d03, 0x01030d0b, + 0x01030f05, 0x01050101, 0x01050103, 0x0105010b, 0x0105010f, 0x01050301, 0x01050307, 0x0105030d, + 0x01050503, 0x0105050b, 0x01050701, 0x01050709, 0x01050905, 0x0105090b, 0x0105090f, 0x01050b03, + 0x01050b07, 0x01050f01, 0x01050f07, 0x01070107, 0x01070303, 0x0107030b, 0x01070501, 0x01070505, + 0x01070703, 0x01070707, 0x0107070d, 0x01070909, 0x01070b01, 0x01070b05, 0x01070d0f, 0x01070f03, + 0x01070f0b, 0x01090101, 0x01090307, 0x0109030f, 0x01090503, 0x01090509, 0x01090705, 0x01090901, + 0x01090907, 0x01090b03, 0x01090f01, 0x010b0105, 0x010b0109, 0x010b0501, 0x010b0505, 0x010b050d, + 0x010b0707, 0x010b0903, 0x010b090b, 0x010b090f, 0x010b0d0d, 0x010b0f07, 0x010d010d, 0x010d0303, + 0x010d0307, 0x010d0703, 0x010d0b05, 0x010d0f03, 0x010f0101, 0x010f0105, 0x010f0109, 0x010f0501, + 0x010f0505, 0x010f050d, 0x010f0707, 0x010f0b01, 0x010f0b09, 0x03010101, 0x03010103, 0x03010105, + 0x03010109, 0x03010301, 0x03010303, 0x03010307, 0x0301030b, 0x0301030f, 0x03010501, 0x03010505, + 0x03010703, 0x03010709, 0x0301070d, 0x03010b09, 0x03010b0d, 0x03010d03, 0x03010f05, 0x03030101, + 0x03030103, 0x03030107, 0x0303010d, 0x03030301, 0x03030309, 0x03030503, 0x03030701, 0x03030707, + 0x03030903, 0x03030b01, 0x03030b05, 0x03030f01, 0x03030f0d, 0x03050101, 0x03050305, 0x0305030b, + 0x0305030f, 0x03050501, 0x03050509, 0x03050705, 0x03050901, 0x03050907, 0x03050b0b, 0x03050d01, + 0x03050f05, 0x03070103, 0x03070109, 0x0307010f, 0x03070301, 0x03070307, 0x03070503, 0x0307050f, + 0x03070701, 0x03070709, 0x03070903, 0x03070d05, 0x03070f01, 0x03090107, 0x0309010b, 0x03090305, + 0x03090309, 0x03090703, 0x03090707, 0x03090905, 0x0309090d, 0x03090b01, 0x03090b09, 0x030b0103, + 0x030b0301, 0x030b0307, 0x030b0503, 0x030b0701, 0x030b0705, 0x030b0b03, 0x030d0501, 0x030d0509, + 0x030d050f, 0x030d0909, 0x030d090d, 0x030f0103, 0x030f0107, 0x030f0301, 0x030f0305, 0x030f0503, + 0x030f070b, 0x030f0903, 0x030f0d05, 0x030f0f01, 0x05010101, 0x05010103, 0x05010107, 0x0501010b, + 0x0501010f, 0x05010301, 0x05010305, 0x05010309, 0x0501030d, 0x05010503, 0x05010507, 0x0501050f, + 0x05010701, 0x05010705, 0x05010903, 0x05010907, 0x0501090b, 0x05010b01, 0x05010b05, 0x05010d0f, + 0x05010f01, 0x05010f07, 0x05010f0b, 0x05030101, 0x05030105, 0x05030301, 0x05030307, 0x0503030f, + 0x05030505, 0x0503050b, 0x05030703, 0x05030709, 0x05030905, 0x05030b03, 0x05050103, 0x05050109, + 0x0505010f, 0x05050503, 0x05050507, 0x05050701, 0x0505070f, 0x05050903, 0x05050b07, 0x05050b0f, + 0x05050f03, 0x05050f09, 0x05070101, 0x05070105, 0x0507010b, 0x05070303, 0x05070505, 0x05070509, + 0x05070703, 0x05070707, 0x05070905, 0x05070b01, 0x05070d0d, 0x05090103, 0x0509010f, 0x05090501, + 0x05090507, 0x05090705, 0x0509070b, 0x05090903, 0x05090f05, 0x05090f0b, 0x050b0109, 0x050b0303, + 0x050b0505, 0x050b070f, 0x050b0901, 0x050b0b07, 0x050b0f01, 0x050d0101, 0x050d0105, 0x050d010f, + 0x050d0503, 0x050d0b0b, 0x050d0d03, 0x050f010b, 0x050f0303, 0x050f050d, 0x050f0701, 0x050f0907, + 0x050f0b01, 0x07010105, 0x07010303, 0x07010307, 0x0701030b, 0x0701030f, 0x07010505, 0x07010703, + 0x07010707, 0x0701070b, 0x07010905, 0x07010909, 0x0701090f, 0x07010b03, 0x07010d07, 0x07010f03, + 0x07030103, 0x07030107, 0x0703010b, 0x07030309, 0x07030503, 0x07030507, 0x07030901, 0x07030d01, + 0x07030f05, 0x07030f0d, 0x07050101, 0x07050305, 0x07050501, 0x07050705, 0x07050709, 0x07050b01, + 0x07070103, 0x07070301, 0x07070309, 0x07070503, 0x07070507, 0x0707050f, 0x07070701, 0x07070903, + 0x07070907, 0x0707090f, 0x07070b0b, 0x07070f07, 0x07090107, 0x07090303, 0x0709030d, 0x07090505, + 0x07090703, 0x07090b05, 0x07090d01, 0x07090d09, 0x070b0103, 0x070b0301, 0x070b0305, 0x070b050b, + 0x070b0705, 0x070b0909, 0x070b0b0d, 0x070b0f07, 0x070d030d, 0x070d0903, 0x070f0103, 0x070f0107, + 0x070f0501, 0x070f0505, 0x070f070b, 0x09010101, 0x09010109, 0x09010305, 0x09010501, 0x09010509, + 0x0901050f, 0x09010705, 0x09010903, 0x09010b01, 0x09010f01, 0x09030105, 0x0903010f, 0x09030303, + 0x09030307, 0x09030505, 0x09030701, 0x0903070b, 0x09030907, 0x09030b03, 0x09030b0b, 0x09050103, + 0x09050107, 0x09050301, 0x0905030b, 0x09050503, 0x09050707, 0x09050901, 0x09050b0f, 0x09050d05, + 0x09050f01, 0x09070109, 0x09070303, 0x09070307, 0x09070501, 0x09070505, 0x09070703, 0x0907070b, + 0x09090101, 0x09090105, 0x09090509, 0x0909070f, 0x09090901, 0x09090f03, 0x090b010b, 0x090b010f, + 0x090b0503, 0x090b0d05, 0x090d0307, 0x090d0709, 0x090d0d01, 0x090f0301, 0x090f030b, 0x090f0701, + 0x090f0907, 0x090f0b03, 0x0b010105, 0x0b010301, 0x0b010309, 0x0b010505, 0x0b010901, 0x0b010909, + 0x0b01090f, 0x0b010b05, 0x0b010d0d, 0x0b010f09, 0x0b030103, 0x0b030107, 0x0b03010b, 0x0b030305, + 0x0b030503, 0x0b030705, 0x0b030f05, 0x0b050101, 0x0b050303, 0x0b050507, 0x0b050701, 0x0b05070d, + 0x0b050b07, 0x0b070105, 0x0b07010f, 0x0b070301, 0x0b07050f, 0x0b070909, 0x0b070b03, 0x0b070d0b, + 0x0b070f07, 0x0b090103, 0x0b090109, 0x0b090501, 0x0b090705, 0x0b09090d, 0x0b0b0305, 0x0b0b050d, + 0x0b0b0b03, 0x0b0b0b07, 0x0b0d0905, 0x0b0f0105, 0x0b0f0109, 0x0b0f0505, 0x0d010303, 0x0d010307, + 0x0d01030b, 0x0d010703, 0x0d010707, 0x0d010d01, 0x0d030101, 0x0d030501, 0x0d03050f, 0x0d030d09, + 0x0d050305, 0x0d050709, 0x0d050905, 0x0d050b0b, 0x0d050d05, 0x0d050f01, 0x0d070101, 0x0d070309, + 0x0d070503, 0x0d070901, 0x0d09050b, 0x0d090907, 0x0d090d05, 0x0d0b0101, 0x0d0b0107, 0x0d0b0709, + 0x0d0b0d01, 0x0d0d010b, 0x0d0d0901, 0x0d0f0303, 0x0d0f0307, 0x0f010101, 0x0f010109, 0x0f01010f, + 0x0f010501, 0x0f010505, 0x0f01070d, 0x0f010901, 0x0f010b09, 0x0f010d05, 0x0f030105, 0x0f030303, + 0x0f030509, 0x0f030907, 0x0f03090b, 0x0f050103, 0x0f050109, 0x0f050301, 0x0f05030d, 0x0f050503, + 0x0f050701, 0x0f050b03, 0x0f070105, 0x0f070705, 0x0f07070b, 0x0f070b07, 0x0f090103, 0x0f09010b, + 0x0f090307, 0x0f090501, 0x0f090b01, 0x0f0b0505, 0x0f0b0905, 0x0f0d0105, 0x0f0d0703, 0x0f0f0101 +); +#enddecl(IQ3_S_GRID) + +#decl(IQ1_GRID) + +const IQ1_DELTA: f32 = 0.125; + +const iq1_grid = array( + 0xfffdffff, 0xfff7fff0, 0xffccfff5, 0xffdfffc0, 0xffd7ffdd, 0xff30ffd5, 0xff03ff0c, 0xff10ff01, + 0xff7dff7f, 0xff75ff77, 0xff5fff40, 0xff57ff5d, 0xfcf3ff55, 0xfcccfcf0, 0xfcc1fcc3, 0xfcc5fcc4, + 0xfc3cfcd0, 0xfc34fc31, 0xfc00fc0d, 0xfc1cfc05, 0xfc11fc13, 0xfc70fc17, 0xfc43fc4c, 0xfc50fc41, + 0xfdfdfdff, 0xfdf5fdf7, 0xfddffdc0, 0xfdd7fddd, 0xfd30fdd5, 0xfd04fd0c, 0xfd14fd13, 0xfd7dfd7f, + 0xfd75fd77, 0xfd40fd4c, 0xfd5ffd44, 0xfd57fd5d, 0xf3ccfd55, 0xf3c1f3c3, 0xf33cf3d0, 0xf300f334, + 0xf313f305, 0xf34cf310, 0xf350f344, 0xf0f3f0fc, 0xf0f1f0f0, 0xf0c7f0c0, 0xf0d4f0c5, 0xf030f03f, + 0xf00ff035, 0xf003f00c, 0xf001f000, 0xf01ff004, 0xf010f01d, 0xf015f017, 0xf04cf07c, 0xf047f040, + 0xf05cf045, 0xf050f053, 0xf054f051, 0xf1c4f1c3, 0xf133f13c, 0xf10df10f, 0xf107f100, 0xf11cf11f, + 0xf114f111, 0xf14cf170, 0xf144f143, 0xf7fdf7ff, 0xf7f5f7f7, 0xf7dff7c0, 0xf7d7f7dd, 0xf730f7d5, + 0xf701f70c, 0xf77ff710, 0xf777f77d, 0xf740f775, 0xf75df75f, 0xf755f757, 0xf4ccf4f0, 0xf4c4f4c3, + 0xf4d0f4d3, 0xf40ff43c, 0xf400f40c, 0xf413f41c, 0xf44cf414, 0xf441f443, 0xf450f444, 0xf5fdf5ff, + 0xf5f5f5f7, 0xf5dff5c0, 0xf5d7f5dd, 0xf530f5d5, 0xf504f50c, 0xf510f51c, 0xf57df57f, 0xf577f570, + 0xf540f575, 0xf55df55f, 0xf555f557, 0xcfcccfcf, 0xcfc4cfc3, 0xcfd0cfd3, 0xcf33cf3c, 0xcf00cf0f, + 0xcf1ccf07, 0xcf10cf13, 0xcf4ccf14, 0xcf41cf43, 0xcf50cf5c, 0xccf3ccfc, 0xccf4ccf1, 0xcccdcccf, + 0xccc7ccc0, 0xccd3ccdc, 0xcc30ccd4, 0xcc0fcc35, 0xcc0dcc0c, 0xcc00cc03, 0xcc04cc01, 0xcc10cc1f, + 0xcc4dcc73, 0xcc5ccc40, 0xcdcccc53, 0xcdc1cdc3, 0xcd3fcdd0, 0xcd34cd31, 0xcd00cd0d, 0xcd05cd07, + 0xcd11cd13, 0xcd4ccd70, 0xcd41cd43, 0xc3fccd50, 0xc3f4c3f1, 0xc3c0c3c3, 0xc3c4c3c7, 0xc3d1c3dc, + 0xc330c33c, 0xc337c331, 0xc30cc335, 0xc300c303, 0xc304c301, 0xc310c31d, 0xc373c317, 0xc34fc374, + 0xc340c343, 0xc344c347, 0xc35cc345, 0xc350c353, 0xc0fdc354, 0xc0f5c0f0, 0xc0c3c0cc, 0xc0c1c0c0, + 0xc0dfc0c4, 0xc0d0c0dd, 0xc0d5c0d7, 0xc033c03c, 0xc031c030, 0xc00dc00c, 0xc000c003, 0xc004c001, + 0xc01cc005, 0xc010c013, 0xc014c011, 0xc07dc07f, 0xc070c073, 0xc075c077, 0xc04cc04f, 0xc040c043, + 0xc044c041, 0xc05fc045, 0xc050c05d, 0xc1f3c1fc, 0xc1f1c1f0, 0xc1c1c1c0, 0xc1c5c1c7, 0xc1d1c1dc, + 0xc13dc13f, 0xc130c133, 0xc135c137, 0xc100c10c, 0xc107c101, 0xc11cc104, 0xc110c113, 0xc114c117, + 0xc171c115, 0xc14dc175, 0xc153c140, 0xc7ccc154, 0xc7d0c7c1, 0xc733c73c, 0xc734c731, 0xc700c70f, + 0xc705c707, 0xc71cc71f, 0xc711c713, 0xc770c714, 0xc743c74c, 0xc4cfc750, 0xc4c0c4cd, 0xc4dcc4c5, + 0xc43dc4d0, 0xc430c433, 0xc40cc437, 0xc400c403, 0xc404c401, 0xc41fc405, 0xc415c410, 0xc44cc474, + 0xc440c44d, 0xc45cc447, 0xc454c451, 0xc5c1c5f4, 0xc5d1c5d3, 0xc531c533, 0xc50fc534, 0xc500c50d, + 0xc51cc507, 0xc514c511, 0xc54cc570, 0xc545c541, 0xdffddfff, 0xdff5dff7, 0xdfdfdfc0, 0xdfd0dfdd, + 0xdfd5dfd7, 0xdf0cdf30, 0xdf1cdf04, 0xdf7fdf10, 0xdf77df7d, 0xdf40df75, 0xdf5ddf5f, 0xdf57df50, + 0xdcf0df55, 0xdcc3dccc, 0xdcd0dcc4, 0xdc33dc3d, 0xdc00dc34, 0xdc05dc07, 0xdc13dc1c, 0xdc11dc10, + 0xdc4fdc70, 0xdc44dc41, 0xddfcdc50, 0xddf5ddf7, 0xddc0ddcc, 0xdddddddf, 0xddd5ddd7, 0xdd0cdd30, + 0xdd04dd01, 0xdd7cdd10, 0xdd75dd77, 0xdd40dd4c, 0xdd5ddd5f, 0xdd55dd57, 0xd3c3d3f0, 0xd3c4d3c1, + 0xd333d3d0, 0xd331d330, 0xd30dd334, 0xd307d300, 0xd311d305, 0xd34cd370, 0xd344d343, 0xd350d35c, + 0xd0c0d0f4, 0xd0d4d0dc, 0xd030d03f, 0xd00cd037, 0xd000d003, 0xd01dd004, 0xd017d010, 0xd04fd074, + 0xd040d043, 0xd045d047, 0xd053d05c, 0xd054d051, 0xd1cfd1f0, 0xd1c4d1cd, 0xd13cd1d0, 0xd100d134, + 0xd11cd11f, 0xd173d114, 0xd14fd171, 0xd7ffd145, 0xd7f7d7fd, 0xd7c0d7f5, 0xd7ddd7df, 0xd7d5d7d7, + 0xd70cd730, 0xd710d703, 0xd77dd77f, 0xd775d777, 0xd75dd75f, 0xd755d757, 0xd4ccd4f4, 0xd4c4d4c3, + 0xd431d4d0, 0xd40dd434, 0xd41cd400, 0xd411d413, 0xd470d414, 0xd441d44f, 0xd453d444, 0xd5ffd450, + 0xd5f7d5fd, 0xd5dfd5f5, 0xd5d7d5dd, 0xd530d5d5, 0xd501d50c, 0xd510d504, 0xd57dd57f, 0xd575d577, + 0xd55fd540, 0xd557d55d, 0x3ff0d555, 0x3fc13fcc, 0x3f343fd0, 0x3f003f0d, 0x3f053f07, 0x3f133f1c, + 0x3f433f11, 0x3f5c3f44, 0x3cff3f51, 0x3cf33cfc, 0x3cf43cf1, 0x3cc03ccd, 0x3cc73cc1, 0x3cdc3cc5, + 0x3cd43cd1, 0x3c373c30, 0x3c0c3c35, 0x3c003c03, 0x3c043c01, 0x3c103c05, 0x3c153c17, 0x3c733c7c, + 0x3c4f3c71, 0x3c403c4d, 0x3c5c3c5f, 0x3df03c5d, 0x3dc33dcc, 0x3dd03dc1, 0x3d0d3d3c, 0x3d053d00, + 0x3d143d13, 0x3d433d74, 0x33fc3d50, 0x33c433c0, 0x333033d4, 0x33353337, 0x3303330c, 0x33013300, + 0x331d331c, 0x33173310, 0x337c3315, 0x33743371, 0x334d334f, 0x335f3340, 0x3354335c, 0x30fd30fc, + 0x30f530f0, 0x30c330cc, 0x30c130c0, 0x30df30c4, 0x30d530d0, 0x3033303c, 0x30313030, 0x300f3034, + 0x3003300c, 0x30013000, 0x30043007, 0x3013301c, 0x30113010, 0x307d3014, 0x30703073, 0x304c3077, + 0x30403043, 0x30443041, 0x30503045, 0x30553057, 0x31f031fc, 0x31c331f4, 0x31c731c0, 0x31dc31c5, + 0x31d431d3, 0x313d313f, 0x31373130, 0x310c310f, 0x3100310d, 0x31043101, 0x3110311d, 0x317c3117, + 0x31753170, 0x31403143, 0x3153315c, 0x37f03151, 0x37c037cc, 0x37d037c5, 0x3734373d, 0x3700370f, + 0x371c3707, 0x37113713, 0x37703714, 0x3743374c, 0x37443741, 0x34fc3750, 0x34f134f0, 0x34cf34f5, + 0x34c034c3, 0x34dc34c7, 0x34d134d3, 0x3430343f, 0x340c3435, 0x3403340d, 0x34013400, 0x341f3404, + 0x3410341d, 0x34153411, 0x34743471, 0x3440344d, 0x34473441, 0x3453345c, 0x34543451, 0x353335c1, + 0x35343531, 0x35073500, 0x35133505, 0x35433514, 0x0ffc3550, 0x0ff00ff3, 0x0ff40ff1, 0x0fc00fcd, + 0x0fdc0fc5, 0x0fd40fd3, 0x0f300f3f, 0x0f0c0f37, 0x0f000f03, 0x0f040f01, 0x0f170f10, 0x0f740f71, + 0x0f470f40, 0x0f5c0f5f, 0x0f540f51, 0x0cf70cf0, 0x0cf50cf4, 0x0cc30ccc, 0x0cc10cc0, 0x0cc40cc7, + 0x0cd00cdf, 0x0cd70cd1, 0x0c3c0cd5, 0x0c300c33, 0x0c340c31, 0x0c0c0c0f, 0x0c030c0d, 0x0c010c00, + 0x0c040c07, 0x0c1c0c05, 0x0c100c13, 0x0c140c11, 0x0c700c7d, 0x0c430c4c, 0x0c410c40, 0x0c5f0c44, + 0x0c550c50, 0x0df10dfc, 0x0dc00dcd, 0x0ddc0dc5, 0x0d3d0dd3, 0x0d350d30, 0x0d030d0c, 0x0d010d00, + 0x0d1d0d04, 0x0d700d10, 0x0d4d0d4f, 0x0d440d40, 0x0d530d45, 0x03f003f3, 0x03c303cc, 0x03c103c0, + 0x03c403c7, 0x03d003dc, 0x03d503d7, 0x0333033c, 0x03310330, 0x03350334, 0x030c030f, 0x03000303, + 0x03070301, 0x03050304, 0x031d031c, 0x03100313, 0x03140311, 0x0377037f, 0x034c0375, 0x03400343, + 0x03440341, 0x0353035c, 0x03550350, 0x00fd00fc, 0x00f000f3, 0x00f400f1, 0x00cc00cf, 0x00c300cd, + 0x00c100c0, 0x00c500c4, 0x00d300dc, 0x00d100d0, 0x003f00d4, 0x003d003c, 0x00300033, 0x00370031, + 0x000f0034, 0x000d000c, 0x00000003, 0x00070001, 0x00050004, 0x001c001f, 0x00100013, 0x00170011, + 0x00150014, 0x0073007c, 0x00740070, 0x004f0075, 0x0043004c, 0x00410040, 0x00440047, 0x0053005c, + 0x00510050, 0x01ff0054, 0x01fd01fc, 0x01f101f3, 0x01f401f7, 0x01c301cc, 0x01c701c0, 0x01df01c4, + 0x01dd01dc, 0x01d001d3, 0x01d701d1, 0x013c01d4, 0x01310130, 0x01340137, 0x010f0135, 0x010d010c, + 0x01000103, 0x01070101, 0x01050104, 0x0113011c, 0x01140110, 0x0170017d, 0x01770171, 0x01750174, + 0x0140014c, 0x015d0145, 0x01510150, 0x01540157, 0x07f007f3, 0x07f407f1, 0x07c007cf, 0x07dc07c7, + 0x073007d5, 0x07350737, 0x0703070c, 0x07010700, 0x07040707, 0x071d071f, 0x07100713, 0x0774077d, + 0x074d074f, 0x07470740, 0x0754075c, 0x04fd04fc, 0x04f504f0, 0x04c304cc, 0x04c104c0, 0x04d004c4, + 0x0433043c, 0x04310430, 0x040f0434, 0x040d040c, 0x04000403, 0x04070401, 0x04050404, 0x0413041c, + 0x04110410, 0x047c0414, 0x04740470, 0x0443044c, 0x04410440, 0x04440447, 0x05f30450, 0x05c005f7, + 0x05df05c5, 0x05d105d0, 0x053005d4, 0x05340537, 0x0500050c, 0x05070501, 0x051d0504, 0x05170510, + 0x057c0515, 0x054d0575, 0x05410540, 0x05450547, 0x1ff0055c, 0x1fc11fc3, 0x1fd01fc4, 0x1f0f1f33, + 0x1f011f00, 0x1f051f07, 0x1f131f1c, 0x1f141f11, 0x1f411f7c, 0x1cfc1f50, 0x1cf11cf3, 0x1ccd1cf4, + 0x1cdc1cc0, 0x1cd11cdd, 0x1c301cd4, 0x1c0c1c34, 0x1c011c00, 0x1c101c04, 0x1c151c11, 0x1c751c73, + 0x1c401c4d, 0x1c511c5c, 0x1dcc1c54, 0x1dc41dc1, 0x1d3c1d3f, 0x1d001d31, 0x1d071d01, 0x1d701d1f, + 0x1d411d4c, 0x13cc1d50, 0x13c013cd, 0x13c513c1, 0x13d113dc, 0x133f13d4, 0x1330133d, 0x13351337, + 0x1303130c, 0x13011300, 0x13051304, 0x131d131f, 0x13731310, 0x13741370, 0x134d134f, 0x13401343, + 0x13471341, 0x135c1345, 0x13541353, 0x10f710f0, 0x10cc10f5, 0x10c110c0, 0x103310c4, 0x10311030, + 0x100f1034, 0x1003100c, 0x10011000, 0x101c1004, 0x10101013, 0x10141011, 0x10741071, 0x104c1075, + 0x10411040, 0x10451044, 0x1050105d, 0x10571051, 0x11f411fd, 0x11df11c0, 0x11d711d1, 0x113f11d4, + 0x11371130, 0x110c1135, 0x11001103, 0x11071101, 0x111f1105, 0x11171110, 0x117d117f, 0x11751170, + 0x11411143, 0x11441147, 0x1153115f, 0x11551151, 0x17c417c1, 0x173c17d0, 0x1700170d, 0x171c1705, + 0x17701714, 0x1747174c, 0x14fc1751, 0x14cf14f3, 0x14dc14c0, 0x14d114d3, 0x143f14d4, 0x1430143c, + 0x14371431, 0x1403140c, 0x14011400, 0x141f1404, 0x14151410, 0x1473147d, 0x14401475, 0x1453145c, + 0x14541450, 0x15c115cc, 0x153c15c7, 0x15341533, 0x1500150f, 0x15051507, 0x15101513, 0x15711514, + 0x15471543, 0x15511545, 0x7ffd7fff, 0x7ff57ff7, 0x7fdd7fdf, 0x7fd57fd7, 0x7f0f7f30, 0x7f037f0c, + 0x7f047f01, 0x7f7f7f10, 0x7f777f7d, 0x7f407f75, 0x7f5d7f5f, 0x7f557f57, 0x7ccc7cf0, 0x7cc17cc3, + 0x7cd07cc4, 0x7c337c3c, 0x7c0f7c34, 0x7c007c0d, 0x7c077c01, 0x7c137c04, 0x7c147c11, 0x7c747c70, + 0x7c417c43, 0x7c507c44, 0x7dfd7dff, 0x7df57df7, 0x7ddf7dc0, 0x7dd77ddd, 0x7d0c7dd5, 0x7d047d03, + 0x7d7f7d10, 0x7d777d7d, 0x7d407d75, 0x7d5d7d5f, 0x7d557d57, 0x73c473c3, 0x7333733c, 0x7300730c, + 0x731c7305, 0x73147313, 0x73447343, 0x70f470fc, 0x70c070cd, 0x70d170c5, 0x703f70d4, 0x7030703c, + 0x700c7037, 0x70007003, 0x70047001, 0x70107005, 0x70177011, 0x707c7015, 0x70717073, 0x704f7074, + 0x7040704d, 0x70517047, 0x71c171cc, 0x71d071c4, 0x7133713c, 0x71357134, 0x7100710f, 0x71057104, + 0x7111711c, 0x71707115, 0x7145714c, 0x77ff7153, 0x77f777fd, 0x77c077f5, 0x77dd77df, 0x77d577d7, + 0x7730773c, 0x7703770c, 0x77107704, 0x777f7714, 0x7777777d, 0x77407775, 0x775d775f, 0x77557757, + 0x74f174f0, 0x74c374cc, 0x74d074c1, 0x7433743c, 0x74347431, 0x740d740f, 0x74057400, 0x7413741c, + 0x74417470, 0x74507444, 0x75fd75ff, 0x75f575f7, 0x75df75c0, 0x75d775dd, 0x753075d5, 0x7503750c, + 0x757f7501, 0x7577757d, 0x75407575, 0x755d755f, 0x75557557, 0x4fcc4ff0, 0x4fc74fc1, 0x4fd04fc4, + 0x4f314f3c, 0x4f004f34, 0x4f054f07, 0x4f154f14, 0x4f4c4f70, 0x4f414f43, 0x4f504f44, 0x4cf34cfc, + 0x4cf44cf1, 0x4cc04ccf, 0x4cc54cc7, 0x4cd34cdc, 0x4cd44cd1, 0x4c304c3f, 0x4c0c4c0f, 0x4c004c03, + 0x4c044c01, 0x4c104c1d, 0x4c714c73, 0x4c404c4d, 0x4c5c4c47, 0x4c514c53, 0x4df04c54, 0x4dc34dcc, + 0x4dd04dc4, 0x4d314d33, 0x4d0f4d34, 0x4d004d0d, 0x4d114d07, 0x4d704d14, 0x4d414d43, 0x43fc4d54, + 0x43f143f3, 0x43c043cf, 0x43d143c7, 0x4335433f, 0x4303430c, 0x43014300, 0x43044307, 0x431c431f, + 0x4310431d, 0x43714373, 0x4343434d, 0x43474340, 0x4354435c, 0x40f040ff, 0x40f540f7, 0x40cc40cf, + 0x40c040c3, 0x40c440c1, 0x40d040dc, 0x40d540d4, 0x4033403c, 0x40314030, 0x400f4034, 0x400d400c, + 0x40004003, 0x40074001, 0x40054004, 0x4013401c, 0x40114010, 0x407c4014, 0x40774070, 0x404d404c, + 0x40404043, 0x40444041, 0x405f4045, 0x4050405d, 0x40554057, 0x41f341fc, 0x41c041cf, 0x41df41c4, + 0x41d441d1, 0x41374130, 0x410c4134, 0x4100410d, 0x41044101, 0x41174110, 0x4173417d, 0x41754174, + 0x4143414d, 0x41534140, 0x41544151, 0x47c147f0, 0x47d047c4, 0x4731473c, 0x470d470f, 0x47014700, + 0x47134705, 0x47704710, 0x4741474c, 0x47504744, 0x44f144f3, 0x44cf44f4, 0x44c044cd, 0x44c544c7, + 0x44dc44df, 0x44d144d3, 0x443d443f, 0x44374430, 0x440c4435, 0x44004403, 0x44044401, 0x4410441d, + 0x44154411, 0x4473447c, 0x444d444f, 0x44454440, 0x4451445c, 0x45c045f0, 0x453345d0, 0x45344531, + 0x4500450f, 0x451c4507, 0x454c4570, 0x45404543, 0x5fff4541, 0x5ff75ffd, 0x5fc05ff5, 0x5fdd5fdf, + 0x5fd55fd7, 0x5f0c5f30, 0x5f015f03, 0x5f7f5f04, 0x5f775f7d, 0x5f405f75, 0x5f5d5f5f, 0x5f555f57, + 0x5cf45cf0, 0x5cc35ccc, 0x5cc45cc1, 0x5c315cc5, 0x5c0c5c34, 0x5c075c00, 0x5c1c5c05, 0x5c705c13, + 0x5c4d5c4f, 0x5c445c41, 0x5df75dfd, 0x5dcf5df5, 0x5ddd5dc4, 0x5dd55dd7, 0x5d0c5d30, 0x5d045d01, + 0x5d7f5d10, 0x5d775d7d, 0x5d405d75, 0x5d5d5d5f, 0x5d555d57, 0x53d053c4, 0x5333533c, 0x5303530f, + 0x53075300, 0x531c5305, 0x53115310, 0x53145317, 0x50f15370, 0x50cf50f4, 0x50c050cd, 0x50d150c7, + 0x503d50d4, 0x500c5030, 0x50005003, 0x50045001, 0x50155010, 0x5073507c, 0x50715070, 0x504d5074, + 0x50475040, 0x51cc51f0, 0x51c551c1, 0x51d051dc, 0x51315133, 0x510d5135, 0x51015100, 0x511f5107, + 0x5171511d, 0x5140514f, 0x51445141, 0x5153515c, 0x57ff5151, 0x57f757fd, 0x57df57f5, 0x57d757dd, + 0x570c57d5, 0x57015703, 0x577f5704, 0x5777577d, 0x57405775, 0x575d575f, 0x57555757, 0x54c354f0, + 0x54dc54c4, 0x543c54d0, 0x5400540f, 0x541c5405, 0x54145411, 0x5441544f, 0x55fd55ff, 0x55f555f7, + 0x55dd55df, 0x55d555d7, 0x5503550c, 0x557f5501, 0x5577557d, 0x55405575, 0x555d555f, 0x55555557 +); + +#enddecl(IQ1_GRID) + +#decl(IQ4_GRID) + +const kvalues_iq4nl = array( + -127, -104, -83, -65, -49, -35, -22, -10, 1, 13, 25, 38, 53, 69, 89, 113 +); + +#enddecl(IQ4_GRID) diff --git a/ggml/src/ggml-webgpu/wgsl-shaders/embed_wgsl.py b/ggml/src/ggml-webgpu/wgsl-shaders/embed_wgsl.py index cc8def7f13..d9dfd7d6f4 100755 --- a/ggml/src/ggml-webgpu/wgsl-shaders/embed_wgsl.py +++ b/ggml/src/ggml-webgpu/wgsl-shaders/embed_wgsl.py @@ -27,6 +27,26 @@ def replace_placeholders(shader_text, replacements): return shader_text +def expand_includes(shader, input_dir): + """ + Replace #include "file" lines in the text with the contents of that file. + Searches for files relative to input_dir. + """ + include_pattern = re.compile(r'^\s*#include\s+"([^"]+)"\s*$', re.MULTILINE) + + def replacer(match): + fname = match.group(1) + file_path = os.path.join(input_dir, fname) + if not os.path.exists(file_path): + raise FileNotFoundError(f"Included file not found: {file_path}") + with open(file_path, "r", encoding="utf-8") as f: + included_code = f.read() + # Recursively expand includes inside the included file + return expand_includes(included_code, input_dir) + + return include_pattern.sub(replacer, shader) + + def write_shader(shader_name, shader_code, output_dir, outfile): if output_dir: wgsl_filename = os.path.join(output_dir, f"{shader_name}.wgsl") @@ -35,8 +55,9 @@ def write_shader(shader_name, shader_code, output_dir, outfile): outfile.write(f'const char* wgsl_{shader_name} = R"({shader_code})";\n\n') -def generate_variants(shader_path, output_dir, outfile): - shader_base_name = shader_path.split("/")[-1].split(".")[0] +def generate_variants(fname, input_dir, output_dir, outfile): + shader_path = os.path.join(input_dir, fname) + shader_base_name = fname.split(".")[0] with open(shader_path, "r", encoding="utf-8") as f: text = f.read() @@ -46,11 +67,21 @@ def generate_variants(shader_path, output_dir, outfile): except ValueError: write_shader(shader_base_name, text, output_dir, outfile) else: - decls_map = parse_decls(extract_block(text, "DECLS")) - shader_template = extract_block(text, "SHADER") + try: + decls_map = parse_decls(extract_block(text, "DECLS")) + except ValueError: + decls_map = {} + with open(os.path.join(input_dir, "common_decls.tmpl"), "r", encoding="utf-8") as f: + common_decls = f.read() + decls_map.update(parse_decls(common_decls)) + + shader_template = extract_block(text, "SHADER") for variant in variants: - decls = variant["DECLS"] + if "DECLS" in variant: + decls = variant["DECLS"] + else: + decls = [] decls_code = "" for key in decls: if key not in decls_map: @@ -59,8 +90,16 @@ def generate_variants(shader_path, output_dir, outfile): shader_variant = replace_placeholders(shader_template, variant["REPLS"]) final_shader = re.sub(r'\bDECLS\b', decls_code, shader_variant) + final_shader = expand_includes(final_shader, input_dir) - output_name = f"{shader_base_name}_" + "_".join([variant["REPLS"]["SRC0_TYPE"], variant["REPLS"]["SRC1_TYPE"]]) + if "SRC0_TYPE" in variant["REPLS"] and "SRC1_TYPE" in variant["REPLS"]: + output_name = f"{shader_base_name}_" + "_".join([variant["REPLS"]["SRC0_TYPE"], variant["REPLS"]["SRC1_TYPE"]]) + elif "TYPE_SUFFIX" in variant["REPLS"]: + output_name = f"{shader_base_name}_" + variant["REPLS"]["TYPE_SUFFIX"] + elif "TYPE" in variant["REPLS"]: + output_name = f"{shader_base_name}_" + variant["REPLS"]["TYPE"] + else: + output_name = shader_base_name write_shader(output_name, final_shader, output_dir, outfile) @@ -78,7 +117,7 @@ def main(): out.write("// Auto-generated shader embedding\n\n") for fname in sorted(os.listdir(args.input_dir)): if fname.endswith(".wgsl"): - generate_variants(os.path.join(args.input_dir, fname), args.output_dir, out) + generate_variants(fname, args.input_dir, args.output_dir, out) if __name__ == "__main__": diff --git a/ggml/src/ggml-webgpu/wgsl-shaders/get_rows.tmpl.wgsl b/ggml/src/ggml-webgpu/wgsl-shaders/get_rows.tmpl.wgsl new file mode 100644 index 0000000000..e3fe311b26 --- /dev/null +++ b/ggml/src/ggml-webgpu/wgsl-shaders/get_rows.tmpl.wgsl @@ -0,0 +1,874 @@ +#define(VARIANTS) + +[ + { + "REPLS": { + "TYPE" : "vec4", + "TYPE_SUFFIX": "f32_vec", + "DST_TYPE": "vec4", + "BLOCK_SIZE": 4 + }, + "DECLS": ["F32_VEC"] + }, + { + "REPLS": { + "TYPE" : "f32", + "DST_TYPE": "f32", + "BLOCK_SIZE": 1 + }, + "DECLS": ["F32"] + }, + { + "REPLS": { + "TYPE" : "f16", + "DST_TYPE": "f32", + "BLOCK_SIZE": 1 + }, + "DECLS": ["F16"] + }, + { + "REPLS": { + "TYPE" : "i32", + "DST_TYPE": "i32", + "BLOCK_SIZE": 1 + }, + "DECLS": ["I32"] + }, + { + "REPLS": { + "TYPE" : "q4_0", + "DST_TYPE": "f32", + "BLOCK_SIZE": 32 + }, + "DECLS": ["BYTE_HELPERS", "Q4_0_T", "Q4_0"] + }, + { + "REPLS": { + "TYPE" : "q4_1", + "DST_TYPE": "f32", + "BLOCK_SIZE": 32 + }, + "DECLS": ["BYTE_HELPERS", "Q4_1_T", "Q4_1"] + }, + { + "REPLS": { + "TYPE" : "q5_0", + "DST_TYPE": "f32", + "BLOCK_SIZE": 32 + }, + "DECLS": ["BYTE_HELPERS", "Q5_0_T", "Q5_0"] + }, + { + "REPLS": { + "TYPE" : "q5_1", + "DST_TYPE": "f32", + "BLOCK_SIZE": 32 + }, + "DECLS": ["BYTE_HELPERS", "Q5_1_T", "Q5_1"] + }, + { + "REPLS": { + "TYPE" : "q8_0", + "DST_TYPE": "f32", + "BLOCK_SIZE": 32 + }, + "DECLS": ["BYTE_HELPERS", "Q8_0_T", "Q8_0"] + }, + { + "REPLS": { + "TYPE" : "q2_k", + "DST_TYPE": "f32", + "BLOCK_SIZE": 256 + }, + "DECLS": ["BYTE_HELPERS", "Q2_K_T", "Q2_K"] + }, + { + "REPLS": { + "TYPE" : "q3_k", + "DST_TYPE": "f32", + "BLOCK_SIZE": 256 + }, + "DECLS": ["BYTE_HELPERS", "Q3_K_T", "Q3_K"] + }, + { + "REPLS": { + "TYPE" : "q4_k", + "DST_TYPE": "f32", + "BLOCK_SIZE": 256 + }, + "DECLS": ["Q45_K_SCALE_MIN", "BYTE_HELPERS", "Q4_K_T", "Q4_K"] + }, + { + "REPLS": { + "TYPE" : "q5_k", + "DST_TYPE": "f32", + "BLOCK_SIZE": 256 + }, + "DECLS": ["Q45_K_SCALE_MIN", "BYTE_HELPERS", "Q5_K_T", "Q5_K"] + }, + { + "REPLS": { + "TYPE" : "q6_k", + "DST_TYPE": "f32", + "BLOCK_SIZE": 256 + }, + "DECLS": ["BYTE_HELPERS", "Q6_K_T", "Q6_K"] + }, + { + "REPLS": { + "TYPE" : "iq2_xxs", + "DST_TYPE": "f32", + "BLOCK_SIZE": 256 + }, + "DECLS": ["BYTE_HELPERS", "IQ23_TABLES", "IQ2_XXS_GRID", "IQ2_XXS_T", "IQ2_XXS"] + }, + { + "REPLS": { + "TYPE" : "iq2_xs", + "DST_TYPE": "f32", + "BLOCK_SIZE": 256 + }, + "DECLS": ["BYTE_HELPERS", "IQ23_TABLES", "IQ2_XS_GRID", "IQ2_XS_T", "IQ2_XS"] + }, + { + "REPLS": { + "TYPE": "iq2_s", + "DST_TYPE": "f32", + "BLOCK_SIZE": 256 + }, + "DECLS": ["BYTE_HELPERS", "IQ23_TABLES", "IQ2_S_GRID", "IQ2_S_T", "IQ2_S"] + }, + { + "REPLS": { + "TYPE": "iq3_xxs", + "DST_TYPE": "f32", + "BLOCK_SIZE": 256 + }, + "DECLS": ["BYTE_HELPERS", "IQ23_TABLES", "IQ3_XSS_GRID", "IQ3_XSS_T", "IQ3_XSS"] + }, + { + "REPLS": { + "TYPE": "iq3_s", + "DST_TYPE": "f32", + "BLOCK_SIZE": 256 + }, + "DECLS": ["BYTE_HELPERS", "IQ23_TABLES", "IQ3_S_GRID", "IQ3_S_T", "IQ3_S"] + }, + { + "REPLS": { + "TYPE": "iq1_s", + "DST_TYPE": "f32", + "BLOCK_SIZE": 256 + }, + "DECLS": ["BYTE_HELPERS", "IQ1_GRID", "IQ1_S_T", "IQ1_S"] + }, + { + "REPLS": { + "TYPE": "iq1_m", + "DST_TYPE": "f32", + "BLOCK_SIZE": 256 + }, + "DECLS": ["BYTE_HELPERS", "IQ1_GRID", "IQ1_M_T", "IQ1_M"] + }, + { + "REPLS": { + "TYPE": "iq4_nl", + "DST_TYPE": "f32", + "BLOCK_SIZE": 32, + }, + "DECLS": ["BYTE_HELPERS", "IQ4_GRID", "IQ4_NL_T", "IQ4_NL"] + }, + { + "REPLS": { + "TYPE": "iq4_xs", + "DST_TYPE": "f32", + "BLOCK_SIZE": 256, + }, + "DECLS": ["BYTE_HELPERS", "IQ4_GRID", "IQ4_XS_T", "IQ4_XS"] + } +] + +#end(VARIANTS) + +#define(DECLS) + +#decl(F32_VEC) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + dst[(dst_base / 4) + offset] = src[(src_base / 4) + offset]; +} +#enddecl(F32_VEC) + +#decl(F32) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + dst[dst_base + offset] = src[src_base + offset]; +} +#enddecl(F32) + +#decl(F16) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + dst[dst_base + offset] = f32(src[src_base + offset]); +} +#enddecl(F16) + +#decl(I32) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + dst[dst_base + offset] = src[src_base + offset]; +} +#enddecl(I32) + +#decl(Q4_0) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + let block_q4_0 = src[src_base + offset]; + let d = f32(block_q4_0.d); + for (var j: u32 = 0; j < 4; j++) { + let q_packed = bitcast(vec2(block_q4_0.qs[2 * j], block_q4_0.qs[2 * j + 1])); + for (var k: u32 = 0; k < 4; k++) { + let q_byte = get_byte(q_packed, k); + let q_hi = (f32((q_byte >> 4) & 0xF) - 8.0f) * d; + let q_lo = (f32(q_byte & 0xF) - 8.0f) * d; + let dst_offset = dst_base + offset * 32 + j * 4 + k; + dst[dst_offset] = q_lo; + dst[dst_offset + 16] = q_hi; + } + } +} +#enddecl(Q4_0) + +#decl(Q4_1) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + let block_q4_1 = src[src_base + offset]; + let d = f32(block_q4_1.d); + let m = f32(block_q4_1.m); + for (var j: u32 = 0; j < 4; j++) { + let q_packed = block_q4_1.qs[j]; + for (var k: u32 = 0; k < 4; k++) { + let q_byte = get_byte(q_packed, k); + let q_hi = f32((q_byte >> 4) & 0xF) * d + m; + let q_lo = f32(q_byte & 0xF) * d + m; + let dst_offset = dst_base + offset * 32 + j * 4 + k; + dst[dst_offset] = q_lo; + dst[dst_offset + 16] = q_hi; + } + } +} +#enddecl(Q4_1) + +#decl(Q5_0) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + let block_q5_0 = src[src_base + offset]; + let d = f32(block_q5_0.d); + let qh_packed = bitcast(vec2(block_q5_0.qh[0], block_q5_0.qh[1])); + for (var j: u32 = 0; j < 4; j++) { + let q_packed = bitcast(vec2(block_q5_0.qs[2 * j], block_q5_0.qs[2 * j + 1])); + for (var k: u32 = 0; k < 4; k++) { + let q_byte = get_byte(q_packed, k); + let qh_hi = (qh_packed >> (j * 4 + k + 12)) & 0x10; + let q_hi = (f32(((q_byte >> 4) & 0xF) | qh_hi) - 16.0) * d; + let qh_lo = ((qh_packed >> (j * 4 + k)) << 4) & 0x10; + let q_lo = (f32((q_byte & 0xF) | qh_lo) - 16.0) * d; + let dst_offset = dst_base + offset * 32 + j * 4 + k; + dst[dst_offset] = q_lo; + dst[dst_offset + 16] = q_hi; + } + } +} + +#enddecl(Q5_0) + +#decl(Q5_1) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + let block_q5_1 = src[src_base + offset]; + let d = f32(block_q5_1.d); + let m = f32(block_q5_1.m); + for (var j: u32 = 0; j < 4; j++) { + let q_packed = block_q5_1.qs[j]; + for (var k: u32 = 0; k < 4; k++) { + let q_byte = get_byte(q_packed, k); + let qh_hi = (block_q5_1.qh >> (j * 4 + k + 12)) & 0x10; + let q_hi = f32(((q_byte >> 4) & 0xF) | qh_hi) * d + m; + let qh_lo = ((block_q5_1.qh >> (j * 4 + k)) << 4) & 0x10; + let q_lo = f32((q_byte & 0xF) | qh_lo) * d + m; + let dst_offset = dst_base + offset * 32 + j * 4 + k; + dst[dst_offset] = q_lo; + dst[dst_offset + 16] = q_hi; + } + } +} +#enddecl(Q5_1) + +#decl(Q8_0) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + let block_q8_0 = src[src_base + offset]; + let d = f32(block_q8_0.d); + for (var j: u32 = 0; j < 8; j++) { + let q_packed = bitcast(vec2(block_q8_0.qs[2 * j], block_q8_0.qs[2 * j + 1])); + for (var k: u32 = 0; k < 4; k++) { + let q_byte = get_byte_i32(q_packed, k); + let q_val = f32(q_byte) * d; + let dst_offset = dst_base + offset * 32 + j * 4 + k; + dst[dst_offset] = q_val; + } + } +} +#enddecl(Q8_0) + +#decl(Q2_K) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + let block = src[src_base + offset]; + let d = f32(block.d); + let m = f32(block.dmin); + var dst_i = dst_base + offset * 256; + var is: u32 = 0; + // 2 halves of the block (128 elements each) + for (var q_b_idx: u32 = 0; q_b_idx < 64; q_b_idx += 32) { + // 4 groups (each group has 2 blocks of 16 elements) + for (var shift: u32 = 0; shift < 8; shift += 2) { + // 2 blocks + for (var k: u32 = 0; k < 32; k += 16) { + let sc = get_byte(block.scales[is / 4], is % 4); + is++; + let dl = d * f32(sc & 0xF); + let ml = m * f32(sc >> 4); + for (var l: u32 = 0u; l < 16; l++) { + let q_idx = q_b_idx + k + l; + let q_byte = get_byte(block.qs[q_idx / 4], q_idx % 4); + let qs_val = (q_byte >> shift) & 3; + dst[dst_i] = (f32(qs_val) * dl - ml); + dst_i++; + } + } + } + } +} +#enddecl(Q2_K) + +#decl(Q3_K) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + let block = src[src_base + offset]; + let d = f32(block.d); + + // extract 6-bit scales, which consist of 4-bits from first 8 bytes of scale, + // and 2-bits from the last 4 bytes + let kmask1: u32 = 0x03030303; + let kmask2: u32 = 0x0f0f0f0f; + var scale_vals: array; + for (var i: u32 = 0; i < 4; i++) { + scale_vals[i] = bitcast(vec2(block.scales[2 * i], block.scales[2 * i + 1])); + } + var tmp: u32 = scale_vals[2]; + scale_vals[2] = ((scale_vals[0] >> 4) & kmask2) | (((tmp >> 4) & kmask1) << 4); + scale_vals[3] = ((scale_vals[1] >> 4) & kmask2) | (((tmp >> 6) & kmask1) << 4); + scale_vals[0] = (scale_vals[0] & kmask2) | ((tmp & kmask1) << 4); + scale_vals[1] = (scale_vals[1] & kmask2) | (((tmp >> 2) & kmask1) << 4); + + // convert arrays of f16 -> u32 + var hmask_vals: array; + for (var i: u32 = 0; i < 8; i++) { + hmask_vals[i] = bitcast(vec2(block.hmask[2 * i], block.hmask[2 * i + 1])); + } + var qs_vals: array; + for (var i: u32 = 0; i < 16; i++) { + qs_vals[i] = bitcast(vec2(block.qs[2 * i], block.qs[2 * i + 1])); + } + + var dst_i = dst_base + offset * 256; + var is: u32 = 0; + var m: u32 = 1; + // 2 halves of the block (128 elements each) + for (var q_b_idx: u32 = 0; q_b_idx < 64; q_b_idx += 32) { + // 4 groups (each group has 2 blocks of 16 elements) + for (var shift: u32 = 0; shift < 8; shift += 2) { + // 2 blocks + for (var k: u32 = 0; k < 32; k += 16) { + let sc = get_byte(scale_vals[is / 4], is % 4); + is++; + let dl = d * (f32(sc) - 32.0); + for (var l: u32 = 0u; l < 16u; l++) { + let q_idx = q_b_idx + k + l; + let hm_idx = k + l; + let q_byte = get_byte(qs_vals[q_idx / 4], q_idx % 4); + let hmask_byte = get_byte(hmask_vals[hm_idx / 4], hm_idx % 4); + let hm = select(4.0, 0.0, (hmask_byte & m) != 0); + let qs_val = (q_byte >> shift) & 3; + dst[dst_i] = (f32(qs_val) - hm) * dl; + dst_i++; + } + } + m <<= 1; + } + } +} +#enddecl(Q3_K) + +#decl(Q4_K) +// 8 blocks of 32 elements each +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + let block = src[src_base + offset]; + let d = f32(block.d); + let m = f32(block.dmin); + var dst_i = dst_base + offset * 256; + var is: u32 = 0; + // 2 blocks each iteration + for (var q_b_idx: u32 = 0; q_b_idx < 128; q_b_idx += 32) { + for (var shift: u32 = 0; shift < 8; shift += 4) { + let scale_min = get_scale_min(is, block.scales); + is++; + let dl = d * scale_min.x; + let ml = m * scale_min.y; + for (var l: u32 = 0; l < 32; l++) { + let q_idx = q_b_idx + l; + let q_byte = get_byte(block.qs[q_idx / 4], q_idx % 4); + let qs_val = (q_byte >> shift) & 0xF; + dst[dst_i] = (f32(qs_val) * dl - ml); + dst_i++; + } + } + } +} +#enddecl(Q4_K) + +#decl(Q5_K) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + let block = src[src_base + offset]; + let d = f32(block.d); + let m = f32(block.dmin); + var dst_i = dst_base + offset * 256; + var is: u32 = 0; + var u: u32 = 1; + // 2 blocks each iteration + for (var q_b_idx: u32 = 0; q_b_idx < 128; q_b_idx += 32) { + for (var shift: u32 = 0; shift < 8; shift += 4) { + let scale_min = get_scale_min(is, block.scales); + is++; + let dl = d * scale_min.x; + let ml = m * scale_min.y; + for (var l: u32 = 0; l < 32; l++) { + let q_idx = q_b_idx + l; + let q_byte = get_byte(block.qs[q_idx / 4], q_idx % 4); + let qh_byte = get_byte(block.qh[l / 4], l % 4); + let qs_val = (q_byte >> shift) & 0xF; + let qh_val = select(0.0, 16.0, (qh_byte & u) != 0); + dst[dst_i] = (f32(qs_val) + qh_val) * dl - ml; + dst_i++; + } + u <<= 1; + } + } +} +#enddecl(Q5_K) + +#decl(Q6_K) +// 16 blocks of 16 elements each +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + let block = src[src_base + offset]; + let d = f32(block.d); + + // convert arrays of f16 -> u32 + var ql_vals: array; + for (var i: u32 = 0; i < 32; i++) { + ql_vals[i] = bitcast(vec2(block.ql[2 * i], block.ql[2 * i + 1])); + } + var qh_vals: array; + for (var i: u32 = 0; i < 16; i++) { + qh_vals[i] = bitcast(vec2(block.qh[2 * i], block.qh[2 * i + 1])); + } + var scale_vals: array; + for (var i: u32 = 0; i < 4; i++) { + scale_vals[i] = bitcast(vec2(block.scales[2 * i], block.scales[2 * i + 1])); + } + + var dst_i = dst_base + offset * 256; + var qh_b_idx: u32 = 0; + var sc_b_idx: u32 = 0; + for (var ql_b_idx: u32 = 0; ql_b_idx < 128; ql_b_idx += 64) { + for (var l: u32 = 0; l < 32; l++) { + let ql13_b = get_byte(ql_vals[(ql_b_idx + l) / 4], (ql_b_idx + l) % 4); + let ql24_b = get_byte(ql_vals[(ql_b_idx + l + 32) / 4], (ql_b_idx + l + 32) % 4); + let qh_b = get_byte(qh_vals[(qh_b_idx + l) / 4], (qh_b_idx + l) % 4); + + let q1 = f32((ql13_b & 0xF) | ((qh_b & 3) << 4)) - 32.0; + let q2 = f32((ql24_b & 0xF) | (((qh_b >> 2) & 3) << 4)) - 32.0; + let q3 = f32((ql13_b >> 4) | (((qh_b >> 4) & 3) << 4)) - 32.0; + let q4 = f32((ql24_b >> 4) | (((qh_b >> 6) & 3) << 4)) - 32.0; + + let is = l/16; + let is1 = sc_b_idx + is; + let sc1 = get_byte_i32(scale_vals[is1 / 4], is1 % 4); + let is2 = sc_b_idx + is + 2; + let sc2 = get_byte_i32(scale_vals[is2 / 4], is2 % 4); + let is3 = sc_b_idx + is + 4; + let sc3 = get_byte_i32(scale_vals[is3 / 4], is3 % 4); + let is4 = sc_b_idx + is + 6; + let sc4 = get_byte_i32(scale_vals[is4 / 4], is4 % 4); + + dst[dst_i + l] = (q1 * f32(sc1)) * d; + dst[dst_i + l + 32] = (q2 * f32(sc2)) * d; + dst[dst_i + l + 64] = (q3 * f32(sc3)) * d; + dst[dst_i + l + 96] = (q4 * f32(sc4)) * d; + } + dst_i += 128; + qh_b_idx += 32; + sc_b_idx += 8; + } +} + +#enddecl(Q6_K) + +#decl(IQ2_XXS) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + let block = src[src_base + offset]; + let d = f32(block.d); + var dst_i = dst_base + offset * 256; + for (var ib: u32 = 0; ib < 32; ib += 4) { + let aux0 = bitcast(vec2(block.qs[ib], block.qs[ib + 1])); + let aux1 = bitcast(vec2(block.qs[ib + 2], block.qs[ib + 3])); + let db = d * (0.5 + f32(aux1 >> 28)) * 0.25; + for (var l: u32 = 0; l < 4; l++) { + let ig = get_byte(aux0, l) * 8; + let is = (aux1 >> (7 * l)) & 127; + let signs = get_byte(ksigns_iq2xs[is / 4], is % 4); + for (var j: u32 = 0; j < 8; j++) { + let g = get_byte(iq2xxs_grid[(ig + j) / 4], (ig + j) % 4); + let m = select(1.0, -1.0, (get_byte(kmask_iq2xs[j / 4], j % 4) & signs) != 0); + dst[dst_i] = db * f32(g) * m; + dst_i++; + } + } + } +} +#enddecl(IQ2_XXS) + +#decl(IQ2_XS) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + let block = src[src_base + offset]; + let d = f32(block.d); + var dst_i = dst_base + offset * 256; + var scale_vals = array( + bitcast(vec2(block.scales[0], block.scales[1])), + bitcast(vec2(block.scales[2], block.scales[3])) + ); + for (var ib: u32 = 0; ib < 32; ib += 4) { + let s = get_byte(scale_vals[ib / 16], (ib % 16) / 4); + let db = array( + d * (0.5 + f32(s & 0xF)) * 0.25, + d * (0.5 + f32(s >> 4)) * 0.25 + ); + for (var l: u32 = 0; l < 4; l++) { + let qs_val = bitcast(vec2(block.qs[ib + l], 0.0)); + let ig = (qs_val & 511) * 8; + let is = qs_val >> 9; + let signs = get_byte(ksigns_iq2xs[is / 4], is % 4); + let dl = db[l/2]; + for (var j: u32 = 0; j < 8; j++) { + let g = get_byte(iq2xs_grid[(ig + j) / 4], (ig + j) % 4); + let m = select(1.0, -1.0, (get_byte(kmask_iq2xs[j / 4], j % 4) & signs) != 0); + dst[dst_i] = dl * f32(g) * m; + dst_i++; + } + } + } +} +#enddecl(IQ2_XS) + +#decl(IQ2_S) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + let block = src[src_base + offset]; + let d = f32(block.d); + var dst_i = dst_base + offset * 256; + var qs_vals : array; + for (var i: u32 = 0; i < 16; i++) { + qs_vals[i] = bitcast(vec2(block.qs[i * 2], block.qs[i * 2 + 1])); + } + var qh_vals = array( + bitcast(vec2(block.qh[0], block.qh[1])), + bitcast(vec2(block.qh[2], block.qh[3])) + ); + var scale_vals = array( + bitcast(vec2(block.scales[0], block.scales[1])), + bitcast(vec2(block.scales[2], block.scales[3])) + ); + for (var ib: u32 = 0; ib < 8; ib ++) { + let s = get_byte(scale_vals[ib / 4], ib % 4); + let db = array( + d * (0.5 + f32(s & 0xF)) * 0.25, + d * (0.5 + f32(s >> 4)) * 0.25 + ); + let qs_w = qs_vals[ib]; + for (var l: u32 = 0; l < 4; l++) { + let qh_b = (get_byte(qh_vals[ib / 4], ib % 4) << (8 - 2 * l)) & 0x300; + let ig = (get_byte(qs_w, l) | qh_b) * 8; + let signs = get_byte(qs_vals[ib + 8], l); + let dl = db[l/2]; + for (var j: u32 = 0; j < 8; j++) { + let g = get_byte(iq2s_grid[(ig + j) / 4], (ig + j) % 4); + let m = select(1.0, -1.0, (get_byte(kmask_iq2xs[j / 4], j % 4) & signs) != 0); + dst[dst_i] = dl * f32(g) * m; + dst_i++; + } + } + } +} + +#enddecl(IQ2_S) + +#decl(IQ3_XSS) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + let block = src[src_base + offset]; + let d = f32(block.d); + var dst_i = dst_base + offset * 256; + for (var ib: u32 = 0; ib < 16; ib += 2) { + let sc_sign = bitcast(vec2(block.qs[ib + 32], block.qs[ib + 33])); + let db = d * (0.5 + f32(sc_sign >> 28)) * 0.5; + for (var l: u32 = 0; l < 4; l++) { + let is = (sc_sign >> (7 * l)) & 127; + let signs = get_byte(ksigns_iq2xs[is / 4], is % 4); + let ig_val = bitcast(vec2(block.qs[ib * 2 + l], 0.0)); + let ig1 = get_byte(ig_val, 0); + let ig2 = get_byte(ig_val, 1); + for (var j: u32 = 0; j < 4; j++) { + let g1 = get_byte(iq3xxs_grid[ig1], j); + let g2 = get_byte(iq3xxs_grid[ig2], j); + let m1 = select(1.0, -1.0, (get_byte(kmask_iq2xs[0], j) & signs) != 0); + let m2 = select(1.0, -1.0, (get_byte(kmask_iq2xs[1], j) & signs) != 0); + dst[dst_i] = db * f32(g1) * m1; + dst[dst_i + 4] = db * f32(g2) * m2; + dst_i++; + } + dst_i += 4; + } + } +} +#enddecl(IQ3_XSS) + +#decl(IQ3_S) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + let block = src[src_base + offset]; + let d = f32(block.d); + var dst_i = dst_base + offset * 256; + var qh_vals = array( + bitcast(vec2(block.qh[0], block.qh[1])), + bitcast(vec2(block.qh[2], block.qh[3])) + ); + var sign_vals: array; + for (var i: u32 = 0; i < 8; i++) { + sign_vals[i] = bitcast(vec2(block.signs[i * 2], block.signs[i * 2 + 1])); + } + var scale_vals = bitcast(vec2(block.scales[0], block.scales[1])); + for (var ib: u32 = 0; ib < 4; ib++) { + let s = get_byte(scale_vals, ib); + let db = array( + d * (1.0 + 2.0 * f32(s & 0xF)), + d * (1.0 + 2.0 * f32(s >> 4)) + ); + for (var k: u32 = 0; k < 2; k++) { + let dl = db[k]; + let qh_byte = get_byte(qh_vals[ib / 2], (ib % 2) * 2 + k); + let sign_w = sign_vals[ib * 2 + k]; + for (var l: u32 = 0; l < 4; l++) { + let signs = get_byte(sign_w, l); + let ig_val = bitcast(vec2(block.qs[ib * 8 + k * 4 + l], 0.0)); + let ig1 = get_byte(ig_val, 0) | ((qh_byte << ((8 - (2 * l)))) & 256); + let ig2 = get_byte(ig_val, 1) | ((qh_byte << ((7 - (2 * l)))) & 256); + for (var j: u32 = 0; j < 4; j++) { + let g1 = get_byte(iq3s_grid[ig1], j); + let g2 = get_byte(iq3s_grid[ig2], j); + let m1 = select(1.0, -1.0, (get_byte(kmask_iq2xs[0], j) & signs) != 0); + let m2 = select(1.0, -1.0, (get_byte(kmask_iq2xs[1], j) & signs) != 0); + dst[dst_i] = dl * f32(g1) * m1; + dst[dst_i + 4] = dl * f32(g2) * m2; + dst_i++; + } + dst_i += 4; + } + } + } +} +#enddecl(IQ3_S) + +#decl(IQ1_S) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + let block = src[src_base + offset]; + let d = f32(block.d); + var dst_i = dst_base + offset * 256; + for (var ib: u32 = 0; ib < 8; ib++) { + let qh = bitcast(vec2(block.qh[ib], 0.0)); + let dl = d * (2 * f32((qh >> 12) & 7) + 1); + let delta = select(IQ1_DELTA, -IQ1_DELTA, (qh & 0x8000) != 0); + let qs_w = bitcast(vec2(block.qs[ib * 2], block.qs[ib * 2 + 1])); + for (var l: u32 = 0; l < 4; l++) { + let ig = (get_byte(qs_w, l) | (((qh >> (3 * l)) & 7) << 8)) * 8; + for (var j: u32 = 0; j < 8; j++) { + let gw = iq1_grid[(ig + j) / 16]; + let g = (gw >> (((ig + j) % 16) * 2)) & 3; + let gs = bitcast(g << 30) >> 30; + dst[dst_i] = dl * (f32(gs) + delta); + dst_i++; + } + } + } +} + +#enddecl(IQ1_S) + +#decl(IQ1_M) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + let block = src[src_base + offset]; + + let scale = ((block.scales[0] >> 12) & 0xF) | ((block.scales[0] >> 24) & 0x00F0) | ((block.scales[1] >> 4) & 0x0F00) | ((block.scales[1] >> 16) & 0xF000); + let d = f32(bitcast>(scale).x); + var dst_i = dst_base + offset * 256; + for (var ib: u32 = 0; ib < 8; ib++) { + let sw = (block.scales[ib / 4] >> (16 * ((ib / 2) % 2))) & 0xFFFF; + let s1 : u32 = (sw >> (6 * (ib % 2))) & 0x7; + let s2 : u32 = (sw >> (6 * (ib % 2) + 3)) & 0x7; + var dl = array( + d * f32(2 * s1 + 1), + d * f32(2 * s2 + 1) + ); + + let qh = block.qh[ib / 2] >> (16 * (ib % 2)); + var idx = array( + get_byte(block.qs[ib], 0) | ((qh << 8) & 0x700), + get_byte(block.qs[ib], 1) | ((qh << 4) & 0x700), + get_byte(block.qs[ib], 2) | ((qh) & 0x700), + get_byte(block.qs[ib], 3) | ((qh >> 4) & 0x700) + ); + var delta = array( + select(IQ1_DELTA, -IQ1_DELTA, (qh & 0x08) != 0), + select(IQ1_DELTA, -IQ1_DELTA, (qh & 0x80) != 0), + select(IQ1_DELTA, -IQ1_DELTA, ((qh >> 8) & 0x08) != 0), + select(IQ1_DELTA, -IQ1_DELTA, ((qh >> 8) & 0x80) != 0) + ); + for (var l: u32 = 0; l < 4; l++) { + let ig = idx[l] * 8; + for (var j: u32 = 0; j < 8; j++) { + let gw = iq1_grid[(ig + j) / 16]; + let g = (gw >> (((ig + j) % 16) * 2)) & 3; + let gs = bitcast(g << 30) >> 30; + dst[dst_i] = dl[l/2] * (f32(gs) + delta[l]); + dst_i++; + } + } + } +} + +#enddecl(IQ1_M) + +#decl(IQ4_NL) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + let block = src[src_base + offset]; + let d = f32(block.d); + var dst_i = dst_base + offset * 32; + var qs: array; + for (var i: u32 = 0; i < 4; i++) { + qs[i] = bitcast(vec2(block.qs[i * 2], block.qs[i * 2 + 1])); + } + for (var j: u32 = 0; j < 16; j++) { + let qsb = get_byte(qs[j / 4], j % 4); + dst[dst_i] = d * f32(kvalues_iq4nl[qsb & 0xF]); + dst[dst_i + 16] = d * f32(kvalues_iq4nl[qsb >> 4]); + dst_i++; + } +} +#enddecl(IQ4_NL) + +#decl(IQ4_XS) +fn copy_elements(src_base: u32, dst_base: u32, offset: u32) { + let block = src[src_base + offset]; + let d = f32(block.d); + let scales_h = bitcast(vec2(block.scales_h, 0.0)); + var dst_i = dst_base + offset * 256; + for (var ib: u32 = 0; ib < 8; ib++) { + let ls = ((get_byte(block.scales_l, ib / 2) >> (4 * (ib % 2))) & 0xF) | (((scales_h >> (2 * ib)) & 3) << 4); + let dl = d * (f32(ls) - 32.0); + for (var j: u32 = 0; j < 16; j++) { + let iqs = ib * 16 + j; + let qsb = get_byte(block.qs[iqs / 4], iqs % 4); + dst[dst_i] = dl * f32(kvalues_iq4nl[qsb & 0xF]); + dst[dst_i + 16] = dl * f32(kvalues_iq4nl[qsb >> 4]); + dst_i++; + } + dst_i += 16; + } +} +#enddecl(IQ4_XS) + +#end(DECLS) + +#define(SHADER) + +enable f16; + +DECLS + +@group(0) @binding(0) +var src: array<{{TYPE}}>; + +@group(0) @binding(1) +var idx: array; + +@group(0) @binding(2) +var dst: array<{{DST_TYPE}}>; + +struct Params { + offset_src: u32, // in elements + offset_idx: u32, // in elements + offset_dst: u32, // in elements + + // Strides (in elements) + stride_src1: u32, + stride_src2: u32, + stride_src3: u32, + + stride_idx0: u32, + stride_idx1: u32, + stride_idx2: u32, + + stride_dst1: u32, + stride_dst2: u32, + stride_dst3: u32, + + // Shape of dst + ne0: u32, + n_rows: u32, + ne2: u32, + ne3: u32, + + // Shape of idx + idx1: u32, + idx2: u32, +}; + +@group(0) @binding(3) +var params: Params; + +override wg_size: u32; +@compute @workgroup_size(wg_size) +fn main(@builtin(global_invocation_id) gid: vec3) { + if (gid.x >= params.n_rows * params.ne2 * params.ne3) { + return; + } + var i = gid.x; + let i_dst3 = i / (params.ne2 * params.n_rows); + + i = i % (params.ne2 * params.n_rows); + let i_dst2 = i / params.n_rows; + let i_dst1 = i % params.n_rows; + + let i_idx2 = i_dst3 % params.idx2; + let i_idx1 = i_dst2 % params.idx1; + let i_idx0 = i_dst1; + + let i_idx = params.offset_idx + i_idx0 * params.stride_idx0 + i_idx1 * params.stride_idx1 + i_idx2 * params.stride_idx2; + + let idx_val = u32(idx[i_idx]); + + let i_src_row = params.offset_src + idx_val * params.stride_src1 + i_dst2 * params.stride_src2 + i_dst3 * params.stride_src3; + let i_dst_row = params.offset_dst + i_dst1 * params.stride_dst1 + i_dst2 * params.stride_dst2 + i_dst3 * params.stride_dst3; + + for (var i: u32 = 0; i < params.ne0/{{BLOCK_SIZE}}; i++) { + copy_elements(i_src_row, i_dst_row, i); + } +} + +#end(SHADER) diff --git a/ggml/src/ggml-webgpu/wgsl-shaders/mul.tmpl.wgsl b/ggml/src/ggml-webgpu/wgsl-shaders/mul.tmpl.wgsl new file mode 100644 index 0000000000..12506e1420 --- /dev/null +++ b/ggml/src/ggml-webgpu/wgsl-shaders/mul.tmpl.wgsl @@ -0,0 +1,44 @@ +#define(VARIANTS) + +[ + { + "REPLS": { + "TYPE" : "f32", + } + }, + { + "REPLS": { + "TYPE" : "f16", + } + } +] + +#end(VARIANTS) + +#define(SHADER) + +enable f16; + +#include "binary_head.tmpl" + +@group(0) @binding(0) +var src0: array<{{TYPE}}>; + +@group(0) @binding(1) +var src1: array<{{TYPE}}>; + +@group(0) @binding(2) +var dst: array<{{TYPE}}>; + +@group(0) @binding(3) +var params: Params; + +override wg_size: u32; +@compute @workgroup_size(wg_size) +fn main(@builtin(global_invocation_id) gid: vec3) { + if (gid.x < params.ne) { + dst[params.offset_dst + gid.x] = src0[params.offset_src0 + gid.x] * src1[params.offset_src1 + src1_index(gid.x)]; + } +} + +#end(SHADER) diff --git a/ggml/src/ggml-webgpu/wgsl-shaders/mul_in_place.tmpl.wgsl b/ggml/src/ggml-webgpu/wgsl-shaders/mul_in_place.tmpl.wgsl new file mode 100644 index 0000000000..e467e59edb --- /dev/null +++ b/ggml/src/ggml-webgpu/wgsl-shaders/mul_in_place.tmpl.wgsl @@ -0,0 +1,41 @@ +#define(VARIANTS) + +[ + { + "REPLS": { + "TYPE" : "f32", + } + }, + { + "REPLS": { + "TYPE" : "f16", + } + } +] + +#end(VARIANTS) + +#define(SHADER) + +enable f16; + +#include "binary_head.tmpl" + +@group(0) @binding(0) +var src0: array<{{TYPE}}>; + +@group(0) @binding(1) +var src1: array<{{TYPE}}>; + +@group(0) @binding(2) +var params: Params; + +override wg_size: u32; +@compute @workgroup_size(wg_size) +fn main(@builtin(global_invocation_id) gid: vec3) { + if (gid.x < params.ne) { + src0[params.offset_dst + gid.x] = src0[params.offset_src0 + gid.x] * src1[params.offset_src1 + src1_index(gid.x)]; + } +} + +#end(SHADER) diff --git a/ggml/src/ggml-webgpu/wgsl-shaders/mul_mat.tmpl.wgsl b/ggml/src/ggml-webgpu/wgsl-shaders/mul_mat.tmpl.wgsl index 79465c298d..25e2185de8 100644 --- a/ggml/src/ggml-webgpu/wgsl-shaders/mul_mat.tmpl.wgsl +++ b/ggml/src/ggml-webgpu/wgsl-shaders/mul_mat.tmpl.wgsl @@ -31,7 +31,7 @@ "SRC1_TYPE": "f32", "BLOCK_SIZE": 32 }, - "DECLS": ["BYTE_HELPERS", "Q4_0"] + "DECLS": ["BYTE_HELPERS", "Q4_0_T", "Q4_0"] }, { "REPLS": { @@ -39,7 +39,7 @@ "SRC1_TYPE": "f32", "BLOCK_SIZE": 32 }, - "DECLS": ["BYTE_HELPERS", "Q4_1"] + "DECLS": ["BYTE_HELPERS", "Q4_1_T", "Q4_1"] }, { "REPLS": { @@ -47,7 +47,7 @@ "SRC1_TYPE": "f32", "BLOCK_SIZE": 32 }, - "DECLS": ["BYTE_HELPERS", "Q5_0"] + "DECLS": ["BYTE_HELPERS", "Q5_0_T", "Q5_0"] }, { "REPLS": { @@ -55,7 +55,7 @@ "SRC1_TYPE": "f32", "BLOCK_SIZE": 32 }, - "DECLS": ["BYTE_HELPERS", "Q5_1"] + "DECLS": ["BYTE_HELPERS", "Q5_1_T", "Q5_1"] }, { "REPLS": { @@ -63,7 +63,7 @@ "SRC1_TYPE": "f32", "BLOCK_SIZE": 32 }, - "DECLS": ["BYTE_HELPERS", "Q8_0"] + "DECLS": ["BYTE_HELPERS", "Q8_0_T", "Q8_0"] }, { "REPLS": { @@ -71,7 +71,7 @@ "SRC1_TYPE": "f32", "BLOCK_SIZE": 256 }, - "DECLS": ["BYTE_HELPERS", "Q2_K"] + "DECLS": ["BYTE_HELPERS", "Q2_K_T", "Q2_K"] }, { "REPLS": { @@ -79,7 +79,7 @@ "SRC1_TYPE": "f32", "BLOCK_SIZE": 256 }, - "DECLS": ["BYTE_HELPERS", "Q3_K"] + "DECLS": ["BYTE_HELPERS", "Q3_K_T", "Q3_K"] }, { "REPLS": { @@ -87,7 +87,7 @@ "SRC1_TYPE": "f32", "BLOCK_SIZE": 256 }, - "DECLS": ["Q45_K_SCALE_MIN", "BYTE_HELPERS", "Q4_K"] + "DECLS": ["Q45_K_SCALE_MIN", "BYTE_HELPERS", "Q4_K_T", "Q4_K"] }, { "REPLS": { @@ -95,7 +95,7 @@ "SRC1_TYPE": "f32", "BLOCK_SIZE": 256 }, - "DECLS": ["Q45_K_SCALE_MIN", "BYTE_HELPERS", "Q5_K"] + "DECLS": ["Q45_K_SCALE_MIN", "BYTE_HELPERS", "Q5_K_T", "Q5_K"] }, { "REPLS": { @@ -103,7 +103,7 @@ "SRC1_TYPE": "f32", "BLOCK_SIZE": 256 }, - "DECLS": ["BYTE_HELPERS", "Q6_K"] + "DECLS": ["BYTE_HELPERS", "Q6_K_T", "Q6_K"] }, { "REPLS": { @@ -111,7 +111,7 @@ "SRC1_TYPE": "f32", "BLOCK_SIZE": 256 }, - "DECLS": ["BYTE_HELPERS", "IQ23_TABLES", "IQ2_XXS"] + "DECLS": ["BYTE_HELPERS", "IQ23_TABLES", "IQ2_XXS_GRID", "IQ2_XXS_T", "IQ2_XXS"] }, { "REPLS": { @@ -119,7 +119,7 @@ "SRC1_TYPE": "f32", "BLOCK_SIZE": 256 }, - "DECLS": ["BYTE_HELPERS", "IQ23_TABLES", "IQ2_XS"] + "DECLS": ["BYTE_HELPERS", "IQ23_TABLES", "IQ2_XS_GRID", "IQ2_XS_T", "IQ2_XS"] }, { "REPLS": { @@ -127,7 +127,7 @@ "SRC1_TYPE": "f32", "BLOCK_SIZE": 256 }, - "DECLS": ["BYTE_HELPERS", "IQ23_TABLES", "IQ2_S"] + "DECLS": ["BYTE_HELPERS", "IQ23_TABLES", "IQ2_S_GRID", "IQ2_S_T", "IQ2_S"] }, { "REPLS": { @@ -135,7 +135,7 @@ "SRC1_TYPE": "f32", "BLOCK_SIZE": 256 }, - "DECLS": ["BYTE_HELPERS", "IQ23_TABLES", "IQ3_XSS"] + "DECLS": ["BYTE_HELPERS", "IQ23_TABLES", "IQ3_XSS_GRID", "IQ3_XSS_T", "IQ3_XSS"] }, { "REPLS": { @@ -143,7 +143,7 @@ "SRC1_TYPE": "f32", "BLOCK_SIZE": 256 }, - "DECLS": ["BYTE_HELPERS", "IQ23_TABLES", "IQ3_S"] + "DECLS": ["BYTE_HELPERS", "IQ23_TABLES", "IQ3_S_GRID", "IQ3_S_T", "IQ3_S"] }, { "REPLS": { @@ -151,7 +151,7 @@ "SRC1_TYPE": "f32", "BLOCK_SIZE": 256 }, - "DECLS": ["BYTE_HELPERS", "IQ1_TABLE","IQ1_S"] + "DECLS": ["BYTE_HELPERS", "IQ1_GRID", "IQ1_S_T", "IQ1_S"] }, { "REPLS": { @@ -159,7 +159,7 @@ "SRC1_TYPE": "f32", "BLOCK_SIZE": 256 }, - "DECLS": ["BYTE_HELPERS", "IQ1_TABLE","IQ1_M"] + "DECLS": ["BYTE_HELPERS", "IQ1_GRID", "IQ1_M_T", "IQ1_M"] }, { "REPLS": { @@ -167,7 +167,7 @@ "SRC1_TYPE": "f32", "BLOCK_SIZE": 32, }, - "DECLS": ["BYTE_HELPERS", "IQ4_TABLE", "IQ4_NL"] + "DECLS": ["BYTE_HELPERS", "IQ4_GRID", "IQ4_NL_T", "IQ4_NL"] }, { "REPLS": { @@ -175,7 +175,7 @@ "SRC1_TYPE": "f32", "BLOCK_SIZE": 256, }, - "DECLS": ["BYTE_HELPERS", "IQ4_TABLE", "IQ4_XS"] + "DECLS": ["BYTE_HELPERS", "IQ4_GRID", "IQ4_XS_T", "IQ4_XS"] } ] @@ -183,18 +183,6 @@ #define(DECLS) -#decl(BYTE_HELPERS) - -fn get_byte(value: u32, index: u32) -> u32 { - return (value >> (index * 8)) & 0xFF; -} - -fn get_byte_i32(value: u32, index: u32) -> i32 { - return bitcast(((value >> (index * 8)) & 0xFF) << 24) >> 24; -} - -#enddecl(BYTE_HELPERS) - #decl(FLOAT) fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { return f32(src0[src0_idx_base + offset]) * f32(src1[src1_idx_base + offset]); @@ -202,11 +190,6 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { #enddecl(FLOAT) #decl(Q4_0) -struct q4_0 { - d: f16, - qs: array -}; - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block_q4_0 = src0[src0_idx_base + offset]; let d = f32(block_q4_0.d); @@ -227,12 +210,6 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { #enddecl(Q4_0) #decl(Q4_1) -struct q4_1 { - d: f16, - m: f16, - qs: array -}; - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block_q4_1 = src0[src0_idx_base + offset]; let d = f32(block_q4_1.d); @@ -254,12 +231,6 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { #enddecl(Q4_1) #decl(Q5_0) -struct q5_0 { - d: f16, - qh: array, - qs: array -}; - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block_q5_0 = src0[src0_idx_base + offset]; let d = f32(block_q5_0.d); @@ -283,13 +254,6 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { #enddecl(Q5_0) #decl(Q5_1) -struct q5_1 { - d: f16, - m: f16, - qh: u32, - qs: array -}; - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block_q5_1 = src0[src0_idx_base + offset]; let d = f32(block_q5_1.d); @@ -313,11 +277,6 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { #enddecl(Q5_1) #decl(Q8_0) -struct q8_0 { - d: f16, - qs: array -}; - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block_q8_0 = src0[src0_idx_base + offset]; let d = f32(block_q8_0.d); @@ -336,12 +295,6 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { #enddecl(Q8_0) #decl(Q8_1) -struct q8_1 { - d: f16, - m: f16, - qs: array -}; - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block_q8_1 = src0[src0_idx_base + offset]; let d = f32(block_q8_1.d); @@ -362,13 +315,6 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { #decl(Q2_K) // 16 blocks of 16 elements each -struct q2_k { - scales: array, - qs: array, - d: f16, - dmin: f16 -}; - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block = src0[src0_idx_base + offset]; let d = f32(block.d); @@ -403,13 +349,6 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { #decl(Q3_K) // 16 blocks of 16 elements each -struct q3_k { - hmask: array, - qs: array, - scales: array, // 6-bit quantized values - d: f16 -}; - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block = src0[src0_idx_base + offset]; let d = f32(block.d); @@ -470,34 +409,8 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { #enddecl(Q3_K) -#decl(Q45_K_SCALE_MIN) - -fn get_scale_min(is: u32, scales: array) -> vec2 { - if (is < 4) { - let sc_byte = get_byte(scales[is / 4], is % 4); - let min_byte = get_byte(scales[(is + 4) / 4], is % 4); - return vec2(f32(sc_byte & 63), f32(min_byte & 63)); - } else { - let sc_min_lo = get_byte(scales[(is + 4) / 4], (is + 4) % 4); - let sc_hi = get_byte(scales[(is - 4) / 4], (is - 4) % 4); - let min_hi = get_byte(scales[is / 4], is % 4); - let sc = (sc_min_lo & 0xF) | ((sc_hi >> 6) << 4); - let m = (sc_min_lo >> 4) | ((min_hi >> 6) << 4); - return vec2(f32(sc), f32(m)); - } -} - -#enddecl(Q45_K_SCALE_MIN) - #decl(Q4_K) // 8 blocks of 32 elements each -struct q4_k { - d: f16, - dmin: f16, - scales: array, - qs: array -}; - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block = src0[src0_idx_base + offset]; let d = f32(block.d); @@ -528,14 +441,6 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { #decl(Q5_K) // 8 blocks of 32 elements each -struct q5_k { - d: f16, - dmin: f16, - scales: array, - qh: array, - qs: array -}; - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block = src0[src0_idx_base + offset]; let d = f32(block.d); @@ -570,13 +475,6 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { #decl(Q6_K) // 16 blocks of 16 elements each -struct q6_k { - ql: array, - qh: array, - scales: array, - d: f16 -}; - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block = src0[src0_idx_base + offset]; let d = f32(block.d); @@ -634,98 +532,7 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { #enddecl(Q6_K) -#decl(IQ23_TABLES) -const kmask_iq2xs : array = array( - 0x08040201u, // 1, 2, 4, 8 - 0x80402010u // 16, 32, 64, 128 -); - -const ksigns_iq2xs: array = array( - 0x03828100,0x87060584,0x8b0a0988,0x0f8e8d0c, - 0x93121190,0x17969514,0x1b9a9918,0x9f1e1d9c, - 0xa32221a0,0x27a6a524,0x2baaa928,0xaf2e2dac, - 0x33b2b130,0xb73635b4,0xbb3a39b8,0x3fbebd3c, - 0xc34241c0,0x47c6c544,0x4bcac948,0xcf4e4dcc, - 0x53d2d150,0xd75655d4,0xdb5a59d8,0x5fdedd5c, - 0x63e2e160,0xe76665e4,0xeb6a69e8,0x6feeed6c, - 0xf37271f0,0x77f6f574,0x7bfaf978,0xff7e7dfc -); -#enddecl(IQ23_TABLES) - #decl(IQ2_XXS) - -const iq2xxs_grid = array( - 0x08080808, 0x08080808, 0x0808082b, 0x08080808, 0x08081919, 0x08080808, 0x08082b08, 0x08080808, - 0x08082b2b, 0x08080808, 0x08190819, 0x08080808, 0x08191908, 0x08080808, 0x082b0808, 0x08080808, - 0x082b082b, 0x08080808, 0x082b2b08, 0x08080808, 0x082b2b2b, 0x08080808, 0x19080819, 0x08080808, - 0x19081908, 0x08080808, 0x19190808, 0x08080808, 0x19192b08, 0x08080808, 0x192b0819, 0x08080808, - 0x192b1908, 0x08080808, 0x2b080808, 0x08080808, 0x2b08082b, 0x08080808, 0x2b082b2b, 0x08080808, - 0x2b2b082b, 0x08080808, 0x08080819, 0x08080819, 0x08081908, 0x08080819, 0x08190808, 0x08080819, - 0x08191919, 0x08080819, 0x19080808, 0x08080819, 0x2b081908, 0x08080819, 0x2b192b08, 0x08080819, - 0x08080808, 0x0808082b, 0x0808082b, 0x0808082b, 0x082b082b, 0x0808082b, 0x2b08082b, 0x0808082b, - 0x08080819, 0x08081908, 0x08081908, 0x08081908, 0x08190808, 0x08081908, 0x082b0819, 0x08081908, - 0x082b1908, 0x08081908, 0x19080808, 0x08081908, 0x1908082b, 0x08081908, 0x19082b08, 0x08081908, - 0x192b0808, 0x08081908, 0x2b080819, 0x08081908, 0x2b081908, 0x08081908, 0x2b190808, 0x08081908, - 0x2b2b1908, 0x08081908, 0x08080808, 0x08081919, 0x0808082b, 0x08081919, 0x08082b08, 0x08081919, - 0x082b0808, 0x08081919, 0x1908192b, 0x08081919, 0x192b2b19, 0x08081919, 0x2b080808, 0x08081919, - 0x2b190819, 0x08081919, 0x08082b19, 0x0808192b, 0x08190808, 0x0808192b, 0x19080808, 0x0808192b, - 0x2b081908, 0x0808192b, 0x2b2b1908, 0x0808192b, 0x08080808, 0x08082b08, 0x08081919, 0x08082b08, - 0x08082b08, 0x08082b08, 0x08191908, 0x08082b08, 0x082b2b08, 0x08082b08, 0x19080819, 0x08082b08, - 0x19081908, 0x08082b08, 0x19190808, 0x08082b08, 0x1919082b, 0x08082b08, 0x2b082b08, 0x08082b08, - 0x08081908, 0x08082b19, 0x19080808, 0x08082b19, 0x0808082b, 0x08082b2b, 0x08191908, 0x08082b2b, - 0x08080819, 0x08190808, 0x08081908, 0x08190808, 0x08190808, 0x08190808, 0x082b0819, 0x08190808, - 0x19080808, 0x08190808, 0x192b0808, 0x08190808, 0x2b081908, 0x08190808, 0x2b190808, 0x08190808, - 0x2b191919, 0x08190808, 0x08080808, 0x08190819, 0x08082b08, 0x08190819, 0x082b0808, 0x08190819, - 0x19190808, 0x08190819, 0x19192b2b, 0x08190819, 0x2b080808, 0x08190819, 0x082b1908, 0x0819082b, - 0x19081919, 0x0819082b, 0x08080808, 0x08191908, 0x08082b08, 0x08191908, 0x082b0808, 0x08191908, - 0x082b1919, 0x08191908, 0x19082b19, 0x08191908, 0x2b080808, 0x08191908, 0x08192b08, 0x08191919, - 0x192b082b, 0x08191919, 0x08080808, 0x0819192b, 0x0819192b, 0x0819192b, 0x08080819, 0x08192b08, - 0x08081908, 0x08192b08, 0x08190808, 0x08192b08, 0x19080808, 0x08192b08, 0x2b080819, 0x08192b08, - 0x08080808, 0x08192b19, 0x08081919, 0x08192b19, 0x2b2b0808, 0x08192b19, 0x19190819, 0x08192b2b, - 0x08080808, 0x082b0808, 0x0808082b, 0x082b0808, 0x08082b2b, 0x082b0808, 0x19081908, 0x082b0808, - 0x192b0819, 0x082b0808, 0x2b080808, 0x082b0808, 0x2b08082b, 0x082b0808, 0x082b2b19, 0x082b0819, - 0x19082b08, 0x082b0819, 0x08080808, 0x082b082b, 0x0808082b, 0x082b082b, 0x08080819, 0x082b1908, - 0x08081908, 0x082b1908, 0x08190808, 0x082b1908, 0x19080808, 0x082b1908, 0x1919192b, 0x082b1908, - 0x08080808, 0x082b1919, 0x19080819, 0x082b1919, 0x192b1908, 0x082b1919, 0x2b190808, 0x082b192b, - 0x08082b08, 0x082b2b08, 0x082b0808, 0x082b2b08, 0x2b191908, 0x082b2b08, 0x19081908, 0x082b2b2b, - 0x08080819, 0x19080808, 0x08081908, 0x19080808, 0x08190808, 0x19080808, 0x08192b08, 0x19080808, - 0x082b0819, 0x19080808, 0x082b1908, 0x19080808, 0x19080808, 0x19080808, 0x19082b08, 0x19080808, - 0x1919192b, 0x19080808, 0x192b0808, 0x19080808, 0x2b080819, 0x19080808, 0x2b081908, 0x19080808, - 0x2b190808, 0x19080808, 0x08080808, 0x19080819, 0x082b0808, 0x19080819, 0x192b0819, 0x19080819, - 0x2b080808, 0x19080819, 0x2b081919, 0x19080819, 0x08080819, 0x1908082b, 0x08190808, 0x1908082b, - 0x19082b08, 0x1908082b, 0x1919192b, 0x1908082b, 0x192b2b08, 0x1908082b, 0x08080808, 0x19081908, - 0x08082b08, 0x19081908, 0x082b0808, 0x19081908, 0x2b080808, 0x19081908, 0x2b192b19, 0x19081908, - 0x0819082b, 0x19081919, 0x082b1908, 0x19081919, 0x08080808, 0x1908192b, 0x08080819, 0x19082b08, - 0x08081908, 0x19082b08, 0x08190808, 0x19082b08, 0x19080808, 0x19082b08, 0x19081919, 0x19082b08, - 0x08080808, 0x19082b19, 0x19192b08, 0x19082b19, 0x192b0819, 0x19082b19, 0x2b08082b, 0x19082b19, - 0x19081919, 0x19082b2b, 0x2b190808, 0x19082b2b, 0x08080808, 0x19190808, 0x08082b08, 0x19190808, - 0x08190819, 0x19190808, 0x08192b19, 0x19190808, 0x082b0808, 0x19190808, 0x2b080808, 0x19190808, - 0x2b082b08, 0x19190808, 0x08081908, 0x19190819, 0x1908082b, 0x19190819, 0x2b2b1908, 0x19190819, - 0x2b190819, 0x1919082b, 0x2b190808, 0x19191908, 0x2b19082b, 0x19191908, 0x08082b2b, 0x19191919, - 0x08080819, 0x1919192b, 0x19191908, 0x1919192b, 0x08080808, 0x19192b08, 0x08190819, 0x19192b08, - 0x08192b19, 0x19192b08, 0x192b1908, 0x19192b08, 0x19080808, 0x19192b19, 0x08082b08, 0x19192b2b, - 0x08081908, 0x192b0808, 0x08190808, 0x192b0808, 0x19080808, 0x192b0808, 0x192b2b08, 0x192b0808, - 0x08080808, 0x192b0819, 0x19191919, 0x192b0819, 0x08192b08, 0x192b082b, 0x192b0808, 0x192b082b, - 0x08080808, 0x192b1908, 0x08081919, 0x192b1908, 0x08190808, 0x192b1919, 0x0819082b, 0x192b1919, - 0x2b081908, 0x192b1919, 0x1908082b, 0x192b2b08, 0x08080808, 0x2b080808, 0x0808082b, 0x2b080808, - 0x08082b2b, 0x2b080808, 0x19080819, 0x2b080808, 0x2b08082b, 0x2b080808, 0x08081908, 0x2b080819, - 0x08192b08, 0x2b080819, 0x19080808, 0x2b080819, 0x08190819, 0x2b08082b, 0x08080819, 0x2b081908, - 0x08081908, 0x2b081908, 0x08190808, 0x2b081908, 0x08191919, 0x2b081908, 0x19080808, 0x2b081908, - 0x192b0808, 0x2b081908, 0x08080808, 0x2b081919, 0x1908192b, 0x2b081919, 0x2b191908, 0x2b081919, - 0x08082b19, 0x2b08192b, 0x19080808, 0x2b08192b, 0x192b0808, 0x2b08192b, 0x0808082b, 0x2b082b08, - 0x08081908, 0x2b082b19, 0x08190819, 0x2b082b2b, 0x08081908, 0x2b190808, 0x08190808, 0x2b190808, - 0x082b1908, 0x2b190808, 0x19080808, 0x2b190808, 0x2b2b0819, 0x2b190808, 0x0819192b, 0x2b190819, - 0x2b080808, 0x2b190819, 0x19081919, 0x2b19082b, 0x08080808, 0x2b191908, 0x082b082b, 0x2b191908, - 0x19081908, 0x2b191908, 0x19190819, 0x2b191919, 0x2b080819, 0x2b192b08, 0x082b0808, 0x2b192b19, - 0x0808082b, 0x2b2b0808, 0x19190808, 0x2b2b0808, 0x2b081919, 0x2b2b0808, 0x08082b19, 0x2b2b0819, - 0x08080808, 0x2b2b082b, 0x08192b08, 0x2b2b1908, 0x19190808, 0x2b2b2b08, 0x08081908, 0x2b2b2b19 -); - -struct iq2_xxs { - d: f16, - qs: array -}; - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block = src0[src0_idx_base + offset]; let d = f32(block.d); @@ -753,143 +560,6 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { #enddecl(IQ2_XXS) #decl(IQ2_XS) -const iq2xs_grid = array( - 0x08080808, 0x08080808, 0x0808082b, 0x08080808, 0x08081919, 0x08080808, 0x08082b08, 0x08080808, - 0x08082b2b, 0x08080808, 0x08190819, 0x08080808, 0x08191908, 0x08080808, 0x0819192b, 0x08080808, - 0x08192b19, 0x08080808, 0x082b0808, 0x08080808, 0x082b082b, 0x08080808, 0x082b1919, 0x08080808, - 0x082b2b08, 0x08080808, 0x19080819, 0x08080808, 0x19081908, 0x08080808, 0x1908192b, 0x08080808, - 0x19082b19, 0x08080808, 0x19190808, 0x08080808, 0x1919082b, 0x08080808, 0x19191919, 0x08080808, - 0x19192b08, 0x08080808, 0x192b0819, 0x08080808, 0x192b1908, 0x08080808, 0x2b080808, 0x08080808, - 0x2b08082b, 0x08080808, 0x2b081919, 0x08080808, 0x2b082b08, 0x08080808, 0x2b190819, 0x08080808, - 0x2b191908, 0x08080808, 0x2b192b19, 0x08080808, 0x2b2b0808, 0x08080808, 0x08080819, 0x08080819, - 0x08081908, 0x08080819, 0x0808192b, 0x08080819, 0x08082b19, 0x08080819, 0x08190808, 0x08080819, - 0x0819082b, 0x08080819, 0x08191919, 0x08080819, 0x08192b08, 0x08080819, 0x08192b2b, 0x08080819, - 0x082b0819, 0x08080819, 0x082b1908, 0x08080819, 0x19080808, 0x08080819, 0x1908082b, 0x08080819, - 0x19081919, 0x08080819, 0x19082b08, 0x08080819, 0x19190819, 0x08080819, 0x19191908, 0x08080819, - 0x192b0808, 0x08080819, 0x192b2b08, 0x08080819, 0x2b080819, 0x08080819, 0x2b081908, 0x08080819, - 0x2b190808, 0x08080819, 0x08080808, 0x0808082b, 0x0808082b, 0x0808082b, 0x08081919, 0x0808082b, - 0x08082b08, 0x0808082b, 0x08190819, 0x0808082b, 0x08191908, 0x0808082b, 0x082b0808, 0x0808082b, - 0x19080819, 0x0808082b, 0x19081908, 0x0808082b, 0x19190808, 0x0808082b, 0x19191919, 0x0808082b, - 0x2b080808, 0x0808082b, 0x2b082b2b, 0x0808082b, 0x08080819, 0x08081908, 0x08081908, 0x08081908, - 0x0808192b, 0x08081908, 0x08082b19, 0x08081908, 0x08190808, 0x08081908, 0x0819082b, 0x08081908, - 0x08191919, 0x08081908, 0x08192b08, 0x08081908, 0x082b0819, 0x08081908, 0x082b1908, 0x08081908, - 0x19080808, 0x08081908, 0x1908082b, 0x08081908, 0x19081919, 0x08081908, 0x19082b08, 0x08081908, - 0x19190819, 0x08081908, 0x19191908, 0x08081908, 0x1919192b, 0x08081908, 0x192b0808, 0x08081908, - 0x2b080819, 0x08081908, 0x2b081908, 0x08081908, 0x2b190808, 0x08081908, 0x08080808, 0x08081919, - 0x0808082b, 0x08081919, 0x08081919, 0x08081919, 0x08082b08, 0x08081919, 0x08190819, 0x08081919, - 0x08191908, 0x08081919, 0x082b0808, 0x08081919, 0x19080819, 0x08081919, 0x19081908, 0x08081919, - 0x19190808, 0x08081919, 0x192b0819, 0x08081919, 0x2b080808, 0x08081919, 0x08080819, 0x0808192b, - 0x08081908, 0x0808192b, 0x08190808, 0x0808192b, 0x082b192b, 0x0808192b, 0x19080808, 0x0808192b, - 0x1908082b, 0x0808192b, 0x2b081908, 0x0808192b, 0x08080808, 0x08082b08, 0x0808082b, 0x08082b08, - 0x08081919, 0x08082b08, 0x08082b08, 0x08082b08, 0x08082b2b, 0x08082b08, 0x08190819, 0x08082b08, - 0x08191908, 0x08082b08, 0x082b0808, 0x08082b08, 0x082b1919, 0x08082b08, 0x19080819, 0x08082b08, - 0x19081908, 0x08082b08, 0x19190808, 0x08082b08, 0x19192b08, 0x08082b08, 0x2b080808, 0x08082b08, - 0x2b2b0808, 0x08082b08, 0x2b2b2b2b, 0x08082b08, 0x08080819, 0x08082b19, 0x08081908, 0x08082b19, - 0x08190808, 0x08082b19, 0x19080808, 0x08082b19, 0x2b080819, 0x08082b19, 0x2b082b19, 0x08082b19, - 0x08080808, 0x08082b2b, 0x082b0808, 0x08082b2b, 0x082b2b08, 0x08082b2b, 0x2b19192b, 0x08082b2b, - 0x2b2b0808, 0x08082b2b, 0x08080819, 0x08190808, 0x08081908, 0x08190808, 0x0808192b, 0x08190808, - 0x08082b19, 0x08190808, 0x08190808, 0x08190808, 0x0819082b, 0x08190808, 0x08191919, 0x08190808, - 0x08192b08, 0x08190808, 0x082b0819, 0x08190808, 0x082b1908, 0x08190808, 0x19080808, 0x08190808, - 0x1908082b, 0x08190808, 0x19081919, 0x08190808, 0x19082b08, 0x08190808, 0x19190819, 0x08190808, - 0x19191908, 0x08190808, 0x192b0808, 0x08190808, 0x192b2b2b, 0x08190808, 0x2b080819, 0x08190808, - 0x2b081908, 0x08190808, 0x2b190808, 0x08190808, 0x08080808, 0x08190819, 0x0808082b, 0x08190819, - 0x08081919, 0x08190819, 0x08082b08, 0x08190819, 0x08190819, 0x08190819, 0x08191908, 0x08190819, - 0x082b0808, 0x08190819, 0x19080819, 0x08190819, 0x19081908, 0x08190819, 0x19190808, 0x08190819, - 0x2b080808, 0x08190819, 0x2b191908, 0x08190819, 0x2b19192b, 0x08190819, 0x08080819, 0x0819082b, - 0x08081908, 0x0819082b, 0x0808192b, 0x0819082b, 0x08190808, 0x0819082b, 0x19080808, 0x0819082b, - 0x192b0808, 0x0819082b, 0x08080808, 0x08191908, 0x0808082b, 0x08191908, 0x08081919, 0x08191908, - 0x08082b08, 0x08191908, 0x08190819, 0x08191908, 0x08191908, 0x08191908, 0x082b0808, 0x08191908, - 0x19080819, 0x08191908, 0x19081908, 0x08191908, 0x19082b19, 0x08191908, 0x19190808, 0x08191908, - 0x192b1908, 0x08191908, 0x2b080808, 0x08191908, 0x08080819, 0x08191919, 0x08081908, 0x08191919, - 0x08190808, 0x08191919, 0x19080808, 0x08191919, 0x08080808, 0x0819192b, 0x08191908, 0x0819192b, - 0x19082b19, 0x0819192b, 0x08080819, 0x08192b08, 0x08081908, 0x08192b08, 0x08190808, 0x08192b08, - 0x0819082b, 0x08192b08, 0x19080808, 0x08192b08, 0x19191908, 0x08192b08, 0x2b08192b, 0x08192b08, - 0x08080808, 0x08192b19, 0x08081919, 0x08192b19, 0x192b192b, 0x08192b19, 0x19190819, 0x08192b2b, - 0x2b2b2b19, 0x08192b2b, 0x08080808, 0x082b0808, 0x0808082b, 0x082b0808, 0x08081919, 0x082b0808, - 0x08082b08, 0x082b0808, 0x08082b2b, 0x082b0808, 0x08190819, 0x082b0808, 0x08191908, 0x082b0808, - 0x082b0808, 0x082b0808, 0x19080819, 0x082b0808, 0x19081908, 0x082b0808, 0x19190808, 0x082b0808, - 0x2b080808, 0x082b0808, 0x2b2b0808, 0x082b0808, 0x08080819, 0x082b0819, 0x08081908, 0x082b0819, - 0x08190808, 0x082b0819, 0x19080808, 0x082b0819, 0x19082b08, 0x082b0819, 0x192b1919, 0x082b0819, - 0x08080808, 0x082b082b, 0x082b082b, 0x082b082b, 0x2b080808, 0x082b082b, 0x2b2b2b08, 0x082b082b, - 0x08080819, 0x082b1908, 0x08081908, 0x082b1908, 0x08190808, 0x082b1908, 0x082b2b19, 0x082b1908, - 0x19080808, 0x082b1908, 0x08080808, 0x082b1919, 0x19080819, 0x082b1919, 0x1919082b, 0x082b1919, - 0x2b192b19, 0x082b1919, 0x08080819, 0x082b192b, 0x08192b2b, 0x082b192b, 0x2b2b192b, 0x082b192b, - 0x08080808, 0x082b2b08, 0x08082b08, 0x082b2b08, 0x08082b2b, 0x082b2b08, 0x082b0808, 0x082b2b08, - 0x19191919, 0x082b2b08, 0x2b082b08, 0x082b2b08, 0x2b2b082b, 0x082b2b08, 0x192b2b08, 0x082b2b19, - 0x2b190808, 0x082b2b19, 0x08082b08, 0x082b2b2b, 0x082b0808, 0x082b2b2b, 0x2b08082b, 0x082b2b2b, - 0x2b082b08, 0x082b2b2b, 0x2b082b2b, 0x082b2b2b, 0x08080819, 0x19080808, 0x08081908, 0x19080808, - 0x0808192b, 0x19080808, 0x08082b19, 0x19080808, 0x08190808, 0x19080808, 0x0819082b, 0x19080808, - 0x08191919, 0x19080808, 0x08192b08, 0x19080808, 0x082b0819, 0x19080808, 0x082b1908, 0x19080808, - 0x19080808, 0x19080808, 0x1908082b, 0x19080808, 0x19081919, 0x19080808, 0x19082b08, 0x19080808, - 0x19082b2b, 0x19080808, 0x19190819, 0x19080808, 0x19191908, 0x19080808, 0x192b0808, 0x19080808, - 0x192b1919, 0x19080808, 0x2b080819, 0x19080808, 0x2b081908, 0x19080808, 0x2b190808, 0x19080808, - 0x08080808, 0x19080819, 0x0808082b, 0x19080819, 0x08081919, 0x19080819, 0x08082b08, 0x19080819, - 0x08190819, 0x19080819, 0x08191908, 0x19080819, 0x082b0808, 0x19080819, 0x19080819, 0x19080819, - 0x19081908, 0x19080819, 0x19190808, 0x19080819, 0x2b080808, 0x19080819, 0x2b081919, 0x19080819, - 0x2b2b082b, 0x19080819, 0x08080819, 0x1908082b, 0x08081908, 0x1908082b, 0x08190808, 0x1908082b, - 0x0819082b, 0x1908082b, 0x082b2b19, 0x1908082b, 0x19080808, 0x1908082b, 0x08080808, 0x19081908, - 0x0808082b, 0x19081908, 0x08081919, 0x19081908, 0x08082b08, 0x19081908, 0x08190819, 0x19081908, - 0x08191908, 0x19081908, 0x08192b19, 0x19081908, 0x082b0808, 0x19081908, 0x19080819, 0x19081908, - 0x19081908, 0x19081908, 0x19190808, 0x19081908, 0x2b080808, 0x19081908, 0x2b191908, 0x19081908, - 0x08080819, 0x19081919, 0x08081908, 0x19081919, 0x08190808, 0x19081919, 0x082b1908, 0x19081919, - 0x19080808, 0x19081919, 0x2b192b2b, 0x19081919, 0x08080808, 0x1908192b, 0x08082b2b, 0x1908192b, - 0x19081908, 0x1908192b, 0x19190808, 0x1908192b, 0x08080819, 0x19082b08, 0x08081908, 0x19082b08, - 0x08190808, 0x19082b08, 0x19080808, 0x19082b08, 0x19081919, 0x19082b08, 0x19191908, 0x19082b08, - 0x192b082b, 0x19082b08, 0x08080808, 0x19082b19, 0x08190819, 0x19082b19, 0x19081908, 0x19082b19, - 0x19190808, 0x19082b19, 0x192b2b19, 0x19082b19, 0x08081908, 0x19082b2b, 0x08080808, 0x19190808, - 0x0808082b, 0x19190808, 0x08081919, 0x19190808, 0x08082b08, 0x19190808, 0x08190819, 0x19190808, - 0x08191908, 0x19190808, 0x082b0808, 0x19190808, 0x082b2b08, 0x19190808, 0x19080819, 0x19190808, - 0x19081908, 0x19190808, 0x19190808, 0x19190808, 0x2b080808, 0x19190808, 0x08080819, 0x19190819, - 0x08081908, 0x19190819, 0x08190808, 0x19190819, 0x08191919, 0x19190819, 0x19080808, 0x19190819, - 0x1908082b, 0x19190819, 0x08080808, 0x1919082b, 0x19081908, 0x1919082b, 0x2b2b2b2b, 0x1919082b, - 0x08080819, 0x19191908, 0x08081908, 0x19191908, 0x08190808, 0x19191908, 0x082b0819, 0x19191908, - 0x19080808, 0x19191908, 0x192b0808, 0x19191908, 0x2b080819, 0x19191908, 0x2b2b0819, 0x19191908, - 0x08080808, 0x19191919, 0x08082b08, 0x19191919, 0x2b080808, 0x19191919, 0x2b082b08, 0x19191919, - 0x082b0819, 0x1919192b, 0x192b2b08, 0x1919192b, 0x2b2b0819, 0x1919192b, 0x08080808, 0x19192b08, - 0x08191908, 0x19192b08, 0x19080819, 0x19192b08, 0x19190808, 0x19192b08, 0x2b192b19, 0x19192b08, - 0x08192b2b, 0x19192b19, 0x19080808, 0x19192b19, 0x1908082b, 0x19192b19, 0x2b081919, 0x19192b2b, - 0x08080819, 0x192b0808, 0x08081908, 0x192b0808, 0x08190808, 0x192b0808, 0x19080808, 0x192b0808, - 0x19191908, 0x192b0808, 0x192b082b, 0x192b0808, 0x2b08192b, 0x192b0808, 0x2b2b2b19, 0x192b0808, - 0x08080808, 0x192b0819, 0x082b1908, 0x192b082b, 0x19082b2b, 0x192b082b, 0x2b19082b, 0x192b082b, - 0x08080808, 0x192b1908, 0x0819192b, 0x192b1908, 0x08190808, 0x192b1919, 0x19080808, 0x192b1919, - 0x19081919, 0x192b1919, 0x2b2b1908, 0x192b1919, 0x08080819, 0x192b2b08, 0x192b2b2b, 0x192b2b08, - 0x082b1919, 0x192b2b19, 0x0808192b, 0x192b2b2b, 0x19191908, 0x192b2b2b, 0x192b082b, 0x192b2b2b, - 0x08080808, 0x2b080808, 0x0808082b, 0x2b080808, 0x08081919, 0x2b080808, 0x08082b08, 0x2b080808, - 0x08190819, 0x2b080808, 0x08191908, 0x2b080808, 0x082b0808, 0x2b080808, 0x082b2b2b, 0x2b080808, - 0x19080819, 0x2b080808, 0x19081908, 0x2b080808, 0x19190808, 0x2b080808, 0x2b080808, 0x2b080808, - 0x2b08082b, 0x2b080808, 0x2b2b2b08, 0x2b080808, 0x2b2b2b2b, 0x2b080808, 0x08080819, 0x2b080819, - 0x08081908, 0x2b080819, 0x0808192b, 0x2b080819, 0x08190808, 0x2b080819, 0x19080808, 0x2b080819, - 0x19190819, 0x2b080819, 0x19192b19, 0x2b080819, 0x08080808, 0x2b08082b, 0x082b0808, 0x2b08082b, - 0x2b080808, 0x2b08082b, 0x2b08082b, 0x2b08082b, 0x2b2b0808, 0x2b08082b, 0x2b2b2b08, 0x2b08082b, - 0x08080819, 0x2b081908, 0x08081908, 0x2b081908, 0x08190808, 0x2b081908, 0x0819082b, 0x2b081908, - 0x08191919, 0x2b081908, 0x19080808, 0x2b081908, 0x192b0808, 0x2b081908, 0x2b082b19, 0x2b081908, - 0x08080808, 0x2b081919, 0x19081908, 0x2b081919, 0x2b2b1919, 0x2b081919, 0x08192b08, 0x2b08192b, - 0x192b2b2b, 0x2b08192b, 0x08080808, 0x2b082b08, 0x08082b08, 0x2b082b08, 0x082b1919, 0x2b082b08, - 0x19192b2b, 0x2b082b08, 0x2b080808, 0x2b082b08, 0x2b08082b, 0x2b082b08, 0x2b2b2b08, 0x2b082b08, - 0x0808192b, 0x2b082b19, 0x082b082b, 0x2b082b2b, 0x2b080808, 0x2b082b2b, 0x2b082b08, 0x2b082b2b, - 0x2b19192b, 0x2b082b2b, 0x2b2b2b08, 0x2b082b2b, 0x08080819, 0x2b190808, 0x08081908, 0x2b190808, - 0x08190808, 0x2b190808, 0x19080808, 0x2b190808, 0x1919192b, 0x2b190808, 0x2b081908, 0x2b190808, - 0x08080808, 0x2b190819, 0x082b082b, 0x2b190819, 0x192b1908, 0x2b190819, 0x1919192b, 0x2b19082b, - 0x2b082b19, 0x2b19082b, 0x08080808, 0x2b191908, 0x08081919, 0x2b191908, 0x19081908, 0x2b191908, - 0x19190808, 0x2b191908, 0x19192b08, 0x2b191908, 0x082b2b19, 0x2b191919, 0x2b190808, 0x2b191919, - 0x2b19082b, 0x2b191919, 0x19080819, 0x2b19192b, 0x19190819, 0x2b192b08, 0x2b2b192b, 0x2b192b08, - 0x19082b19, 0x2b192b19, 0x08191919, 0x2b192b2b, 0x192b0808, 0x2b192b2b, 0x08080808, 0x2b2b0808, - 0x0808082b, 0x2b2b0808, 0x08082b08, 0x2b2b0808, 0x08082b2b, 0x2b2b0808, 0x082b0808, 0x2b2b0808, - 0x082b2b2b, 0x2b2b0808, 0x2b2b0808, 0x2b2b0808, 0x19190819, 0x2b2b0819, 0x19192b19, 0x2b2b0819, - 0x2b2b192b, 0x2b2b0819, 0x08080808, 0x2b2b082b, 0x0808082b, 0x2b2b082b, 0x08082b08, 0x2b2b082b, - 0x082b2b2b, 0x2b2b082b, 0x2b080808, 0x2b2b082b, 0x2b2b0808, 0x2b2b082b, 0x19080808, 0x2b2b1908, - 0x2b191919, 0x2b2b1908, 0x192b1919, 0x2b2b192b, 0x2b192b08, 0x2b2b192b, 0x08082b2b, 0x2b2b2b08, - 0x082b0808, 0x2b2b2b08, 0x082b082b, 0x2b2b2b08, 0x082b2b08, 0x2b2b2b08, 0x2b2b0808, 0x2b2b2b08, - 0x2b2b2b08, 0x2b2b2b08, 0x08081908, 0x2b2b2b19, 0x2b081908, 0x2b2b2b19, 0x2b08192b, 0x2b2b2b19, - 0x082b2b08, 0x2b2b2b2b, 0x082b2b2b, 0x2b2b2b2b, 0x2b190819, 0x2b2b2b2b, 0x2b2b2b2b, 0x2b2b2b2b -); - -struct iq2_xs { - d: f16, - qs: array, - scales: array -}; - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block = src0[src0_idx_base + offset]; let d = f32(block.d); @@ -925,273 +595,6 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { #enddecl(IQ2_XS) #decl(IQ2_S) - -const iq2s_grid = array( - 0x08080808, 0x08080808, 0x0808082b, 0x08080808, 0x08081919, 0x08080808, 0x08082b08, 0x08080808, - 0x08082b2b, 0x08080808, 0x08190819, 0x08080808, 0x08191908, 0x08080808, 0x0819192b, 0x08080808, - 0x08192b19, 0x08080808, 0x082b0808, 0x08080808, 0x082b082b, 0x08080808, 0x082b1919, 0x08080808, - 0x082b2b08, 0x08080808, 0x19080819, 0x08080808, 0x19081908, 0x08080808, 0x1908192b, 0x08080808, - 0x19082b19, 0x08080808, 0x19190808, 0x08080808, 0x1919082b, 0x08080808, 0x19191919, 0x08080808, - 0x19192b08, 0x08080808, 0x192b0819, 0x08080808, 0x192b1908, 0x08080808, 0x192b192b, 0x08080808, - 0x192b2b19, 0x08080808, 0x2b080808, 0x08080808, 0x2b08082b, 0x08080808, 0x2b081919, 0x08080808, - 0x2b082b08, 0x08080808, 0x2b190819, 0x08080808, 0x2b191908, 0x08080808, 0x2b2b0808, 0x08080808, - 0x2b2b1919, 0x08080808, 0x2b2b2b2b, 0x08080808, 0x08080819, 0x08080819, 0x08081908, 0x08080819, - 0x0808192b, 0x08080819, 0x08082b19, 0x08080819, 0x08190808, 0x08080819, 0x0819082b, 0x08080819, - 0x08191919, 0x08080819, 0x08192b08, 0x08080819, 0x082b0819, 0x08080819, 0x082b1908, 0x08080819, - 0x19080808, 0x08080819, 0x1908082b, 0x08080819, 0x19081919, 0x08080819, 0x19082b08, 0x08080819, - 0x19190819, 0x08080819, 0x19191908, 0x08080819, 0x1919192b, 0x08080819, 0x19192b19, 0x08080819, - 0x192b0808, 0x08080819, 0x192b1919, 0x08080819, 0x192b2b08, 0x08080819, 0x2b080819, 0x08080819, - 0x2b081908, 0x08080819, 0x2b190808, 0x08080819, 0x2b19082b, 0x08080819, 0x2b191919, 0x08080819, - 0x2b2b0819, 0x08080819, 0x2b2b1908, 0x08080819, 0x08080808, 0x0808082b, 0x0808082b, 0x0808082b, - 0x08081919, 0x0808082b, 0x08082b08, 0x0808082b, 0x08190819, 0x0808082b, 0x08191908, 0x0808082b, - 0x082b0808, 0x0808082b, 0x082b2b2b, 0x0808082b, 0x19080819, 0x0808082b, 0x19081908, 0x0808082b, - 0x1908192b, 0x0808082b, 0x19082b19, 0x0808082b, 0x19190808, 0x0808082b, 0x19191919, 0x0808082b, - 0x2b080808, 0x0808082b, 0x2b081919, 0x0808082b, 0x2b082b2b, 0x0808082b, 0x2b191908, 0x0808082b, - 0x2b2b082b, 0x0808082b, 0x08080819, 0x08081908, 0x08081908, 0x08081908, 0x0808192b, 0x08081908, - 0x08082b19, 0x08081908, 0x08190808, 0x08081908, 0x0819082b, 0x08081908, 0x08191919, 0x08081908, - 0x08192b08, 0x08081908, 0x082b0819, 0x08081908, 0x082b1908, 0x08081908, 0x082b192b, 0x08081908, - 0x082b2b19, 0x08081908, 0x19080808, 0x08081908, 0x1908082b, 0x08081908, 0x19081919, 0x08081908, - 0x19082b08, 0x08081908, 0x19082b2b, 0x08081908, 0x19190819, 0x08081908, 0x19191908, 0x08081908, - 0x1919192b, 0x08081908, 0x19192b19, 0x08081908, 0x192b0808, 0x08081908, 0x192b082b, 0x08081908, - 0x192b1919, 0x08081908, 0x2b080819, 0x08081908, 0x2b081908, 0x08081908, 0x2b08192b, 0x08081908, - 0x2b082b19, 0x08081908, 0x2b190808, 0x08081908, 0x2b191919, 0x08081908, 0x2b192b08, 0x08081908, - 0x2b2b0819, 0x08081908, 0x2b2b1908, 0x08081908, 0x08080808, 0x08081919, 0x0808082b, 0x08081919, - 0x08081919, 0x08081919, 0x08082b08, 0x08081919, 0x08082b2b, 0x08081919, 0x08190819, 0x08081919, - 0x08191908, 0x08081919, 0x0819192b, 0x08081919, 0x08192b19, 0x08081919, 0x082b0808, 0x08081919, - 0x082b1919, 0x08081919, 0x082b2b08, 0x08081919, 0x19080819, 0x08081919, 0x19081908, 0x08081919, - 0x1908192b, 0x08081919, 0x19082b19, 0x08081919, 0x19190808, 0x08081919, 0x1919082b, 0x08081919, - 0x19191919, 0x08081919, 0x19192b08, 0x08081919, 0x192b0819, 0x08081919, 0x192b1908, 0x08081919, - 0x2b080808, 0x08081919, 0x2b08082b, 0x08081919, 0x2b081919, 0x08081919, 0x2b082b08, 0x08081919, - 0x2b190819, 0x08081919, 0x2b191908, 0x08081919, 0x2b2b0808, 0x08081919, 0x08080819, 0x0808192b, - 0x08081908, 0x0808192b, 0x0808192b, 0x0808192b, 0x08082b19, 0x0808192b, 0x08190808, 0x0808192b, - 0x08191919, 0x0808192b, 0x19080808, 0x0808192b, 0x19081919, 0x0808192b, 0x19082b08, 0x0808192b, - 0x19190819, 0x0808192b, 0x19191908, 0x0808192b, 0x192b0808, 0x0808192b, 0x2b080819, 0x0808192b, - 0x2b081908, 0x0808192b, 0x2b190808, 0x0808192b, 0x08080808, 0x08082b08, 0x0808082b, 0x08082b08, - 0x08081919, 0x08082b08, 0x08082b08, 0x08082b08, 0x08190819, 0x08082b08, 0x08191908, 0x08082b08, - 0x0819192b, 0x08082b08, 0x08192b19, 0x08082b08, 0x082b0808, 0x08082b08, 0x082b1919, 0x08082b08, - 0x082b2b2b, 0x08082b08, 0x19080819, 0x08082b08, 0x19081908, 0x08082b08, 0x1908192b, 0x08082b08, - 0x19082b19, 0x08082b08, 0x19190808, 0x08082b08, 0x1919082b, 0x08082b08, 0x19191919, 0x08082b08, - 0x19192b08, 0x08082b08, 0x192b0819, 0x08082b08, 0x192b1908, 0x08082b08, 0x2b080808, 0x08082b08, - 0x2b081919, 0x08082b08, 0x2b191908, 0x08082b08, 0x2b2b2b2b, 0x08082b08, 0x08080819, 0x08082b19, - 0x08081908, 0x08082b19, 0x08190808, 0x08082b19, 0x0819082b, 0x08082b19, 0x08191919, 0x08082b19, - 0x08192b08, 0x08082b19, 0x082b0819, 0x08082b19, 0x19080808, 0x08082b19, 0x19081919, 0x08082b19, - 0x19082b08, 0x08082b19, 0x19190819, 0x08082b19, 0x19191908, 0x08082b19, 0x192b0808, 0x08082b19, - 0x2b080819, 0x08082b19, 0x2b190808, 0x08082b19, 0x08080808, 0x08082b2b, 0x08190819, 0x08082b2b, - 0x08191908, 0x08082b2b, 0x082b082b, 0x08082b2b, 0x082b2b08, 0x08082b2b, 0x082b2b2b, 0x08082b2b, - 0x19190808, 0x08082b2b, 0x2b192b19, 0x08082b2b, 0x08080819, 0x08190808, 0x08081908, 0x08190808, - 0x0808192b, 0x08190808, 0x08082b19, 0x08190808, 0x08190808, 0x08190808, 0x0819082b, 0x08190808, - 0x08191919, 0x08190808, 0x08192b08, 0x08190808, 0x082b0819, 0x08190808, 0x082b1908, 0x08190808, - 0x082b192b, 0x08190808, 0x19080808, 0x08190808, 0x1908082b, 0x08190808, 0x19081919, 0x08190808, - 0x19082b08, 0x08190808, 0x19190819, 0x08190808, 0x19191908, 0x08190808, 0x1919192b, 0x08190808, - 0x19192b19, 0x08190808, 0x192b0808, 0x08190808, 0x192b082b, 0x08190808, 0x192b1919, 0x08190808, - 0x192b2b08, 0x08190808, 0x2b080819, 0x08190808, 0x2b081908, 0x08190808, 0x2b08192b, 0x08190808, - 0x2b190808, 0x08190808, 0x2b191919, 0x08190808, 0x2b192b08, 0x08190808, 0x2b2b0819, 0x08190808, - 0x2b2b1908, 0x08190808, 0x08080808, 0x08190819, 0x0808082b, 0x08190819, 0x08081919, 0x08190819, - 0x08082b08, 0x08190819, 0x08082b2b, 0x08190819, 0x08190819, 0x08190819, 0x08191908, 0x08190819, - 0x0819192b, 0x08190819, 0x08192b19, 0x08190819, 0x082b0808, 0x08190819, 0x082b082b, 0x08190819, - 0x082b1919, 0x08190819, 0x082b2b08, 0x08190819, 0x19080819, 0x08190819, 0x19081908, 0x08190819, - 0x1908192b, 0x08190819, 0x19082b19, 0x08190819, 0x19190808, 0x08190819, 0x1919082b, 0x08190819, - 0x19191919, 0x08190819, 0x19192b08, 0x08190819, 0x192b0819, 0x08190819, 0x192b1908, 0x08190819, - 0x2b080808, 0x08190819, 0x2b08082b, 0x08190819, 0x2b081919, 0x08190819, 0x2b082b08, 0x08190819, - 0x2b190819, 0x08190819, 0x2b191908, 0x08190819, 0x08080819, 0x0819082b, 0x08081908, 0x0819082b, - 0x08082b19, 0x0819082b, 0x08190808, 0x0819082b, 0x08191919, 0x0819082b, 0x082b0819, 0x0819082b, - 0x082b1908, 0x0819082b, 0x19080808, 0x0819082b, 0x19081919, 0x0819082b, 0x19190819, 0x0819082b, - 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0x08191919, 0x192b0808, 0x08192b08, 0x192b0808, - 0x082b0819, 0x192b0808, 0x082b1908, 0x192b0808, 0x19080808, 0x192b0808, 0x19081919, 0x192b0808, - 0x19082b08, 0x192b0808, 0x19190819, 0x192b0808, 0x19191908, 0x192b0808, 0x192b0808, 0x192b0808, - 0x2b081908, 0x192b0808, 0x2b190808, 0x192b0808, 0x08080808, 0x192b0819, 0x0808082b, 0x192b0819, - 0x08081919, 0x192b0819, 0x08082b08, 0x192b0819, 0x08190819, 0x192b0819, 0x08191908, 0x192b0819, - 0x082b0808, 0x192b0819, 0x19080819, 0x192b0819, 0x19081908, 0x192b0819, 0x19190808, 0x192b0819, - 0x2b080808, 0x192b0819, 0x2b192b19, 0x192b0819, 0x08081908, 0x192b082b, 0x08190808, 0x192b082b, - 0x19080808, 0x192b082b, 0x1919192b, 0x192b082b, 0x2b2b0819, 0x192b082b, 0x08080808, 0x192b1908, - 0x08081919, 0x192b1908, 0x08082b08, 0x192b1908, 0x08190819, 0x192b1908, 0x08191908, 0x192b1908, - 0x082b0808, 0x192b1908, 0x19080819, 0x192b1908, 0x19081908, 0x192b1908, 0x19190808, 0x192b1908, - 0x2b080808, 0x192b1908, 0x08080819, 0x192b1919, 0x08081908, 0x192b1919, 0x08190808, 0x192b1919, - 0x19080808, 0x192b1919, 0x19082b2b, 0x192b1919, 0x192b2b08, 0x192b1919, 0x2b19082b, 0x192b1919, - 0x08080808, 0x192b192b, 0x2b191908, 0x192b192b, 0x08080819, 0x192b2b08, 0x08081908, 0x192b2b08, - 0x08190808, 0x192b2b08, 0x192b1919, 0x192b2b08, 0x2b192b08, 0x192b2b08, 0x08080808, 0x192b2b19, - 0x082b2b2b, 0x192b2b19, 0x1908082b, 0x192b2b2b, 0x2b2b0819, 0x192b2b2b, 0x08080808, 0x2b080808, - 0x0808082b, 0x2b080808, 0x08081919, 0x2b080808, 0x08082b08, 0x2b080808, 0x08190819, 0x2b080808, - 0x08191908, 0x2b080808, 0x08192b19, 0x2b080808, 0x082b0808, 0x2b080808, 0x082b1919, 0x2b080808, - 0x19080819, 0x2b080808, 0x19081908, 0x2b080808, 0x19190808, 0x2b080808, 0x1919082b, 0x2b080808, - 0x19191919, 0x2b080808, 0x19192b08, 0x2b080808, 0x192b0819, 0x2b080808, 0x2b080808, 0x2b080808, - 0x2b081919, 0x2b080808, 0x2b190819, 0x2b080808, 0x2b191908, 0x2b080808, 0x08080819, 0x2b080819, - 0x08081908, 0x2b080819, 0x08082b19, 0x2b080819, 0x08190808, 0x2b080819, 0x0819082b, 0x2b080819, - 0x08191919, 0x2b080819, 0x08192b08, 0x2b080819, 0x082b0819, 0x2b080819, 0x082b1908, 0x2b080819, - 0x19080808, 0x2b080819, 0x1908082b, 0x2b080819, 0x19081919, 0x2b080819, 0x19082b08, 0x2b080819, - 0x19190819, 0x2b080819, 0x19191908, 0x2b080819, 0x2b080819, 0x2b080819, 0x2b081908, 0x2b080819, - 0x2b190808, 0x2b080819, 0x2b2b2b19, 0x2b080819, 0x08080808, 0x2b08082b, 0x08081919, 0x2b08082b, - 0x08082b2b, 0x2b08082b, 0x08190819, 0x2b08082b, 0x08191908, 0x2b08082b, 0x19080819, 0x2b08082b, - 0x19081908, 0x2b08082b, 0x19190808, 0x2b08082b, 0x08080819, 0x2b081908, 0x08081908, 0x2b081908, - 0x0808192b, 0x2b081908, 0x08082b19, 0x2b081908, 0x08190808, 0x2b081908, 0x0819082b, 0x2b081908, - 0x08191919, 0x2b081908, 0x08192b08, 0x2b081908, 0x082b0819, 0x2b081908, 0x19080808, 0x2b081908, - 0x1908082b, 0x2b081908, 0x19081919, 0x2b081908, 0x19082b08, 0x2b081908, 0x19190819, 0x2b081908, - 0x19191908, 0x2b081908, 0x192b0808, 0x2b081908, 0x2b080819, 0x2b081908, 0x2b081908, 0x2b081908, - 0x2b190808, 0x2b081908, 0x08080808, 0x2b081919, 0x0808082b, 0x2b081919, 0x08081919, 0x2b081919, - 0x08082b08, 0x2b081919, 0x08190819, 0x2b081919, 0x08191908, 0x2b081919, 0x082b0808, 0x2b081919, - 0x19080819, 0x2b081919, 0x19081908, 0x2b081919, 0x19190808, 0x2b081919, 0x2b080808, 0x2b081919, - 0x2b082b2b, 0x2b081919, 0x08080819, 0x2b08192b, 0x08081908, 0x2b08192b, 0x08190808, 0x2b08192b, - 0x082b2b19, 0x2b08192b, 0x19080808, 0x2b08192b, 0x08080808, 0x2b082b08, 0x08081919, 0x2b082b08, - 0x08190819, 0x2b082b08, 0x08191908, 0x2b082b08, 0x19080819, 0x2b082b08, 0x19081908, 0x2b082b08, - 0x19190808, 0x2b082b08, 0x2b2b082b, 0x2b082b08, 0x08080819, 0x2b082b19, 0x08081908, 0x2b082b19, - 0x19080808, 0x2b082b19, 0x192b1919, 0x2b082b19, 0x082b082b, 0x2b082b2b, 0x19192b08, 0x2b082b2b, - 0x19192b2b, 0x2b082b2b, 0x2b08082b, 0x2b082b2b, 0x2b2b082b, 0x2b082b2b, 0x08080819, 0x2b190808, - 0x08081908, 0x2b190808, 0x08082b19, 0x2b190808, 0x08190808, 0x2b190808, 0x0819082b, 0x2b190808, - 0x08191919, 0x2b190808, 0x08192b08, 0x2b190808, 0x082b1908, 0x2b190808, 0x19080808, 0x2b190808, - 0x1908082b, 0x2b190808, 0x19081919, 0x2b190808, 0x19082b08, 0x2b190808, 0x19190819, 0x2b190808, - 0x19191908, 0x2b190808, 0x192b0808, 0x2b190808, 0x2b080819, 0x2b190808, 0x2b081908, 0x2b190808, - 0x2b190808, 0x2b190808, 0x08080808, 0x2b190819, 0x08081919, 0x2b190819, 0x08190819, 0x2b190819, - 0x08191908, 0x2b190819, 0x19080819, 0x2b190819, 0x19081908, 0x2b190819, 0x19190808, 0x2b190819, - 0x19192b2b, 0x2b190819, 0x08080819, 0x2b19082b, 0x08081908, 0x2b19082b, 0x08190808, 0x2b19082b, - 0x19080808, 0x2b19082b, 0x2b2b192b, 0x2b19082b, 0x08080808, 0x2b191908, 0x0808082b, 0x2b191908, - 0x08081919, 0x2b191908, 0x08082b08, 0x2b191908, 0x08190819, 0x2b191908, 0x08191908, 0x2b191908, - 0x082b0808, 0x2b191908, 0x19080819, 0x2b191908, 0x19081908, 0x2b191908, 0x19190808, 0x2b191908, - 0x2b080808, 0x2b191908, 0x2b19192b, 0x2b191908, 0x08080819, 0x2b191919, 0x08081908, 0x2b191919, - 0x08190808, 0x2b191919, 0x19080808, 0x2b191919, 0x2b192b08, 0x2b191919, 0x2b2b0819, 0x2b191919, - 0x08080808, 0x2b19192b, 0x1908192b, 0x2b19192b, 0x192b1908, 0x2b19192b, 0x08080819, 0x2b192b08, - 0x08081908, 0x2b192b08, 0x08190808, 0x2b192b08, 0x082b192b, 0x2b192b08, 0x19080808, 0x2b192b08, - 0x2b2b2b19, 0x2b192b08, 0x08080808, 0x2b192b19, 0x19082b19, 0x2b192b19, 0x1919082b, 0x2b192b19, - 0x2b190808, 0x2b192b2b, 0x08080808, 0x2b2b0808, 0x08081919, 0x2b2b0808, 0x08082b2b, 0x2b2b0808, - 0x08191908, 0x2b2b0808, 0x082b082b, 0x2b2b0808, 0x082b2b2b, 0x2b2b0808, 0x19080819, 0x2b2b0808, - 0x19081908, 0x2b2b0808, 0x19190808, 0x2b2b0808, 0x2b2b082b, 0x2b2b0808, 0x2b2b2b2b, 0x2b2b0808, - 0x19080808, 0x2b2b0819, 0x192b1919, 0x2b2b0819, 0x0808082b, 0x2b2b082b, 0x08082b2b, 0x2b2b082b, - 0x082b082b, 0x2b2b082b, 0x082b2b08, 0x2b2b082b, 0x082b2b2b, 0x2b2b082b, 0x2b08082b, 0x2b2b082b, - 0x2b082b08, 0x2b2b082b, 0x2b082b2b, 0x2b2b082b, 0x2b2b2b08, 0x2b2b082b, 0x08080819, 0x2b2b1908, - 0x08081908, 0x2b2b1908, 0x08190808, 0x2b2b1908, 0x19080808, 0x2b2b1908, 0x2b082b19, 0x2b2b1908, - 0x2b2b1908, 0x2b2b1908, 0x08080808, 0x2b2b1919, 0x08192b19, 0x2b2b1919, 0x19190819, 0x2b2b192b, - 0x08082b2b, 0x2b2b2b08, 0x082b2b08, 0x2b2b2b08, 0x2b2b082b, 0x2b2b2b08, 0x19191908, 0x2b2b2b19, - 0x2b08192b, 0x2b2b2b19, 0x08082b08, 0x2b2b2b2b, 0x08082b2b, 0x2b2b2b2b, 0x082b0808, 0x2b2b2b2b, - 0x082b082b, 0x2b2b2b2b, 0x082b2b08, 0x2b2b2b2b, 0x2b082b08, 0x2b2b2b2b, 0x2b2b2b2b, 0x2b2b2b2b -); - -struct iq2_s { - d: f16, - qs: array, - qh: array, - scales: array -}; - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block = src0[src0_idx_base + offset]; let d = f32(block.d); @@ -1236,47 +639,6 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { #enddecl(IQ2_S) #decl(IQ3_XSS) - -const iq3xxs_grid = array( - 0x04040404, 0x04040414, 0x04040424, 0x04040c0c, 0x04040c1c, 0x04040c3e, 0x04041404, 0x04041414, - 0x04041c0c, 0x04042414, 0x04043e1c, 0x04043e2c, 0x040c040c, 0x040c041c, 0x040c0c04, 0x040c0c14, - 0x040c140c, 0x040c142c, 0x040c1c04, 0x040c1c14, 0x040c240c, 0x040c2c24, 0x040c3e04, 0x04140404, - 0x04140414, 0x04140424, 0x04140c0c, 0x04141404, 0x04141414, 0x04141c0c, 0x04141c1c, 0x04141c3e, - 0x04142c0c, 0x04142c3e, 0x04143e2c, 0x041c040c, 0x041c043e, 0x041c0c04, 0x041c0c14, 0x041c142c, - 0x041c3e04, 0x04240c1c, 0x04241c3e, 0x04242424, 0x04242c3e, 0x04243e1c, 0x04243e2c, 0x042c040c, - 0x042c043e, 0x042c1c14, 0x042c2c14, 0x04341c2c, 0x04343424, 0x043e0c04, 0x043e0c24, 0x043e0c34, - 0x043e241c, 0x043e340c, 0x0c04040c, 0x0c04041c, 0x0c040c04, 0x0c040c14, 0x0c04140c, 0x0c04141c, - 0x0c041c04, 0x0c041c14, 0x0c041c24, 0x0c04243e, 0x0c042c04, 0x0c0c0404, 0x0c0c0414, 0x0c0c0c0c, - 0x0c0c1404, 0x0c0c1414, 0x0c14040c, 0x0c14041c, 0x0c140c04, 0x0c140c14, 0x0c14140c, 0x0c141c04, - 0x0c143e14, 0x0c1c0404, 0x0c1c0414, 0x0c1c1404, 0x0c1c1c0c, 0x0c1c2434, 0x0c1c3434, 0x0c24040c, - 0x0c24042c, 0x0c242c04, 0x0c2c1404, 0x0c2c1424, 0x0c2c2434, 0x0c2c3e0c, 0x0c34042c, 0x0c3e1414, - 0x0c3e2404, 0x14040404, 0x14040414, 0x14040c0c, 0x14040c1c, 0x14041404, 0x14041414, 0x14041434, - 0x14041c0c, 0x14042414, 0x140c040c, 0x140c041c, 0x140c042c, 0x140c0c04, 0x140c0c14, 0x140c140c, - 0x140c1c04, 0x140c341c, 0x140c343e, 0x140c3e04, 0x14140404, 0x14140414, 0x14140c0c, 0x14140c3e, - 0x14141404, 0x14141414, 0x14141c3e, 0x14142404, 0x14142c2c, 0x141c040c, 0x141c0c04, 0x141c0c24, - 0x141c3e04, 0x141c3e24, 0x14241c2c, 0x14242c1c, 0x142c041c, 0x142c143e, 0x142c240c, 0x142c3e24, - 0x143e040c, 0x143e041c, 0x143e0c34, 0x143e242c, 0x1c04040c, 0x1c040c04, 0x1c040c14, 0x1c04140c, - 0x1c04141c, 0x1c042c04, 0x1c04342c, 0x1c043e14, 0x1c0c0404, 0x1c0c0414, 0x1c0c1404, 0x1c0c1c0c, - 0x1c0c2424, 0x1c0c2434, 0x1c14040c, 0x1c14041c, 0x1c140c04, 0x1c14142c, 0x1c142c14, 0x1c143e14, - 0x1c1c0c0c, 0x1c1c1c1c, 0x1c241c04, 0x1c24243e, 0x1c243e14, 0x1c2c0404, 0x1c2c0434, 0x1c2c1414, - 0x1c2c2c2c, 0x1c340c24, 0x1c341c34, 0x1c34341c, 0x1c3e1c1c, 0x1c3e3404, 0x24040424, 0x24040c3e, - 0x24041c2c, 0x24041c3e, 0x24042c1c, 0x24042c3e, 0x240c3e24, 0x24141404, 0x24141c3e, 0x24142404, - 0x24143404, 0x24143434, 0x241c043e, 0x241c242c, 0x24240424, 0x24242c0c, 0x24243424, 0x242c142c, - 0x242c241c, 0x242c3e04, 0x243e042c, 0x243e0c04, 0x243e0c14, 0x243e1c04, 0x2c040c14, 0x2c04240c, - 0x2c043e04, 0x2c0c0404, 0x2c0c0434, 0x2c0c1434, 0x2c0c2c2c, 0x2c140c24, 0x2c141c14, 0x2c143e14, - 0x2c1c0414, 0x2c1c2c1c, 0x2c240c04, 0x2c24141c, 0x2c24143e, 0x2c243e14, 0x2c2c0414, 0x2c2c1c0c, - 0x2c342c04, 0x2c3e1424, 0x2c3e2414, 0x34041424, 0x34042424, 0x34042434, 0x34043424, 0x340c140c, - 0x340c340c, 0x34140c3e, 0x34143424, 0x341c1c04, 0x341c1c34, 0x34242424, 0x342c042c, 0x342c2c14, - 0x34341c1c, 0x343e041c, 0x343e140c, 0x3e04041c, 0x3e04042c, 0x3e04043e, 0x3e040c04, 0x3e041c14, - 0x3e042c14, 0x3e0c1434, 0x3e0c2404, 0x3e140c14, 0x3e14242c, 0x3e142c14, 0x3e1c0404, 0x3e1c0c2c, - 0x3e1c1c1c, 0x3e1c3404, 0x3e24140c, 0x3e24240c, 0x3e2c0404, 0x3e2c0414, 0x3e2c1424, 0x3e341c04 -); - -struct iq3_xxs { - d: f16, - qs: array -}; - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block = src0[src0_idx_base + offset]; let d = f32(block.d); @@ -1309,82 +671,6 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { #enddecl(IQ3_XSS) #decl(IQ3_S) - -const iq3s_grid = array( - 0x01010101, 0x01010103, 0x01010105, 0x0101010b, 0x0101010f, 0x01010301, 0x01010303, 0x01010305, - 0x01010309, 0x0101030d, 0x01010501, 0x01010503, 0x0101050b, 0x01010707, 0x01010901, 0x01010905, - 0x0101090b, 0x0101090f, 0x01010b03, 0x01010b07, 0x01010d01, 0x01010d05, 0x01010f03, 0x01010f09, - 0x01010f0f, 0x01030101, 0x01030103, 0x01030105, 0x01030109, 0x01030301, 0x01030303, 0x0103030b, - 0x01030501, 0x01030507, 0x0103050f, 0x01030703, 0x0103070b, 0x01030909, 0x01030d03, 0x01030d0b, - 0x01030f05, 0x01050101, 0x01050103, 0x0105010b, 0x0105010f, 0x01050301, 0x01050307, 0x0105030d, - 0x01050503, 0x0105050b, 0x01050701, 0x01050709, 0x01050905, 0x0105090b, 0x0105090f, 0x01050b03, - 0x01050b07, 0x01050f01, 0x01050f07, 0x01070107, 0x01070303, 0x0107030b, 0x01070501, 0x01070505, - 0x01070703, 0x01070707, 0x0107070d, 0x01070909, 0x01070b01, 0x01070b05, 0x01070d0f, 0x01070f03, - 0x01070f0b, 0x01090101, 0x01090307, 0x0109030f, 0x01090503, 0x01090509, 0x01090705, 0x01090901, - 0x01090907, 0x01090b03, 0x01090f01, 0x010b0105, 0x010b0109, 0x010b0501, 0x010b0505, 0x010b050d, - 0x010b0707, 0x010b0903, 0x010b090b, 0x010b090f, 0x010b0d0d, 0x010b0f07, 0x010d010d, 0x010d0303, - 0x010d0307, 0x010d0703, 0x010d0b05, 0x010d0f03, 0x010f0101, 0x010f0105, 0x010f0109, 0x010f0501, - 0x010f0505, 0x010f050d, 0x010f0707, 0x010f0b01, 0x010f0b09, 0x03010101, 0x03010103, 0x03010105, - 0x03010109, 0x03010301, 0x03010303, 0x03010307, 0x0301030b, 0x0301030f, 0x03010501, 0x03010505, - 0x03010703, 0x03010709, 0x0301070d, 0x03010b09, 0x03010b0d, 0x03010d03, 0x03010f05, 0x03030101, - 0x03030103, 0x03030107, 0x0303010d, 0x03030301, 0x03030309, 0x03030503, 0x03030701, 0x03030707, - 0x03030903, 0x03030b01, 0x03030b05, 0x03030f01, 0x03030f0d, 0x03050101, 0x03050305, 0x0305030b, - 0x0305030f, 0x03050501, 0x03050509, 0x03050705, 0x03050901, 0x03050907, 0x03050b0b, 0x03050d01, - 0x03050f05, 0x03070103, 0x03070109, 0x0307010f, 0x03070301, 0x03070307, 0x03070503, 0x0307050f, - 0x03070701, 0x03070709, 0x03070903, 0x03070d05, 0x03070f01, 0x03090107, 0x0309010b, 0x03090305, - 0x03090309, 0x03090703, 0x03090707, 0x03090905, 0x0309090d, 0x03090b01, 0x03090b09, 0x030b0103, - 0x030b0301, 0x030b0307, 0x030b0503, 0x030b0701, 0x030b0705, 0x030b0b03, 0x030d0501, 0x030d0509, - 0x030d050f, 0x030d0909, 0x030d090d, 0x030f0103, 0x030f0107, 0x030f0301, 0x030f0305, 0x030f0503, - 0x030f070b, 0x030f0903, 0x030f0d05, 0x030f0f01, 0x05010101, 0x05010103, 0x05010107, 0x0501010b, - 0x0501010f, 0x05010301, 0x05010305, 0x05010309, 0x0501030d, 0x05010503, 0x05010507, 0x0501050f, - 0x05010701, 0x05010705, 0x05010903, 0x05010907, 0x0501090b, 0x05010b01, 0x05010b05, 0x05010d0f, - 0x05010f01, 0x05010f07, 0x05010f0b, 0x05030101, 0x05030105, 0x05030301, 0x05030307, 0x0503030f, - 0x05030505, 0x0503050b, 0x05030703, 0x05030709, 0x05030905, 0x05030b03, 0x05050103, 0x05050109, - 0x0505010f, 0x05050503, 0x05050507, 0x05050701, 0x0505070f, 0x05050903, 0x05050b07, 0x05050b0f, - 0x05050f03, 0x05050f09, 0x05070101, 0x05070105, 0x0507010b, 0x05070303, 0x05070505, 0x05070509, - 0x05070703, 0x05070707, 0x05070905, 0x05070b01, 0x05070d0d, 0x05090103, 0x0509010f, 0x05090501, - 0x05090507, 0x05090705, 0x0509070b, 0x05090903, 0x05090f05, 0x05090f0b, 0x050b0109, 0x050b0303, - 0x050b0505, 0x050b070f, 0x050b0901, 0x050b0b07, 0x050b0f01, 0x050d0101, 0x050d0105, 0x050d010f, - 0x050d0503, 0x050d0b0b, 0x050d0d03, 0x050f010b, 0x050f0303, 0x050f050d, 0x050f0701, 0x050f0907, - 0x050f0b01, 0x07010105, 0x07010303, 0x07010307, 0x0701030b, 0x0701030f, 0x07010505, 0x07010703, - 0x07010707, 0x0701070b, 0x07010905, 0x07010909, 0x0701090f, 0x07010b03, 0x07010d07, 0x07010f03, - 0x07030103, 0x07030107, 0x0703010b, 0x07030309, 0x07030503, 0x07030507, 0x07030901, 0x07030d01, - 0x07030f05, 0x07030f0d, 0x07050101, 0x07050305, 0x07050501, 0x07050705, 0x07050709, 0x07050b01, - 0x07070103, 0x07070301, 0x07070309, 0x07070503, 0x07070507, 0x0707050f, 0x07070701, 0x07070903, - 0x07070907, 0x0707090f, 0x07070b0b, 0x07070f07, 0x07090107, 0x07090303, 0x0709030d, 0x07090505, - 0x07090703, 0x07090b05, 0x07090d01, 0x07090d09, 0x070b0103, 0x070b0301, 0x070b0305, 0x070b050b, - 0x070b0705, 0x070b0909, 0x070b0b0d, 0x070b0f07, 0x070d030d, 0x070d0903, 0x070f0103, 0x070f0107, - 0x070f0501, 0x070f0505, 0x070f070b, 0x09010101, 0x09010109, 0x09010305, 0x09010501, 0x09010509, - 0x0901050f, 0x09010705, 0x09010903, 0x09010b01, 0x09010f01, 0x09030105, 0x0903010f, 0x09030303, - 0x09030307, 0x09030505, 0x09030701, 0x0903070b, 0x09030907, 0x09030b03, 0x09030b0b, 0x09050103, - 0x09050107, 0x09050301, 0x0905030b, 0x09050503, 0x09050707, 0x09050901, 0x09050b0f, 0x09050d05, - 0x09050f01, 0x09070109, 0x09070303, 0x09070307, 0x09070501, 0x09070505, 0x09070703, 0x0907070b, - 0x09090101, 0x09090105, 0x09090509, 0x0909070f, 0x09090901, 0x09090f03, 0x090b010b, 0x090b010f, - 0x090b0503, 0x090b0d05, 0x090d0307, 0x090d0709, 0x090d0d01, 0x090f0301, 0x090f030b, 0x090f0701, - 0x090f0907, 0x090f0b03, 0x0b010105, 0x0b010301, 0x0b010309, 0x0b010505, 0x0b010901, 0x0b010909, - 0x0b01090f, 0x0b010b05, 0x0b010d0d, 0x0b010f09, 0x0b030103, 0x0b030107, 0x0b03010b, 0x0b030305, - 0x0b030503, 0x0b030705, 0x0b030f05, 0x0b050101, 0x0b050303, 0x0b050507, 0x0b050701, 0x0b05070d, - 0x0b050b07, 0x0b070105, 0x0b07010f, 0x0b070301, 0x0b07050f, 0x0b070909, 0x0b070b03, 0x0b070d0b, - 0x0b070f07, 0x0b090103, 0x0b090109, 0x0b090501, 0x0b090705, 0x0b09090d, 0x0b0b0305, 0x0b0b050d, - 0x0b0b0b03, 0x0b0b0b07, 0x0b0d0905, 0x0b0f0105, 0x0b0f0109, 0x0b0f0505, 0x0d010303, 0x0d010307, - 0x0d01030b, 0x0d010703, 0x0d010707, 0x0d010d01, 0x0d030101, 0x0d030501, 0x0d03050f, 0x0d030d09, - 0x0d050305, 0x0d050709, 0x0d050905, 0x0d050b0b, 0x0d050d05, 0x0d050f01, 0x0d070101, 0x0d070309, - 0x0d070503, 0x0d070901, 0x0d09050b, 0x0d090907, 0x0d090d05, 0x0d0b0101, 0x0d0b0107, 0x0d0b0709, - 0x0d0b0d01, 0x0d0d010b, 0x0d0d0901, 0x0d0f0303, 0x0d0f0307, 0x0f010101, 0x0f010109, 0x0f01010f, - 0x0f010501, 0x0f010505, 0x0f01070d, 0x0f010901, 0x0f010b09, 0x0f010d05, 0x0f030105, 0x0f030303, - 0x0f030509, 0x0f030907, 0x0f03090b, 0x0f050103, 0x0f050109, 0x0f050301, 0x0f05030d, 0x0f050503, - 0x0f050701, 0x0f050b03, 0x0f070105, 0x0f070705, 0x0f07070b, 0x0f070b07, 0x0f090103, 0x0f09010b, - 0x0f090307, 0x0f090501, 0x0f090b01, 0x0f0b0505, 0x0f0b0905, 0x0f0d0105, 0x0f0d0703, 0x0f0f0101 -); - -struct iq3_s { - d: f16, - qs: array, - qh: array, - signs: array, - scales: array -}; - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block = src0[src0_idx_base + offset]; let d = f32(block.d); @@ -1431,151 +717,7 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { } #enddecl(IQ3_S) -#decl(IQ1_TABLE) - -const IQ1_DELTA: f32 = 0.125; - -const iq1_grid = array( - 0xfffdffff, 0xfff7fff0, 0xffccfff5, 0xffdfffc0, 0xffd7ffdd, 0xff30ffd5, 0xff03ff0c, 0xff10ff01, - 0xff7dff7f, 0xff75ff77, 0xff5fff40, 0xff57ff5d, 0xfcf3ff55, 0xfcccfcf0, 0xfcc1fcc3, 0xfcc5fcc4, - 0xfc3cfcd0, 0xfc34fc31, 0xfc00fc0d, 0xfc1cfc05, 0xfc11fc13, 0xfc70fc17, 0xfc43fc4c, 0xfc50fc41, - 0xfdfdfdff, 0xfdf5fdf7, 0xfddffdc0, 0xfdd7fddd, 0xfd30fdd5, 0xfd04fd0c, 0xfd14fd13, 0xfd7dfd7f, - 0xfd75fd77, 0xfd40fd4c, 0xfd5ffd44, 0xfd57fd5d, 0xf3ccfd55, 0xf3c1f3c3, 0xf33cf3d0, 0xf300f334, - 0xf313f305, 0xf34cf310, 0xf350f344, 0xf0f3f0fc, 0xf0f1f0f0, 0xf0c7f0c0, 0xf0d4f0c5, 0xf030f03f, - 0xf00ff035, 0xf003f00c, 0xf001f000, 0xf01ff004, 0xf010f01d, 0xf015f017, 0xf04cf07c, 0xf047f040, - 0xf05cf045, 0xf050f053, 0xf054f051, 0xf1c4f1c3, 0xf133f13c, 0xf10df10f, 0xf107f100, 0xf11cf11f, - 0xf114f111, 0xf14cf170, 0xf144f143, 0xf7fdf7ff, 0xf7f5f7f7, 0xf7dff7c0, 0xf7d7f7dd, 0xf730f7d5, - 0xf701f70c, 0xf77ff710, 0xf777f77d, 0xf740f775, 0xf75df75f, 0xf755f757, 0xf4ccf4f0, 0xf4c4f4c3, - 0xf4d0f4d3, 0xf40ff43c, 0xf400f40c, 0xf413f41c, 0xf44cf414, 0xf441f443, 0xf450f444, 0xf5fdf5ff, - 0xf5f5f5f7, 0xf5dff5c0, 0xf5d7f5dd, 0xf530f5d5, 0xf504f50c, 0xf510f51c, 0xf57df57f, 0xf577f570, - 0xf540f575, 0xf55df55f, 0xf555f557, 0xcfcccfcf, 0xcfc4cfc3, 0xcfd0cfd3, 0xcf33cf3c, 0xcf00cf0f, - 0xcf1ccf07, 0xcf10cf13, 0xcf4ccf14, 0xcf41cf43, 0xcf50cf5c, 0xccf3ccfc, 0xccf4ccf1, 0xcccdcccf, - 0xccc7ccc0, 0xccd3ccdc, 0xcc30ccd4, 0xcc0fcc35, 0xcc0dcc0c, 0xcc00cc03, 0xcc04cc01, 0xcc10cc1f, - 0xcc4dcc73, 0xcc5ccc40, 0xcdcccc53, 0xcdc1cdc3, 0xcd3fcdd0, 0xcd34cd31, 0xcd00cd0d, 0xcd05cd07, - 0xcd11cd13, 0xcd4ccd70, 0xcd41cd43, 0xc3fccd50, 0xc3f4c3f1, 0xc3c0c3c3, 0xc3c4c3c7, 0xc3d1c3dc, - 0xc330c33c, 0xc337c331, 0xc30cc335, 0xc300c303, 0xc304c301, 0xc310c31d, 0xc373c317, 0xc34fc374, - 0xc340c343, 0xc344c347, 0xc35cc345, 0xc350c353, 0xc0fdc354, 0xc0f5c0f0, 0xc0c3c0cc, 0xc0c1c0c0, - 0xc0dfc0c4, 0xc0d0c0dd, 0xc0d5c0d7, 0xc033c03c, 0xc031c030, 0xc00dc00c, 0xc000c003, 0xc004c001, - 0xc01cc005, 0xc010c013, 0xc014c011, 0xc07dc07f, 0xc070c073, 0xc075c077, 0xc04cc04f, 0xc040c043, - 0xc044c041, 0xc05fc045, 0xc050c05d, 0xc1f3c1fc, 0xc1f1c1f0, 0xc1c1c1c0, 0xc1c5c1c7, 0xc1d1c1dc, - 0xc13dc13f, 0xc130c133, 0xc135c137, 0xc100c10c, 0xc107c101, 0xc11cc104, 0xc110c113, 0xc114c117, - 0xc171c115, 0xc14dc175, 0xc153c140, 0xc7ccc154, 0xc7d0c7c1, 0xc733c73c, 0xc734c731, 0xc700c70f, - 0xc705c707, 0xc71cc71f, 0xc711c713, 0xc770c714, 0xc743c74c, 0xc4cfc750, 0xc4c0c4cd, 0xc4dcc4c5, - 0xc43dc4d0, 0xc430c433, 0xc40cc437, 0xc400c403, 0xc404c401, 0xc41fc405, 0xc415c410, 0xc44cc474, - 0xc440c44d, 0xc45cc447, 0xc454c451, 0xc5c1c5f4, 0xc5d1c5d3, 0xc531c533, 0xc50fc534, 0xc500c50d, - 0xc51cc507, 0xc514c511, 0xc54cc570, 0xc545c541, 0xdffddfff, 0xdff5dff7, 0xdfdfdfc0, 0xdfd0dfdd, - 0xdfd5dfd7, 0xdf0cdf30, 0xdf1cdf04, 0xdf7fdf10, 0xdf77df7d, 0xdf40df75, 0xdf5ddf5f, 0xdf57df50, - 0xdcf0df55, 0xdcc3dccc, 0xdcd0dcc4, 0xdc33dc3d, 0xdc00dc34, 0xdc05dc07, 0xdc13dc1c, 0xdc11dc10, - 0xdc4fdc70, 0xdc44dc41, 0xddfcdc50, 0xddf5ddf7, 0xddc0ddcc, 0xdddddddf, 0xddd5ddd7, 0xdd0cdd30, - 0xdd04dd01, 0xdd7cdd10, 0xdd75dd77, 0xdd40dd4c, 0xdd5ddd5f, 0xdd55dd57, 0xd3c3d3f0, 0xd3c4d3c1, - 0xd333d3d0, 0xd331d330, 0xd30dd334, 0xd307d300, 0xd311d305, 0xd34cd370, 0xd344d343, 0xd350d35c, - 0xd0c0d0f4, 0xd0d4d0dc, 0xd030d03f, 0xd00cd037, 0xd000d003, 0xd01dd004, 0xd017d010, 0xd04fd074, - 0xd040d043, 0xd045d047, 0xd053d05c, 0xd054d051, 0xd1cfd1f0, 0xd1c4d1cd, 0xd13cd1d0, 0xd100d134, - 0xd11cd11f, 0xd173d114, 0xd14fd171, 0xd7ffd145, 0xd7f7d7fd, 0xd7c0d7f5, 0xd7ddd7df, 0xd7d5d7d7, - 0xd70cd730, 0xd710d703, 0xd77dd77f, 0xd775d777, 0xd75dd75f, 0xd755d757, 0xd4ccd4f4, 0xd4c4d4c3, - 0xd431d4d0, 0xd40dd434, 0xd41cd400, 0xd411d413, 0xd470d414, 0xd441d44f, 0xd453d444, 0xd5ffd450, - 0xd5f7d5fd, 0xd5dfd5f5, 0xd5d7d5dd, 0xd530d5d5, 0xd501d50c, 0xd510d504, 0xd57dd57f, 0xd575d577, - 0xd55fd540, 0xd557d55d, 0x3ff0d555, 0x3fc13fcc, 0x3f343fd0, 0x3f003f0d, 0x3f053f07, 0x3f133f1c, - 0x3f433f11, 0x3f5c3f44, 0x3cff3f51, 0x3cf33cfc, 0x3cf43cf1, 0x3cc03ccd, 0x3cc73cc1, 0x3cdc3cc5, - 0x3cd43cd1, 0x3c373c30, 0x3c0c3c35, 0x3c003c03, 0x3c043c01, 0x3c103c05, 0x3c153c17, 0x3c733c7c, - 0x3c4f3c71, 0x3c403c4d, 0x3c5c3c5f, 0x3df03c5d, 0x3dc33dcc, 0x3dd03dc1, 0x3d0d3d3c, 0x3d053d00, - 0x3d143d13, 0x3d433d74, 0x33fc3d50, 0x33c433c0, 0x333033d4, 0x33353337, 0x3303330c, 0x33013300, - 0x331d331c, 0x33173310, 0x337c3315, 0x33743371, 0x334d334f, 0x335f3340, 0x3354335c, 0x30fd30fc, - 0x30f530f0, 0x30c330cc, 0x30c130c0, 0x30df30c4, 0x30d530d0, 0x3033303c, 0x30313030, 0x300f3034, - 0x3003300c, 0x30013000, 0x30043007, 0x3013301c, 0x30113010, 0x307d3014, 0x30703073, 0x304c3077, - 0x30403043, 0x30443041, 0x30503045, 0x30553057, 0x31f031fc, 0x31c331f4, 0x31c731c0, 0x31dc31c5, - 0x31d431d3, 0x313d313f, 0x31373130, 0x310c310f, 0x3100310d, 0x31043101, 0x3110311d, 0x317c3117, - 0x31753170, 0x31403143, 0x3153315c, 0x37f03151, 0x37c037cc, 0x37d037c5, 0x3734373d, 0x3700370f, - 0x371c3707, 0x37113713, 0x37703714, 0x3743374c, 0x37443741, 0x34fc3750, 0x34f134f0, 0x34cf34f5, - 0x34c034c3, 0x34dc34c7, 0x34d134d3, 0x3430343f, 0x340c3435, 0x3403340d, 0x34013400, 0x341f3404, - 0x3410341d, 0x34153411, 0x34743471, 0x3440344d, 0x34473441, 0x3453345c, 0x34543451, 0x353335c1, - 0x35343531, 0x35073500, 0x35133505, 0x35433514, 0x0ffc3550, 0x0ff00ff3, 0x0ff40ff1, 0x0fc00fcd, - 0x0fdc0fc5, 0x0fd40fd3, 0x0f300f3f, 0x0f0c0f37, 0x0f000f03, 0x0f040f01, 0x0f170f10, 0x0f740f71, - 0x0f470f40, 0x0f5c0f5f, 0x0f540f51, 0x0cf70cf0, 0x0cf50cf4, 0x0cc30ccc, 0x0cc10cc0, 0x0cc40cc7, - 0x0cd00cdf, 0x0cd70cd1, 0x0c3c0cd5, 0x0c300c33, 0x0c340c31, 0x0c0c0c0f, 0x0c030c0d, 0x0c010c00, - 0x0c040c07, 0x0c1c0c05, 0x0c100c13, 0x0c140c11, 0x0c700c7d, 0x0c430c4c, 0x0c410c40, 0x0c5f0c44, - 0x0c550c50, 0x0df10dfc, 0x0dc00dcd, 0x0ddc0dc5, 0x0d3d0dd3, 0x0d350d30, 0x0d030d0c, 0x0d010d00, - 0x0d1d0d04, 0x0d700d10, 0x0d4d0d4f, 0x0d440d40, 0x0d530d45, 0x03f003f3, 0x03c303cc, 0x03c103c0, - 0x03c403c7, 0x03d003dc, 0x03d503d7, 0x0333033c, 0x03310330, 0x03350334, 0x030c030f, 0x03000303, - 0x03070301, 0x03050304, 0x031d031c, 0x03100313, 0x03140311, 0x0377037f, 0x034c0375, 0x03400343, - 0x03440341, 0x0353035c, 0x03550350, 0x00fd00fc, 0x00f000f3, 0x00f400f1, 0x00cc00cf, 0x00c300cd, - 0x00c100c0, 0x00c500c4, 0x00d300dc, 0x00d100d0, 0x003f00d4, 0x003d003c, 0x00300033, 0x00370031, - 0x000f0034, 0x000d000c, 0x00000003, 0x00070001, 0x00050004, 0x001c001f, 0x00100013, 0x00170011, - 0x00150014, 0x0073007c, 0x00740070, 0x004f0075, 0x0043004c, 0x00410040, 0x00440047, 0x0053005c, - 0x00510050, 0x01ff0054, 0x01fd01fc, 0x01f101f3, 0x01f401f7, 0x01c301cc, 0x01c701c0, 0x01df01c4, - 0x01dd01dc, 0x01d001d3, 0x01d701d1, 0x013c01d4, 0x01310130, 0x01340137, 0x010f0135, 0x010d010c, - 0x01000103, 0x01070101, 0x01050104, 0x0113011c, 0x01140110, 0x0170017d, 0x01770171, 0x01750174, - 0x0140014c, 0x015d0145, 0x01510150, 0x01540157, 0x07f007f3, 0x07f407f1, 0x07c007cf, 0x07dc07c7, - 0x073007d5, 0x07350737, 0x0703070c, 0x07010700, 0x07040707, 0x071d071f, 0x07100713, 0x0774077d, - 0x074d074f, 0x07470740, 0x0754075c, 0x04fd04fc, 0x04f504f0, 0x04c304cc, 0x04c104c0, 0x04d004c4, - 0x0433043c, 0x04310430, 0x040f0434, 0x040d040c, 0x04000403, 0x04070401, 0x04050404, 0x0413041c, - 0x04110410, 0x047c0414, 0x04740470, 0x0443044c, 0x04410440, 0x04440447, 0x05f30450, 0x05c005f7, - 0x05df05c5, 0x05d105d0, 0x053005d4, 0x05340537, 0x0500050c, 0x05070501, 0x051d0504, 0x05170510, - 0x057c0515, 0x054d0575, 0x05410540, 0x05450547, 0x1ff0055c, 0x1fc11fc3, 0x1fd01fc4, 0x1f0f1f33, - 0x1f011f00, 0x1f051f07, 0x1f131f1c, 0x1f141f11, 0x1f411f7c, 0x1cfc1f50, 0x1cf11cf3, 0x1ccd1cf4, - 0x1cdc1cc0, 0x1cd11cdd, 0x1c301cd4, 0x1c0c1c34, 0x1c011c00, 0x1c101c04, 0x1c151c11, 0x1c751c73, - 0x1c401c4d, 0x1c511c5c, 0x1dcc1c54, 0x1dc41dc1, 0x1d3c1d3f, 0x1d001d31, 0x1d071d01, 0x1d701d1f, - 0x1d411d4c, 0x13cc1d50, 0x13c013cd, 0x13c513c1, 0x13d113dc, 0x133f13d4, 0x1330133d, 0x13351337, - 0x1303130c, 0x13011300, 0x13051304, 0x131d131f, 0x13731310, 0x13741370, 0x134d134f, 0x13401343, - 0x13471341, 0x135c1345, 0x13541353, 0x10f710f0, 0x10cc10f5, 0x10c110c0, 0x103310c4, 0x10311030, - 0x100f1034, 0x1003100c, 0x10011000, 0x101c1004, 0x10101013, 0x10141011, 0x10741071, 0x104c1075, - 0x10411040, 0x10451044, 0x1050105d, 0x10571051, 0x11f411fd, 0x11df11c0, 0x11d711d1, 0x113f11d4, - 0x11371130, 0x110c1135, 0x11001103, 0x11071101, 0x111f1105, 0x11171110, 0x117d117f, 0x11751170, - 0x11411143, 0x11441147, 0x1153115f, 0x11551151, 0x17c417c1, 0x173c17d0, 0x1700170d, 0x171c1705, - 0x17701714, 0x1747174c, 0x14fc1751, 0x14cf14f3, 0x14dc14c0, 0x14d114d3, 0x143f14d4, 0x1430143c, - 0x14371431, 0x1403140c, 0x14011400, 0x141f1404, 0x14151410, 0x1473147d, 0x14401475, 0x1453145c, - 0x14541450, 0x15c115cc, 0x153c15c7, 0x15341533, 0x1500150f, 0x15051507, 0x15101513, 0x15711514, - 0x15471543, 0x15511545, 0x7ffd7fff, 0x7ff57ff7, 0x7fdd7fdf, 0x7fd57fd7, 0x7f0f7f30, 0x7f037f0c, - 0x7f047f01, 0x7f7f7f10, 0x7f777f7d, 0x7f407f75, 0x7f5d7f5f, 0x7f557f57, 0x7ccc7cf0, 0x7cc17cc3, - 0x7cd07cc4, 0x7c337c3c, 0x7c0f7c34, 0x7c007c0d, 0x7c077c01, 0x7c137c04, 0x7c147c11, 0x7c747c70, - 0x7c417c43, 0x7c507c44, 0x7dfd7dff, 0x7df57df7, 0x7ddf7dc0, 0x7dd77ddd, 0x7d0c7dd5, 0x7d047d03, - 0x7d7f7d10, 0x7d777d7d, 0x7d407d75, 0x7d5d7d5f, 0x7d557d57, 0x73c473c3, 0x7333733c, 0x7300730c, - 0x731c7305, 0x73147313, 0x73447343, 0x70f470fc, 0x70c070cd, 0x70d170c5, 0x703f70d4, 0x7030703c, - 0x700c7037, 0x70007003, 0x70047001, 0x70107005, 0x70177011, 0x707c7015, 0x70717073, 0x704f7074, - 0x7040704d, 0x70517047, 0x71c171cc, 0x71d071c4, 0x7133713c, 0x71357134, 0x7100710f, 0x71057104, - 0x7111711c, 0x71707115, 0x7145714c, 0x77ff7153, 0x77f777fd, 0x77c077f5, 0x77dd77df, 0x77d577d7, - 0x7730773c, 0x7703770c, 0x77107704, 0x777f7714, 0x7777777d, 0x77407775, 0x775d775f, 0x77557757, - 0x74f174f0, 0x74c374cc, 0x74d074c1, 0x7433743c, 0x74347431, 0x740d740f, 0x74057400, 0x7413741c, - 0x74417470, 0x74507444, 0x75fd75ff, 0x75f575f7, 0x75df75c0, 0x75d775dd, 0x753075d5, 0x7503750c, - 0x757f7501, 0x7577757d, 0x75407575, 0x755d755f, 0x75557557, 0x4fcc4ff0, 0x4fc74fc1, 0x4fd04fc4, - 0x4f314f3c, 0x4f004f34, 0x4f054f07, 0x4f154f14, 0x4f4c4f70, 0x4f414f43, 0x4f504f44, 0x4cf34cfc, - 0x4cf44cf1, 0x4cc04ccf, 0x4cc54cc7, 0x4cd34cdc, 0x4cd44cd1, 0x4c304c3f, 0x4c0c4c0f, 0x4c004c03, - 0x4c044c01, 0x4c104c1d, 0x4c714c73, 0x4c404c4d, 0x4c5c4c47, 0x4c514c53, 0x4df04c54, 0x4dc34dcc, - 0x4dd04dc4, 0x4d314d33, 0x4d0f4d34, 0x4d004d0d, 0x4d114d07, 0x4d704d14, 0x4d414d43, 0x43fc4d54, - 0x43f143f3, 0x43c043cf, 0x43d143c7, 0x4335433f, 0x4303430c, 0x43014300, 0x43044307, 0x431c431f, - 0x4310431d, 0x43714373, 0x4343434d, 0x43474340, 0x4354435c, 0x40f040ff, 0x40f540f7, 0x40cc40cf, - 0x40c040c3, 0x40c440c1, 0x40d040dc, 0x40d540d4, 0x4033403c, 0x40314030, 0x400f4034, 0x400d400c, - 0x40004003, 0x40074001, 0x40054004, 0x4013401c, 0x40114010, 0x407c4014, 0x40774070, 0x404d404c, - 0x40404043, 0x40444041, 0x405f4045, 0x4050405d, 0x40554057, 0x41f341fc, 0x41c041cf, 0x41df41c4, - 0x41d441d1, 0x41374130, 0x410c4134, 0x4100410d, 0x41044101, 0x41174110, 0x4173417d, 0x41754174, - 0x4143414d, 0x41534140, 0x41544151, 0x47c147f0, 0x47d047c4, 0x4731473c, 0x470d470f, 0x47014700, - 0x47134705, 0x47704710, 0x4741474c, 0x47504744, 0x44f144f3, 0x44cf44f4, 0x44c044cd, 0x44c544c7, - 0x44dc44df, 0x44d144d3, 0x443d443f, 0x44374430, 0x440c4435, 0x44004403, 0x44044401, 0x4410441d, - 0x44154411, 0x4473447c, 0x444d444f, 0x44454440, 0x4451445c, 0x45c045f0, 0x453345d0, 0x45344531, - 0x4500450f, 0x451c4507, 0x454c4570, 0x45404543, 0x5fff4541, 0x5ff75ffd, 0x5fc05ff5, 0x5fdd5fdf, - 0x5fd55fd7, 0x5f0c5f30, 0x5f015f03, 0x5f7f5f04, 0x5f775f7d, 0x5f405f75, 0x5f5d5f5f, 0x5f555f57, - 0x5cf45cf0, 0x5cc35ccc, 0x5cc45cc1, 0x5c315cc5, 0x5c0c5c34, 0x5c075c00, 0x5c1c5c05, 0x5c705c13, - 0x5c4d5c4f, 0x5c445c41, 0x5df75dfd, 0x5dcf5df5, 0x5ddd5dc4, 0x5dd55dd7, 0x5d0c5d30, 0x5d045d01, - 0x5d7f5d10, 0x5d775d7d, 0x5d405d75, 0x5d5d5d5f, 0x5d555d57, 0x53d053c4, 0x5333533c, 0x5303530f, - 0x53075300, 0x531c5305, 0x53115310, 0x53145317, 0x50f15370, 0x50cf50f4, 0x50c050cd, 0x50d150c7, - 0x503d50d4, 0x500c5030, 0x50005003, 0x50045001, 0x50155010, 0x5073507c, 0x50715070, 0x504d5074, - 0x50475040, 0x51cc51f0, 0x51c551c1, 0x51d051dc, 0x51315133, 0x510d5135, 0x51015100, 0x511f5107, - 0x5171511d, 0x5140514f, 0x51445141, 0x5153515c, 0x57ff5151, 0x57f757fd, 0x57df57f5, 0x57d757dd, - 0x570c57d5, 0x57015703, 0x577f5704, 0x5777577d, 0x57405775, 0x575d575f, 0x57555757, 0x54c354f0, - 0x54dc54c4, 0x543c54d0, 0x5400540f, 0x541c5405, 0x54145411, 0x5441544f, 0x55fd55ff, 0x55f555f7, - 0x55dd55df, 0x55d555d7, 0x5503550c, 0x557f5501, 0x5577557d, 0x55405575, 0x555d555f, 0x55555557 -); - -#enddecl(IQ1_TABLE) - #decl(IQ1_S) - -struct iq1_s { - d: f16, - qs: array, - qh: array -}; - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block = src0[src0_idx_base + offset]; let d = f32(block.d); @@ -1603,13 +745,6 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { #enddecl(IQ1_S) #decl(IQ1_M) - -struct iq1_m { - qs: array, - qh: array, - scales: array -}; - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block = src0[src0_idx_base + offset]; @@ -1655,21 +790,7 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { #enddecl(IQ1_M) -#decl(IQ4_TABLE) - -const kvalues_iq4nl = array( - -127, -104, -83, -65, -49, -35, -22, -10, 1, 13, 25, 38, 53, 69, 89, 113 -); - -#enddecl(IQ4_TABLE) - #decl(IQ4_NL) - -struct iq4_nl { - d: f16, - qs: array, -} - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block = src0[src0_idx_base + offset]; let d = f32(block.d); @@ -1691,14 +812,6 @@ fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { #enddecl(IQ4_NL) #decl(IQ4_XS) - -struct iq4_xs { - d: f16, - scales_h: f16, - scales_l: u32, - qs: array -}; - fn multiply_add(src0_idx_base: u32, src1_idx_base: u32, offset: u32) -> f32 { let block = src0[src0_idx_base + offset]; let d = f32(block.d); diff --git a/ggml/src/ggml-webgpu/wgsl-shaders/rms_norm.wgsl b/ggml/src/ggml-webgpu/wgsl-shaders/rms_norm.wgsl new file mode 100644 index 0000000000..f919a51336 --- /dev/null +++ b/ggml/src/ggml-webgpu/wgsl-shaders/rms_norm.wgsl @@ -0,0 +1,57 @@ +@group(0) @binding(0) +var src: array; + +@group(0) @binding(1) +var dst: array; + +struct Params { + offset_src: u32, // in elements + offset_dst: u32, // in elements + + // Strides (in elements) + stride_src1: u32, + stride_src2: u32, + stride_src3: u32, + + stride_dst1: u32, + stride_dst2: u32, + stride_dst3: u32, + + // Shape of src/dst + ne0: u32, + ne1: u32, + ne2: u32, + ne3: u32, + + eps: u32 +}; + +@group(0) @binding(2) +var params: Params; + +override wg_size: u32; +@compute @workgroup_size(wg_size) +fn main(@builtin(global_invocation_id) gid: vec3) { + if (gid.x >= params.ne1 * params.ne2 * params.ne3) { + return; + } + + // one thread per row + var i = gid.x; + let i3 = i / (params.ne2 * params.ne1); + i = i % (params.ne2 * params.ne1); + let i2 = i / params.ne1; + let i1 = i % params.ne1; + let i_src_row = params.offset_src + i3 * params.stride_src3 + i2 * params.stride_src2 + i1 * params.stride_src1; + let i_dst_row = params.offset_src + i3 * params.stride_dst3 + i2 * params.stride_dst2 + i1 * params.stride_dst1; + + var sum = 0.0f; + for (var j: u32 = 0; j < params.ne0; j++) { + sum += src[i_src_row + j] * src[i_src_row + j]; + } + let eps = bitcast(params.eps); + let scale = 1.0/sqrt(sum/f32(params.ne0) + eps); + for (var j: u32 = 0; j < params.ne0; j++) { + dst[i_dst_row + j] = scale * src[i_src_row + j]; + } +} diff --git a/ggml/src/ggml-webgpu/wgsl-shaders/rms_norm_in_place.wgsl b/ggml/src/ggml-webgpu/wgsl-shaders/rms_norm_in_place.wgsl new file mode 100644 index 0000000000..ae84f556d6 --- /dev/null +++ b/ggml/src/ggml-webgpu/wgsl-shaders/rms_norm_in_place.wgsl @@ -0,0 +1,48 @@ +@group(0) @binding(0) +var a: array; + +struct Params { + offset: u32, // in elements + + // Strides (in elements) + stride1: u32, + stride2: u32, + stride3: u32, + + // Shape + ne0: u32, + ne1: u32, + ne2: u32, + ne3: u32, + + eps: u32 +}; + +@group(0) @binding(1) +var params: Params; + +override wg_size: u32; +@compute @workgroup_size(wg_size) +fn main(@builtin(global_invocation_id) gid: vec3) { + if (gid.x >= params.ne1 * params.ne2 * params.ne3) { + return; + } + + // one thread per row + var i = gid.x; + let i3 = i / (params.ne2 * params.ne1); + i = i % (params.ne2 * params.ne1); + let i2 = i / params.ne1; + let i1 = i % params.ne1; + let i_row = params.offset + i3 * params.stride3 + i2 * params.stride2 + i1 * params.stride1; + + var sum = 0.0f; + for (var j: u32 = 0; j < params.ne0; j++) { + sum += a[i_row + j] * a[i_row + j]; + } + let eps = bitcast(params.eps); + let scale = 1.0/sqrt(sum/f32(params.ne0) + eps); + for (var j: u32 = 0; j < params.ne0; j++) { + a[i_row + j] = scale * a[i_row + j]; + } +} diff --git a/ggml/src/ggml-webgpu/wgsl-shaders/set_rows.wgsl b/ggml/src/ggml-webgpu/wgsl-shaders/set_rows.wgsl index 4bd6f94a23..3567713dc2 100644 --- a/ggml/src/ggml-webgpu/wgsl-shaders/set_rows.wgsl +++ b/ggml/src/ggml-webgpu/wgsl-shaders/set_rows.wgsl @@ -52,7 +52,6 @@ fn main(@builtin(global_invocation_id) gid: vec3) { } var i = gid.x; let i_src3 = i / (params.ne2 * params.n_rows); - let i_dst3 = i / (params.ne2 * 3); i = i % (params.ne2 * params.n_rows); let i_src2 = i / params.n_rows; diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp index ce4a88761c..893c2af313 100644 --- a/tests/test-backend-ops.cpp +++ b/tests/test-backend-ops.cpp @@ -6071,6 +6071,10 @@ static std::vector> make_test_cases_eval() { //add_test_bin_bcast(type, {3, 3, 2560, 1280}, {2, 1, 1, 1}); } + // single in-place tests, especially important for WebGPU backend since kernels for in-place vs. not are different + test_cases.emplace_back(new test_bin_bcast(ggml_add_inplace, GGML_TYPE_F32, {16, 5, 4, 3}, {1, 1, 1, 1}, 16)); + test_cases.emplace_back(new test_bin_bcast(ggml_mul_inplace, GGML_TYPE_F32, {16, 5, 4, 3}, {1, 1, 1, 1}, 16)); + // fusion test_cases.emplace_back(new test_bin_bcast(ggml_add, GGML_TYPE_F32, {10, 5, 4, 3}, {2, 1, 1, 1}, 2)); test_cases.emplace_back(new test_bin_bcast(ggml_add, GGML_TYPE_F32, {16, 5, 4, 3}, {1, 2, 1, 1}, 3)); From 62c3b645c56ad5288aa401901f043b050edac5a2 Mon Sep 17 00:00:00 2001 From: Chenguang Li <757486878@qq.com> Date: Thu, 18 Sep 2025 09:26:33 +0800 Subject: [PATCH 28/52] CANN: Remove print (#16044) Signed-off-by: noemotiovon <757486878@qq.com> --- ggml/src/ggml-cann/ggml-cann.cpp | 1 - 1 file changed, 1 deletion(-) diff --git a/ggml/src/ggml-cann/ggml-cann.cpp b/ggml/src/ggml-cann/ggml-cann.cpp index 56d82b4af3..cbeafa6bc9 100755 --- a/ggml/src/ggml-cann/ggml-cann.cpp +++ b/ggml/src/ggml-cann/ggml-cann.cpp @@ -1728,7 +1728,6 @@ static bool ggml_cann_compute_forward(ggml_backend_cann_context& ctx, ggml_cann_get_rows(ctx, dst); break; case GGML_OP_SET_ROWS: - std::cout << "lcg GGML_OP_SET_ROWS"<< std::endl; ggml_cann_set_rows(ctx, dst); break; case GGML_OP_DUP: From f2f28380ea68939c0481df3e4216b698824a59df Mon Sep 17 00:00:00 2001 From: Georgi Gerganov Date: Thu, 18 Sep 2025 10:03:24 +0300 Subject: [PATCH 29/52] metal : handle nil cv during pipeline creation (#16065) ggml-ci --- ggml/src/ggml-metal/ggml-metal-device.m | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) diff --git a/ggml/src/ggml-metal/ggml-metal-device.m b/ggml/src/ggml-metal/ggml-metal-device.m index 9983640b43..4974bd15b9 100644 --- a/ggml/src/ggml-metal/ggml-metal-device.m +++ b/ggml/src/ggml-metal/ggml-metal-device.m @@ -327,12 +327,19 @@ ggml_metal_pipeline_t ggml_metal_library_compile_pipeline(ggml_metal_library_t l GGML_LOG_DEBUG("%s: compiling pipeline: base = '%s', name = '%s'\n", __func__, base, name); - id mtl_function = [lib->obj newFunctionWithName:base_func constantValues:(cv ? cv->obj : nil) error:&error]; + id mtl_function; + if (!cv) { + mtl_function = [lib->obj newFunctionWithName:base_func]; + } else { + mtl_function = [lib->obj newFunctionWithName:base_func constantValues:cv->obj error:&error]; + } if (!mtl_function) { ggml_critical_section_end(); GGML_LOG_ERROR("%s: error: failed to compile pipeline: base = '%s', name = '%s'\n", __func__, base, name); - GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]); + if (error) { + GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]); + } return nil; } From e00f3fd8fff2cf5a8c8c9f475034bd089c8bcce4 Mon Sep 17 00:00:00 2001 From: Jhen-Jie Hong Date: Thu, 18 Sep 2025 15:06:48 +0800 Subject: [PATCH 30/52] metal : avoid call free for non-owned buffer (#16067) --- ggml/src/ggml-metal/ggml-metal-device.m | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/ggml/src/ggml-metal/ggml-metal-device.m b/ggml/src/ggml-metal/ggml-metal-device.m index 4974bd15b9..8f83c5cc16 100644 --- a/ggml/src/ggml-metal/ggml-metal-device.m +++ b/ggml/src/ggml-metal/ggml-metal-device.m @@ -824,6 +824,7 @@ struct ggml_metal_buffer { // if false, the Metal buffer data is allocated in private GPU memory and is not shared with the host bool is_shared; + bool owned; // multiple buffers are used only to avoid the maximum buffer size limitation when using mmap int n_buffers; @@ -956,6 +957,7 @@ ggml_metal_buffer_t ggml_metal_buffer_init(ggml_metal_device_t dev, size_t size, if (shared) { res->all_data = ggml_metal_host_malloc(size_aligned); res->is_shared = true; + res->owned = true; } else { // dummy, non-NULL value - we'll populate this after creating the Metal buffer below res->all_data = (void *) 0x000000400ULL; @@ -1014,6 +1016,7 @@ ggml_metal_buffer_t ggml_metal_buffer_map(ggml_metal_device_t dev, void * ptr, s res->all_size = size; res->is_shared = true; + res->owned = false; res->n_buffers = 0; @@ -1107,7 +1110,7 @@ void ggml_metal_buffer_free(ggml_metal_buffer_t buf) { ggml_metal_buffer_rset_free(buf); - if (buf->is_shared) { + if (buf->is_shared && buf->owned) { #if TARGET_OS_OSX vm_deallocate((vm_map_t)mach_task_self(), (vm_address_t)buf->all_data, buf->all_size); #else From b213fce89bee8cb56b587b91e15a4278f8ed0180 Mon Sep 17 00:00:00 2001 From: Georgi Gerganov Date: Thu, 18 Sep 2025 12:33:45 +0300 Subject: [PATCH 31/52] metal : improve F32, F16 and BF16 mat-vec multiplication (#16057) * metal : improve F32, F16 and BF16 mat-vec multiplication ggml-ci * metal : make the NSG a function constant in mul_mv kernels ggml-ci --- ggml/src/ggml-metal/ggml-metal-device.cpp | 91 ++-- ggml/src/ggml-metal/ggml-metal-device.h | 1 + ggml/src/ggml-metal/ggml-metal-device.m | 4 + ggml/src/ggml-metal/ggml-metal-impl.h | 4 + ggml/src/ggml-metal/ggml-metal-ops.cpp | 10 +- ggml/src/ggml-metal/ggml-metal.metal | 533 ++++++++++++---------- 6 files changed, 355 insertions(+), 288 deletions(-) diff --git a/ggml/src/ggml-metal/ggml-metal-device.cpp b/ggml/src/ggml-metal/ggml-metal-device.cpp index 5f04789967..bada84cef3 100644 --- a/ggml/src/ggml-metal/ggml-metal-device.cpp +++ b/ggml/src/ggml-metal/ggml-metal-device.cpp @@ -34,6 +34,10 @@ ggml_metal_pipelines_t ggml_metal_pipelines_init(void) { } void ggml_metal_pipelines_free(ggml_metal_pipelines_t ppls) { + if (!ppls) { + return; + } + for (auto it = ppls->data.begin(); it != ppls->data.end(); ++it) { ggml_metal_pipeline_free(it->second); } @@ -467,37 +471,25 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mv(ggml_metal_library_ // use custom matrix x vector kernel switch (tsrc0) { case GGML_TYPE_F32: - { - GGML_ASSERT(op->src[1]->type == GGML_TYPE_F32); - - nsg = 1; - nr0 = 1; - nr1 = 4; - if (ne00 == 4) { - nr0 = 32; - suffix = "_c4"; - } - } break; case GGML_TYPE_F16: case GGML_TYPE_BF16: { - nsg = 1; - nr0 = 1; - if (op->src[1]->type == GGML_TYPE_F32) { - if (ne00 == 4) { - nr0 = 32; - nr1 = 4; - suffix = "_c4"; - } else if (ne11 * ne12 < 4) { - suffix = "_1row"; - } else if (ne00 >= 128 && ne01 >= 8 && ne00%4 == 0) { - suffix = "_l4"; - nr1 = ne11; - } else { - nr1 = 4; - } - } else { + if (ne00 == 4) { + nsg = 1; + nr0 = 32; nr1 = 4; + suffix = "_c4"; + } else if (ne00 % 4 == 0) { + nsg = N_SG_F; + nr0 = N_R0_F; + nr1 = 1; + smem = 32*sizeof(float)*N_R0_F; + suffix = "_4"; + } else { + nsg = N_SG_F; + nr0 = N_R0_F; + nr1 = 1; + smem = 32*sizeof(float)*N_R0_F; } } break; case GGML_TYPE_Q4_0: @@ -623,7 +615,13 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mv(ggml_metal_library_ return res; } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + 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); @@ -689,25 +687,26 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mv_id(ggml_metal_libra const ggml_type tsrc0 = op->src[0]->type; const ggml_type tsrc1 = op->src[1]->type; + const char * suffix = ""; + // use custom matrix x vector kernel switch (tsrc0) { case GGML_TYPE_F32: - { - GGML_ASSERT(op->src[1]->type == GGML_TYPE_F32); - nsg = 1; - nr0 = 1; - } break; case GGML_TYPE_F16: - { - GGML_ASSERT(op->src[1]->type == GGML_TYPE_F32); - nsg = 1; - nr0 = 1; - } break; case GGML_TYPE_BF16: { - GGML_ASSERT(op->src[1]->type == GGML_TYPE_F32); - nsg = 1; - nr0 = 1; + if (ne00 % 4 == 0) { + nsg = N_SG_F; + nr0 = N_R0_F; + nr1 = 1; + smem = 32*sizeof(float)*N_R0_F; + suffix = "_4"; + } else { + nsg = N_SG_F; + nr0 = N_R0_F; + nr1 = 1; + smem = 32*sizeof(float)*N_R0_F; + } } break; case GGML_TYPE_Q4_0: { @@ -824,7 +823,7 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mv_id(ggml_metal_libra } }; - snprintf(base, 256, "kernel_mul_mv_id_%s_%s", ggml_type_name(tsrc0), ggml_type_name(tsrc1)); + snprintf(base, 256, "kernel_mul_mv_id_%s_%s%s", ggml_type_name(tsrc0), ggml_type_name(tsrc1), suffix); snprintf(name, 256, "%s", base); ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); @@ -832,7 +831,13 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mv_id(ggml_metal_libra return res; } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + 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); diff --git a/ggml/src/ggml-metal/ggml-metal-device.h b/ggml/src/ggml-metal/ggml-metal-device.h index c48337f514..4a3a819fc0 100644 --- a/ggml/src/ggml-metal/ggml-metal-device.h +++ b/ggml/src/ggml-metal/ggml-metal-device.h @@ -22,6 +22,7 @@ typedef struct ggml_metal_cv * ggml_metal_cv_t; ggml_metal_cv_t ggml_metal_cv_init(void); void ggml_metal_cv_free(ggml_metal_cv_t cv); +void ggml_metal_cv_set_int16(ggml_metal_cv_t cv, int16_t value, int32_t idx); void ggml_metal_cv_set_int32(ggml_metal_cv_t cv, int32_t value, int32_t idx); void ggml_metal_cv_set_bool (ggml_metal_cv_t cv, bool value, int32_t idx); diff --git a/ggml/src/ggml-metal/ggml-metal-device.m b/ggml/src/ggml-metal/ggml-metal-device.m index 8f83c5cc16..67f71ace2b 100644 --- a/ggml/src/ggml-metal/ggml-metal-device.m +++ b/ggml/src/ggml-metal/ggml-metal-device.m @@ -51,6 +51,10 @@ void ggml_metal_cv_free(ggml_metal_cv_t cv) { free(cv); } +void ggml_metal_cv_set_int16(ggml_metal_cv_t cv, int16_t value, int32_t idx) { + [cv->obj setConstantValue:&value type:MTLDataTypeShort atIndex:idx]; +} + void ggml_metal_cv_set_int32(ggml_metal_cv_t cv, int32_t value, int32_t idx) { [cv->obj setConstantValue:&value type:MTLDataTypeInt atIndex:idx]; } diff --git a/ggml/src/ggml-metal/ggml-metal-impl.h b/ggml/src/ggml-metal/ggml-metal-impl.h index 0776bb6485..b257296540 100644 --- a/ggml/src/ggml-metal/ggml-metal-impl.h +++ b/ggml/src/ggml-metal/ggml-metal-impl.h @@ -8,6 +8,9 @@ // // TODO: for optimal performance, become function of the device and work size +#define N_R0_F 2 +#define N_SG_F 4 + #define N_R0_Q4_0 4 #define N_SG_Q4_0 2 @@ -72,6 +75,7 @@ #define FC_FLASH_ATTN_EXT 100 #define FC_FLASH_ATTN_EXT_VEC 200 #define FC_FLASH_ATTN_EXT_VEC_REDUCE 300 +#define FC_MUL_MV 400 // kernel argument structs // diff --git a/ggml/src/ggml-metal/ggml-metal-ops.cpp b/ggml/src/ggml-metal/ggml-metal-ops.cpp index 839c16894d..a28206e786 100644 --- a/ggml/src/ggml-metal/ggml-metal-ops.cpp +++ b/ggml/src/ggml-metal/ggml-metal-ops.cpp @@ -1564,7 +1564,10 @@ int ggml_metal_op_mul_mat(ggml_metal_op_t ctx, int idx) { ggml_metal_encoder_set_threadgroup_memory_size(enc, smem, 0); - if (op->src[0]->type == GGML_TYPE_Q8_0) { + if (op->src[0]->type == GGML_TYPE_F32 || + op->src[0]->type == GGML_TYPE_F16 || + op->src[0]->type == GGML_TYPE_BF16 || + op->src[0]->type == GGML_TYPE_Q8_0) { ggml_metal_encoder_dispatch_threadgroups(enc, ((ne01 + nr0 - 1)/(nr0)), ((ne11 + nr1 - 1)/nr1), ne12*ne13, 32, nsg, 1); } else { ggml_metal_encoder_dispatch_threadgroups(enc, ((ne01 + nr0*nsg - 1)/(nr0*nsg)), ((ne11 + nr1 - 1)/nr1), ne12*ne13, 32, nsg, 1); @@ -1772,7 +1775,10 @@ int ggml_metal_op_mul_mat_id(ggml_metal_op_t ctx, int idx) { ggml_metal_encoder_set_threadgroup_memory_size(enc, smem, 0); - if (op->src[0]->type == GGML_TYPE_Q8_0) { + if (op->src[0]->type == GGML_TYPE_F32 || + op->src[0]->type == GGML_TYPE_F16 || + op->src[0]->type == GGML_TYPE_BF16 || + op->src[0]->type == GGML_TYPE_Q8_0) { ggml_metal_encoder_dispatch_threadgroups(enc, (ne01 + nr0 - 1)/(nr0), (_ne1 + nr1 - 1)/nr1, ne123, 32, nsg, 1); } else { ggml_metal_encoder_dispatch_threadgroups(enc, (ne01 + nr0*nsg - 1)/(nr0*nsg), (_ne1 + nr1 - 1)/nr1, ne123, 32, nsg, 1); diff --git a/ggml/src/ggml-metal/ggml-metal.metal b/ggml/src/ggml-metal/ggml-metal.metal index f34b89e590..20ceb1fe04 100644 --- a/ggml/src/ggml-metal/ggml-metal.metal +++ b/ggml/src/ggml-metal/ggml-metal.metal @@ -2883,7 +2883,9 @@ static inline void helper_mv_reduce_and_write( } } -template +constant short FC_mul_mv_nsg [[function_constant(FC_MUL_MV + 0)]]; + +template void mul_vec_q_n_f32_impl( args_t args, device const char * src0, @@ -2893,6 +2895,8 @@ void mul_vec_q_n_f32_impl( uint3 tgpig, ushort tiisg, ushort sgitg) { + const short NSG = FC_mul_mv_nsg; + constexpr short NQ = 16; const int nb = args.ne00/QK4_0; @@ -2977,7 +2981,7 @@ kernel void kernel_mul_mv_q4_0_f32( uint3 tgpig[[threadgroup_position_in_grid]], ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - mul_vec_q_n_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + mul_vec_q_n_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } kernel void kernel_mul_mv_q4_1_f32( @@ -2989,7 +2993,7 @@ kernel void kernel_mul_mv_q4_1_f32( uint3 tgpig[[threadgroup_position_in_grid]], ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - mul_vec_q_n_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + mul_vec_q_n_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } kernel void kernel_mul_mv_q5_0_f32( @@ -3001,7 +3005,7 @@ kernel void kernel_mul_mv_q5_0_f32( uint3 tgpig[[threadgroup_position_in_grid]], ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - mul_vec_q_n_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + mul_vec_q_n_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } kernel void kernel_mul_mv_q5_1_f32( @@ -3013,10 +3017,10 @@ kernel void kernel_mul_mv_q5_1_f32( uint3 tgpig[[threadgroup_position_in_grid]], ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - mul_vec_q_n_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + mul_vec_q_n_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_q8_0_f32_impl( args_t args, device const char * src0, @@ -3026,6 +3030,8 @@ void kernel_mul_mv_q8_0_f32_impl( uint3 tgpig, ushort tiisg, ushort sgitg) { + const short NSG = FC_mul_mv_nsg; + constexpr short NQ = 8; const int nb = args.ne00/QK8_0; @@ -3097,7 +3103,7 @@ kernel void kernel_mul_mv_q8_0_f32( uint3 tgpig[[threadgroup_position_in_grid]], ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_q8_0_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_q8_0_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } // mat-vec kernel processing in chunks of float4 @@ -3404,104 +3410,215 @@ template [[host_name("kernel_mul_mv_ext_q6_K_f32_r1_3")]] kernel mul_mv_ext_q4x4 template [[host_name("kernel_mul_mv_ext_q6_K_f32_r1_4")]] kernel mul_mv_ext_q4x4_f32_t kernel_mul_mv_ext_q4x4_f32_disp<4, block_q6_K, 256, dequantize_q6_K>; template [[host_name("kernel_mul_mv_ext_q6_K_f32_r1_5")]] kernel mul_mv_ext_q4x4_f32_t kernel_mul_mv_ext_q4x4_f32_disp<5, block_q6_K, 256, dequantize_q6_K>; -#define N_MV_T_T 4 - -template -void kernel_mul_mv_impl( +template +void kernel_mul_mv_t_t_impl( args_t args, device const char * src0, device const char * src1, device char * dst, + threadgroup char * shmem, uint3 tgpig, - ushort tiisg) { - const int r0 = tgpig.x; - const int rb = tgpig.y*N_MV_T_T; + ushort tiisg, + ushort sgitg) { + const short NSG = FC_mul_mv_nsg; + + constexpr short NB = 32; + constexpr short NF = 8; + + const int nb = args.ne00/NB; + + const int r0 = tgpig.x*NR0; + const int r1 = tgpig.y; const int im = tgpig.z; const uint i12 = im%args.ne12; const uint i13 = im/args.ne12; - const uint64_t offset0 = r0*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03; + //const uint64_t offset0 = r0*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03; + const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13; - device const T0 * x = (device const T0 *) (src0 + offset0); + //device const T0 * x = (device const T0 *) (src0 + offset0); + device const T1 * y = (device const T1 *) (src1 + offset1); - device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1; + // pointers to src0 rows + device const T0 * ax [NR0]; + FOR_UNROLL (short row = 0; row < NR0; ++row) { + const uint64_t offset0 = (r0 + row)*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03; - if (args.ne00 < 128) { - for (int row = 0; row < N_MV_T_T; ++row) { - int r1 = rb + row; - if (r1 >= args.ne11) { - break; - } + ax[row] = (device const T0 *) ((device char *) src0 + offset0); + } - const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13; + float sumf[NR0] = { 0.f }; - device const T1 * y = (device const T1 *) (src1 + offset1); + const short ix = tiisg/(NW/NF); + const short il = tiisg%(NW/NF); - float sumf = 0; - for (int i = tiisg; i < args.ne00; i += 32) { - sumf += (T0) x[i] * (T1) y[i]; - } + const int ib0 = sgitg*NF + ix; - float sum_all = simd_sum(sumf); - if (tiisg == 0) { - dst_f32[(uint64_t)r1*args.ne0 + r0] = sum_all; - } + T1 yl[NF]; + + device const T1 * yb = y + (ib0*NB + il*NF); + + for (int ib = ib0; ib < nb; ib += NSG*NF) { + for (short i = 0; i < NF; ++i) { + yl[i] = yb[i]; } - } else { - device const T04 * x4 = (device const T04 *) x; - for (int row = 0; row < N_MV_T_T; ++row) { - int r1 = rb + row; - if (r1 >= args.ne11) { - break; + + for (short row = 0; row < NR0; row++) { + device const T0 * xb = ax[row] + (ib*NB + il*NF); + + float sumq = 0.f; + FOR_UNROLL (short i = 0; i < NF; ++i) { + sumq += xb[i] * yl[i]; } - const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13; + sumf[row] += sumq; + } - device const T1 * y = (device const T1 *) (src1 + offset1); - device const T14 * y4 = (device const T14 *) y; + yb += NSG*NF*NW; + } - float sumf = 0; - for (int i = tiisg; i < args.ne00/4; i += 32) { - sumf += dot((float4) x4[i], (float4) y4[i]); - } - - float sum_all = simd_sum(sumf); - if (tiisg == 0) { - for (int i = 4*(args.ne00/4); i < args.ne00; ++i) sum_all += (float) (x[i] * y[i]); - dst_f32[(uint64_t)r1*args.ne0 + r0] = sum_all; - } + for (int i = nb*NB + sgitg*NW + tiisg; i < args.ne00; i += NW*NSG) { + for (short row = 0; row < NR0; row++) { + sumf[row] += ax[row][i] * y[i]; } } + + device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0; + + helper_mv_reduce_and_write(dst_f32, sumf, r0, args.ne01, tiisg, sgitg, shmem); } -template -kernel void kernel_mul_mv( +template +kernel void kernel_mul_mv_t_t( constant ggml_metal_kargs_mul_mv & args, device const char * src0, device const char * src1, device char * dst, + threadgroup char * shmem [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], - ushort tiisg[[thread_index_in_simdgroup]]) { - kernel_mul_mv_impl( - args, - src0, - src1, - dst, - tgpig, - tiisg); + ushort tiisg[[thread_index_in_simdgroup]], + ushort sgitg[[simdgroup_index_in_threadgroup]]) { + kernel_mul_mv_t_t_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -typedef decltype(kernel_mul_mv) mul_mv_t; +typedef decltype(kernel_mul_mv_t_t) mul_mv_t_t; -template [[host_name("kernel_mul_mv_f32_f32")]] kernel mul_mv_t kernel_mul_mv; -template [[host_name("kernel_mul_mv_f16_f32")]] kernel mul_mv_t kernel_mul_mv; -template [[host_name("kernel_mul_mv_f16_f16")]] kernel mul_mv_t kernel_mul_mv; +template [[host_name("kernel_mul_mv_f32_f32")]] kernel mul_mv_t_t kernel_mul_mv_t_t; +template [[host_name("kernel_mul_mv_f16_f32")]] kernel mul_mv_t_t kernel_mul_mv_t_t; +template [[host_name("kernel_mul_mv_f16_f16")]] kernel mul_mv_t_t kernel_mul_mv_t_t; #if defined(GGML_METAL_HAS_BF16) -template [[host_name("kernel_mul_mv_bf16_f32")]] kernel mul_mv_t kernel_mul_mv; -template [[host_name("kernel_mul_mv_bf16_bf16")]] kernel mul_mv_t kernel_mul_mv; +template [[host_name("kernel_mul_mv_bf16_f32")]] kernel mul_mv_t_t kernel_mul_mv_t_t; +template [[host_name("kernel_mul_mv_bf16_bf16")]] kernel mul_mv_t_t kernel_mul_mv_t_t; #endif +template +void kernel_mul_mv_t_t_4_impl( + args_t args, + device const char * src0, + device const char * src1, + device char * dst, + threadgroup char * shmem, + uint3 tgpig, + ushort tiisg, + ushort sgitg) { + const short NSG = FC_mul_mv_nsg; + + constexpr short NB = 32; + constexpr short NF = 16; + constexpr short NF4 = NF/4; + + const int nb = args.ne00/NB; + + const int r0 = tgpig.x*NR0; + const int r1 = tgpig.y; + const int im = tgpig.z; + + const uint i12 = im%args.ne12; + const uint i13 = im/args.ne12; + + //const uint64_t offset0 = r0*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03; + const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13; + + device const T1 * y = (device const T1 *) (src1 + offset1); + device const T14 * y4 = (device const T14 *) (src1 + offset1); + + // pointers to src0 rows + device const T0 * ax [NR0]; + device const T04 * ax4[NR0]; + FOR_UNROLL (short row = 0; row < NR0; ++row) { + const uint64_t offset0 = (r0 + row)*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03; + + ax [row] = (device const T0 *) ((device char *) src0 + offset0); + ax4[row] = (device const T04 *) ((device char *) src0 + offset0); + } + + float sumf[NR0] = { 0.f }; + + const short ix = tiisg/(NW/NF); + const short il = tiisg%(NW/NF); + + const int ib0 = sgitg*NF + ix; + + T14 yl4[NF4]; + + device const T14 * yb4 = y4 + (ib0*NB + il*NF)/4; + + for (int ib = ib0; ib < nb; ib += NSG*NF) { + for (short i = 0; i < NF4; ++i) { + yl4[i] = yb4[i]; + } + + for (short row = 0; row < NR0; row++) { + device const T04 * xb4 = ax4[row] + (ib*NB + il*NF)/4; + + float sumq = 0.f; + FOR_UNROLL (short i = 0; i < NF4; ++i) { + sumq += dot(float4(xb4[i]), float4(yl4[i])); + } + + sumf[row] += sumq; + } + + yb4 += NSG*NF*NW/4; + } + + for (int i = nb*NB + sgitg*NW + tiisg; i < args.ne00; i += NW*NSG) { + for (short row = 0; row < NR0; row++) { + sumf[row] += ax[row][i] * y[i]; + } + } + + device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0; + + helper_mv_reduce_and_write(dst_f32, sumf, r0, args.ne01, tiisg, sgitg, shmem); +} + +template +kernel void kernel_mul_mv_t_t_4( + constant ggml_metal_kargs_mul_mv & args, + device const char * src0, + device const char * src1, + device char * dst, + threadgroup char * shmem [[threadgroup(0)]], + uint3 tgpig[[threadgroup_position_in_grid]], + ushort tiisg[[thread_index_in_simdgroup]], + ushort sgitg[[simdgroup_index_in_threadgroup]]) { + kernel_mul_mv_t_t_4_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); +} + +typedef decltype(kernel_mul_mv_t_t_4) mul_mv_t_t_4; + +template [[host_name("kernel_mul_mv_f32_f32_4")]] kernel mul_mv_t_t_4 kernel_mul_mv_t_t_4; +template [[host_name("kernel_mul_mv_f16_f32_4")]] kernel mul_mv_t_t_4 kernel_mul_mv_t_t_4; +template [[host_name("kernel_mul_mv_f16_f16_4")]] kernel mul_mv_t_t_4 kernel_mul_mv_t_t_4; +#if defined(GGML_METAL_HAS_BF16) +template [[host_name("kernel_mul_mv_bf16_f32_4")]] kernel mul_mv_t_t_4 kernel_mul_mv_t_t_4; +template [[host_name("kernel_mul_mv_bf16_bf16_4")]] kernel mul_mv_t_t_4 kernel_mul_mv_t_t_4; +#endif + +#define N_MV_T_T 4 + template void kernel_mul_mv_c4_impl( args_t args, @@ -3562,112 +3679,10 @@ typedef decltype(kernel_mul_mv_c4) mul_mv_c4_t; template [[host_name("kernel_mul_mv_f32_f32_c4")]] kernel mul_mv_c4_t kernel_mul_mv_c4; template [[host_name("kernel_mul_mv_f16_f32_c4")]] kernel mul_mv_c4_t kernel_mul_mv_c4; +template [[host_name("kernel_mul_mv_f16_f16_c4")]] kernel mul_mv_c4_t kernel_mul_mv_c4; #if defined(GGML_METAL_HAS_BF16) -template [[host_name("kernel_mul_mv_bf16_f32_c4")]] kernel mul_mv_c4_t kernel_mul_mv_c4; -#endif - -template -kernel void kernel_mul_mv_1row( - constant ggml_metal_kargs_mul_mv & args, - device const char * src0, - device const char * src1, - device char * dst, - uint3 tgpig[[threadgroup_position_in_grid]], - ushort tiisg[[thread_index_in_simdgroup]]) { - - const int r0 = tgpig.x; - const int r1 = tgpig.y; - const int im = tgpig.z; - - const uint i12 = im%args.ne12; - const uint i13 = im/args.ne12; - - const uint64_t offset0 = r0*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03; - const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13; - - device const T * x = (device const T *) (src0 + offset0); - device const float * y = (device const float *) (src1 + offset1); - - device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0; - - float sumf = 0; - if (args.ne00 < 128) { - for (int i = tiisg; i < args.ne00; i += 32) { - sumf += (float) x[i] * (float) y[i]; - } - float sum_all = simd_sum(sumf); - if (tiisg == 0) { - dst_f32[r0] = sum_all; - } - } else { - device const T4 * x4 = (device const T4 *) x; - device const float4 * y4 = (device const float4 *) y; - - for (int i = tiisg; i < args.ne00/4; i += 32) { - sumf += dot((float4) x4[i], y4[i]); - } - - float sum_all = simd_sum(sumf); - - if (tiisg == 0) { - for (int i = 4*(args.ne00/4); i < args.ne00; ++i) sum_all += (float) (x[i] * y[i]); - dst_f32[r0] = sum_all; - } - } -} - -typedef decltype(kernel_mul_mv_1row) mul_mv_1row_t; - -template [[host_name("kernel_mul_mv_f16_f32_1row")]] kernel mul_mv_1row_t kernel_mul_mv_1row; -#if defined(GGML_METAL_HAS_BF16) -template [[host_name("kernel_mul_mv_bf16_f32_1row")]] kernel mul_mv_1row_t kernel_mul_mv_1row; -#endif - -// Assumes row size (ne00) is a multiple of 4 -template -kernel void kernel_mul_mv_l4( - constant ggml_metal_kargs_mul_mv & args, - device const char * src0, - device const char * src1, - device char * dst, - uint3 tgpig[[threadgroup_position_in_grid]], - ushort tiisg[[thread_index_in_simdgroup]]) { - - const int nrows = args.ne11; - const int r0 = tgpig.x; - const int im = tgpig.z; - - const uint i12 = im%args.ne12; - const uint i13 = im/args.ne12; - - const uint64_t offset0 = r0*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03; - - device const T4 * x4 = (device const T4 *) (src0 + offset0); - - device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1; - - for (int r1 = 0; r1 < nrows; ++r1) { - const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13; - - device const float4 * y4 = (device const float4 *) (src1 + offset1); - - float sumf = 0; - for (int i = tiisg; i < args.ne00/4; i += 32) { - sumf += dot((float4) x4[i], y4[i]); - } - - float sum_all = simd_sum(sumf); - if (tiisg == 0) { - dst_f32[(uint64_t)r1*args.ne0 + r0] = sum_all; - } - } -} - -typedef decltype(kernel_mul_mv_l4) mul_mv_l4_t; - -template [[host_name("kernel_mul_mv_f16_f32_l4")]] kernel mul_mv_l4_t kernel_mul_mv_l4; -#if defined(GGML_METAL_HAS_BF16) -template [[host_name("kernel_mul_mv_bf16_f32_l4")]] kernel mul_mv_l4_t kernel_mul_mv_l4; +template [[host_name("kernel_mul_mv_bf16_f32_c4")]] kernel mul_mv_c4_t kernel_mul_mv_c4; +template [[host_name("kernel_mul_mv_bf16_bf16_c4")]] kernel mul_mv_c4_t kernel_mul_mv_c4; #endif static float rope_yarn_ramp(const float low, const float high, const int i0) { @@ -5951,7 +5966,7 @@ kernel void kernel_concat( } } -template +template void kernel_mul_mv_q2_K_f32_impl( args_t args, device const char * src0, @@ -5961,13 +5976,15 @@ void kernel_mul_mv_q2_K_f32_impl( uint3 tgpig, ushort tiisg, ushort sgitg) { + const short NSG = FC_mul_mv_nsg; const int nb = args.ne00/QK_K; + const int r0 = tgpig.x; const int r1 = tgpig.y; const int im = tgpig.z; - const int first_row = (r0 * nsg + sgitg) * nr0; + const int first_row = (r0 * NSG + sgitg) * nr0; const uint i12 = im%args.ne12; const uint i13 = im/args.ne12; @@ -6051,10 +6068,10 @@ kernel void kernel_mul_mv_q2_K_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_q2_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); + kernel_mul_mv_q2_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_q3_K_f32_impl( args_t args, device const char * src0, @@ -6064,6 +6081,7 @@ void kernel_mul_mv_q3_K_f32_impl( uint3 tgpig, ushort tiisg, ushort sgitg) { + const short NSG = FC_mul_mv_nsg; const int nb = args.ne00/QK_K; @@ -6071,7 +6089,7 @@ void kernel_mul_mv_q3_K_f32_impl( const int r1 = tgpig.y; const int im = tgpig.z; - const int first_row = (r0 * nsg + sgitg) * nr0; + const int first_row = (r0 * NSG + sgitg) * nr0; const uint i12 = im%args.ne12; const uint i13 = im/args.ne12; @@ -6215,10 +6233,10 @@ kernel void kernel_mul_mv_q3_K_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_q3_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); + kernel_mul_mv_q3_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_q4_K_f32_impl( args_t args, device const char * src0, @@ -6228,6 +6246,8 @@ void kernel_mul_mv_q4_K_f32_impl( uint3 tgpig, ushort tiisg, ushort sgitg) { + const short NSG = FC_mul_mv_nsg; + const uint16_t kmask1 = 0x3f3f; const uint16_t kmask2 = 0x0f0f; const uint16_t kmask3 = 0xc0c0; @@ -6243,7 +6263,7 @@ void kernel_mul_mv_q4_K_f32_impl( const int r1 = tgpig.y; const int im = tgpig.z; - const int first_row = (r0 * nsg + sgitg) * nr0; + const int first_row = (r0 * NSG + sgitg) * nr0; const uint i12 = im%args.ne12; const uint i13 = im/args.ne12; @@ -6337,10 +6357,10 @@ kernel void kernel_mul_mv_q4_K_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_q4_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); + kernel_mul_mv_q4_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_q5_K_f32_impl( args_t args, device const char * src0, @@ -6350,6 +6370,7 @@ void kernel_mul_mv_q5_K_f32_impl( uint3 tgpig, ushort tiisg, ushort sgitg) { + const short NSG = FC_mul_mv_nsg; const int nb = args.ne00/QK_K; @@ -6357,7 +6378,7 @@ void kernel_mul_mv_q5_K_f32_impl( const int r1 = tgpig.y; const int im = tgpig.z; - const int first_row = (r0 * nsg + sgitg) * nr0; + const int first_row = (r0 * NSG + sgitg) * nr0; const uint i12 = im%args.ne12; const uint i13 = im/args.ne12; @@ -6468,10 +6489,10 @@ kernel void kernel_mul_mv_q5_K_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_q5_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); + kernel_mul_mv_q5_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_q6_K_f32_impl( args_t args, device const char * src0, @@ -6481,6 +6502,7 @@ void kernel_mul_mv_q6_K_f32_impl( uint3 tgpig, ushort tiisg, ushort sgitg) { + const short NSG = FC_mul_mv_nsg; const uint8_t kmask1 = 0x03; const uint8_t kmask2 = 0x0C; @@ -6493,7 +6515,7 @@ void kernel_mul_mv_q6_K_f32_impl( const int r1 = tgpig.y; const int im = tgpig.z; - const int first_row = (r0 * nsg + sgitg) * nr0; + const int first_row = (r0 * NSG + sgitg) * nr0; const uint i12 = im%args.ne12; const uint i13 = im/args.ne12; @@ -6577,12 +6599,12 @@ kernel void kernel_mul_mv_q6_K_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_q6_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); + kernel_mul_mv_q6_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); } // ======================= "True" 2-bit -template +template void kernel_mul_mv_iq2_xxs_f32_impl( args_t args, device const char * src0, @@ -6592,13 +6614,15 @@ void kernel_mul_mv_iq2_xxs_f32_impl( uint3 tgpig, ushort tiisg, ushort sgitg) { + const short NSG = FC_mul_mv_nsg; const int nb = args.ne00/QK_K; + const int r0 = tgpig.x; const int r1 = tgpig.y; const int im = tgpig.z; - const int first_row = (r0 * nsg + sgitg) * nr0; + const int first_row = (r0 * NSG + sgitg) * nr0; const uint i12 = im%args.ne12; const uint i13 = im/args.ne12; @@ -6685,10 +6709,10 @@ kernel void kernel_mul_mv_iq2_xxs_f32( uint3 tgpig[[threadgroup_position_in_grid]], ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_iq2_xxs_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_iq2_xxs_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_iq2_xs_f32_impl( args_t args, device const char * src0, @@ -6698,13 +6722,15 @@ void kernel_mul_mv_iq2_xs_f32_impl( uint3 tgpig, ushort tiisg, ushort sgitg) { + const short NSG = FC_mul_mv_nsg; const int nb = args.ne00/QK_K; + const int r0 = tgpig.x; const int r1 = tgpig.y; const int im = tgpig.z; - const int first_row = (r0 * nsg + sgitg) * nr0; + const int first_row = (r0 * NSG + sgitg) * nr0; const uint i12 = im%args.ne12; const uint i13 = im/args.ne12; @@ -6802,10 +6828,10 @@ kernel void kernel_mul_mv_iq2_xs_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_iq2_xs_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_iq2_xs_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_iq3_xxs_f32_impl( args_t args, device const char * src0, @@ -6815,13 +6841,15 @@ void kernel_mul_mv_iq3_xxs_f32_impl( uint3 tgpig, ushort tiisg, ushort sgitg) { + const short NSG = FC_mul_mv_nsg; const int nb = args.ne00/QK_K; + const int r0 = tgpig.x; const int r1 = tgpig.y; const int im = tgpig.z; - const int first_row = (r0 * nsg + sgitg) * nr0; + const int first_row = (r0 * NSG + sgitg) * nr0; const uint i12 = im%args.ne12; const uint i13 = im/args.ne12; @@ -6912,10 +6940,10 @@ kernel void kernel_mul_mv_iq3_xxs_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_iq3_xxs_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_iq3_xxs_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_iq3_s_f32_impl( args_t args, device const char * src0, @@ -6925,13 +6953,15 @@ void kernel_mul_mv_iq3_s_f32_impl( uint3 tgpig, ushort tiisg, ushort sgitg) { + const short NSG = FC_mul_mv_nsg; const int nb = args.ne00/QK_K; + const int r0 = tgpig.x; const int r1 = tgpig.y; const int im = tgpig.z; - const int first_row = (r0 * nsg + sgitg) * nr0; + const int first_row = (r0 * NSG + sgitg) * nr0; const uint i12 = im%args.ne12; const uint i13 = im/args.ne12; @@ -7022,10 +7052,10 @@ kernel void kernel_mul_mv_iq3_s_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_iq3_s_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_iq3_s_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_iq2_s_f32_impl( args_t args, device const char * src0, @@ -7035,13 +7065,15 @@ void kernel_mul_mv_iq2_s_f32_impl( uint3 tgpig, ushort tiisg, ushort sgitg) { + const short NSG = FC_mul_mv_nsg; const int nb = args.ne00/QK_K; + const int r0 = tgpig.x; const int r1 = tgpig.y; const int im = tgpig.z; - const int first_row = (r0 * nsg + sgitg) * nr0; + const int first_row = (r0 * NSG + sgitg) * nr0; const uint i12 = im%args.ne12; const uint i13 = im/args.ne12; @@ -7133,10 +7165,10 @@ kernel void kernel_mul_mv_iq2_s_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_iq2_s_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_iq2_s_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_iq1_s_f32_impl( args_t args, device const char * src0, @@ -7146,13 +7178,15 @@ void kernel_mul_mv_iq1_s_f32_impl( uint3 tgpig, ushort tiisg, ushort sgitg) { + const short NSG = FC_mul_mv_nsg; const int nb = args.ne00/QK_K; + const int r0 = tgpig.x; const int r1 = tgpig.y; const int im = tgpig.z; - const int first_row = (r0 * nsg + sgitg) * nr0; + const int first_row = (r0 * NSG + sgitg) * nr0; const uint i12 = im%args.ne12; const uint i13 = im/args.ne12; @@ -7230,10 +7264,10 @@ kernel void kernel_mul_mv_iq1_s_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_iq1_s_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); + kernel_mul_mv_iq1_s_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_iq1_m_f32_impl( args_t args, device const char * src0, @@ -7243,6 +7277,7 @@ void kernel_mul_mv_iq1_m_f32_impl( uint3 tgpig, ushort tiisg, ushort sgitg) { + const short NSG = FC_mul_mv_nsg; const int nb = args.ne00/QK_K; @@ -7250,7 +7285,7 @@ void kernel_mul_mv_iq1_m_f32_impl( const int r1 = tgpig.y; const int im = tgpig.z; - const int first_row = (r0 * nsg + sgitg) * nr0; + const int first_row = (r0 * NSG + sgitg) * nr0; const uint i12 = im%args.ne12; const uint i13 = im/args.ne12; @@ -7338,10 +7373,10 @@ kernel void kernel_mul_mv_iq1_m_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_iq1_m_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); + kernel_mul_mv_iq1_m_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_iq4_nl_f32_impl( args_t args, device const char * src0, @@ -7351,6 +7386,7 @@ void kernel_mul_mv_iq4_nl_f32_impl( uint3 tgpig, ushort tiisg, ushort sgitg) { + const short NSG = FC_mul_mv_nsg; threadgroup float * shmem_f32 = (threadgroup float *) shmem; const int nb = args.ne00/QK4_NL; @@ -7359,7 +7395,7 @@ void kernel_mul_mv_iq4_nl_f32_impl( const int r1 = tgpig.y; const int im = tgpig.z; - const int first_row = (r0 * nsg + sgitg) * nr0; + const int first_row = (r0 * NSG + sgitg) * nr0; const uint i12 = im%args.ne12; const uint i13 = im/args.ne12; @@ -7444,10 +7480,10 @@ kernel void kernel_mul_mv_iq4_nl_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_iq4_nl_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_iq4_nl_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_iq4_xs_f32_impl( args_t args, device const char * src0, @@ -7457,13 +7493,15 @@ void kernel_mul_mv_iq4_xs_f32_impl( uint3 tgpig, ushort tiisg, ushort sgitg) { + const short NSG = FC_mul_mv_nsg; threadgroup float * shmem_f32 = (threadgroup float *) shmem; const int nb = args.ne00/QK_K; + const int r0 = tgpig.x; const int r1 = tgpig.y; const int im = tgpig.z; - const int first_row = (r0 * nsg + sgitg) * nr0; + const int first_row = (r0 * NSG + sgitg) * nr0; const uint i12 = im%args.ne12; const uint i13 = im/args.ne12; @@ -7549,10 +7587,10 @@ kernel void kernel_mul_mv_iq4_xs_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_iq4_xs_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_iq4_xs_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_mxfp4_f32_impl( args_t args, device const char * src0, @@ -7562,6 +7600,7 @@ void kernel_mul_mv_mxfp4_f32_impl( uint3 tgpig, ushort tiisg, ushort sgitg) { + const short NSG = FC_mul_mv_nsg; threadgroup float * shmem_f32 = (threadgroup float *) shmem; const int nb = args.ne00/QK_MXFP4; @@ -7570,7 +7609,7 @@ void kernel_mul_mv_mxfp4_f32_impl( const int r1 = tgpig.y; const int im = tgpig.z; - const int first_row = (r0 * nsg + sgitg) * nr0; + const int first_row = (r0 * NSG + sgitg) * nr0; const uint i12 = im%args.ne12; const uint i13 = im/args.ne12; @@ -7638,7 +7677,7 @@ kernel void kernel_mul_mv_mxfp4_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_mxfp4_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_mxfp4_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } template @@ -8314,7 +8353,7 @@ void mmv_fn( impl_fn(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -typedef decltype(mmv_fn>) mul_mv_impl_fn_t; +typedef decltype(mmv_fn>) mul_mv_impl_fn_t; template kernel void kernel_mul_mv_id( @@ -8379,36 +8418,44 @@ kernel void kernel_mul_mv_id( sgitg); } -typedef decltype(kernel_mul_mv_id>>) kernel_mul_mv_id_t; +typedef decltype(kernel_mul_mv_id>>) kernel_mul_mv_id_t; -template [[host_name("kernel_mul_mv_id_f32_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_f16_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +typedef decltype(kernel_mul_mv_id>>) kernel_mul_mv_id_4_t; + +template [[host_name("kernel_mul_mv_id_f32_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_f16_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; #if defined(GGML_METAL_HAS_BF16) -template [[host_name("kernel_mul_mv_id_bf16_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_bf16_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +#endif +template [[host_name("kernel_mul_mv_id_f32_f32_4")]] kernel kernel_mul_mv_id_4_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_f16_f32_4")]] kernel kernel_mul_mv_id_4_t kernel_mul_mv_id>>; +#if defined(GGML_METAL_HAS_BF16) +template [[host_name("kernel_mul_mv_id_bf16_f32_4")]] kernel kernel_mul_mv_id_4_t kernel_mul_mv_id>>; #endif -template [[host_name("kernel_mul_mv_id_q8_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_q4_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_q4_1_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_q5_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_q5_1_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q8_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_mxfp4_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q4_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q4_1_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q5_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q5_1_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_q2_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_q3_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_q4_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_q5_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_q6_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_iq1_s_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_iq1_m_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_iq2_xxs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_iq2_xs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_iq3_xxs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_iq3_s_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_iq2_s_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_iq4_nl_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_iq4_xs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_mxfp4_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; + +template [[host_name("kernel_mul_mv_id_q2_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q3_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q4_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q5_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q6_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_iq1_s_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_iq1_m_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_iq2_xxs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_iq2_xs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_iq3_xxs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_iq3_s_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_iq2_s_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_iq4_nl_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_iq4_xs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; kernel void kernel_pool_2d_max_f32( constant ggml_metal_kargs_pool_2d & args, From e58174cecbc45bf79bf653cd2c984395940c6ef4 Mon Sep 17 00:00:00 2001 From: Georgi Gerganov Date: Thu, 18 Sep 2025 12:47:56 +0300 Subject: [PATCH 32/52] llama : bump max seq limit from 64 to 256 (#15916) ggml-ci --- src/llama-cparams.h | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/llama-cparams.h b/src/llama-cparams.h index dbbaba9f62..eae7b839f4 100644 --- a/src/llama-cparams.h +++ b/src/llama-cparams.h @@ -4,7 +4,7 @@ #include -#define LLAMA_MAX_SEQ 64 +#define LLAMA_MAX_SEQ 256 struct llama_cparams { uint32_t n_ctx; // context size used during inference From 2b6b55a59f590a1e1eb2dcd09d5b8b6feb9cc748 Mon Sep 17 00:00:00 2001 From: Radoslav Gerganov Date: Thu, 18 Sep 2025 13:36:57 +0300 Subject: [PATCH 33/52] server : include usage statistics only when user request them (#16052) * server : include usage statistics only when user request them When serving the OpenAI compatible API, we should check if {"stream_options": {"include_usage": true} is set in the request when deciding whether we should send usage statistics closes: #16048 * add unit test --- tools/server/server.cpp | 59 +++++++++++-------- .../server/tests/unit/test_chat_completion.py | 4 ++ 2 files changed, 37 insertions(+), 26 deletions(-) diff --git a/tools/server/server.cpp b/tools/server/server.cpp index 5e5698e672..c0ffe17692 100644 --- a/tools/server/server.cpp +++ b/tools/server/server.cpp @@ -111,6 +111,7 @@ static bool server_task_type_need_logits(server_task_type task_type) { struct slot_params { bool stream = true; + bool include_usage = false; bool cache_prompt = true; // remember the prompt to avoid reprocessing all prompt bool return_tokens = false; bool return_progress = false; @@ -310,17 +311,19 @@ struct server_task { params.verbose = params_base.verbosity > 9; params.timings_per_token = json_value(data, "timings_per_token", false); - params.stream = json_value(data, "stream", false); - params.cache_prompt = json_value(data, "cache_prompt", true); - params.return_tokens = json_value(data, "return_tokens", false); - params.return_progress = json_value(data, "return_progress", false); - params.n_predict = json_value(data, "n_predict", json_value(data, "max_tokens", defaults.n_predict)); - 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.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()); + params.stream = json_value(data, "stream", false); + auto stream_opt = json_value(data, "stream_options", json::object()); + params.include_usage = json_value(stream_opt, "include_usage", false); + params.cache_prompt = json_value(data, "cache_prompt", true); + params.return_tokens = json_value(data, "return_tokens", false); + params.return_progress = json_value(data, "return_progress", false); + params.n_predict = json_value(data, "n_predict", json_value(data, "max_tokens", defaults.n_predict)); + 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.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()); params.sampling.top_k = json_value(data, "top_k", defaults.sampling.top_k); params.sampling.top_p = json_value(data, "top_p", defaults.sampling.top_p); @@ -775,6 +778,7 @@ struct server_task_result_cmpl_final : server_task_result { llama_tokens tokens; bool stream; + bool include_usage; result_timings timings; std::string prompt; @@ -982,21 +986,23 @@ struct server_task_result_cmpl_final : server_task_result { {"object", "chat.completion.chunk"}, }); - // OpenAI API spec for chat.completion.chunks specifies an empty `choices` array for the last chunk when including usage - // https://platform.openai.com/docs/api-reference/chat_streaming/streaming#chat_streaming/streaming-choices - deltas.push_back({ - {"choices", json::array()}, - {"created", t}, - {"id", oaicompat_cmpl_id}, - {"model", oaicompat_model}, - {"system_fingerprint", build_info}, - {"object", "chat.completion.chunk"}, - {"usage", json { - {"completion_tokens", n_decoded}, - {"prompt_tokens", n_prompt_tokens}, - {"total_tokens", n_decoded + n_prompt_tokens}, - }}, - }); + if (include_usage) { + // OpenAI API spec for chat.completion.chunks specifies an empty `choices` array for the last chunk when including usage + // https://platform.openai.com/docs/api-reference/chat_streaming/streaming#chat_streaming/streaming-choices + deltas.push_back({ + {"choices", json::array()}, + {"created", t}, + {"id", oaicompat_cmpl_id}, + {"model", oaicompat_model}, + {"system_fingerprint", build_info}, + {"object", "chat.completion.chunk"}, + {"usage", json { + {"completion_tokens", n_decoded}, + {"prompt_tokens", n_prompt_tokens}, + {"total_tokens", n_decoded + n_prompt_tokens}, + }}, + }); + } if (timings.prompt_n >= 0) { deltas.back().push_back({"timings", timings.to_json()}); @@ -2815,6 +2821,7 @@ struct server_context { res->verbose = slot.params.verbose; res->stream = slot.params.stream; + res->include_usage = slot.params.include_usage; res->oaicompat = slot.params.oaicompat; res->oaicompat_model = slot.params.oaicompat_model; res->oaicompat_cmpl_id = slot.params.oaicompat_cmpl_id; diff --git a/tools/server/tests/unit/test_chat_completion.py b/tools/server/tests/unit/test_chat_completion.py index 53421d1b57..2979ed4bb7 100644 --- a/tools/server/tests/unit/test_chat_completion.py +++ b/tools/server/tests/unit/test_chat_completion.py @@ -271,8 +271,10 @@ def test_chat_completion_with_timings_per_token(): "max_tokens": 10, "messages": [{"role": "user", "content": "test"}], "stream": True, + "stream_options": {"include_usage": True}, "timings_per_token": True, }) + stats_received = False for i, data in enumerate(res): if i == 0: # Check first role message for stream=True @@ -288,6 +290,8 @@ def test_chat_completion_with_timings_per_token(): assert "predicted_per_second" in data["timings"] assert "predicted_n" in data["timings"] assert data["timings"]["predicted_n"] <= 10 + stats_received = True + assert stats_received def test_logprobs(): From ad6bd9083bc346afd4ecd2fbb83e0306c0141c99 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Sigbj=C3=B8rn=20Skj=C3=A6ret?= Date: Thu, 18 Sep 2025 13:28:22 +0200 Subject: [PATCH 34/52] cuda : add missing F32<->I32 entries in ggml_cuda_cpy_fn (#16060) --- ggml/src/ggml-cuda/cpy.cu | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/ggml/src/ggml-cuda/cpy.cu b/ggml/src/ggml-cuda/cpy.cu index 8567c3d5a1..1b763a6289 100644 --- a/ggml/src/ggml-cuda/cpy.cu +++ b/ggml/src/ggml-cuda/cpy.cu @@ -441,6 +441,10 @@ void* ggml_cuda_cpy_fn(const ggml_tensor * src0, ggml_tensor * src1) { return (void*) cpy_flt>; } else if (src0->type == GGML_TYPE_BF16 && src1->type == GGML_TYPE_F32) { return (void*) cpy_flt>; + } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_I32) { + return (void*) cpy_flt>; + } else if (src0->type == GGML_TYPE_I32 && src1->type == GGML_TYPE_F32) { + return (void*) cpy_flt>; } else { GGML_ABORT("%s: unsupported type combination (%s to %s)\n", __func__, ggml_type_name(src0->type), ggml_type_name(src1->type)); From 703f9e32c4eb3166f8d63007c26e31a1466c21af Mon Sep 17 00:00:00 2001 From: Georgi Gerganov Date: Thu, 18 Sep 2025 16:28:41 +0300 Subject: [PATCH 35/52] metal : use function constants for mul_mv_ext kernels (#16074) * metal : use function constants for mul_mv_ext kernels ggml-ci * metal : remove NW template argument ggml-ci * metal : adjust constants ggml-ci --- ggml/src/ggml-metal/ggml-metal-device.cpp | 33 +-- ggml/src/ggml-metal/ggml-metal-device.h | 2 +- ggml/src/ggml-metal/ggml-metal-impl.h | 7 +- ggml/src/ggml-metal/ggml-metal-ops.cpp | 5 +- ggml/src/ggml-metal/ggml-metal.metal | 271 +++++++++++----------- 5 files changed, 155 insertions(+), 163 deletions(-) diff --git a/ggml/src/ggml-metal/ggml-metal-device.cpp b/ggml/src/ggml-metal/ggml-metal-device.cpp index bada84cef3..fe015afc54 100644 --- a/ggml/src/ggml-metal/ggml-metal-device.cpp +++ b/ggml/src/ggml-metal/ggml-metal-device.cpp @@ -414,19 +414,26 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_rwkv(ggml_metal_library_t 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 r1ptg) { +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) { 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", base); + 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; } - res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr); + 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; } @@ -608,7 +615,7 @@ 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", base); + snprintf(name, 256, "%s_nsg=%d", base, nsg); ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); if (res) { @@ -824,7 +831,7 @@ 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", base); + snprintf(name, 256, "%s_nsg=%d", base, nsg); ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name); if (res) { @@ -923,11 +930,8 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext( dk, dv); - snprintf(name, 256, "kernel_%s_%s_dk%d_dv%d_mask=%d_sinks=%d_bias=%d_scap=%d_ns10=%d_ns20=%d_nsg=%d", - "flash_attn_ext", - ggml_type_name(op->src[1]->type), - dk, - dv, + snprintf(name, 256, "%s_mask=%d_sinks=%d_bias=%d_scap=%d_ns10=%d_ns20=%d_nsg=%d", + base, has_mask, has_sinks, has_bias, @@ -985,11 +989,8 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext_vec( dk, dv); - snprintf(name, 256, "kernel_%s_%s_dk%d_dv%d_mask=%d_sink=%d_bias=%d_softcap=%d_ns10=%d_ns20=%d_nsg=%d_nwg=%d", - "flash_attn_ext_vec", - ggml_type_name(op->src[1]->type), - dk, - dv, + snprintf(name, 256, "%s_mask=%d_sink=%d_bias=%d_softcap=%d_ns10=%d_ns20=%d_nsg=%d_nwg=%d", + base, has_mask, has_sinks, has_bias, @@ -1033,7 +1034,7 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext_vec_reduce( char name[256]; snprintf(base, 256, "kernel_flash_attn_ext_vec_reduce"); - snprintf(name, 256, "kernel_flash_attn_ext_vec_reduce_dv=%d_nwg=%d", dv, nwg); + 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) { diff --git a/ggml/src/ggml-metal/ggml-metal-device.h b/ggml/src/ggml-metal/ggml-metal-device.h index 4a3a819fc0..044d6953f6 100644 --- a/ggml/src/ggml-metal/ggml-metal-device.h +++ b/ggml/src/ggml-metal/ggml-metal-device.h @@ -114,7 +114,7 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_soft_max (ggml_me 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 r1ptg); +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, enum ggml_type tsrc0, enum ggml_type tsrc1); 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); diff --git a/ggml/src/ggml-metal/ggml-metal-impl.h b/ggml/src/ggml-metal/ggml-metal-impl.h index b257296540..3a7a4f317c 100644 --- a/ggml/src/ggml-metal/ggml-metal-impl.h +++ b/ggml/src/ggml-metal/ggml-metal-impl.h @@ -35,13 +35,13 @@ #define N_R0_Q3_K 2 #define N_SG_Q3_K 2 -#define N_R0_Q4_K 4 +#define N_R0_Q4_K 2 #define N_SG_Q4_K 2 #define N_R0_Q5_K 2 #define N_SG_Q5_K 2 -#define N_R0_Q6_K 1 +#define N_R0_Q6_K 2 #define N_SG_Q6_K 2 #define N_R0_IQ1_S 4 @@ -374,9 +374,6 @@ typedef struct { int32_t ne1; int16_t r2; int16_t r3; - int16_t nsg; - int16_t nxpsg; - int16_t r1ptg; } ggml_metal_kargs_mul_mv_ext; typedef struct { diff --git a/ggml/src/ggml-metal/ggml-metal-ops.cpp b/ggml/src/ggml-metal/ggml-metal-ops.cpp index a28206e786..04665b3d6d 100644 --- a/ggml/src/ggml-metal/ggml-metal-ops.cpp +++ b/ggml/src/ggml-metal/ggml-metal-ops.cpp @@ -1444,7 +1444,7 @@ 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, r1ptg); + 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); ggml_metal_kargs_mul_mv_ext args = { /*.ne00 =*/ ne00, @@ -1465,9 +1465,6 @@ int ggml_metal_op_mul_mat(ggml_metal_op_t ctx, int idx) { /*.ne1 =*/ ne1, /*.r2 =*/ r2, /*.r3 =*/ r3, - /*.nsg =*/ nsg, - /*.nxpsg =*/ nxpsg, - /*.r1ptg =*/ r1ptg, }; ggml_metal_encoder_set_pipeline(enc, pipeline); diff --git a/ggml/src/ggml-metal/ggml-metal.metal b/ggml/src/ggml-metal/ggml-metal.metal index 20ceb1fe04..c7d97ba70b 100644 --- a/ggml/src/ggml-metal/ggml-metal.metal +++ b/ggml/src/ggml-metal/ggml-metal.metal @@ -2843,7 +2843,7 @@ inline float block_q_n_dot_y(device const block_q5_1 * qb_curr, float sumy, thre return d * (acc[0] + acc[1] + acc[2] + acc[3]) + sumy * m; } -template +template static inline void helper_mv_reduce_and_write( device float * dst_f32, float sumf[NR0], @@ -2852,6 +2852,8 @@ static inline void helper_mv_reduce_and_write( ushort tiisg, ushort sgitg, threadgroup char * shmem) { + constexpr short NW = N_SIMDWIDTH; + threadgroup float * shmem_f32[NR0]; for (short row = 0; row < NR0; ++row) { @@ -2883,9 +2885,10 @@ static inline void helper_mv_reduce_and_write( } } -constant short FC_mul_mv_nsg [[function_constant(FC_MUL_MV + 0)]]; +constant short FC_mul_mv_nsg [[function_constant(FC_MUL_MV + 0)]]; +constant short FC_mul_mv_nxpsg [[function_constant(FC_MUL_MV + 1)]]; -template +template void mul_vec_q_n_f32_impl( args_t args, device const char * src0, @@ -2897,6 +2900,7 @@ void mul_vec_q_n_f32_impl( ushort sgitg) { const short NSG = FC_mul_mv_nsg; + constexpr short NW = N_SIMDWIDTH; constexpr short NQ = 16; const int nb = args.ne00/QK4_0; @@ -2961,7 +2965,7 @@ void mul_vec_q_n_f32_impl( device float * dst_f32 = (device float *) dst + im*args.ne0*args.ne1 + r1*args.ne0; - //helper_mv_reduce_and_write(dst_f32, sumf, r0, args.ne01, tiisg, sgitg, shmem); + //helper_mv_reduce_and_write(dst_f32, sumf, r0, args.ne01, tiisg, sgitg, shmem); for (int row = 0; row < NR0; ++row) { const float tot = simd_sum(sumf[row]); @@ -2981,7 +2985,7 @@ kernel void kernel_mul_mv_q4_0_f32( uint3 tgpig[[threadgroup_position_in_grid]], ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - mul_vec_q_n_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + mul_vec_q_n_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } kernel void kernel_mul_mv_q4_1_f32( @@ -2993,7 +2997,7 @@ kernel void kernel_mul_mv_q4_1_f32( uint3 tgpig[[threadgroup_position_in_grid]], ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - mul_vec_q_n_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + mul_vec_q_n_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } kernel void kernel_mul_mv_q5_0_f32( @@ -3005,7 +3009,7 @@ kernel void kernel_mul_mv_q5_0_f32( uint3 tgpig[[threadgroup_position_in_grid]], ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - mul_vec_q_n_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + mul_vec_q_n_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } kernel void kernel_mul_mv_q5_1_f32( @@ -3017,10 +3021,10 @@ kernel void kernel_mul_mv_q5_1_f32( uint3 tgpig[[threadgroup_position_in_grid]], ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - mul_vec_q_n_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + mul_vec_q_n_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_q8_0_f32_impl( args_t args, device const char * src0, @@ -3032,6 +3036,7 @@ void kernel_mul_mv_q8_0_f32_impl( ushort sgitg) { const short NSG = FC_mul_mv_nsg; + constexpr short NW = N_SIMDWIDTH; constexpr short NQ = 8; const int nb = args.ne00/QK8_0; @@ -3090,7 +3095,7 @@ void kernel_mul_mv_q8_0_f32_impl( device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0; - helper_mv_reduce_and_write(dst_f32, sumf, r0, args.ne01, tiisg, sgitg, shmem); + helper_mv_reduce_and_write(dst_f32, sumf, r0, args.ne01, tiisg, sgitg, shmem); } [[host_name("kernel_mul_mv_q8_0_f32")]] @@ -3103,12 +3108,12 @@ kernel void kernel_mul_mv_q8_0_f32( uint3 tgpig[[threadgroup_position_in_grid]], ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_q8_0_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_q8_0_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } // mat-vec kernel processing in chunks of float4 // chpb - chunks per quantization block -template +template void kernel_mul_mv_ext_q4_f32_impl( constant ggml_metal_kargs_mul_mv_ext & args, device const char * src0, @@ -3117,6 +3122,9 @@ void kernel_mul_mv_ext_q4_f32_impl( uint3 tgpig[[threadgroup_position_in_grid]], ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { + const short NSG = FC_mul_mv_nsg; + const short nxpsg = FC_mul_mv_nxpsg; + const short chpt = 4; // chunks per thread //const short nxpsg = (32); @@ -3125,7 +3133,7 @@ void kernel_mul_mv_ext_q4_f32_impl( const short tx = tiisg%nxpsg; const short ty = tiisg/nxpsg; - const int i01 = tgpig.x*(nypsg*args.nsg) + nypsg*sgitg + ty; + const int i01 = tgpig.x*(nypsg*NSG) + nypsg*sgitg + ty; const int i11 = tgpig.y*r1ptg; const int i1m = tgpig.z; @@ -3208,7 +3216,7 @@ void kernel_mul_mv_ext_q4_f32_impl( } // mat-vec kernel processing in chunks of float4x4 -template +template void kernel_mul_mv_ext_q4x4_f32_impl( constant ggml_metal_kargs_mul_mv_ext & args, device const char * src0, @@ -3217,6 +3225,9 @@ void kernel_mul_mv_ext_q4x4_f32_impl( uint3 tgpig[[threadgroup_position_in_grid]], ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { + const short NSG = FC_mul_mv_nsg; + const short nxpsg = FC_mul_mv_nxpsg; + const short chpt = 1; //const short nxpsg = (32); @@ -3225,7 +3236,7 @@ void kernel_mul_mv_ext_q4x4_f32_impl( const short tx = tiisg%nxpsg; const short ty = tiisg/nxpsg; - const int i01 = tgpig.x*(nypsg*args.nsg) + nypsg*sgitg + ty; + const int i01 = tgpig.x*(nypsg*NSG) + nypsg*sgitg + ty; const int i11 = tgpig.y*r1ptg; const int i1m = tgpig.z; @@ -3322,12 +3333,7 @@ kernel void kernel_mul_mv_ext_q4_f32_disp( uint3 tgpig[[threadgroup_position_in_grid]], ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - switch (args.nxpsg) { - case 4: kernel_mul_mv_ext_q4_f32_impl<4, r1ptg, q_t, epb/4, deq_t4>(args, src0, src1, dst, tgpig, tiisg, sgitg); break; - case 8: kernel_mul_mv_ext_q4_f32_impl<8, r1ptg, q_t, epb/4, deq_t4>(args, src0, src1, dst, tgpig, tiisg, sgitg); break; - case 16: kernel_mul_mv_ext_q4_f32_impl<16, r1ptg, q_t, epb/4, deq_t4>(args, src0, src1, dst, tgpig, tiisg, sgitg); break; - case 32: kernel_mul_mv_ext_q4_f32_impl<32, r1ptg, q_t, epb/4, deq_t4>(args, src0, src1, dst, tgpig, tiisg, sgitg); break; - } + kernel_mul_mv_ext_q4_f32_impl(args, src0, src1, dst, tgpig, tiisg, sgitg); } template @@ -3339,12 +3345,7 @@ kernel void kernel_mul_mv_ext_q4x4_f32_disp( uint3 tgpig[[threadgroup_position_in_grid]], ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - switch (args.nxpsg) { - case 4: kernel_mul_mv_ext_q4x4_f32_impl<4, r1ptg, q_t, epb/16, deq_t4x4>(args, src0, src1, dst, tgpig, tiisg, sgitg); break; - case 8: kernel_mul_mv_ext_q4x4_f32_impl<8, r1ptg, q_t, epb/16, deq_t4x4>(args, src0, src1, dst, tgpig, tiisg, sgitg); break; - case 16: kernel_mul_mv_ext_q4x4_f32_impl<16, r1ptg, q_t, epb/16, deq_t4x4>(args, src0, src1, dst, tgpig, tiisg, sgitg); break; - case 32: kernel_mul_mv_ext_q4x4_f32_impl<32, r1ptg, q_t, epb/16, deq_t4x4>(args, src0, src1, dst, tgpig, tiisg, sgitg); break; - } + kernel_mul_mv_ext_q4x4_f32_impl(args, src0, src1, dst, tgpig, tiisg, sgitg); } typedef decltype(kernel_mul_mv_ext_q4_f32_disp <2, block_q8_0, 32, dequantize_q8_0_t4>) mul_mv_ext_q4_f32_t; @@ -3410,7 +3411,7 @@ template [[host_name("kernel_mul_mv_ext_q6_K_f32_r1_3")]] kernel mul_mv_ext_q4x4 template [[host_name("kernel_mul_mv_ext_q6_K_f32_r1_4")]] kernel mul_mv_ext_q4x4_f32_t kernel_mul_mv_ext_q4x4_f32_disp<4, block_q6_K, 256, dequantize_q6_K>; template [[host_name("kernel_mul_mv_ext_q6_K_f32_r1_5")]] kernel mul_mv_ext_q4x4_f32_t kernel_mul_mv_ext_q4x4_f32_disp<5, block_q6_K, 256, dequantize_q6_K>; -template +template void kernel_mul_mv_t_t_impl( args_t args, device const char * src0, @@ -3422,6 +3423,7 @@ void kernel_mul_mv_t_t_impl( ushort sgitg) { const short NSG = FC_mul_mv_nsg; + constexpr short NW = N_SIMDWIDTH; constexpr short NB = 32; constexpr short NF = 8; @@ -3486,10 +3488,10 @@ void kernel_mul_mv_t_t_impl( device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0; - helper_mv_reduce_and_write(dst_f32, sumf, r0, args.ne01, tiisg, sgitg, shmem); + helper_mv_reduce_and_write(dst_f32, sumf, r0, args.ne01, tiisg, sgitg, shmem); } -template +template kernel void kernel_mul_mv_t_t( constant ggml_metal_kargs_mul_mv & args, device const char * src0, @@ -3499,20 +3501,20 @@ kernel void kernel_mul_mv_t_t( uint3 tgpig[[threadgroup_position_in_grid]], ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_t_t_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_t_t_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -typedef decltype(kernel_mul_mv_t_t) mul_mv_t_t; +typedef decltype(kernel_mul_mv_t_t) mul_mv_t_t; -template [[host_name("kernel_mul_mv_f32_f32")]] kernel mul_mv_t_t kernel_mul_mv_t_t; -template [[host_name("kernel_mul_mv_f16_f32")]] kernel mul_mv_t_t kernel_mul_mv_t_t; -template [[host_name("kernel_mul_mv_f16_f16")]] kernel mul_mv_t_t kernel_mul_mv_t_t; +template [[host_name("kernel_mul_mv_f32_f32")]] kernel mul_mv_t_t kernel_mul_mv_t_t; +template [[host_name("kernel_mul_mv_f16_f32")]] kernel mul_mv_t_t kernel_mul_mv_t_t; +template [[host_name("kernel_mul_mv_f16_f16")]] kernel mul_mv_t_t kernel_mul_mv_t_t; #if defined(GGML_METAL_HAS_BF16) -template [[host_name("kernel_mul_mv_bf16_f32")]] kernel mul_mv_t_t kernel_mul_mv_t_t; -template [[host_name("kernel_mul_mv_bf16_bf16")]] kernel mul_mv_t_t kernel_mul_mv_t_t; +template [[host_name("kernel_mul_mv_bf16_f32")]] kernel mul_mv_t_t kernel_mul_mv_t_t; +template [[host_name("kernel_mul_mv_bf16_bf16")]] kernel mul_mv_t_t kernel_mul_mv_t_t; #endif -template +template void kernel_mul_mv_t_t_4_impl( args_t args, device const char * src0, @@ -3524,6 +3526,7 @@ void kernel_mul_mv_t_t_4_impl( ushort sgitg) { const short NSG = FC_mul_mv_nsg; + constexpr short NW = N_SIMDWIDTH; constexpr short NB = 32; constexpr short NF = 16; constexpr short NF4 = NF/4; @@ -3591,10 +3594,10 @@ void kernel_mul_mv_t_t_4_impl( device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0; - helper_mv_reduce_and_write(dst_f32, sumf, r0, args.ne01, tiisg, sgitg, shmem); + helper_mv_reduce_and_write(dst_f32, sumf, r0, args.ne01, tiisg, sgitg, shmem); } -template +template kernel void kernel_mul_mv_t_t_4( constant ggml_metal_kargs_mul_mv & args, device const char * src0, @@ -3604,17 +3607,17 @@ kernel void kernel_mul_mv_t_t_4( uint3 tgpig[[threadgroup_position_in_grid]], ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_t_t_4_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_t_t_4_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -typedef decltype(kernel_mul_mv_t_t_4) mul_mv_t_t_4; +typedef decltype(kernel_mul_mv_t_t_4) mul_mv_t_t_4; -template [[host_name("kernel_mul_mv_f32_f32_4")]] kernel mul_mv_t_t_4 kernel_mul_mv_t_t_4; -template [[host_name("kernel_mul_mv_f16_f32_4")]] kernel mul_mv_t_t_4 kernel_mul_mv_t_t_4; -template [[host_name("kernel_mul_mv_f16_f16_4")]] kernel mul_mv_t_t_4 kernel_mul_mv_t_t_4; +template [[host_name("kernel_mul_mv_f32_f32_4")]] kernel mul_mv_t_t_4 kernel_mul_mv_t_t_4; +template [[host_name("kernel_mul_mv_f16_f32_4")]] kernel mul_mv_t_t_4 kernel_mul_mv_t_t_4; +template [[host_name("kernel_mul_mv_f16_f16_4")]] kernel mul_mv_t_t_4 kernel_mul_mv_t_t_4; #if defined(GGML_METAL_HAS_BF16) -template [[host_name("kernel_mul_mv_bf16_f32_4")]] kernel mul_mv_t_t_4 kernel_mul_mv_t_t_4; -template [[host_name("kernel_mul_mv_bf16_bf16_4")]] kernel mul_mv_t_t_4 kernel_mul_mv_t_t_4; +template [[host_name("kernel_mul_mv_bf16_f32_4")]] kernel mul_mv_t_t_4 kernel_mul_mv_t_t_4; +template [[host_name("kernel_mul_mv_bf16_bf16_4")]] kernel mul_mv_t_t_4 kernel_mul_mv_t_t_4; #endif #define N_MV_T_T 4 @@ -5966,7 +5969,7 @@ kernel void kernel_concat( } } -template +template void kernel_mul_mv_q2_K_f32_impl( args_t args, device const char * src0, @@ -6068,10 +6071,10 @@ kernel void kernel_mul_mv_q2_K_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_q2_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); + kernel_mul_mv_q2_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_q3_K_f32_impl( args_t args, device const char * src0, @@ -6233,10 +6236,10 @@ kernel void kernel_mul_mv_q3_K_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_q3_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); + kernel_mul_mv_q3_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_q4_K_f32_impl( args_t args, device const char * src0, @@ -6248,9 +6251,9 @@ void kernel_mul_mv_q4_K_f32_impl( ushort sgitg) { const short NSG = FC_mul_mv_nsg; - const uint16_t kmask1 = 0x3f3f; - const uint16_t kmask2 = 0x0f0f; - const uint16_t kmask3 = 0xc0c0; + constexpr uint16_t kmask1 = 0x3f3f; + constexpr uint16_t kmask2 = 0x0f0f; + constexpr uint16_t kmask3 = 0xc0c0; const short ix = tiisg/8; // 0...3 const short it = tiisg%8; // 0...7 @@ -6309,7 +6312,7 @@ void kernel_mul_mv_q4_K_f32_impl( float4 acc1 = {0.f, 0.f, 0.f, 0.f}; float4 acc2 = {0.f, 0.f, 0.f, 0.f}; - for (short i = 0; i < 4; ++i) { + FOR_UNROLL (short i = 0; i < 4; ++i) { acc1[0] += yl[2*i + 0] * (q1[i] & 0x000F); acc1[1] += yl[2*i + 1] * (q1[i] & 0x0F00); acc1[2] += yl[2*i + 8] * (q1[i] & 0x00F0); @@ -6320,14 +6323,11 @@ void kernel_mul_mv_q4_K_f32_impl( acc2[3] += yh[2*i + 9] * (q2[i] & 0xF000); } - float dall = dh[0]; - float dmin = dh[1]; - - sumf[row] += dall * ((acc1[0] + 1.f/256.f * acc1[1]) * sc8[0] + - (acc1[2] + 1.f/256.f * acc1[3]) * sc8[1] * 1.f/16.f + - (acc2[0] + 1.f/256.f * acc2[1]) * sc8[4] + - (acc2[2] + 1.f/256.f * acc2[3]) * sc8[5] * 1.f/16.f) - - dmin * (sumy[0] * sc8[2] + sumy[1] * sc8[3] + sumy[2] * sc8[6] + sumy[3] * sc8[7]); + sumf[row] += dh[0] * ((acc1[0] + 1.f/256.f * acc1[1]) * sc8[0] + + (acc1[2] + 1.f/256.f * acc1[3]) * sc8[1] * 1.f/16.f + + (acc2[0] + 1.f/256.f * acc2[1]) * sc8[4] + + (acc2[2] + 1.f/256.f * acc2[3]) * sc8[5] * 1.f/16.f) - + dh[1] * (sumy[0] * sc8[2] + sumy[1] * sc8[3] + sumy[2] * sc8[6] + sumy[3] * sc8[7]); q1 += args.nb01/2; sc += args.nb01/2; @@ -6357,10 +6357,10 @@ kernel void kernel_mul_mv_q4_K_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_q4_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); + kernel_mul_mv_q4_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_q5_K_f32_impl( args_t args, device const char * src0, @@ -6393,9 +6393,9 @@ void kernel_mul_mv_q5_K_f32_impl( float yl[16], yh[16]; - const uint16_t kmask1 = 0x3f3f; - const uint16_t kmask2 = 0x0f0f; - const uint16_t kmask3 = 0xc0c0; + constexpr uint16_t kmask1 = 0x3f3f; + constexpr uint16_t kmask2 = 0x0f0f; + constexpr uint16_t kmask3 = 0xc0c0; const short tid = tiisg/4; const short ix = tiisg%4; @@ -6441,7 +6441,7 @@ void kernel_mul_mv_q5_K_f32_impl( float4 acc1 = {0.f}; float4 acc2 = {0.f}; - for (short l = 0; l < 8; ++l) { + FOR_UNROLL (short l = 0; l < 8; ++l) { uint8_t h = qh[l]; acc1[0] += yl[l+0] * (q1[l] & 0x0F); acc1[1] += yl[l+8] * (q1[l] & 0xF0); @@ -6452,13 +6452,12 @@ void kernel_mul_mv_q5_K_f32_impl( acc2[2] += h & hm3 ? yh[l+0] : 0.f; acc2[3] += h & hm4 ? yh[l+8] : 0.f; } - const float dall = dh[0]; - const float dmin = dh[1]; - sumf[row] += dall * (sc8[0] * (acc1[0] + 16.f*acc2[0]) + - sc8[1] * (acc1[1]/16.f + 16.f*acc2[1]) + - sc8[4] * (acc1[2] + 16.f*acc2[2]) + - sc8[5] * (acc1[3]/16.f + 16.f*acc2[3])) - - dmin * (sumy[0] * sc8[2] + sumy[1] * sc8[3] + sumy[2] * sc8[6] + sumy[3] * sc8[7]); + + sumf[row] += dh[0] * (sc8[0] * (acc1[0] + 16.f*acc2[0]) + + sc8[1] * (acc1[1]/16.f + 16.f*acc2[1]) + + sc8[4] * (acc1[2] + 16.f*acc2[2]) + + sc8[5] * (acc1[3]/16.f + 16.f*acc2[3])) - + dh[1] * (sumy[0] * sc8[2] + sumy[1] * sc8[3] + sumy[2] * sc8[6] + sumy[3] * sc8[7]); q1 += args.nb01; qh += args.nb01; @@ -6489,10 +6488,10 @@ kernel void kernel_mul_mv_q5_K_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_q5_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); + kernel_mul_mv_q5_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_q6_K_f32_impl( args_t args, device const char * src0, @@ -6504,10 +6503,10 @@ void kernel_mul_mv_q6_K_f32_impl( ushort sgitg) { const short NSG = FC_mul_mv_nsg; - const uint8_t kmask1 = 0x03; - const uint8_t kmask2 = 0x0C; - const uint8_t kmask3 = 0x30; - const uint8_t kmask4 = 0xC0; + constexpr uint8_t kmask1 = 0x03; + constexpr uint8_t kmask2 = 0x0C; + constexpr uint8_t kmask3 = 0x30; + constexpr uint8_t kmask4 = 0xC0; const int nb = args.ne00/QK_K; @@ -6558,18 +6557,16 @@ void kernel_mul_mv_q6_K_f32_impl( } for (short row = 0; row < nr0; ++row) { - const float dall = dh[0]; - float4 sums = {0.f, 0.f, 0.f, 0.f}; - for (short l = 0; l < 4; ++l) { + FOR_UNROLL (short l = 0; l < 4; ++l) { sums[0] += yl[4*l + 0] * ((int8_t)((q1[l] & 0xF) | ((qh[l] & kmask1) << 4)) - 32); sums[1] += yl[4*l + 1] * ((int8_t)((q2[l] & 0xF) | ((qh[l] & kmask2) << 2)) - 32); sums[2] += yl[4*l + 2] * ((int8_t)((q1[l] >> 4) | ((qh[l] & kmask3) << 0)) - 32); sums[3] += yl[4*l + 3] * ((int8_t)((q2[l] >> 4) | ((qh[l] & kmask4) >> 2)) - 32); } - sumf[row] += dall * (sums[0] * sc[0] + sums[1] * sc[2] + sums[2] * sc[4] + sums[3] * sc[6]); + sumf[row] += dh[0] * (sums[0] * sc[0] + sums[1] * sc[2] + sums[2] * sc[4] + sums[3] * sc[6]); q1 += args.nb01; q2 += args.nb01; @@ -6599,12 +6596,12 @@ kernel void kernel_mul_mv_q6_K_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_q6_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); + kernel_mul_mv_q6_K_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); } // ======================= "True" 2-bit -template +template void kernel_mul_mv_iq2_xxs_f32_impl( args_t args, device const char * src0, @@ -6709,10 +6706,10 @@ kernel void kernel_mul_mv_iq2_xxs_f32( uint3 tgpig[[threadgroup_position_in_grid]], ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_iq2_xxs_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_iq2_xxs_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_iq2_xs_f32_impl( args_t args, device const char * src0, @@ -6828,10 +6825,10 @@ kernel void kernel_mul_mv_iq2_xs_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_iq2_xs_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_iq2_xs_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_iq3_xxs_f32_impl( args_t args, device const char * src0, @@ -6940,10 +6937,10 @@ kernel void kernel_mul_mv_iq3_xxs_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_iq3_xxs_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_iq3_xxs_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_iq3_s_f32_impl( args_t args, device const char * src0, @@ -7052,10 +7049,10 @@ kernel void kernel_mul_mv_iq3_s_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_iq3_s_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_iq3_s_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_iq2_s_f32_impl( args_t args, device const char * src0, @@ -7165,10 +7162,10 @@ kernel void kernel_mul_mv_iq2_s_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_iq2_s_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_iq2_s_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_iq1_s_f32_impl( args_t args, device const char * src0, @@ -7264,10 +7261,10 @@ kernel void kernel_mul_mv_iq1_s_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_iq1_s_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); + kernel_mul_mv_iq1_s_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_iq1_m_f32_impl( args_t args, device const char * src0, @@ -7373,10 +7370,10 @@ kernel void kernel_mul_mv_iq1_m_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_iq1_m_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); + kernel_mul_mv_iq1_m_f32_impl(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_iq4_nl_f32_impl( args_t args, device const char * src0, @@ -7480,10 +7477,10 @@ kernel void kernel_mul_mv_iq4_nl_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_iq4_nl_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_iq4_nl_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_iq4_xs_f32_impl( args_t args, device const char * src0, @@ -7587,10 +7584,10 @@ kernel void kernel_mul_mv_iq4_xs_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_iq4_xs_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_iq4_xs_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -template +template void kernel_mul_mv_mxfp4_f32_impl( args_t args, device const char * src0, @@ -7677,7 +7674,7 @@ kernel void kernel_mul_mv_mxfp4_f32( ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]) { - kernel_mul_mv_mxfp4_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); + kernel_mul_mv_mxfp4_f32_impl(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } template @@ -8353,7 +8350,7 @@ void mmv_fn( impl_fn(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg); } -typedef decltype(mmv_fn>) mul_mv_impl_fn_t; +typedef decltype(mmv_fn>) mul_mv_impl_fn_t; template kernel void kernel_mul_mv_id( @@ -8418,44 +8415,44 @@ kernel void kernel_mul_mv_id( sgitg); } -typedef decltype(kernel_mul_mv_id>>) kernel_mul_mv_id_t; +typedef decltype(kernel_mul_mv_id>>) kernel_mul_mv_id_t; -typedef decltype(kernel_mul_mv_id>>) kernel_mul_mv_id_4_t; +typedef decltype(kernel_mul_mv_id>>) kernel_mul_mv_id_4_t; -template [[host_name("kernel_mul_mv_id_f32_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_f16_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_f32_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_f16_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; #if defined(GGML_METAL_HAS_BF16) -template [[host_name("kernel_mul_mv_id_bf16_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_bf16_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; #endif -template [[host_name("kernel_mul_mv_id_f32_f32_4")]] kernel kernel_mul_mv_id_4_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_f16_f32_4")]] kernel kernel_mul_mv_id_4_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_f32_f32_4")]] kernel kernel_mul_mv_id_4_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_f16_f32_4")]] kernel kernel_mul_mv_id_4_t kernel_mul_mv_id>>; #if defined(GGML_METAL_HAS_BF16) -template [[host_name("kernel_mul_mv_id_bf16_f32_4")]] kernel kernel_mul_mv_id_4_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_bf16_f32_4")]] kernel kernel_mul_mv_id_4_t kernel_mul_mv_id>>; #endif -template [[host_name("kernel_mul_mv_id_q8_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q8_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_q4_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_q4_1_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_q5_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_q5_1_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q4_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q4_1_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q5_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q5_1_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_mxfp4_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_mxfp4_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_q2_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_q3_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_q4_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_q5_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_q6_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_iq1_s_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_iq1_m_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_iq2_xxs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_iq2_xs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_iq3_xxs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_iq3_s_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_iq2_s_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_iq4_nl_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; -template [[host_name("kernel_mul_mv_id_iq4_xs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q2_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q3_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q4_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q5_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q6_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_iq1_s_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_iq1_m_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_iq2_xxs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_iq2_xs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_iq3_xxs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_iq3_s_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_iq2_s_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_iq4_nl_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_iq4_xs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; kernel void kernel_pool_2d_max_f32( constant ggml_metal_kargs_pool_2d & args, From 4ca088b036313c2d8e682f4cfeb7c29edd85d0b9 Mon Sep 17 00:00:00 2001 From: Eric Curtin Date: Thu, 18 Sep 2025 16:22:50 +0100 Subject: [PATCH 36/52] Add resumable downloads for llama-server model loading (#15963) - Implement resumable downloads in common_download_file_single function - Add detection of partial download files (.downloadInProgress) - Check server support for HTTP Range requests via Accept-Ranges header - Implement HTTP Range request with "bytes=-" header - Open files in append mode when resuming vs create mode for new downloads Signed-off-by: Eric Curtin --- common/arg.cpp | 484 ++++++++++++++++++++++++++++--------------------- 1 file changed, 274 insertions(+), 210 deletions(-) diff --git a/common/arg.cpp b/common/arg.cpp index 9fd8858e82..54df2df872 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -57,12 +57,32 @@ static std::string read_file(const std::string & fname) { } static void write_file(const std::string & fname, const std::string & content) { - std::ofstream file(fname); + const std::string fname_tmp = fname + ".tmp"; + std::ofstream file(fname_tmp); if (!file) { throw std::runtime_error(string_format("error: failed to open file '%s'\n", fname.c_str())); } - file << content; - file.close(); + + try { + file << content; + file.close(); + + // Makes write atomic + if (rename(fname_tmp.c_str(), fname.c_str()) != 0) { + LOG_ERR("%s: unable to rename file: %s to %s\n", __func__, fname_tmp.c_str(), fname.c_str()); + // If rename fails, try to delete the temporary file + if (remove(fname_tmp.c_str()) != 0) { + LOG_ERR("%s: unable to delete temporary file: %s\n", __func__, fname_tmp.c_str()); + } + } + } catch (...) { + // If anything fails, try to delete the temporary file + if (remove(fname_tmp.c_str()) != 0) { + LOG_ERR("%s: unable to delete temporary file: %s\n", __func__, fname_tmp.c_str()); + } + + throw std::runtime_error(string_format("error: failed to write file '%s'\n", fname.c_str())); + } } common_arg & common_arg::set_examples(std::initializer_list examples) { @@ -217,250 +237,294 @@ struct curl_slist_ptr { } }; -#define CURL_MAX_RETRY 3 -#define CURL_RETRY_DELAY_SECONDS 2 - -static bool curl_perform_with_retry(const std::string & url, CURL * curl, int max_attempts, int retry_delay_seconds, const char * method_name) { - int remaining_attempts = max_attempts; - - while (remaining_attempts > 0) { - LOG_INF("%s: %s %s (attempt %d of %d)...\n", __func__ , method_name, url.c_str(), max_attempts - remaining_attempts + 1, max_attempts); - - CURLcode res = curl_easy_perform(curl); - if (res == CURLE_OK) { - return true; - } - - int exponential_backoff_delay = std::pow(retry_delay_seconds, max_attempts - remaining_attempts) * 1000; - LOG_WRN("%s: curl_easy_perform() failed: %s, retrying after %d milliseconds...\n", __func__, curl_easy_strerror(res), exponential_backoff_delay); - - remaining_attempts--; - if (remaining_attempts == 0) break; - std::this_thread::sleep_for(std::chrono::milliseconds(exponential_backoff_delay)); +static CURLcode common_curl_perf(CURL * curl) { + CURLcode res = curl_easy_perform(curl); + if (res != CURLE_OK) { + LOG_ERR("%s: curl_easy_perform() failed\n", __func__); } - LOG_ERR("%s: curl_easy_perform() failed after %d attempts\n", __func__, max_attempts); - - return false; + return res; } -// download one single file from remote URL to local path -static bool common_download_file_single(const std::string & url, const std::string & path, const std::string & bearer_token, bool offline) { - // Check if the file already exists locally - auto file_exists = std::filesystem::exists(path); - - // If the file exists, check its JSON metadata companion file. - std::string metadata_path = path + ".json"; - nlohmann::json metadata; // TODO @ngxson : get rid of this json, use regex instead +// Send a HEAD request to retrieve the etag and last-modified headers +struct common_load_model_from_url_headers { std::string etag; std::string last_modified; + std::string accept_ranges; +}; - if (file_exists) { - if (offline) { - LOG_INF("%s: using cached file (offline mode): %s\n", __func__, path.c_str()); - return true; // skip verification/downloading +struct FILE_deleter { + void operator()(FILE * f) const { fclose(f); } +}; + +static size_t common_header_callback(char * buffer, size_t, size_t n_items, void * userdata) { + common_load_model_from_url_headers * headers = (common_load_model_from_url_headers *) userdata; + static std::regex header_regex("([^:]+): (.*)\r\n"); + static std::regex etag_regex("ETag", std::regex_constants::icase); + static std::regex last_modified_regex("Last-Modified", std::regex_constants::icase); + static std::regex accept_ranges_regex("Accept-Ranges", std::regex_constants::icase); + std::string header(buffer, n_items); + std::smatch match; + if (std::regex_match(header, match, header_regex)) { + const std::string & key = match[1]; + const std::string & value = match[2]; + if (std::regex_match(key, match, etag_regex)) { + headers->etag = value; + } else if (std::regex_match(key, match, last_modified_regex)) { + headers->last_modified = value; + } else if (std::regex_match(key, match, accept_ranges_regex)) { + headers->accept_ranges = value; } - // Try and read the JSON metadata file (note: stream autoclosed upon exiting this block). - std::ifstream metadata_in(metadata_path); - if (metadata_in.good()) { - try { - metadata_in >> metadata; - LOG_DBG("%s: previous metadata file found %s: %s\n", __func__, metadata_path.c_str(), metadata.dump().c_str()); - if (metadata.contains("etag") && metadata.at("etag").is_string()) { - etag = metadata.at("etag"); - } - if (metadata.contains("lastModified") && metadata.at("lastModified").is_string()) { - last_modified = metadata.at("lastModified"); - } - } catch (const nlohmann::json::exception & e) { - LOG_ERR("%s: error reading metadata file %s: %s\n", __func__, metadata_path.c_str(), e.what()); - } - } - // if we cannot open the metadata file, we assume that the downloaded file is not valid (etag and last-modified are left empty, so we will download it again) - } else { - if (offline) { - LOG_ERR("%s: required file is not available in cache (offline mode): %s\n", __func__, path.c_str()); - return false; - } - LOG_INF("%s: no previous model file found %s\n", __func__, path.c_str()); } - // Send a HEAD request to retrieve the etag and last-modified headers - struct common_load_model_from_url_headers { - std::string etag; - std::string last_modified; - }; + return n_items; +} - common_load_model_from_url_headers headers; - bool head_request_ok = false; - bool should_download = !file_exists; // by default, we should download if the file does not exist +static size_t common_write_callback(void * data, size_t size, size_t nmemb, void * fd) { + return std::fwrite(data, size, nmemb, static_cast(fd)); +} - // Initialize libcurl - curl_ptr curl(curl_easy_init(), &curl_easy_cleanup); - curl_slist_ptr http_headers; +// helper function to hide password in URL +static std::string llama_download_hide_password_in_url(const std::string & url) { + // Use regex to match and replace the user[:password]@ pattern in URLs + // Pattern: scheme://[user[:password]@]host[...] + static const std::regex url_regex(R"(^(?:[A-Za-z][A-Za-z0-9+.-]://)(?:[^/@]+@)?.$)"); + std::smatch match; + + if (std::regex_match(url, match, url_regex)) { + // match[1] = scheme (e.g., "https://") + // match[2] = user[:password]@ part + // match[3] = rest of URL (host and path) + return match[1].str() + "********@" + match[3].str(); + } + + return url; // No credentials found or malformed URL +} + +static void common_curl_easy_setopt_head(CURL * curl, const std::string & url) { + // Set the URL, allow to follow http redirection + curl_easy_setopt(curl, CURLOPT_URL, url.c_str()); + curl_easy_setopt(curl, CURLOPT_FOLLOWLOCATION, 1L); + +# if defined(_WIN32) + // CURLSSLOPT_NATIVE_CA tells libcurl to use standard certificate store of + // operating system. Currently implemented under MS-Windows. + curl_easy_setopt(curl, CURLOPT_SSL_OPTIONS, CURLSSLOPT_NATIVE_CA); +# endif + + curl_easy_setopt(curl, CURLOPT_NOBODY, 1L); // will trigger the HEAD verb + curl_easy_setopt(curl, CURLOPT_NOPROGRESS, 1L); // hide head request progress + curl_easy_setopt(curl, CURLOPT_HEADERFUNCTION, common_header_callback); +} + +static void common_curl_easy_setopt_get(CURL * curl) { + curl_easy_setopt(curl, CURLOPT_NOBODY, 0L); + curl_easy_setopt(curl, CURLOPT_WRITEFUNCTION, common_write_callback); + + // display download progress + curl_easy_setopt(curl, CURLOPT_NOPROGRESS, 0L); +} + +static bool common_pull_file(CURL * curl, const std::string & path_temporary) { + if (std::filesystem::exists(path_temporary)) { + const std::string partial_size = std::to_string(std::filesystem::file_size(path_temporary)); + LOG_INF("%s: server supports range requests, resuming download from byte %s\n", __func__, partial_size.c_str()); + const std::string range_str = partial_size + "-"; + curl_easy_setopt(curl, CURLOPT_RANGE, range_str.c_str()); + } + + // Always open file in append mode could be resuming + std::unique_ptr outfile(fopen(path_temporary.c_str(), "ab")); + if (!outfile) { + LOG_ERR("%s: error opening local file for writing: %s\n", __func__, path_temporary.c_str()); + return false; + } + + common_curl_easy_setopt_get(curl); + curl_easy_setopt(curl, CURLOPT_WRITEDATA, outfile.get()); + + return common_curl_perf(curl) == CURLE_OK; +} + +static bool common_download_head(CURL * curl, + curl_slist_ptr & http_headers, + const std::string & url, + const std::string & bearer_token) { if (!curl) { LOG_ERR("%s: error initializing libcurl\n", __func__); return false; } - // Set the URL, allow to follow http redirection - curl_easy_setopt(curl.get(), CURLOPT_URL, url.c_str()); - curl_easy_setopt(curl.get(), CURLOPT_FOLLOWLOCATION, 1L); - http_headers.ptr = curl_slist_append(http_headers.ptr, "User-Agent: llama-cpp"); // Check if hf-token or bearer-token was specified if (!bearer_token.empty()) { std::string auth_header = "Authorization: Bearer " + bearer_token; - http_headers.ptr = curl_slist_append(http_headers.ptr, auth_header.c_str()); - } - curl_easy_setopt(curl.get(), CURLOPT_HTTPHEADER, http_headers.ptr); - -#if defined(_WIN32) - // CURLSSLOPT_NATIVE_CA tells libcurl to use standard certificate store of - // operating system. Currently implemented under MS-Windows. - curl_easy_setopt(curl.get(), CURLOPT_SSL_OPTIONS, CURLSSLOPT_NATIVE_CA); -#endif - - typedef size_t(*CURLOPT_HEADERFUNCTION_PTR)(char *, size_t, size_t, void *); - auto header_callback = [](char * buffer, size_t /*size*/, size_t n_items, void * userdata) -> size_t { - common_load_model_from_url_headers * headers = (common_load_model_from_url_headers *) userdata; - - static std::regex header_regex("([^:]+): (.*)\r\n"); - static std::regex etag_regex("ETag", std::regex_constants::icase); - static std::regex last_modified_regex("Last-Modified", std::regex_constants::icase); - - std::string header(buffer, n_items); - std::smatch match; - if (std::regex_match(header, match, header_regex)) { - const std::string & key = match[1]; - const std::string & value = match[2]; - if (std::regex_match(key, match, etag_regex)) { - headers->etag = value; - } else if (std::regex_match(key, match, last_modified_regex)) { - headers->last_modified = value; - } - } - return n_items; - }; - - curl_easy_setopt(curl.get(), CURLOPT_NOBODY, 1L); // will trigger the HEAD verb - curl_easy_setopt(curl.get(), CURLOPT_NOPROGRESS, 1L); // hide head request progress - curl_easy_setopt(curl.get(), CURLOPT_HEADERFUNCTION, static_cast(header_callback)); - curl_easy_setopt(curl.get(), CURLOPT_HEADERDATA, &headers); - - // we only allow retrying once for HEAD requests - // this is for the use case of using running offline (no internet), retrying can be annoying - bool was_perform_successful = curl_perform_with_retry(url, curl.get(), 1, 0, "HEAD"); - if (!was_perform_successful) { - head_request_ok = false; + http_headers.ptr = curl_slist_append(http_headers.ptr, auth_header.c_str()); } - long http_code = 0; - curl_easy_getinfo(curl.get(), CURLINFO_RESPONSE_CODE, &http_code); - if (http_code == 200) { - head_request_ok = true; - } else { - LOG_WRN("%s: HEAD invalid http status code received: %ld\n", __func__, http_code); - head_request_ok = false; - } + curl_easy_setopt(curl, CURLOPT_HTTPHEADER, http_headers.ptr); + common_curl_easy_setopt_head(curl, url); + return common_curl_perf(curl) == CURLE_OK; +} - // if head_request_ok is false, we don't have the etag or last-modified headers - // we leave should_download as-is, which is true if the file does not exist - if (head_request_ok) { - // check if ETag or Last-Modified headers are different - // if it is, we need to download the file again - if (!etag.empty() && etag != headers.etag) { - LOG_WRN("%s: ETag header is different (%s != %s): triggering a new download\n", __func__, etag.c_str(), headers.etag.c_str()); - should_download = true; - } else if (!last_modified.empty() && last_modified != headers.last_modified) { - LOG_WRN("%s: Last-Modified header is different (%s != %s): triggering a new download\n", __func__, last_modified.c_str(), headers.last_modified.c_str()); - should_download = true; - } - } +// download one single file from remote URL to local path +static bool common_download_file_single(const std::string & url, + const std::string & path, + const std::string & bearer_token, + bool offline) { + // If the file exists, check its JSON metadata companion file. + std::string metadata_path = path + ".json"; + static const int max_attempts = 3; + static const int retry_delay_seconds = 2; + for (int i = 0; i < max_attempts; ++i) { + nlohmann::json metadata; // TODO @ngxson : get rid of this json, use regex instead + std::string etag; + std::string last_modified; - if (should_download) { - std::string path_temporary = path + ".downloadInProgress"; + // Check if the file already exists locally + const auto file_exists = std::filesystem::exists(path); if (file_exists) { - LOG_WRN("%s: deleting previous downloaded file: %s\n", __func__, path.c_str()); - if (remove(path.c_str()) != 0) { - LOG_ERR("%s: unable to delete file: %s\n", __func__, path.c_str()); + if (offline) { + LOG_INF("%s: using cached file (offline mode): %s\n", __func__, path.c_str()); + return true; // skip verification/downloading + } + // Try and read the JSON metadata file (note: stream autoclosed upon exiting this block). + std::ifstream metadata_in(metadata_path); + if (metadata_in.good()) { + try { + metadata_in >> metadata; + LOG_DBG("%s: previous metadata file found %s: %s\n", __func__, metadata_path.c_str(), + metadata.dump().c_str()); + if (metadata.contains("etag") && metadata.at("etag").is_string()) { + etag = metadata.at("etag"); + } + if (metadata.contains("lastModified") && metadata.at("lastModified").is_string()) { + last_modified = metadata.at("lastModified"); + } + } catch (const nlohmann::json::exception & e) { + LOG_ERR("%s: error reading metadata file %s: %s\n", __func__, metadata_path.c_str(), e.what()); + } + } + // if we cannot open the metadata file, we assume that the downloaded file is not valid (etag and last-modified are left empty, so we will download it again) + } else { + if (offline) { + LOG_ERR("%s: required file is not available in cache (offline mode): %s\n", __func__, path.c_str()); return false; } + LOG_INF("%s: no previous model file found %s\n", __func__, path.c_str()); } - // Set the output file + bool head_request_ok = false; + bool should_download = !file_exists; // by default, we should download if the file does not exist - struct FILE_deleter { - void operator()(FILE * f) const { - fclose(f); - } - }; - - std::unique_ptr outfile(fopen(path_temporary.c_str(), "wb")); - if (!outfile) { - LOG_ERR("%s: error opening local file for writing: %s\n", __func__, path.c_str()); - return false; - } - - typedef size_t(*CURLOPT_WRITEFUNCTION_PTR)(void * data, size_t size, size_t nmemb, void * fd); - auto write_callback = [](void * data, size_t size, size_t nmemb, void * fd) -> size_t { - return fwrite(data, size, nmemb, (FILE *)fd); - }; - curl_easy_setopt(curl.get(), CURLOPT_NOBODY, 0L); - curl_easy_setopt(curl.get(), CURLOPT_WRITEFUNCTION, static_cast(write_callback)); - curl_easy_setopt(curl.get(), CURLOPT_WRITEDATA, outfile.get()); - - // display download progress - curl_easy_setopt(curl.get(), CURLOPT_NOPROGRESS, 0L); - - // helper function to hide password in URL - auto llama_download_hide_password_in_url = [](const std::string & url) -> std::string { - std::size_t protocol_pos = url.find("://"); - if (protocol_pos == std::string::npos) { - return url; // Malformed URL - } - - std::size_t at_pos = url.find('@', protocol_pos + 3); - if (at_pos == std::string::npos) { - return url; // No password in URL - } - - return url.substr(0, protocol_pos + 3) + "********" + url.substr(at_pos); - }; - - // start the download - LOG_INF("%s: trying to download model from %s to %s (server_etag:%s, server_last_modified:%s)...\n", __func__, - llama_download_hide_password_in_url(url).c_str(), path.c_str(), headers.etag.c_str(), headers.last_modified.c_str()); - bool was_perform_successful = curl_perform_with_retry(url, curl.get(), CURL_MAX_RETRY, CURL_RETRY_DELAY_SECONDS, "GET"); + // Initialize libcurl + curl_ptr curl(curl_easy_init(), &curl_easy_cleanup); + common_load_model_from_url_headers headers; + curl_easy_setopt(curl.get(), CURLOPT_HEADERDATA, &headers); + curl_slist_ptr http_headers; + const bool was_perform_successful = common_download_head(curl.get(), http_headers, url, bearer_token); if (!was_perform_successful) { - return false; + head_request_ok = false; } long http_code = 0; - curl_easy_getinfo (curl.get(), CURLINFO_RESPONSE_CODE, &http_code); - if (http_code < 200 || http_code >= 400) { - LOG_ERR("%s: invalid http status code received: %ld\n", __func__, http_code); - return false; + curl_easy_getinfo(curl.get(), CURLINFO_RESPONSE_CODE, &http_code); + if (http_code == 200) { + head_request_ok = true; + } else { + LOG_WRN("%s: HEAD invalid http status code received: %ld\n", __func__, http_code); + head_request_ok = false; } - // Causes file to be closed explicitly here before we rename it. - outfile.reset(); - - // Write the updated JSON metadata file. - metadata.update({ - {"url", url}, - {"etag", headers.etag}, - {"lastModified", headers.last_modified} - }); - write_file(metadata_path, metadata.dump(4)); - LOG_DBG("%s: file metadata saved: %s\n", __func__, metadata_path.c_str()); - - if (rename(path_temporary.c_str(), path.c_str()) != 0) { - LOG_ERR("%s: unable to rename file: %s to %s\n", __func__, path_temporary.c_str(), path.c_str()); - return false; + // if head_request_ok is false, we don't have the etag or last-modified headers + // we leave should_download as-is, which is true if the file does not exist + bool should_download_from_scratch = false; + if (head_request_ok) { + // check if ETag or Last-Modified headers are different + // if it is, we need to download the file again + if (!etag.empty() && etag != headers.etag) { + LOG_WRN("%s: ETag header is different (%s != %s): triggering a new download\n", __func__, etag.c_str(), + headers.etag.c_str()); + should_download = true; + should_download_from_scratch = true; + } else if (!last_modified.empty() && last_modified != headers.last_modified) { + LOG_WRN("%s: Last-Modified header is different (%s != %s): triggering a new download\n", __func__, + last_modified.c_str(), headers.last_modified.c_str()); + should_download = true; + should_download_from_scratch = true; + } } - } else { - LOG_INF("%s: using cached file: %s\n", __func__, path.c_str()); + + const bool accept_ranges_supported = !headers.accept_ranges.empty() && headers.accept_ranges != "none"; + if (should_download) { + if (file_exists && + !accept_ranges_supported) { // Resumable downloads not supported, delete and start again. + LOG_WRN("%s: deleting previous downloaded file: %s\n", __func__, path.c_str()); + if (remove(path.c_str()) != 0) { + LOG_ERR("%s: unable to delete file: %s\n", __func__, path.c_str()); + return false; + } + } + + const std::string path_temporary = path + ".downloadInProgress"; + if (should_download_from_scratch) { + if (std::filesystem::exists(path_temporary)) { + if (remove(path_temporary.c_str()) != 0) { + LOG_ERR("%s: unable to delete file: %s\n", __func__, path_temporary.c_str()); + return false; + } + } + + if (std::filesystem::exists(path)) { + if (remove(path.c_str()) != 0) { + LOG_ERR("%s: unable to delete file: %s\n", __func__, path.c_str()); + return false; + } + } + } + + // Write the updated JSON metadata file. + metadata.update({ + { "url", url }, + { "etag", headers.etag }, + { "lastModified", headers.last_modified } + }); + write_file(metadata_path, metadata.dump(4)); + LOG_DBG("%s: file metadata saved: %s\n", __func__, metadata_path.c_str()); + + // start the download + LOG_INF("%s: trying to download model from %s to %s (server_etag:%s, server_last_modified:%s)...\n", + __func__, llama_download_hide_password_in_url(url).c_str(), path_temporary.c_str(), + headers.etag.c_str(), headers.last_modified.c_str()); + const bool was_pull_successful = common_pull_file(curl.get(), path_temporary); + if (!was_pull_successful) { + if (i + 1 < max_attempts) { + const int exponential_backoff_delay = std::pow(retry_delay_seconds, i) * 1000; + LOG_WRN("%s: retrying after %d milliseconds...\n", __func__, exponential_backoff_delay); + std::this_thread::sleep_for(std::chrono::milliseconds(exponential_backoff_delay)); + } else { + LOG_ERR("%s: curl_easy_perform() failed after %d attempts\n", __func__, max_attempts); + } + + continue; + } + + long http_code = 0; + curl_easy_getinfo(curl.get(), CURLINFO_RESPONSE_CODE, &http_code); + if (http_code < 200 || http_code >= 400) { + LOG_ERR("%s: invalid http status code received: %ld\n", __func__, http_code); + return false; + } + + if (rename(path_temporary.c_str(), path.c_str()) != 0) { + LOG_ERR("%s: unable to rename file: %s to %s\n", __func__, path_temporary.c_str(), path.c_str()); + return false; + } + } else { + LOG_INF("%s: using cached file: %s\n", __func__, path.c_str()); + } + + break; } return true; @@ -770,7 +834,7 @@ static std::string common_docker_get_token(const std::string & repo) { } static std::string common_docker_resolve_model(const std::string & docker) { - // Parse ai/smollm2:135M-Q4_K_M + // Parse ai/smollm2:135M-Q4_0 size_t colon_pos = docker.find(':'); std::string repo, tag; if (colon_pos != std::string::npos) { From 368560a1e3b9a3bc83af741b0b2bc9e46fb420d2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Johannes=20G=C3=A4=C3=9Fler?= Date: Thu, 18 Sep 2025 19:28:32 +0200 Subject: [PATCH 37/52] CUDA: fix compilation on CC 6.0 (#16091) --- ggml/src/ggml-cuda/fattn-tile.cu | 2 -- 1 file changed, 2 deletions(-) diff --git a/ggml/src/ggml-cuda/fattn-tile.cu b/ggml/src/ggml-cuda/fattn-tile.cu index a2d9951ea5..131a5099a3 100644 --- a/ggml/src/ggml-cuda/fattn-tile.cu +++ b/ggml/src/ggml-cuda/fattn-tile.cu @@ -35,7 +35,6 @@ static int fattn_tile_get_kq_stride_host(const int D, const int ncols, const int switch (D) { case 64: case 128: - return 128; case 256: return ncols <= 16 ? 128 : 64; default: @@ -86,7 +85,6 @@ static constexpr __device__ int fattn_tile_get_kq_stride_device(int D, int ncols switch (D) { case 64: case 128: - return 128; case 256: return ncols <= 16 ? 128 : 64; default: From 38dbdf4c057515ccea9bec0ca2518f86d5e4d28e Mon Sep 17 00:00:00 2001 From: Bowen Han Date: Thu, 18 Sep 2025 11:26:03 -0700 Subject: [PATCH 38/52] CUDA: Optimize PAD_REFLECT_1D (#15957) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * CUDA: Optimize PAD_REFLECT_1D feat: add more test cases for PAD_REFLECT_1D * use fast_div to improve performance * Apply suggestion from JohannesGaessler Co-authored-by: Johannes Gäßler * Apply suggestion from JohannesGaessler Co-authored-by: Johannes Gäßler * optimize * use a concise expression to further speedup the cuda kernel --------- Co-authored-by: Johannes Gäßler --- ggml/src/ggml-cuda/common.cuh | 8 ++ ggml/src/ggml-cuda/pad_reflect_1d.cu | 115 ++++++++++++++------------- tests/test-backend-ops.cpp | 7 ++ 3 files changed, 76 insertions(+), 54 deletions(-) diff --git a/ggml/src/ggml-cuda/common.cuh b/ggml/src/ggml-cuda/common.cuh index 045c6d3006..3b1349171b 100644 --- a/ggml/src/ggml-cuda/common.cuh +++ b/ggml/src/ggml-cuda/common.cuh @@ -652,6 +652,14 @@ static __device__ __forceinline__ uint32_t fastmodulo(uint32_t n, const uint3 fa return n - fastdiv(n, fastdiv_values) * fastdiv_values.z; } +// Calculate both division and modulo at once, returns +static __device__ __forceinline__ uint2 fast_div_modulo(uint32_t n, const uint3 fastdiv_values) { + // expects fastdiv_values to contain in (see init_fastdiv_values) + const uint32_t div_val = fastdiv(n, fastdiv_values); + const uint32_t mod_val = n - div_val * fastdiv_values.z; + return make_uint2(div_val, mod_val); +} + typedef void (*dequantize_kernel_t)(const void * vx, const int64_t ib, const int iqs, float2 & v); static __device__ __forceinline__ float get_alibi_slope( diff --git a/ggml/src/ggml-cuda/pad_reflect_1d.cu b/ggml/src/ggml-cuda/pad_reflect_1d.cu index 4ed34aec3d..0478889da1 100644 --- a/ggml/src/ggml-cuda/pad_reflect_1d.cu +++ b/ggml/src/ggml-cuda/pad_reflect_1d.cu @@ -1,82 +1,89 @@ #include "pad_reflect_1d.cuh" -static __global__ void pad_reflect_1d_kernel_f32( - const void * __restrict__ src0, - void * __restrict__ dst, - const int64_t ne0, - 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 int p0, - const int p1) { - +static __global__ __launch_bounds__(CUDA_PAD_REFLECT_1D_BLOCK_SIZE, 1) void + pad_reflect_1d_kernel_f32( + const void * __restrict__ src0, + void * __restrict__ dst, + const int64_t ne0, + const int64_t ne00, + const uint3 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 int p0, + const int p1) { const int64_t i3 = blockIdx.z; const int64_t i2 = blockIdx.y; - const int64_t i1 = blockIdx.x; - if (i1 >= ne01 || i2 >= ne02 || i3 >= ne03) { + const uint2 div_mod_packed = fast_div_modulo(blockIdx.x, ne01); + const int64_t tile1 = div_mod_packed.y; // i1 + const int64_t tile0 = div_mod_packed.x; // nth i0 tile + const int64_t i1 = tile1; + const int64_t i0 = threadIdx.x + tile0 * blockDim.x; + + // ne01.z is original value of unpacked ne01 (see init_fastdiv_values in common.cuh) + if (i0 >= ne0 || i1 >= ne01.z || i2 >= ne02 || i3 >= ne03) { return; } - const char * src0_ptr = (const char *)src0 + i3*nb03 + i2*nb02 + i1*nb01; - char * dst_ptr = (char *)dst + i3*nb3 + i2*nb2 + i1*nb1; + const char * src0_ptr = (const char *) src0 + i3 * nb03 + i2 * nb02 + i1 * nb01; + char * dst_ptr = (char *) dst + i3 * nb3 + i2 * nb2 + i1 * nb1; - for (int64_t i0 = threadIdx.x; i0 < ne0; i0 += blockDim.x) { - float value; + const int64_t rel_i0 = i0 - p0; // relative i0 in src0 + int64_t src_idx; - if (i0 < p0) { - // Left padding - reflect - value = *(const float *)(src0_ptr + (p0 - i0) * nb00); - } else if (i0 < ne0 - p1) { - // Middle - copy - value = *(const float *)(src0_ptr + (i0 - p0) * nb00); - } else { - // Right padding - reflect - int64_t src_idx = (ne0 - p1 - p0) - (p1 + 1 - (ne0 - i0)) - 1; - value = *(const float *)(src0_ptr + src_idx * nb00); - } - - *(float *)(dst_ptr + i0 * nb0) = value; + if (rel_i0 < 0) { + // Left padding - reflect + src_idx = -rel_i0; + } else if (rel_i0 < ne00) { + // Middle - copy + src_idx = rel_i0; + } else { + // Right padding - reflect + src_idx = 2 * ne00 - 2 - rel_i0; } + const float value = *(const float *) (src0_ptr + src_idx * nb00); + *(float *) (dst_ptr + i0 * nb0) = value; } void ggml_cuda_op_pad_reflect_1d(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { - const ggml_tensor * src0 = dst->src[0]; - cudaStream_t stream = ctx.stream(); + const ggml_tensor * src0 = dst->src[0]; + cudaStream_t stream = ctx.stream(); GGML_ASSERT(src0->type == GGML_TYPE_F32); GGML_ASSERT(dst->type == GGML_TYPE_F32); const int32_t * opts = (const int32_t *) dst->op_params; - const int p0 = opts[0]; - const int p1 = opts[1]; + const int p0 = opts[0]; + const int p1 = opts[1]; - const int64_t ne00 = src0->ne[0]; - const int64_t ne01 = src0->ne[1]; - const int64_t ne02 = src0->ne[2]; - const int64_t ne03 = src0->ne[3]; + const int64_t ne00 = src0->ne[0]; + const int64_t ne01 = src0->ne[1]; + const uint3 ne01_packed = init_fastdiv_values(ne01); + const int64_t ne02 = src0->ne[2]; + const int64_t ne03 = src0->ne[3]; const int64_t ne0 = dst->ne[0]; + // sanity: padded length matches GGML_ASSERT(ne0 == ne00 + p0 + p1); - const dim3 block_dims(CUDA_PAD_REFLECT_1D_BLOCK_SIZE, 1, 1); - const dim3 grid_dims(ne01, ne02, ne03); + constexpr int64_t bx = CUDA_PAD_REFLECT_1D_BLOCK_SIZE; // threads per block (x) + const int64_t tiles0 = (ne0 + bx - 1) / bx; // number of tiles along i0 + // grid.x covers i1 and all tiles of i0: [ne01 * tiles0] + // grid.y covers i2: [ne02] + // grid.z covers i3: [ne03] + const dim3 grid_dims((unsigned) (ne01 * tiles0), (unsigned) ne02, (unsigned) ne03); + const dim3 block_dims((unsigned) bx, 1, 1); pad_reflect_1d_kernel_f32<<>>( - src0->data, dst->data, - ne0, ne00, ne01, ne02, ne03, - src0->nb[0], src0->nb[1], src0->nb[2], src0->nb[3], - dst->nb[0], dst->nb[1], dst->nb[2], dst->nb[3], - p0, p1 - ); + src0->data, dst->data, ne0, ne00, ne01_packed, ne02, ne03, src0->nb[0], src0->nb[1], src0->nb[2], src0->nb[3], + dst->nb[0], dst->nb[1], dst->nb[2], dst->nb[3], p0, p1); } diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp index 893c2af313..01cbf87533 100644 --- a/tests/test-backend-ops.cpp +++ b/tests/test-backend-ops.cpp @@ -6507,6 +6507,7 @@ static std::vector> make_test_cases_eval() { test_cases.emplace_back(new test_pad()); 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})); test_cases.emplace_back(new test_roll()); test_cases.emplace_back(new test_arange()); test_cases.emplace_back(new test_timestep_embedding()); @@ -6645,6 +6646,12 @@ static std::vector> make_test_cases_perf() { test_cases.emplace_back(new test_argmax(GGML_TYPE_F32, {1024, 10, 1, 1})); test_cases.emplace_back(new test_argmax(GGML_TYPE_F32, {32000, 512, 1, 1})); + test_cases.emplace_back(new test_pad_reflect_1d(GGML_TYPE_F32, {512, 34, 2, 1})); + test_cases.emplace_back(new test_pad_reflect_1d(GGML_TYPE_F32, {3000, 80, 1, 1})); + test_cases.emplace_back(new test_pad_reflect_1d(GGML_TYPE_F32, {3000, 80, 4, 1})); + test_cases.emplace_back(new test_pad_reflect_1d(GGML_TYPE_F32, {3000, 384, 1, 1})); + test_cases.emplace_back(new test_pad_reflect_1d(GGML_TYPE_F32, {3000, 384, 4, 1})); + test_cases.emplace_back(new test_mul_mat(GGML_TYPE_F16, GGML_TYPE_F32, 16416, 1, 128, {8, 1}, {4, 1}, {0, 2, 1, 3})); test_cases.emplace_back(new test_mul_mat(GGML_TYPE_F16, GGML_TYPE_F32, 128, 1, 16416, {8, 1}, {4, 1}, {0, 1, 2, 3}, true)); From c0b45097c33e2667a94444f08cc9e36bec0a5e2e Mon Sep 17 00:00:00 2001 From: Jeff Bolz Date: Thu, 18 Sep 2025 13:46:17 -0500 Subject: [PATCH 39/52] rename optimize_graph to graph_optimize (#16082) --- ggml/src/ggml-backend-impl.h | 2 +- ggml/src/ggml-backend.cpp | 8 ++++---- ggml/src/ggml-blas/ggml-blas.cpp | 2 +- ggml/src/ggml-cann/ggml-cann.cpp | 2 +- ggml/src/ggml-cpu/ggml-cpu.cpp | 2 +- ggml/src/ggml-cuda/ggml-cuda.cu | 2 +- ggml/src/ggml-metal/ggml-metal.cpp | 2 +- ggml/src/ggml-opencl/ggml-opencl.cpp | 2 +- ggml/src/ggml-rpc/ggml-rpc.cpp | 2 +- ggml/src/ggml-sycl/ggml-sycl.cpp | 2 +- ggml/src/ggml-vulkan/ggml-vulkan.cpp | 14 +++++++------- ggml/src/ggml-webgpu/ggml-webgpu.cpp | 2 +- ggml/src/ggml-zdnn/ggml-zdnn.cpp | 2 +- 13 files changed, 22 insertions(+), 22 deletions(-) diff --git a/ggml/src/ggml-backend-impl.h b/ggml/src/ggml-backend-impl.h index 89d80db6e6..07784d6f66 100644 --- a/ggml/src/ggml-backend-impl.h +++ b/ggml/src/ggml-backend-impl.h @@ -116,7 +116,7 @@ extern "C" { void (*event_wait) (ggml_backend_t backend, ggml_backend_event_t event); // (optional) sort/optimize the nodes in the graph - void (*optimize_graph) (ggml_backend_t backend, struct ggml_cgraph * cgraph); + void (*graph_optimize) (ggml_backend_t backend, struct ggml_cgraph * cgraph); }; struct ggml_backend { diff --git a/ggml/src/ggml-backend.cpp b/ggml/src/ggml-backend.cpp index 7646f3f134..79a5282be3 100644 --- a/ggml/src/ggml-backend.cpp +++ b/ggml/src/ggml-backend.cpp @@ -463,10 +463,10 @@ void ggml_backend_event_wait(ggml_backend_t backend, ggml_backend_event_t event) backend->iface.event_wait(backend, event); } -static void ggml_backend_optimize_graph(ggml_backend_t backend, struct ggml_cgraph * cgraph) { +static void ggml_backend_graph_optimize(ggml_backend_t backend, struct ggml_cgraph * cgraph) { GGML_ASSERT(backend); - if (backend->iface.optimize_graph != NULL) { - backend->iface.optimize_graph(backend, cgraph); + if (backend->iface.graph_optimize != NULL) { + backend->iface.graph_optimize(backend, cgraph); } } @@ -1307,7 +1307,7 @@ void ggml_backend_sched_split_graph(ggml_backend_sched_t sched, struct ggml_cgra // Optimize this split of the graph. This needs to happen before we make graph_copy, // so they are in sync. - ggml_backend_optimize_graph(sched->backends[split->backend_id], &split->graph); + ggml_backend_graph_optimize(sched->backends[split->backend_id], &split->graph); // add inputs to the graph copy so that they are allocated by ggml-alloc at the start of the split for (int j = 0; j < split->n_inputs; j++) { diff --git a/ggml/src/ggml-blas/ggml-blas.cpp b/ggml/src/ggml-blas/ggml-blas.cpp index cdfc5a9bc2..5b888cdd8c 100644 --- a/ggml/src/ggml-blas/ggml-blas.cpp +++ b/ggml/src/ggml-blas/ggml-blas.cpp @@ -270,7 +270,7 @@ static struct ggml_backend_i blas_backend_i = { /* .graph_compute = */ ggml_backend_blas_graph_compute, /* .event_record = */ NULL, /* .event_wait = */ NULL, - /* .optimize_graph = */ NULL, + /* .graph_optimize = */ NULL, }; static ggml_guid_t ggml_backend_blas_guid(void) { diff --git a/ggml/src/ggml-cann/ggml-cann.cpp b/ggml/src/ggml-cann/ggml-cann.cpp index cbeafa6bc9..b51b554e75 100755 --- a/ggml/src/ggml-cann/ggml-cann.cpp +++ b/ggml/src/ggml-cann/ggml-cann.cpp @@ -2756,7 +2756,7 @@ static const ggml_backend_i ggml_backend_cann_interface = { /* .graph_compute = */ ggml_backend_cann_graph_compute, /* .event_record = */ ggml_backend_cann_event_record, /* .event_wait = */ ggml_backend_cann_event_wait, - /* .optimize_graph = */ NULL, + /* .graph_optimize = */ NULL, }; /** diff --git a/ggml/src/ggml-cpu/ggml-cpu.cpp b/ggml/src/ggml-cpu/ggml-cpu.cpp index 2b81f8b9af..81a314e4d6 100644 --- a/ggml/src/ggml-cpu/ggml-cpu.cpp +++ b/ggml/src/ggml-cpu/ggml-cpu.cpp @@ -190,7 +190,7 @@ static const struct ggml_backend_i ggml_backend_cpu_i = { /* .graph_compute = */ ggml_backend_cpu_graph_compute, /* .event_record = */ NULL, /* .event_wait = */ NULL, - /* .optimize_graph = */ NULL, + /* .graph_optimize = */ NULL, }; static ggml_guid_t ggml_backend_cpu_guid(void) { diff --git a/ggml/src/ggml-cuda/ggml-cuda.cu b/ggml/src/ggml-cuda/ggml-cuda.cu index 9ea8f4589d..f3ba20fe3f 100644 --- a/ggml/src/ggml-cuda/ggml-cuda.cu +++ b/ggml/src/ggml-cuda/ggml-cuda.cu @@ -3140,7 +3140,7 @@ static const ggml_backend_i ggml_backend_cuda_interface = { /* .graph_compute = */ ggml_backend_cuda_graph_compute, /* .event_record = */ ggml_backend_cuda_event_record, /* .event_wait = */ ggml_backend_cuda_event_wait, - /* .optimize_graph = */ NULL, + /* .graph_optimize = */ NULL, }; static ggml_guid_t ggml_backend_cuda_guid() { diff --git a/ggml/src/ggml-metal/ggml-metal.cpp b/ggml/src/ggml-metal/ggml-metal.cpp index fd0e6ed6e4..e11555a78f 100644 --- a/ggml/src/ggml-metal/ggml-metal.cpp +++ b/ggml/src/ggml-metal/ggml-metal.cpp @@ -447,7 +447,7 @@ static ggml_backend_i ggml_backend_metal_i = { // https://developer.apple.com/documentation/metal/mtlcommandbuffer#Synchronizing-Passes-with-Events /* .event_record = */ NULL, /* .event_wait = */ NULL, - /* .optimize_graph = */ ggml_backend_metal_graph_optimize, + /* .graph_optimize = */ ggml_backend_metal_graph_optimize, }; static ggml_guid_t ggml_backend_metal_guid(void) { diff --git a/ggml/src/ggml-opencl/ggml-opencl.cpp b/ggml/src/ggml-opencl/ggml-opencl.cpp index b188c5af34..b4ae2f882b 100644 --- a/ggml/src/ggml-opencl/ggml-opencl.cpp +++ b/ggml/src/ggml-opencl/ggml-opencl.cpp @@ -2838,7 +2838,7 @@ static ggml_backend_i ggml_backend_opencl_i = { /* .graph_compute = */ ggml_backend_opencl_graph_compute, /* .event_record = */ NULL, /* .event_wait = */ NULL, - /* .optimize_graph = */ NULL, + /* .graph_optimize = */ NULL, }; ggml_backend_t ggml_backend_opencl_init(void) { diff --git a/ggml/src/ggml-rpc/ggml-rpc.cpp b/ggml/src/ggml-rpc/ggml-rpc.cpp index d4833068d0..dde1a5945a 100644 --- a/ggml/src/ggml-rpc/ggml-rpc.cpp +++ b/ggml/src/ggml-rpc/ggml-rpc.cpp @@ -795,7 +795,7 @@ static ggml_backend_i ggml_backend_rpc_interface = { /* .graph_compute = */ ggml_backend_rpc_graph_compute, /* .event_record = */ NULL, /* .event_wait = */ NULL, - /* .optimize_graph = */ NULL, + /* .graph_optimize = */ NULL, }; ggml_backend_buffer_type_t ggml_backend_rpc_buffer_type(const char * endpoint) { diff --git a/ggml/src/ggml-sycl/ggml-sycl.cpp b/ggml/src/ggml-sycl/ggml-sycl.cpp index 9404e3ff4a..78853eb676 100644 --- a/ggml/src/ggml-sycl/ggml-sycl.cpp +++ b/ggml/src/ggml-sycl/ggml-sycl.cpp @@ -4073,7 +4073,7 @@ static ggml_backend_i ggml_backend_sycl_interface = { /* .graph_compute = */ ggml_backend_sycl_graph_compute, /* .event_record = */ ggml_backend_sycl_event_record, /* .event_wait = */ ggml_backend_sycl_event_wait, - /* .optimize_graph = */ NULL, + /* .graph_optimize = */ NULL, }; static ggml_guid_t ggml_backend_sycl_guid() { diff --git a/ggml/src/ggml-vulkan/ggml-vulkan.cpp b/ggml/src/ggml-vulkan/ggml-vulkan.cpp index 1f1136382e..5c941e7213 100644 --- a/ggml/src/ggml-vulkan/ggml-vulkan.cpp +++ b/ggml/src/ggml-vulkan/ggml-vulkan.cpp @@ -593,7 +593,7 @@ struct vk_device_struct { bool disable_fusion; bool disable_host_visible_vidmem; bool allow_sysmem_fallback; - bool disable_optimize_graph; + bool disable_graph_optimize; #ifdef GGML_VULKAN_MEMORY_DEBUG std::unique_ptr memory_logger; @@ -3624,8 +3624,8 @@ static vk_device ggml_vk_get_device(size_t idx) { const char* GGML_VK_ALLOW_SYSMEM_FALLBACK = getenv("GGML_VK_ALLOW_SYSMEM_FALLBACK"); device->allow_sysmem_fallback = GGML_VK_ALLOW_SYSMEM_FALLBACK != nullptr; - const char* GGML_VK_DISABLE_OPTIMIZE_GRAPH = getenv("GGML_VK_DISABLE_OPTIMIZE_GRAPH"); - device->disable_optimize_graph = GGML_VK_DISABLE_OPTIMIZE_GRAPH != nullptr; + const char* GGML_VK_DISABLE_GRAPH_OPTIMIZE = getenv("GGML_VK_DISABLE_GRAPH_OPTIMIZE"); + device->disable_graph_optimize = GGML_VK_DISABLE_GRAPH_OPTIMIZE != nullptr; bool fp16_storage = false; bool fp16_compute = false; @@ -11914,12 +11914,12 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg } // Sort the graph for improved parallelism. -static void ggml_vk_optimize_graph(ggml_backend_t backend, struct ggml_cgraph * graph) +static void ggml_vk_graph_optimize(ggml_backend_t backend, struct ggml_cgraph * graph) { - VK_LOG_DEBUG("ggml_vk_optimize_graph(" << graph->n_nodes << " nodes)"); + VK_LOG_DEBUG("ggml_vk_graph_optimize(" << graph->n_nodes << " nodes)"); ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context; - if (ctx->device->disable_optimize_graph) { + if (ctx->device->disable_graph_optimize) { return; } @@ -12053,7 +12053,7 @@ static ggml_backend_i ggml_backend_vk_interface = { /* .graph_compute = */ ggml_backend_vk_graph_compute, /* .event_record = */ NULL, /* .event_wait = */ NULL, - /* .optimize_graph = */ ggml_vk_optimize_graph, + /* .graph_optimize = */ ggml_vk_graph_optimize, }; static ggml_guid_t ggml_backend_vk_guid() { diff --git a/ggml/src/ggml-webgpu/ggml-webgpu.cpp b/ggml/src/ggml-webgpu/ggml-webgpu.cpp index 8e7b986df8..a92ddc582a 100644 --- a/ggml/src/ggml-webgpu/ggml-webgpu.cpp +++ b/ggml/src/ggml-webgpu/ggml-webgpu.cpp @@ -823,7 +823,7 @@ static ggml_backend_i ggml_backend_webgpu_i = { /* .graph_compute = */ ggml_backend_webgpu_graph_compute, /* .event_record = */ NULL, /* .event_wait = */ NULL, - /* .optimize_graph = */ NULL, + /* .graph_optimize = */ NULL, }; /* End GGML Backend Interface */ diff --git a/ggml/src/ggml-zdnn/ggml-zdnn.cpp b/ggml/src/ggml-zdnn/ggml-zdnn.cpp index 9ba23a3300..57a8f26620 100644 --- a/ggml/src/ggml-zdnn/ggml-zdnn.cpp +++ b/ggml/src/ggml-zdnn/ggml-zdnn.cpp @@ -574,7 +574,7 @@ static ggml_backend_i ggml_backend_zdnn_i = { /* .graph_compute = */ ggml_backend_zdnn_graph_compute, /* .event_record = */ NULL, /* .event_wait = */ NULL, - /* .optimize_graph = */ NULL, + /* .graph_optimize = */ NULL, }; static ggml_guid_t ggml_backend_zdnn_guid(void) { From 3edd87cd055a45d885fa914d879d36d33ecfc3e1 Mon Sep 17 00:00:00 2001 From: Shawn Gu Date: Thu, 18 Sep 2025 12:03:34 -0700 Subject: [PATCH 40/52] opencl: optimize mxfp4 kernels (#16037) - flatten mxfp4 and packed fp4->fp16 bit-wise convert function (replace lut) - MoE kernel optimizations --------- Co-authored-by: Li He --- ggml/src/ggml-opencl/CMakeLists.txt | 2 + ggml/src/ggml-opencl/ggml-opencl.cpp | 312 +++++++++++++++++- ggml/src/ggml-opencl/kernels/cvt.cl | 46 +++ .../kernels/mul_mv_id_mxfp4_f32_flat.cl | 176 ++++++++++ .../kernels/mul_mv_mxfp4_f32_flat.cl | 167 ++++++++++ 5 files changed, 701 insertions(+), 2 deletions(-) create mode 100644 ggml/src/ggml-opencl/kernels/mul_mv_id_mxfp4_f32_flat.cl create mode 100644 ggml/src/ggml-opencl/kernels/mul_mv_mxfp4_f32_flat.cl diff --git a/ggml/src/ggml-opencl/CMakeLists.txt b/ggml/src/ggml-opencl/CMakeLists.txt index 9a7ccbcff0..1c06aa138b 100644 --- a/ggml/src/ggml-opencl/CMakeLists.txt +++ b/ggml/src/ggml-opencl/CMakeLists.txt @@ -83,8 +83,10 @@ set(GGML_OPENCL_KERNELS mul_mv_q4_0_f32_1d_16x_flat mul_mv_q6_k mul_mv_mxfp4_f32 + mul_mv_mxfp4_f32_flat mul_mv_id_q4_0_f32_8x_flat mul_mv_id_mxfp4_f32 + mul_mv_id_mxfp4_f32_flat mul_mm_f32_f32_l4_lm mul_mm_f16_f32_l4_lm mul diff --git a/ggml/src/ggml-opencl/ggml-opencl.cpp b/ggml/src/ggml-opencl/ggml-opencl.cpp index b4ae2f882b..2cb838b713 100644 --- a/ggml/src/ggml-opencl/ggml-opencl.cpp +++ b/ggml/src/ggml-opencl/ggml-opencl.cpp @@ -368,6 +368,7 @@ struct ggml_backend_opencl_context { cl_program program_mul_mv_q4_0_f32_1d_16x_flat; cl_program program_mul_mv_q6_K; cl_program program_mul_mv_mxfp4_f32; + cl_program program_mul_mv_mxfp4_f32_flat; cl_program program_mul_mv_f16_f16; cl_program program_mul_mv_f16_f32_1row; cl_program program_mul_mv_f16_f32_l4; @@ -402,6 +403,7 @@ struct ggml_backend_opencl_context { cl_program program_tsembd; cl_program program_mul_mv_id_q4_0_f32_8x_flat; cl_program program_mul_mv_id_mxfp4_f32; + cl_program program_mul_mv_id_mxfp4_f32_flat; cl_program program_mul_mm_f32_f32_l4_lm; cl_program program_mul_mm_f16_f32_l4_lm; @@ -447,11 +449,12 @@ struct ggml_backend_opencl_context { cl_kernel kernel_mul_mat_f16_f32_tiled; cl_kernel kernel_mul_mat_q4_0_f32, kernel_mul_mat_q4_0_f32_v; cl_kernel kernel_convert_block_q4_0, kernel_restore_block_q4_0; + cl_kernel kernel_convert_block_mxfp4, kernel_restore_block_mxfp4; cl_kernel kernel_mul_mat_q4_0_f32_8x_flat; cl_kernel kernel_convert_block_q4_0_noshuffle; cl_kernel kernel_mul_mat_q4_0_f32_1d_8x_flat, kernel_mul_mat_q4_0_f32_1d_16x_flat; cl_kernel kernel_mul_mv_q6_K_f32; - cl_kernel kernel_mul_mv_mxfp4_f32; + cl_kernel kernel_mul_mv_mxfp4_f32, kernel_mul_mv_mxfp4_f32_flat; cl_kernel kernel_im2col_f32, kernel_im2col_f16; cl_kernel kernel_argsort_f32_i32; cl_kernel kernel_sum_rows_f32; @@ -469,6 +472,7 @@ struct ggml_backend_opencl_context { cl_kernel kernel_timestep_embedding; cl_kernel kernel_mul_mv_id_q4_0_f32_8x_flat; cl_kernel kernel_mul_mv_id_mxfp4_f32; + cl_kernel kernel_mul_mv_id_mxfp4_f32_flat; cl_kernel kernel_mul_mm_f32_f32_l4_lm; cl_kernel kernel_mul_mm_f16_f32_l4_lm; @@ -765,6 +769,8 @@ static void load_cl_kernels(ggml_backend_opencl_context *backend_ctx, ggml_cl_ve CL_CHECK((backend_ctx->kernel_convert_block_q4_0_noshuffle = clCreateKernel(backend_ctx->program_cvt, "kernel_convert_block_q4_0_noshuffle", &err), err)); CL_CHECK((backend_ctx->kernel_convert_block_q4_0 = clCreateKernel(backend_ctx->program_cvt, "kernel_convert_block_q4_0", &err), err)); CL_CHECK((backend_ctx->kernel_restore_block_q4_0 = clCreateKernel(backend_ctx->program_cvt, "kernel_restore_block_q4_0", &err), err)); + CL_CHECK((backend_ctx->kernel_convert_block_mxfp4 = clCreateKernel(backend_ctx->program_cvt, "kernel_convert_block_mxfp4", &err), err)); + CL_CHECK((backend_ctx->kernel_restore_block_mxfp4 = clCreateKernel(backend_ctx->program_cvt, "kernel_restore_block_mxfp4", &err), err)); GGML_LOG_CONT("."); } @@ -1002,6 +1008,22 @@ static void load_cl_kernels(ggml_backend_opencl_context *backend_ctx, ggml_cl_ve GGML_LOG_CONT("."); } + // mul_mv_mxfp4_f32_flat + { +#ifdef GGML_OPENCL_EMBED_KERNELS + const std::string kernel_src { + #include "mul_mv_mxfp4_f32_flat.cl.h" + }; +#else + const std::string kernel_src = read_file("mul_mv_mxfp4_f32_flat.cl"); +#endif + backend_ctx->program_mul_mv_mxfp4_f32_flat = + build_program_from_source(backend_ctx->context, backend_ctx->device, kernel_src.c_str(), compile_opts); + + CL_CHECK((backend_ctx->kernel_mul_mv_mxfp4_f32_flat = clCreateKernel(backend_ctx->program_mul_mv_mxfp4_f32_flat, "kernel_mul_mv_mxfp4_f32_flat", &err), err)); + GGML_LOG_CONT("."); + } + // mul_mv_f16_f16 { #ifdef GGML_OPENCL_EMBED_KERNELS @@ -1727,6 +1749,22 @@ static void load_cl_kernels(ggml_backend_opencl_context *backend_ctx, ggml_cl_ve GGML_LOG_CONT("."); } + // mul_mv_id_mxfp4_f32_flat + { +#ifdef GGML_OPENCL_EMBED_KERNELS + const std::string kernel_src { + #include "mul_mv_id_mxfp4_f32_flat.cl.h" + }; +#else + const std::string kernel_src = read_file("mul_mv_id_mxfp4_f32_flat.cl"); +#endif + backend_ctx->program_mul_mv_id_mxfp4_f32_flat = + build_program_from_source(backend_ctx->context, backend_ctx->device, kernel_src.c_str(), compile_opts); + + CL_CHECK((backend_ctx->kernel_mul_mv_id_mxfp4_f32_flat = clCreateKernel(backend_ctx->program_mul_mv_id_mxfp4_f32_flat, "kernel_mul_mv_id_mxfp4_f32_flat", &err), err)); + GGML_LOG_CONT("."); + } + // Adreno kernels #ifdef GGML_OPENCL_USE_ADRENO_KERNELS // transpose @@ -2391,6 +2429,51 @@ struct ggml_tensor_extra_cl_q4_0 { } }; +struct ggml_tensor_extra_cl_mxfp4 { + // Quantized values. + cl_mem q = nullptr; + // Quantized values in image1d_buffer_t. + cl_mem q_img = nullptr; + // Scales in E8M0. + cl_mem e = nullptr; + // Scales in image1d_buffer_t. + cl_mem e_img = nullptr; + // Size of quantized values. + size_t size_q = 0; + // Size of scales. + size_t size_e = 0; + + ~ggml_tensor_extra_cl_mxfp4() { + reset(); + } + + void reset() { + // q and d are subbuffers into the bigger buffer allocated in ggml_backend_buffer. + // They must be properly released so that the original buffer can be + // properly released to avoid memory leak. + if (q != nullptr) { + CL_CHECK(clReleaseMemObject(q)); + q = nullptr; + } + if (e != nullptr) { + CL_CHECK(clReleaseMemObject(e)); + e = nullptr; + } + if (q != nullptr) { + CL_CHECK(clReleaseMemObject(q_img)); + q = nullptr; + } + // Currently, q_img and d_img are only initialized when SMALL_ALLOC is + // enabled. They point to the images in ggml_backend_opencl_buffer_context. + // So, there is no need to release them here. + // TODO: initialize them for non SMALL_PATH path, or remove them. + q_img = nullptr; + e_img = nullptr; + size_q = 0; + size_e = 0; + } +}; + //------------------------------------------------------------------------------ // Backend API //------------------------------------------------------------------------------ @@ -2894,6 +2977,12 @@ struct ggml_backend_opencl_buffer_context { for (ggml_tensor_extra_cl_q4_0 * e : temp_tensor_extras_q4_0_in_use) { delete e; } + for (ggml_tensor_extra_cl_mxfp4 * e : temp_tensor_extras_mxfp4) { + delete e; + } + for (ggml_tensor_extra_cl_mxfp4 * e : temp_tensor_extras_mxfp4_in_use) { + delete e; + } } ggml_tensor_extra_cl * ggml_opencl_alloc_temp_tensor_extra() { @@ -2926,6 +3015,21 @@ struct ggml_backend_opencl_buffer_context { return extra; } + ggml_tensor_extra_cl_mxfp4 * ggml_opencl_alloc_temp_tensor_extra_mxfp4() { + ggml_tensor_extra_cl_mxfp4 * extra; + if (temp_tensor_extras_mxfp4.empty()) { + extra = new ggml_tensor_extra_cl_mxfp4(); + } else { + extra = temp_tensor_extras_mxfp4.back(); + temp_tensor_extras_mxfp4.pop_back(); + } + + temp_tensor_extras_mxfp4_in_use.push_back(extra); + + extra->reset(); + return extra; + } + void reset() { for (ggml_tensor_extra_cl * e : temp_tensor_extras_in_use) { temp_tensor_extras.push_back(e); @@ -2936,6 +3040,11 @@ struct ggml_backend_opencl_buffer_context { temp_tensor_extras_q4_0.push_back(e); } temp_tensor_extras_q4_0_in_use.clear(); + + for (ggml_tensor_extra_cl_mxfp4 * e : temp_tensor_extras_mxfp4_in_use) { + temp_tensor_extras_mxfp4.push_back(e); + } + temp_tensor_extras_mxfp4_in_use.clear(); } // Pools for extras. Available extras are in `temp_tensor_extras`. Extras @@ -2947,6 +3056,8 @@ struct ggml_backend_opencl_buffer_context { std::vector temp_tensor_extras_in_use; std::vector temp_tensor_extras_q4_0; std::vector temp_tensor_extras_q4_0_in_use; + std::vector temp_tensor_extras_mxfp4; + std::vector temp_tensor_extras_mxfp4_in_use; // The buffer_context is initially created by ggml_backend_buft_alloc_buffer // before any tensor is initialized (at the beginning of alloc_tensor_range). @@ -3289,6 +3400,76 @@ static void ggml_backend_opencl_buffer_set_tensor(ggml_backend_buffer_t buffer, } #endif // GGML_OPENCL_USE_ADRENO_KERNELS + return; + + } + if (tensor->type == GGML_TYPE_MXFP4) { + ggml_tensor_extra_cl * extra_orig = (ggml_tensor_extra_cl *)tensor->extra; + GGML_ASSERT(extra_orig && "Tesnors in OpenCL backend should have been allocated and initialized"); + + // Allocate the new extra and create aliases from the original. + ggml_backend_opencl_buffer_context * ctx = (ggml_backend_opencl_buffer_context *) buffer->context; + ggml_tensor_extra_cl_mxfp4 * extra = ctx->ggml_opencl_alloc_temp_tensor_extra_mxfp4(); + + size_t size_e = ggml_nelements(tensor)/ggml_blck_size(tensor->type)*sizeof(char); + size_t size_q = ggml_nelements(tensor)/ggml_blck_size(tensor->type)*ggml_blck_size(tensor->type)/2; + GGML_ASSERT(size_e + size_q == ggml_nbytes(tensor) && "Incorrect tensor size"); + + cl_int err; + cl_mem data_device = clCreateBuffer(context, CL_MEM_READ_WRITE, + ggml_nbytes(tensor), NULL, &err); + CL_CHECK(err); + CL_CHECK(clEnqueueWriteBuffer( + queue, data_device, CL_TRUE, 0, + ggml_nbytes(tensor), data, 0, NULL, NULL)); + + // The original tensor memory is divided into scales and quants, i.e., + // we first store scales, then quants. + cl_buffer_region region; + + // Create subbuffer for scales. + region.origin = align_to(extra_orig->offset + tensor->view_offs + offset, backend_ctx->alignment); + region.size = size_e; + extra->e = clCreateSubBuffer( + extra_orig->data_device, CL_MEM_READ_WRITE, + CL_BUFFER_CREATE_TYPE_REGION, ®ion, &err); + CL_CHECK(err); + auto previous_origin = region.origin; + + // Create subbuffer for quants. + region.origin = align_to(previous_origin + size_e, backend_ctx->alignment); + region.size = size_q; + extra->q = clCreateSubBuffer( + extra_orig->data_device, CL_MEM_READ_WRITE, + CL_BUFFER_CREATE_TYPE_REGION, ®ion, &err); + CL_CHECK(err); + + cl_kernel kernel = backend_ctx->kernel_convert_block_mxfp4; + + CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &data_device)); + CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_mem), &extra->q)); + CL_CHECK(clSetKernelArg(kernel, 2, sizeof(cl_mem), &extra->e)); + + size_t global_work_size[] = {(size_t)ggml_nelements(tensor)/ggml_blck_size(tensor->type), 1, 1}; + size_t local_work_size[] = {64, 1, 1}; + + cl_event evt; + CL_CHECK(clEnqueueNDRangeKernel(queue, kernel, 3, NULL, global_work_size, local_work_size, 0, NULL, &evt)); + CL_CHECK(clWaitForEvents(1, &evt)); + CL_CHECK(clReleaseMemObject(data_device)); + + // Create image for Q + cl_image_format img_format_q = {CL_RG, CL_UNSIGNED_INT32}; + cl_image_desc img_desc_q = { + CL_MEM_OBJECT_IMAGE1D_BUFFER, + static_cast(ggml_nelements(tensor)/32*2), + 0, 0, 0, 0, 0, 0, 0, + { extra->q } + }; + extra->q_img = clCreateImage(context, CL_MEM_READ_ONLY, &img_format_q, &img_desc_q, NULL, &err); + + tensor->extra = extra; + return; } #endif // GGML_OPENCL_SOA_Q @@ -3337,6 +3518,31 @@ static void ggml_backend_opencl_buffer_get_tensor(ggml_backend_buffer_t buffer, size_t global_work_size[] = {(size_t)ggml_nelements(tensor)/ggml_blck_size(tensor->type), 1, 1}; size_t local_work_size[] = {1, 1, 1}; + cl_event evt; + CL_CHECK(clEnqueueNDRangeKernel(queue, kernel, 3, NULL, + global_work_size, local_work_size, 0, NULL, &evt)); + CL_CHECK(clWaitForEvents(1, &evt)); + CL_CHECK(clEnqueueReadBuffer( + queue, data_device, CL_TRUE, offset, + size, data, 0, NULL, NULL)); + CL_CHECK(clReleaseMemObject(data_device)); + return; + } else if (tensor->type == GGML_TYPE_MXFP4) { + ggml_tensor_extra_cl_mxfp4 * extra = (ggml_tensor_extra_cl_mxfp4 *)tensor->extra; + + cl_int err; + cl_mem data_device = clCreateBuffer(context, CL_MEM_READ_WRITE, + ggml_nbytes(tensor), NULL, &err); + CL_CHECK(err); + + cl_kernel kernel = backend_ctx->kernel_restore_block_mxfp4; + CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &extra->q)); + CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_mem), &extra->e)); + CL_CHECK(clSetKernelArg(kernel, 2, sizeof(cl_mem), &data_device)); + + size_t global_work_size[] = {(size_t)ggml_nelements(tensor)/ggml_blck_size(tensor->type), 1, 1}; + size_t local_work_size[] = {1, 1, 1}; + cl_event evt; CL_CHECK(clEnqueueNDRangeKernel(queue, kernel, 3, NULL, global_work_size, local_work_size, 0, NULL, &evt)); @@ -3658,6 +3864,19 @@ static void dump_tensor(ggml_backend_t backend, const struct ggml_tensor * tenso CL_CHECK(clEnqueueReadBuffer(queue, extra->q, CL_TRUE, 0, size_q, buf_q, 0, NULL, NULL)); CL_CHECK(clEnqueueReadBuffer(queue, extra->d, CL_TRUE, 0, size_d, buf_d, 0, NULL, NULL)); CL_CHECK(clFinish(queue)); + } else if (tensor->type == GGML_TYPE_MXFP4) { + ggml_tensor_extra_cl_mxfp4 * extra = (ggml_tensor_extra_cl_mxfp4 *) tensor->extra; + GGML_ASSERT(extra); + + size_t size_q = ggml_nelements(tensor)/QK_MXFP4 * QK_MXFP4/2; + size_t size_e = ggml_nelements(tensor)/QK_MXFP4 * sizeof(char); + GGML_ASSERT(size_q + size_e == ggml_nbytes(tensor)); + buf_q = malloc(size_q); + buf_d = malloc(size_e); + + CL_CHECK(clEnqueueReadBuffer(queue, extra->q, CL_TRUE, 0, size_q, buf_q, 0, NULL, NULL)); + CL_CHECK(clEnqueueReadBuffer(queue, extra->d, CL_TRUE, 0, size_e, buf_d, 0, NULL, NULL)); + CL_CHECK(clFinish(queue)); } else { // Read out the tensor from GPU memory. ggml_tensor_extra_cl * extra = (ggml_tensor_extra_cl *) tensor->extra; @@ -6048,6 +6267,7 @@ static void ggml_cl_mul_mat(ggml_backend_t backend, const ggml_tensor * src0, co #ifdef GGML_OPENCL_SOA_Q ggml_tensor_extra_cl_q4_0 * extra0_q4_0 = (ggml_tensor_extra_cl_q4_0 *)src0->extra; + ggml_tensor_extra_cl_mxfp4 * extra0_mxfp4 = (ggml_tensor_extra_cl_mxfp4 *)src0->extra; #endif const int ne00 = src0 ? src0->ne[0] : 0; @@ -6752,6 +6972,45 @@ static void ggml_cl_mul_mat(ggml_backend_t backend, const ggml_tensor * src0, co CL_CHECK(clSetKernelArg(kernel, 14, sizeof(int), &r3)); break; case GGML_TYPE_MXFP4: { +#ifdef GGML_OPENCL_SOA_Q + kernel = backend_ctx->kernel_mul_mv_mxfp4_f32_flat; + + cl_mem q; + if (backend_ctx->gpu_family == INTEL) { + nth0 = 16; + nth1 = 2; + ndst = nth1*2; + + q = extra0_mxfp4->q; + } else if (backend_ctx->gpu_family == ADRENO) { + nth0 = 64; + nth1 = 2; + ndst = nth1*2; + + q = extra0_mxfp4->q_img; + } else { + GGML_ASSERT(false && "TODO: Unknown GPU"); + } + + CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &q)); + CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_mem), &extra0_mxfp4->e)); + CL_CHECK(clSetKernelArg(kernel, 2, sizeof(cl_mem), &extra1->data_device)); + CL_CHECK(clSetKernelArg(kernel, 3, sizeof(cl_ulong), &offset1)); + CL_CHECK(clSetKernelArg(kernel, 4, sizeof(cl_mem), &extrad->data_device)); + CL_CHECK(clSetKernelArg(kernel, 5, sizeof(cl_ulong), &offsetd)); + CL_CHECK(clSetKernelArg(kernel, 6, sizeof(int), &ne00)); + CL_CHECK(clSetKernelArg(kernel, 7, sizeof(cl_ulong), &nb01)); + CL_CHECK(clSetKernelArg(kernel, 8, sizeof(cl_ulong), &nb02)); + CL_CHECK(clSetKernelArg(kernel, 9, sizeof(cl_ulong), &nb03)); + CL_CHECK(clSetKernelArg(kernel, 10, sizeof(int), &ne12)); + CL_CHECK(clSetKernelArg(kernel, 11, sizeof(cl_ulong), &nb11)); + CL_CHECK(clSetKernelArg(kernel, 12, sizeof(cl_ulong), &nb12)); + CL_CHECK(clSetKernelArg(kernel, 13, sizeof(cl_ulong), &nb13)); + CL_CHECK(clSetKernelArg(kernel, 14, sizeof(int), &ne0)); + CL_CHECK(clSetKernelArg(kernel, 15, sizeof(int), &ne1)); + CL_CHECK(clSetKernelArg(kernel, 16, sizeof(int), &r2)); + CL_CHECK(clSetKernelArg(kernel, 17, sizeof(int), &r3)); +#else kernel = backend_ctx->kernel_mul_mv_mxfp4_f32; if (backend_ctx->gpu_family == INTEL) { @@ -6785,6 +7044,7 @@ static void ggml_cl_mul_mat(ggml_backend_t backend, const ggml_tensor * src0, co CL_CHECK(clSetKernelArg(kernel, 16, sizeof(int), &r2)); CL_CHECK(clSetKernelArg(kernel, 17, sizeof(int), &r3)); CL_CHECK(clSetKernelArg(kernel, 18, sizeof(float)*nth0,nullptr)); +#endif break; } default: @@ -6850,8 +7110,11 @@ static void ggml_cl_mul_mat_id(ggml_backend_t backend, const ggml_tensor * src0, cl_ulong offset2 = extra2->offset + src2->view_offs; cl_ulong offsetd = extrad->offset + dst->view_offs; + GGML_UNUSED(offset0); + #ifdef GGML_OPENCL_SOA_Q ggml_tensor_extra_cl_q4_0 * extra0_q4_0 = (ggml_tensor_extra_cl_q4_0 *)src0->extra; + ggml_tensor_extra_cl_mxfp4 * extra0_mxfp4 = (ggml_tensor_extra_cl_mxfp4 *)src0->extra; #endif const int ne00 = src0->ne[0]; @@ -6940,6 +7203,51 @@ static void ggml_cl_mul_mat_id(ggml_backend_t backend, const ggml_tensor * src0, break; } case GGML_TYPE_MXFP4: { +#ifdef GGML_OPENCL_SOA_Q + kernel = backend_ctx->kernel_mul_mv_id_mxfp4_f32_flat; + + cl_mem q; + if (backend_ctx->gpu_family == INTEL) { + sgs = 16; + nsg = 2; + ndst = 2; + + q = extra0_mxfp4->q; + } else if (backend_ctx->gpu_family == ADRENO) { + sgs = 64; + nsg = 1; + ndst = 4; + + q = extra0_mxfp4->q_img; + } else { + GGML_ASSERT(false && "TODO: Unknown GPU"); + } + + CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &q)); + CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_mem), &extra0_mxfp4->e)); + CL_CHECK(clSetKernelArg(kernel, 2, sizeof(cl_mem), &extra1->data_device)); + CL_CHECK(clSetKernelArg(kernel, 3, sizeof(cl_ulong), &offset1)); + CL_CHECK(clSetKernelArg(kernel, 4, sizeof(cl_mem), &extra2->data_device)); + CL_CHECK(clSetKernelArg(kernel, 5, sizeof(cl_ulong), &offset2)); + CL_CHECK(clSetKernelArg(kernel, 6, sizeof(cl_mem), &extrad->data_device)); + CL_CHECK(clSetKernelArg(kernel, 7, sizeof(cl_ulong), &offsetd)); + CL_CHECK(clSetKernelArg(kernel, 8, sizeof(int), &ne00)); + CL_CHECK(clSetKernelArg(kernel, 9, sizeof(cl_ulong), &nb01)); + CL_CHECK(clSetKernelArg(kernel, 10, sizeof(cl_ulong), &nb02)); + CL_CHECK(clSetKernelArg(kernel, 11, sizeof(cl_ulong), &nb03)); + CL_CHECK(clSetKernelArg(kernel, 12, sizeof(int), &ne11)); + CL_CHECK(clSetKernelArg(kernel, 13, sizeof(int), &ne12)); + CL_CHECK(clSetKernelArg(kernel, 14, sizeof(cl_ulong), &nb11)); + CL_CHECK(clSetKernelArg(kernel, 15, sizeof(cl_ulong), &nb12)); + CL_CHECK(clSetKernelArg(kernel, 16, sizeof(cl_ulong), &nb13)); + CL_CHECK(clSetKernelArg(kernel, 17, sizeof(int), &ne20)); + CL_CHECK(clSetKernelArg(kernel, 18, sizeof(int), &ne21)); + CL_CHECK(clSetKernelArg(kernel, 19, sizeof(cl_ulong), &nb21)); + CL_CHECK(clSetKernelArg(kernel, 20, sizeof(int), &ne0)); + CL_CHECK(clSetKernelArg(kernel, 21, sizeof(int), &ne1)); + CL_CHECK(clSetKernelArg(kernel, 22, sizeof(int), &r2)); + CL_CHECK(clSetKernelArg(kernel, 23, sizeof(int), &r3)); +#else // GGML_OPENCL_SOA_Q kernel = backend_ctx->kernel_mul_mv_id_mxfp4_f32; if (backend_ctx->gpu_family == INTEL) { @@ -6979,7 +7287,7 @@ static void ggml_cl_mul_mat_id(ggml_backend_t backend, const ggml_tensor * src0, CL_CHECK(clSetKernelArg(kernel, 22, sizeof(int), &r2)); CL_CHECK(clSetKernelArg(kernel, 23, sizeof(int), &r3)); CL_CHECK(clSetKernelArg(kernel, 24, sizeof(float)*sgs,nullptr)); - +#endif // GGML_OPENCL_SOA_Q break; } default: diff --git a/ggml/src/ggml-opencl/kernels/cvt.cl b/ggml/src/ggml-opencl/kernels/cvt.cl index fe7975e3db..3440ff5079 100644 --- a/ggml/src/ggml-opencl/kernels/cvt.cl +++ b/ggml/src/ggml-opencl/kernels/cvt.cl @@ -116,3 +116,49 @@ kernel void kernel_convert_block_q4_0_noshuffle( #endif } } + + +//------------------------------------------------------------------------------ +// block_q4_0 +//------------------------------------------------------------------------------ +#define QK_MXFP4 32 +struct block_mxfp4 { + uchar e; // E8M0 + uchar qs[QK_MXFP4 / 2]; +}; + +//------------------------------------------------------------------------------ +// kernel_convert_block_mxfp4 +// Convert the block_mxfp4 format to 2 separate arrays (AOS -> SOA). +// This kernel does not deshuffle the bits. +//------------------------------------------------------------------------------ +kernel void kernel_convert_block_mxfp4( + global struct block_mxfp4 * src0, + global uchar * dst_q, + global uchar * dst_e +) { + global struct block_mxfp4 * b = (global struct block_mxfp4 *) src0 + get_global_id(0); + global uchar * q = (global uchar *) dst_q + QK_MXFP4 / 2 * get_global_id(0); + global uchar * e = (global uchar *) dst_e + get_global_id(0); + + *e = b->e; + + for (int i = 0; i < QK_MXFP4 / 2; ++i) { + q[i] = b->qs[i]; + } +} + +kernel void kernel_restore_block_mxfp4( + global uchar * src_q, + global half * src_e, + global struct block_mxfp4 * dst +) { + global struct block_mxfp4 * b = (global struct block_mxfp4 *) dst + get_global_id(0); + global uchar * q = (global uchar *) src_q + QK_MXFP4 / 2 * get_global_id(0); + global uchar * e = (global uchar *) src_e + get_global_id(0); + + b->e = *e; + for (int i = 0; i < QK_MXFP4 / 2; ++i) { + b->qs[i] = q[i]; + } +} diff --git a/ggml/src/ggml-opencl/kernels/mul_mv_id_mxfp4_f32_flat.cl b/ggml/src/ggml-opencl/kernels/mul_mv_id_mxfp4_f32_flat.cl new file mode 100644 index 0000000000..f65e86ed6a --- /dev/null +++ b/ggml/src/ggml-opencl/kernels/mul_mv_id_mxfp4_f32_flat.cl @@ -0,0 +1,176 @@ +#pragma OPENCL EXTENSION cl_khr_fp16 : enable + +#ifdef cl_intel_subgroups +#pragma OPENCL EXTENSION cl_intel_subgroups : enable +#else +#pragma OPENCL EXTENSION cl_khr_subgroups : enable +#endif + +#ifdef cl_intel_required_subgroup_size +#pragma OPENCL EXTENSION cl_intel_required_subgroup_size : enable +#define INTEL_GPU 1 +#define REQD_SUBGROUP_SIZE_16 __attribute__((intel_reqd_sub_group_size(16))) +#define REQD_SUBGROUP_SIZE_32 __attribute__((intel_reqd_sub_group_size(32))) +#elif defined(cl_qcom_reqd_sub_group_size) +#pragma OPENCL EXTENSION cl_qcom_reqd_sub_group_size : enable +#define ADRENO_GPU 1 +#define REQD_SUBGROUP_SIZE_64 __attribute__((qcom_reqd_sub_group_size("half"))) +#define REQD_SUBGROUP_SIZE_128 __attribute__((qcom_reqd_sub_group_size("full"))) +#endif + +#define QK_MXFP4 32 + +static inline half4 mxfp4_to_fp16_packed(ushort fp4x4) { + ushort2 fp16_packed_a, fp16_packed_b, bias_a, bias_b, sign_a, sign_b; + fp16_packed_a.lo = (fp4x4 << 9) & 0x0E00; + fp16_packed_a.hi = (fp4x4 << 5) & 0x0E00; + fp16_packed_b.lo = (fp4x4 << 1) & 0x0E00; + fp16_packed_b.hi = (fp4x4 >> 3) & 0x0E00; + + bias_a.lo = (fp16_packed_a.lo == 0) ? 0x0 : 0x3800; + bias_a.hi = (fp16_packed_a.hi == 0) ? 0x0 : 0x3800; + bias_b.lo = (fp16_packed_b.lo == 0) ? 0x0 : 0x3800; + bias_b.hi = (fp16_packed_b.hi == 0) ? 0x0 : 0x3800; + + fp16_packed_a.lo = (fp16_packed_a.lo == 0x0200) ? 0x0 : fp16_packed_a.lo; + fp16_packed_a.hi = (fp16_packed_a.hi == 0x0200) ? 0x0 : fp16_packed_a.hi; + fp16_packed_b.lo = (fp16_packed_b.lo == 0x0200) ? 0x0 : fp16_packed_b.lo; + fp16_packed_b.hi = (fp16_packed_b.hi == 0x0200) ? 0x0 : fp16_packed_b.hi; + + sign_a.lo = (fp4x4 << 12) & 0x8000; + sign_a.hi = (fp4x4 << 8) & 0x8000; + sign_b.lo = (fp4x4 << 4) & 0x8000; + sign_b.hi = fp4x4 & 0x8000; + + fp16_packed_a = sign_a + bias_a + fp16_packed_a; + fp16_packed_b = sign_b + bias_b + fp16_packed_b; + + return as_half4((ushort4)(fp16_packed_a, fp16_packed_b)); +} + +static inline float e8m0_to_fp32(uchar x) { + int bits; + bits = (x == 0) ? 0x00400000 : ((uint) x << 23); + return as_float(bits); +} + +#ifdef INTEL_GPU +#define N_R0_MXFP4 2 // number of rows each subgroup works on +#define N_SG_MXFP4 2 // number of subgroups in a work group +#define N_SIMDWIDTH 16 // subgroup size +#elif defined (ADRENO_GPU) +#define N_R0_MXFP4 4 +#define N_SG_MXFP4 1 +#define N_SIMDWIDTH 64 +#define SRC0Q_IMG +#endif + +kernel void kernel_mul_mv_id_mxfp4_f32_flat( +#ifdef SRC0Q_IMG + __read_only image1d_buffer_t src0_q, +#else + global uchar * src0_q, +#endif + global uchar * src0_e, + global uchar * src1, + ulong offset1, + global uchar * src2, + ulong offset2, + global uchar * dst, + ulong offsetd, + int ne00, + ulong nb01, + ulong nb02, + ulong nb03, + int ne11, + int ne12, + ulong nb11, + ulong nb12, + ulong nb13, + int ne20, + int ne21, + ulong nb21, + int ne0, + int ne1, + int r2, + int r3 +) { + dst = dst + offsetd; + + const int iid1 = get_group_id(2) / ne20; + const int idx = get_group_id(2) % ne20; + + uint i02 = ((global uint *) (src2 + offset2 + iid1 * nb21))[idx]; + + int i11 = idx % ne11; + + int nb = ne00 / QK_MXFP4; + + uint src0_off = i02*nb02; + src0_off /= 17; // 17 = sizeof(block_mxfp4) + + src0_e = src0_e + src0_off; + + dst = dst + (idx * ne0 + iid1 * ne1 * ne0) * sizeof(float); + + int r0 = get_group_id(0); + int r1 = get_group_id(1); + + int first_row = (r0 * N_SG_MXFP4 + get_sub_group_id()) * N_R0_MXFP4; + + uint offset_src0 = first_row*nb01; + offset_src0 /= 17; // 17 = sizeof(block_mxfp4) +#ifdef SRC0Q_IMG + ulong offset_q = src0_off + offset_src0; +#else + src0_q = src0_q + src0_off*16; + global uchar16 * x_q = (global uchar16 *)(src0_q) + offset_src0; +#endif + global uchar * x_e = src0_e + offset_src0; + + const short ix = get_sub_group_local_id() >> 1; + const short it = get_sub_group_local_id() & 1; + + float sumf[N_R0_MXFP4] = {0.f}; + + src1 = src1 + offset1 + i11 * nb11 + iid1 * nb12; + global float * y = (global float *) (src1 + r1 * nb11); + global float * yb = y + ix * QK_MXFP4 + it * 8; + + for (int ib = ix; ib < nb; ib += N_SIMDWIDTH / 2) { + global float4 * y4 = (global float4 *)yb; + + #pragma unroll + for (short row = 0; row < N_R0_MXFP4; row++) { + uchar xb_e = x_e[row * nb + ib]; +#ifdef SRC0Q_IMG + ushort4 xb_q = as_ushort4(read_imageui(src0_q, (offset_q + row * nb + ib) * 2 + it).xy); +#else + ushort4 xb_q = vload4(0, (global ushort *)((global uchar *)(x_q + row * nb + ib) + 8 * it)); +#endif + + half4 fp16x4_0 = mxfp4_to_fp16_packed(xb_q.s0); + half4 fp16x4_1 = mxfp4_to_fp16_packed(xb_q.s1); + float4 acc1 = y4[0] * (float4)(fp16x4_0.s0, fp16x4_0.s2, fp16x4_1.s0, fp16x4_1.s2); + acc1 += y4[4] * (float4)(fp16x4_0.s1, fp16x4_0.s3, fp16x4_1.s1, fp16x4_1.s3); + + fp16x4_0 = mxfp4_to_fp16_packed(xb_q.s2); + fp16x4_1 = mxfp4_to_fp16_packed(xb_q.s3); + acc1 += y4[1] * (float4)(fp16x4_0.s0, fp16x4_0.s2, fp16x4_1.s0, fp16x4_1.s2); + acc1 += y4[5] * (float4)(fp16x4_0.s1, fp16x4_0.s3, fp16x4_1.s1, fp16x4_1.s3); + + sumf[row] += e8m0_to_fp32(xb_e) * ((acc1.s0 + acc1.s1) + (acc1.s2 + acc1.s3)); + } + + yb += (N_SIMDWIDTH / 2) * QK_MXFP4; + } + + global float * dst_f32 = (global float *)dst + (ulong)r1 * ne0; + + for (int row = 0; row < N_R0_MXFP4 && first_row + row < ne0; ++row) { + float sum_all = sub_group_reduce_add(sumf[row]); + if (get_sub_group_local_id() == 0) { + dst_f32[first_row + row] = sum_all; + } + } +} diff --git a/ggml/src/ggml-opencl/kernels/mul_mv_mxfp4_f32_flat.cl b/ggml/src/ggml-opencl/kernels/mul_mv_mxfp4_f32_flat.cl new file mode 100644 index 0000000000..3d5a923eee --- /dev/null +++ b/ggml/src/ggml-opencl/kernels/mul_mv_mxfp4_f32_flat.cl @@ -0,0 +1,167 @@ +#pragma OPENCL EXTENSION cl_khr_fp16 : enable + +#ifdef cl_intel_subgroups +#pragma OPENCL EXTENSION cl_intel_subgroups : enable +#else +#pragma OPENCL EXTENSION cl_khr_subgroups : enable +#endif + +#ifdef cl_intel_required_subgroup_size +#pragma OPENCL EXTENSION cl_intel_required_subgroup_size : enable +#define INTEL_GPU 1 +#define REQD_SUBGROUP_SIZE_16 __attribute__((intel_reqd_sub_group_size(16))) +#define REQD_SUBGROUP_SIZE_32 __attribute__((intel_reqd_sub_group_size(32))) +#elif defined(cl_qcom_reqd_sub_group_size) +#pragma OPENCL EXTENSION cl_qcom_reqd_sub_group_size : enable +#define ADRENO_GPU 1 +#define REQD_SUBGROUP_SIZE_64 __attribute__((qcom_reqd_sub_group_size("half"))) +#define REQD_SUBGROUP_SIZE_128 __attribute__((qcom_reqd_sub_group_size("full"))) +#endif + +#define QK_MXFP4 32 + +static inline half4 mxfp4_to_fp16_packed(ushort fp4x4) { + ushort2 fp16_packed_a, fp16_packed_b, bias_a, bias_b, sign_a, sign_b; + fp16_packed_a.lo = (fp4x4 << 9) & 0x0E00; + fp16_packed_a.hi = (fp4x4 << 5) & 0x0E00; + fp16_packed_b.lo = (fp4x4 << 1) & 0x0E00; + fp16_packed_b.hi = (fp4x4 >> 3) & 0x0E00; + + bias_a.lo = (fp16_packed_a.lo == 0) ? 0x0 : 0x3800; + bias_a.hi = (fp16_packed_a.hi == 0) ? 0x0 : 0x3800; + bias_b.lo = (fp16_packed_b.lo == 0) ? 0x0 : 0x3800; + bias_b.hi = (fp16_packed_b.hi == 0) ? 0x0 : 0x3800; + + fp16_packed_a.lo = (fp16_packed_a.lo == 0x0200) ? 0x0 : fp16_packed_a.lo; + fp16_packed_a.hi = (fp16_packed_a.hi == 0x0200) ? 0x0 : fp16_packed_a.hi; + fp16_packed_b.lo = (fp16_packed_b.lo == 0x0200) ? 0x0 : fp16_packed_b.lo; + fp16_packed_b.hi = (fp16_packed_b.hi == 0x0200) ? 0x0 : fp16_packed_b.hi; + + sign_a.lo = (fp4x4 << 12) & 0x8000; + sign_a.hi = (fp4x4 << 8) & 0x8000; + sign_b.lo = (fp4x4 << 4) & 0x8000; + sign_b.hi = fp4x4 & 0x8000; + + fp16_packed_a = sign_a + bias_a + fp16_packed_a; + fp16_packed_b = sign_b + bias_b + fp16_packed_b; + + return as_half4((ushort4)(fp16_packed_a, fp16_packed_b)); +} + +static inline float e8m0_to_fp32(uchar x) { + int bits; + bits = (x == 0) ? 0x00400000 : ((uint) x << 23); + return as_float(bits); +} + +#ifdef INTEL_GPU +#define N_R0_MXFP4 2 // number of rows each subgroup works on +#define N_SG_MXFP4 2 // number of subgroups in a work group +#define N_SIMDWIDTH 16 // subgroup size +#elif defined (ADRENO_GPU) +#define N_R0_MXFP4 2 +#define N_SG_MXFP4 2 +#define N_SIMDWIDTH 64 +#define SRC0Q_IMG +#endif + +#ifdef INTEL_GPU +REQD_SUBGROUP_SIZE_16 +#elif defined (ADRENO_GPU) +REQD_SUBGROUP_SIZE_64 +#endif +kernel void kernel_mul_mv_mxfp4_f32_flat( +#ifdef SRC0Q_IMG + __read_only image1d_buffer_t src0_q, +#else + global uchar * src0_q, +#endif + global uchar * src0_e, + global uchar * src1, + ulong offset1, + global uchar * dst, + ulong offsetd, + int ne00, + ulong nb01, + ulong nb02, + ulong nb03, + int ne12, + ulong nb11, + ulong nb12, + ulong nb13, + int ne0, + int ne1, + int r2, + int r3 +) { + src1 = src1 + offset1; + dst = dst + offsetd; + + int nb = ne00 / QK_MXFP4; + + int r0 = get_group_id(0); + int r1 = get_group_id(1); + int im = get_group_id(2); + + int first_row = (r0 * N_SG_MXFP4 + get_sub_group_id()) * N_R0_MXFP4; + + uint i12 = im % ne12; + uint i13 = im / ne12; + + uint offset_src0 = first_row*nb01 + (i12/r2)*nb02 + (i13/r3)*nb03; + // 17 = sizeof(block_mxfp4) + offset_src0 /= 17; +#ifdef SRC0Q_IMG + ulong offset_q = offset_src0; +#else + global uchar16 * x_q = (global uchar16 *)(src0_q) + offset_src0; +#endif + global uchar * x_e = src0_e + offset_src0; + + ulong offset_src1 = r1 * nb11 + i12 * nb12 + i13 * nb13; + global float * y = (global float *)(src1 + offset_src1); + + const short ix = get_sub_group_local_id() >> 1; // 0...15 + const short it = get_sub_group_local_id() & 1; // 0 or 1 + + float sumf[N_R0_MXFP4] = {0.f}; + + global float * yb = y + ix * QK_MXFP4 + it * 8; + + for (int ib = ix; ib < nb; ib += N_SIMDWIDTH/2) { + global float4 * y4 = (global float4 *)yb; + + #pragma unroll + for (short row = 0; row < N_R0_MXFP4; row++) { + uchar xb_e = x_e[row * nb + ib]; +#ifdef SRC0Q_IMG + ushort4 xb_q = as_ushort4(read_imageui(src0_q, (offset_q + row * nb + ib) * 2 + it).xy); +#else + ushort4 xb_q = vload4(0, (global ushort *)((global uchar *)(x_q + row * nb + ib) + 8 * it)); +#endif + + half4 fp16x4_0 = mxfp4_to_fp16_packed(xb_q.s0); + half4 fp16x4_1 = mxfp4_to_fp16_packed(xb_q.s1); + float4 acc1 = y4[0] * (float4)(fp16x4_0.s0, fp16x4_0.s2, fp16x4_1.s0, fp16x4_1.s2); + acc1 += y4[4] * (float4)(fp16x4_0.s1, fp16x4_0.s3, fp16x4_1.s1, fp16x4_1.s3); + + fp16x4_0 = mxfp4_to_fp16_packed(xb_q.s2); + fp16x4_1 = mxfp4_to_fp16_packed(xb_q.s3); + acc1 += y4[1] * (float4)(fp16x4_0.s0, fp16x4_0.s2, fp16x4_1.s0, fp16x4_1.s2); + acc1 += y4[5] * (float4)(fp16x4_0.s1, fp16x4_0.s3, fp16x4_1.s1, fp16x4_1.s3); + + sumf[row] += e8m0_to_fp32(xb_e) * ((acc1.s0 + acc1.s1) + (acc1.s2 + acc1.s3)); + } + + yb += (N_SIMDWIDTH/2) * QK_MXFP4; + } + + global float * dst_f32 = (global float *) dst + (ulong)im*ne0*ne1 + (ulong)r1*ne0; + + for (int row = 0; row < N_R0_MXFP4 && first_row + row < ne0; ++row) { + float sum_all = sub_group_reduce_add(sumf[row]); + if (get_sub_group_local_id() == 0) { + dst_f32[first_row + row] = sum_all; + } + } +} From 246c0d9c795fb25da8268625d597580155a3672f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Adrien=20Gallou=C3=ABt?= Date: Thu, 18 Sep 2025 23:07:18 +0200 Subject: [PATCH 41/52] cmake : fix static linking for OpenMP on Unix-like systems (#16031) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit When compiling with GGML_STATIC=ON, the build process would produce a binary that was still dynamically linked to OpenMP. This defeats the purpose of a static build: $ cmake -B build \ -DBUILD_SHARED_LIBS=OFF \ -DLLAMA_CURL=OFF \ -DGGML_CCACHE=OFF \ -DGGML_NATIVE=OFF \ -DGGML_STATIC=ON $ ldd llama-server linux-vdso.so.1 (0x0000e1a434e3b000) libgomp.so.1 => /lib/aarch64-linux-gnu/libgomp.so.1 (0x0000e1a4345a0000) libstdc++.so.6 => /lib/aarch64-linux-gnu/libstdc++.so.6 (0x0000e1a434300000) libm.so.6 => /lib/aarch64-linux-gnu/libm.so.6 (0x0000e1a434240000) libgcc_s.so.1 => /lib/aarch64-linux-gnu/libgcc_s.so.1 (0x0000e1a434200000) libc.so.6 => /lib/aarch64-linux-gnu/libc.so.6 (0x0000e1a434030000) /lib/ld-linux-aarch64.so.1 (0x0000e1a434df0000) This commit resolves the issue by modifying `CMAKE_FIND_LIBRARY_SUFFIXES` to prioritize `.a` files, forcing CMake to link the static version of the library. Signed-off-by: Adrien Gallouët --- ggml/src/CMakeLists.txt | 3 +++ 1 file changed, 3 insertions(+) diff --git a/ggml/src/CMakeLists.txt b/ggml/src/CMakeLists.txt index 2b5b8169d7..c8f3d85964 100644 --- a/ggml/src/CMakeLists.txt +++ b/ggml/src/CMakeLists.txt @@ -114,6 +114,9 @@ message(STATUS "GGML_SYSTEM_ARCH: ${GGML_SYSTEM_ARCH}") if (NOT MSVC) if (GGML_STATIC) + if (UNIX AND NOT APPLE) + set(CMAKE_FIND_LIBRARY_SUFFIXES ".a;.so") + endif() add_link_options(-static) if (MINGW) add_link_options(-static-libgcc -static-libstdc++) From 69ffd891631befa9e6b485fd646a16dab4f2c007 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Adrien=20Gallou=C3=ABt?= Date: Thu, 18 Sep 2025 23:07:26 +0200 Subject: [PATCH 42/52] ggml-amx : fix ggml_amx_init() on generic Linux (#16049) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Generalize Linux check to `__linux__` to support non-glibc systems (like musl). Also, return `false` on unknown/untested OS. Without this commit, the code compiles (with warnings) but fails: register_backend: registered backend CPU (1 devices) register_device: registered device CPU (Intel(R) Xeon(R) Platinum 8488C) build: 6487 (51c4cac6) with x86_64-linux-musl-gcc (GCC) 15.1.0 for x86_64-linux-musl (debug) system info: n_threads = 8, n_threads_batch = 8, total_threads = 16 .... print_info: n_ctx_orig_yarn = 262144 print_info: rope_finetuned = unknown print_info: model type = 4B Illegal instruction (core dumped) Signed-off-by: Adrien Gallouët --- ggml/src/ggml-cpu/amx/amx.cpp | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/ggml/src/ggml-cpu/amx/amx.cpp b/ggml/src/ggml-cpu/amx/amx.cpp index 258857b007..867e158dca 100644 --- a/ggml/src/ggml-cpu/amx/amx.cpp +++ b/ggml/src/ggml-cpu/amx/amx.cpp @@ -7,7 +7,7 @@ #include "ggml-cpu.h" #include "traits.h" -#if defined(__gnu_linux__) +#if defined(__linux__) #include #include #endif @@ -186,7 +186,7 @@ static size_t ggml_backend_amx_buffer_type_get_alloc_size(ggml_backend_buffer_ty #define XFEATURE_XTILEDATA 18 static bool ggml_amx_init() { -#if defined(__gnu_linux__) +#if defined(__linux__) if (syscall(SYS_arch_prctl, ARCH_REQ_XCOMP_PERM, XFEATURE_XTILEDATA)) { fprintf(stderr, "AMX is not ready to be used!\n"); return false; @@ -194,6 +194,8 @@ static bool ggml_amx_init() { return true; #elif defined(_WIN32) return true; +#else + return false; #endif } From 0dd58b6877f3dc106593d6bc68d98305f553c566 Mon Sep 17 00:00:00 2001 From: Xuan-Son Nguyen Date: Fri, 19 Sep 2025 11:31:56 +0700 Subject: [PATCH 43/52] ggml : refactor forward_dup for cpu backend (#16062) * ggml : refactor forward_dup for cpu backend * clean up a bit * add quant/dequant perf test --- ggml/src/ggml-cpu/common.h | 14 + ggml/src/ggml-cpu/ops.cpp | 927 +++---------------------------------- tests/test-backend-ops.cpp | 8 +- 3 files changed, 94 insertions(+), 855 deletions(-) diff --git a/ggml/src/ggml-cpu/common.h b/ggml/src/ggml-cpu/common.h index 353563dc35..6adca5437f 100644 --- a/ggml/src/ggml-cpu/common.h +++ b/ggml/src/ggml-cpu/common.h @@ -28,6 +28,14 @@ static inline float bf16_to_f32(ggml_bf16_t x) { return GGML_BF16_TO_FP32(x); } +static inline float i32_to_f32(int32_t x) { + return x; +} + +static inline int32_t f32_to_i32(float x) { + return x; +} + static inline float f32_to_f32(float x) { return x; } @@ -54,6 +62,12 @@ struct type_conversion_table { static constexpr ggml_bf16_t (*from_f32)(float) = f32_to_bf16; }; +template <> +struct type_conversion_table { + static constexpr float (*to_f32)(int32_t) = i32_to_f32; + static constexpr int32_t (*from_f32)(float) = f32_to_i32; +}; + static std::pair get_thread_range(const struct ggml_compute_params * params, const struct ggml_tensor * src0) { const int64_t ith = params->ith; const int64_t nth = params->nth; diff --git a/ggml/src/ggml-cpu/ops.cpp b/ggml/src/ggml-cpu/ops.cpp index c4824d145a..763ab099e3 100644 --- a/ggml/src/ggml-cpu/ops.cpp +++ b/ggml/src/ggml-cpu/ops.cpp @@ -41,13 +41,15 @@ static void ggml_compute_forward_dup_same_cont( } } -static void ggml_compute_forward_dup_f16( +template +static void ggml_compute_forward_dup_flt( const ggml_compute_params * params, ggml_tensor * dst) { const ggml_tensor * src0 = dst->src[0]; GGML_ASSERT(ggml_nelements(dst) == ggml_nelements(src0)); + GGML_ASSERT(!ggml_is_quantized(src0->type) && !ggml_is_quantized(dst->type)); GGML_TENSOR_UNARY_OP_LOCALS @@ -62,6 +64,7 @@ static void ggml_compute_forward_dup_f16( const int ir0 = dr * ith; const int ir1 = MIN(ir0 + dr, nr); + // case: type & row size equal if (src0->type == dst->type && ne00 == ne0 && nb00 == ggml_type_size(src0->type) && nb0 == ggml_type_size(dst->type)) { @@ -80,11 +83,11 @@ static void ggml_compute_forward_dup_f16( return; } - // TODO: add more special-case implementations for tensor shapes/strides that can benefit from memcpy - + // case: dst tensor is contiguous if (ggml_is_contiguous(dst)) { - if (nb00 == sizeof(ggml_fp16_t)) { - if (dst->type == GGML_TYPE_F16) { + if (nb00 == sizeof(src_t)) { + if constexpr (std::is_same_v) { + // same type size_t id = 0; const size_t rs = ne00 * nb00; char * dst_ptr = (char *) dst->data; @@ -100,91 +103,46 @@ static void ggml_compute_forward_dup_f16( id += rs * (ne01 - ir1); } } - } else if (dst->type == GGML_TYPE_F32) { + } else { + // casting between non-quantized types size_t id = 0; - float * dst_ptr = (float *) dst->data; + dst_t * dst_ptr = (dst_t *) dst->data; for (int i03 = 0; i03 < ne03; i03++) { for (int i02 = 0; i02 < ne02; i02++) { id += ne00 * ir0; for (int i01 = ir0; i01 < ir1; i01++) { - const ggml_fp16_t * src0_ptr = (ggml_fp16_t *) ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03); + const src_t * src0_ptr = (src_t *) ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03); for (int i00 = 0; i00 < ne00; i00++) { - dst_ptr[id] = GGML_CPU_FP16_TO_FP32(src0_ptr[i00]); + float tmp = type_conversion_table::to_f32(src0_ptr[i00]); + dst_ptr[id] = type_conversion_table::from_f32(tmp); id++; } } id += ne00 * (ne01 - ir1); } } - } else if (ggml_get_type_traits_cpu(dst->type)->from_float) { - ggml_from_float_t const quantize_row_q = ggml_get_type_traits_cpu(dst->type)->from_float; - float * src0_f32 = (float *) params->wdata + (ne00 + CACHE_LINE_SIZE_F32) * ith; - - size_t id = 0; - size_t rs = nb0 * (ne00 / ggml_blck_size(dst->type)); - char * dst_ptr = (char *) dst->data; - - for (int i03 = 0; i03 < ne03; i03++) { - for (int i02 = 0; i02 < ne02; i02++) { - id += rs * ir0; - for (int i01 = ir0; i01 < ir1; i01++) { - const ggml_fp16_t * src0_ptr = (ggml_fp16_t *) ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03); - - for (int i00 = 0; i00 < ne00; i00++) { - src0_f32[i00] = GGML_CPU_FP16_TO_FP32(src0_ptr[i00]); - } - - quantize_row_q(src0_f32, dst_ptr + id, ne00); - id += rs; - } - id += rs * (ne01 - ir1); - } - } - } else { - GGML_ABORT("fatal error"); // TODO: implement } } else { //printf("%s: this is not optimal - fix me\n", __func__); - if (dst->type == GGML_TYPE_F32) { - size_t id = 0; - float * dst_ptr = (float *) dst->data; + size_t id = 0; + dst_t * dst_ptr = (dst_t *) dst->data; - for (int i03 = 0; i03 < ne03; i03++) { - for (int i02 = 0; i02 < ne02; i02++) { - id += ne00 * ir0; - for (int i01 = ir0; i01 < ir1; i01++) { - for (int i00 = 0; i00 < ne00; i00++) { - const ggml_fp16_t * src0_ptr = (ggml_fp16_t *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); + for (int i03 = 0; i03 < ne03; i03++) { + for (int i02 = 0; i02 < ne02; i02++) { + id += ne00 * ir0; + for (int i01 = ir0; i01 < ir1; i01++) { + for (int i00 = 0; i00 < ne00; i00++) { + const src_t * src0_ptr = (src_t *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); - dst_ptr[id] = GGML_CPU_FP16_TO_FP32(*src0_ptr); - id++; - } + float tmp = type_conversion_table::to_f32(*src0_ptr); + dst_ptr[id] = type_conversion_table::from_f32(tmp); + id++; } - id += ne00 * (ne01 - ir1); } + id += ne00 * (ne01 - ir1); } - } else if (dst->type == GGML_TYPE_F16) { - size_t id = 0; - ggml_fp16_t * dst_ptr = (ggml_fp16_t *) dst->data; - - for (int i03 = 0; i03 < ne03; i03++) { - for (int i02 = 0; i02 < ne02; i02++) { - id += ne00 * ir0; - for (int i01 = ir0; i01 < ir1; i01++) { - for (int i00 = 0; i00 < ne00; i00++) { - const ggml_fp16_t * src0_ptr = (ggml_fp16_t *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); - - dst_ptr[id] = *src0_ptr; - id++; - } - } - id += ne00 * (ne01 - ir1); - } - } - } else { - GGML_ABORT("fatal error"); // TODO: implement } } return; @@ -196,7 +154,7 @@ static void ggml_compute_forward_dup_f16( int64_t i12 = 0; int64_t i13 = 0; - if (dst->type == GGML_TYPE_F16) { + if constexpr (std::is_same_v) { for (int64_t i03 = 0; i03 < ne03; i03++) { for (int64_t i02 = 0; i02 < ne02; i02++) { i10 += ne00 * ir0; @@ -217,7 +175,7 @@ static void ggml_compute_forward_dup_f16( const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3); - memcpy(dst_ptr, src0_ptr, sizeof(ggml_fp16_t)); + memcpy(dst_ptr, src0_ptr, sizeof(dst_t)); if (++i10 == ne00) { i10 = 0; @@ -248,7 +206,8 @@ static void ggml_compute_forward_dup_f16( } } } - } else if (dst->type == GGML_TYPE_F32) { + + } else { for (int64_t i03 = 0; i03 < ne03; i03++) { for (int64_t i02 = 0; i02 < ne02; i02++) { i10 += ne00 * ir0; @@ -269,7 +228,8 @@ static void ggml_compute_forward_dup_f16( const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3); - *(float *) dst_ptr = GGML_CPU_FP16_TO_FP32(*(const ggml_fp16_t *) src0_ptr); + float tmp = type_conversion_table::to_f32(*(const src_t *) src0_ptr); + *(dst_t *) dst_ptr = type_conversion_table::from_f32(tmp); if (++i10 == ne0) { i10 = 0; @@ -300,18 +260,19 @@ static void ggml_compute_forward_dup_f16( } } } - } else { - GGML_ABORT("fatal error"); // TODO: implement } } -static void ggml_compute_forward_dup_bf16( + +template +static void ggml_compute_forward_dup_to_q( const ggml_compute_params * params, ggml_tensor * dst) { const ggml_tensor * src0 = dst->src[0]; GGML_ASSERT(ggml_nelements(dst) == ggml_nelements(src0)); + GGML_ASSERT(!ggml_is_quantized(src0->type)); GGML_TENSOR_UNARY_OP_LOCALS @@ -326,785 +287,36 @@ static void ggml_compute_forward_dup_bf16( const int ir0 = dr * ith; const int ir1 = MIN(ir0 + dr, nr); - if (src0->type == dst->type && - ne00 == ne0 && - nb00 == ggml_type_size(src0->type) && nb0 == ggml_type_size(dst->type)) { - // copy by rows - const size_t rs = ne00*nb00; - for (int64_t i03 = 0; i03 < ne03; i03++) { - for (int64_t i02 = 0; i02 < ne02; i02++) { - for (int64_t i01 = ir0; i01 < ir1; i01++) { - memcpy( - ((char *) dst->data + i01*nb1 + i02*nb2 + i03*nb3), - ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03), - rs); - } - } - } - return; - } + if (ggml_is_contiguous(dst) && + nb00 == sizeof(src_t) && + ggml_get_type_traits_cpu(dst->type)->from_float) { + // casting non-quantized types --> intermediate f32 --> quantized + ggml_from_float_t const quantize_row_q = ggml_get_type_traits_cpu(dst->type)->from_float; + float * src0_f32 = (float *) params->wdata + (ne00 + CACHE_LINE_SIZE_F32) * ith; - // TODO: add more special-case implementations for tensor shapes/strides that can benefit from memcpy + size_t id = 0; + size_t rs = nb0 * (ne00 / ggml_blck_size(dst->type)); + char * dst_ptr = (char *) dst->data; - if (ggml_is_contiguous(dst)) { - if (nb00 == sizeof(ggml_bf16_t)) { - if (dst->type == GGML_TYPE_BF16) { - size_t id = 0; - const size_t rs = ne00 * nb00; - char * dst_ptr = (char *) dst->data; + for (int i03 = 0; i03 < ne03; i03++) { + for (int i02 = 0; i02 < ne02; i02++) { + id += rs * ir0; + for (int i01 = ir0; i01 < ir1; i01++) { + const src_t * src0_ptr = (src_t *) ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03); - for (int i03 = 0; i03 < ne03; i03++) { - for (int i02 = 0; i02 < ne02; i02++) { - id += rs * ir0; - for (int i01 = ir0; i01 < ir1; i01++) { - const char * src0_ptr = (char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03; - memcpy(dst_ptr + id, src0_ptr, rs); - id += rs; - } - id += rs * (ne01 - ir1); - } - } - } else if (dst->type == GGML_TYPE_F16) { - size_t id = 0; - ggml_fp16_t * dst_ptr = (ggml_fp16_t *) dst->data; - - for (int i03 = 0; i03 < ne03; i03++) { - for (int i02 = 0; i02 < ne02; i02++) { - id += ne00 * ir0; - for (int i01 = ir0; i01 < ir1; i01++) { - const ggml_bf16_t * src0_ptr = (ggml_bf16_t *) ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03); - for (int i00 = 0; i00 < ne00; i00++) { - dst_ptr[id] = GGML_CPU_FP32_TO_FP16(GGML_BF16_TO_FP32(src0_ptr[i00])); - id++; - } - } - id += ne00 * (ne01 - ir1); - } - } - } else if (dst->type == GGML_TYPE_F32) { - size_t id = 0; - float * dst_ptr = (float *) dst->data; - - for (int i03 = 0; i03 < ne03; i03++) { - for (int i02 = 0; i02 < ne02; i02++) { - id += ne00 * ir0; - for (int i01 = ir0; i01 < ir1; i01++) { - const ggml_bf16_t * src0_ptr = (ggml_bf16_t *) ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03); - for (int i00 = 0; i00 < ne00; i00++) { - dst_ptr[id] = GGML_BF16_TO_FP32(src0_ptr[i00]); - id++; - } - } - id += ne00 * (ne01 - ir1); - } - } - } else if (ggml_get_type_traits_cpu(dst->type)->from_float) { - ggml_from_float_t const quantize_row_q = ggml_get_type_traits_cpu(dst->type)->from_float; - float * src0_f32 = (float *) params->wdata + (ne00 + CACHE_LINE_SIZE_F32) * ith; - - size_t id = 0; - size_t rs = nb0 * (ne00 / ggml_blck_size(dst->type)); - char * dst_ptr = (char *) dst->data; - - for (int i03 = 0; i03 < ne03; i03++) { - for (int i02 = 0; i02 < ne02; i02++) { - id += rs * ir0; - for (int i01 = ir0; i01 < ir1; i01++) { - const ggml_bf16_t * src0_ptr = (ggml_bf16_t *) ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03); - - for (int i00 = 0; i00 < ne00; i00++) { - src0_f32[i00] = GGML_BF16_TO_FP32(src0_ptr[i00]); - } - - quantize_row_q(src0_f32, dst_ptr + id, ne00); - id += rs; - } - id += rs * (ne01 - ir1); - } - } - } else { - GGML_ABORT("fatal error"); // TODO: implement - } - } else { - //printf("%s: this is not optimal - fix me\n", __func__); - - if (dst->type == GGML_TYPE_F32) { - size_t id = 0; - float * dst_ptr = (float *) dst->data; - - for (int i03 = 0; i03 < ne03; i03++) { - for (int i02 = 0; i02 < ne02; i02++) { - id += ne00 * ir0; - for (int i01 = ir0; i01 < ir1; i01++) { - for (int i00 = 0; i00 < ne00; i00++) { - const ggml_bf16_t * src0_ptr = (ggml_bf16_t *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); - - dst_ptr[id] = GGML_BF16_TO_FP32(*src0_ptr); - id++; - } - } - id += ne00 * (ne01 - ir1); - } - } - } else if (dst->type == GGML_TYPE_BF16) { - size_t id = 0; - ggml_bf16_t * dst_ptr = (ggml_bf16_t *) dst->data; - - for (int i03 = 0; i03 < ne03; i03++) { - for (int i02 = 0; i02 < ne02; i02++) { - id += ne00 * ir0; - for (int i01 = ir0; i01 < ir1; i01++) { - for (int i00 = 0; i00 < ne00; i00++) { - const ggml_bf16_t * src0_ptr = (ggml_bf16_t *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); - - dst_ptr[id] = *src0_ptr; - id++; - } - } - id += ne00 * (ne01 - ir1); - } - } - } else if (dst->type == GGML_TYPE_F16) { - size_t id = 0; - ggml_fp16_t * dst_ptr = (ggml_fp16_t *) dst->data; - - for (int i03 = 0; i03 < ne03; i03++) { - for (int i02 = 0; i02 < ne02; i02++) { - id += ne00 * ir0; - for (int i01 = ir0; i01 < ir1; i01++) { - for (int i00 = 0; i00 < ne00; i00++) { - const ggml_bf16_t * src0_ptr = (ggml_bf16_t *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); - - dst_ptr[id] = GGML_CPU_FP32_TO_FP16(GGML_BF16_TO_FP32(*src0_ptr)); - id++; - } - } - id += ne00 * (ne01 - ir1); - } - } - } else { - GGML_ABORT("fatal error"); // TODO: implement - } - } - return; - } - - // dst counters - int64_t i10 = 0; - int64_t i11 = 0; - int64_t i12 = 0; - int64_t i13 = 0; - - if (dst->type == GGML_TYPE_BF16) { - for (int64_t i03 = 0; i03 < ne03; i03++) { - for (int64_t i02 = 0; i02 < ne02; i02++) { - i10 += ne00 * ir0; - while (i10 >= ne0) { - i10 -= ne0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - for (int64_t i01 = ir0; i01 < ir1; i01++) { - for (int64_t i00 = 0; i00 < ne00; i00++) { - const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); - char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3); - - memcpy(dst_ptr, src0_ptr, sizeof(ggml_bf16_t)); - - if (++i10 == ne00) { - i10 = 0; - if (++i11 == ne01) { - i11 = 0; - if (++i12 == ne02) { - i12 = 0; - if (++i13 == ne03) { - i13 = 0; - } - } - } - } - } - } - i10 += ne00 * (ne01 - ir1); - while (i10 >= ne0) { - i10 -= ne0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - } - } - } else if (dst->type == GGML_TYPE_F16) { - for (int64_t i03 = 0; i03 < ne03; i03++) { - for (int64_t i02 = 0; i02 < ne02; i02++) { - i10 += ne00 * ir0; - while (i10 >= ne0) { - i10 -= ne0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - for (int64_t i01 = ir0; i01 < ir1; i01++) { - for (int64_t i00 = 0; i00 < ne00; i00++) { - const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); - char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3); - - *(ggml_fp16_t *) dst_ptr = GGML_CPU_FP32_TO_FP16(GGML_BF16_TO_FP32(*(const ggml_bf16_t *) src0_ptr)); - - if (++i10 == ne0) { - i10 = 0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - } - } - i10 += ne00 * (ne01 - ir1); - while (i10 >= ne0) { - i10 -= ne0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - } - } - } else if (dst->type == GGML_TYPE_F32) { - for (int64_t i03 = 0; i03 < ne03; i03++) { - for (int64_t i02 = 0; i02 < ne02; i02++) { - i10 += ne00 * ir0; - while (i10 >= ne0) { - i10 -= ne0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - for (int64_t i01 = ir0; i01 < ir1; i01++) { - for (int64_t i00 = 0; i00 < ne00; i00++) { - const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); - char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3); - - *(float *) dst_ptr = GGML_BF16_TO_FP32(*(const ggml_bf16_t *) src0_ptr); - - if (++i10 == ne0) { - i10 = 0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - } - } - i10 += ne00 * (ne01 - ir1); - while (i10 >= ne0) { - i10 -= ne0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } + for (int i00 = 0; i00 < ne00; i00++) { + src0_f32[i00] = type_conversion_table::to_f32(src0_ptr[i00]); } + + quantize_row_q(src0_f32, dst_ptr + id, ne00); + id += rs; } + id += rs * (ne01 - ir1); } } } else { - GGML_ABORT("fatal error"); // TODO: implement - } -} - -static void ggml_compute_forward_dup_f32( - const ggml_compute_params * params, - ggml_tensor * dst) { - - const ggml_tensor * src0 = dst->src[0]; - - GGML_ASSERT(ggml_nelements(dst) == ggml_nelements(src0)); - - GGML_TENSOR_UNARY_OP_LOCALS - - const int ith = params->ith; // thread index - const int nth = params->nth; // number of threads - - // parallelize by rows - const int nr = ne01; - // number of rows per thread - const int dr = (nr + nth - 1) / nth; - // row range for this thread - const int ir0 = dr * ith; - const int ir1 = MIN(ir0 + dr, nr); - - if (src0->type == dst->type && - ne00 == ne0 && - nb00 == ggml_type_size(src0->type) && nb0 == ggml_type_size(dst->type)) { - // copy by rows - const size_t rs = ne00*nb00; - for (int64_t i03 = 0; i03 < ne03; i03++) { - for (int64_t i02 = 0; i02 < ne02; i02++) { - for (int64_t i01 = ir0; i01 < ir1; i01++) { - memcpy( - ((char *) dst->data + i01*nb1 + i02*nb2 + i03*nb3), - ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03), - rs); - } - } - } - return; - } - - if (ggml_is_contiguous(dst)) { - // TODO: simplify - if (nb00 == sizeof(float)) { - if (ggml_get_type_traits_cpu(dst->type)->from_float) { - ggml_from_float_t const from_float = ggml_get_type_traits_cpu(dst->type)->from_float; - - size_t id = 0; - size_t rs = nb0 * (ne00 / ggml_blck_size(dst->type)); - char * dst_ptr = (char *) dst->data; - - for (int i03 = 0; i03 < ne03; i03++) { - for (int i02 = 0; i02 < ne02; i02++) { - id += rs * ir0; - for (int i01 = ir0; i01 < ir1; i01++) { - const float * src0_ptr = (float *) ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03); - from_float(src0_ptr, dst_ptr + id, ne00); - id += rs; - } - id += rs * (ne01 - ir1); - } - } - } else { - GGML_ABORT("fatal error"); // TODO: implement - } - } else { - //printf("%s: this is not optimal - fix me\n", __func__); - - if (dst->type == GGML_TYPE_F32) { - size_t id = 0; - float * dst_ptr = (float *) dst->data; - - for (int i03 = 0; i03 < ne03; i03++) { - for (int i02 = 0; i02 < ne02; i02++) { - id += ne00 * ir0; - for (int i01 = ir0; i01 < ir1; i01++) { - for (int i00 = 0; i00 < ne00; i00++) { - const float * src0_ptr = (float *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); - - dst_ptr[id] = *src0_ptr; - id++; - } - } - id += ne00 * (ne01 - ir1); - } - } - } else if (dst->type == GGML_TYPE_F16) { - size_t id = 0; - ggml_fp16_t * dst_ptr = (ggml_fp16_t *) dst->data; - - for (int i03 = 0; i03 < ne03; i03++) { - for (int i02 = 0; i02 < ne02; i02++) { - id += ne00 * ir0; - for (int i01 = ir0; i01 < ir1; i01++) { - for (int i00 = 0; i00 < ne00; i00++) { - const float * src0_ptr = (float *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); - - dst_ptr[id] = GGML_CPU_FP32_TO_FP16(*src0_ptr); - id++; - } - } - id += ne00 * (ne01 - ir1); - } - } - } else if (dst->type == GGML_TYPE_BF16) { - size_t id = 0; - ggml_bf16_t * dst_ptr = (ggml_bf16_t *) dst->data; - - for (int i03 = 0; i03 < ne03; i03++) { - for (int i02 = 0; i02 < ne02; i02++) { - id += ne00 * ir0; - for (int i01 = ir0; i01 < ir1; i01++) { - for (int i00 = 0; i00 < ne00; i00++) { - const float * src0_ptr = (float *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); - - dst_ptr[id] = GGML_FP32_TO_BF16(*src0_ptr); - id++; - } - } - id += ne00 * (ne01 - ir1); - } - } - } else if (dst->type == GGML_TYPE_I32) { - size_t id = 0; - int32_t * dst_ptr = (int32_t *) dst->data; - - for (int i03 = 0; i03 < ne03; i03++) { - for (int i02 = 0; i02 < ne02; i02++) { - id += ne00 * ir0; - for (int i01 = ir0; i01 < ir1; i01++) { - for (int i00 = 0; i00 < ne00; i00++) { - const float * src0_ptr = (float *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); - - dst_ptr[id] = *src0_ptr; - id++; - } - } - id += ne00 * (ne01 - ir1); - } - } - } else { - GGML_ABORT("fatal error"); // TODO: implement - } - } - - return; - } - - // dst counters - - int64_t i10 = 0; - int64_t i11 = 0; - int64_t i12 = 0; - int64_t i13 = 0; - - if (dst->type == GGML_TYPE_F32) { - for (int64_t i03 = 0; i03 < ne03; i03++) { - for (int64_t i02 = 0; i02 < ne02; i02++) { - i10 += ne00 * ir0; - while (i10 >= ne0) { - i10 -= ne0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - for (int64_t i01 = ir0; i01 < ir1; i01++) { - for (int64_t i00 = 0; i00 < ne00; i00++) { - const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); - char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3); - - memcpy(dst_ptr, src0_ptr, sizeof(float)); - - if (++i10 == ne0) { - i10 = 0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - } - } - i10 += ne00 * (ne01 - ir1); - while (i10 >= ne0) { - i10 -= ne0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - } - } - } else if (dst->type == GGML_TYPE_F16) { - for (int64_t i03 = 0; i03 < ne03; i03++) { - for (int64_t i02 = 0; i02 < ne02; i02++) { - i10 += ne00 * ir0; - while (i10 >= ne0) { - i10 -= ne0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - for (int64_t i01 = ir0; i01 < ir1; i01++) { - for (int64_t i00 = 0; i00 < ne00; i00++) { - const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); - char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3); - - *(ggml_fp16_t *) dst_ptr = GGML_CPU_FP32_TO_FP16(*(const float *) src0_ptr); - - if (++i10 == ne0) { - i10 = 0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - } - } - i10 += ne00 * (ne01 - ir1); - while (i10 >= ne0) { - i10 -= ne0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - } - } - } else if (dst->type == GGML_TYPE_BF16) { - for (int64_t i03 = 0; i03 < ne03; i03++) { - for (int64_t i02 = 0; i02 < ne02; i02++) { - i10 += ne00 * ir0; - while (i10 >= ne0) { - i10 -= ne0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - for (int64_t i01 = ir0; i01 < ir1; i01++) { - for (int64_t i00 = 0; i00 < ne00; i00++) { - const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); - char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3); - - *(ggml_bf16_t *) dst_ptr = GGML_FP32_TO_BF16(*(const float *) src0_ptr); - - if (++i10 == ne0) { - i10 = 0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - } - } - i10 += ne00 * (ne01 - ir1); - while (i10 >= ne0) { - i10 -= ne0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - } - } - } else if (dst->type == GGML_TYPE_I32) { - for (int64_t i03 = 0; i03 < ne03; i03++) { - for (int64_t i02 = 0; i02 < ne02; i02++) { - i10 += ne00 * ir0; - while (i10 >= ne0) { - i10 -= ne0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - for (int64_t i01 = ir0; i01 < ir1; i01++) { - for (int64_t i00 = 0; i00 < ne00; i00++) { - const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); - char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3); - - *(int32_t *) dst_ptr = *(const float *) src0_ptr; - - if (++i10 == ne0) { - i10 = 0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - } - } - i10 += ne00 * (ne01 - ir1); - while (i10 >= ne0) { - i10 -= ne0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - } - } - } else { - GGML_ABORT("fatal error"); // TODO: implement - } -} - -static void ggml_compute_forward_dup_i32( - const ggml_compute_params * params, - ggml_tensor * dst) { - - const ggml_tensor * src0 = dst->src[0]; - - GGML_ASSERT(ggml_nelements(dst) == ggml_nelements(src0)); - - GGML_TENSOR_UNARY_OP_LOCALS - - const int ith = params->ith; // thread index - const int nth = params->nth; // number of threads - - // parallelize by rows - const int nr = ne01; - // number of rows per thread - const int dr = (nr + nth - 1) / nth; - // row range for this thread - const int ir0 = dr * ith; - const int ir1 = MIN(ir0 + dr, nr); - - // dst counters - - int64_t i10 = 0; - int64_t i11 = 0; - int64_t i12 = 0; - int64_t i13 = 0; - - // TODO: not optimal, but works - if (dst->type == GGML_TYPE_F32) { - for (int64_t i03 = 0; i03 < ne03; i03++) { - for (int64_t i02 = 0; i02 < ne02; i02++) { - i10 += ne00 * ir0; - while (i10 >= ne0) { - i10 -= ne0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - for (int64_t i01 = ir0; i01 < ir1; i01++) { - for (int64_t i00 = 0; i00 < ne00; i00++) { - const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); - char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3); - - *(float *) dst_ptr = *(const int32_t *) src0_ptr; - - if (++i10 == ne0) { - i10 = 0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - } - } - i10 += ne00 * (ne01 - ir1); - while (i10 >= ne0) { - i10 -= ne0; - if (++i11 == ne1) { - i11 = 0; - if (++i12 == ne2) { - i12 = 0; - if (++i13 == ne3) { - i13 = 0; - } - } - } - } - } - } - } else { - GGML_ABORT("fatal error"); // TODO: implement + // printf("%s %s\n", ggml_type_name(src0->type), ggml_type_name(dst->type)); + GGML_ABORT("not implemented"); } } @@ -1258,7 +470,7 @@ static void ggml_compute_forward_dup_bytes( } } -static void ggml_compute_forward_dup_q( +static void ggml_compute_forward_dup_from_q( const ggml_compute_params * params, ggml_tensor * dst) { @@ -1323,24 +535,35 @@ void ggml_compute_forward_dup( switch (src0->type) { case GGML_TYPE_F16: { - ggml_compute_forward_dup_f16(params, dst); + /**/ if (dst->type == GGML_TYPE_F16) ggml_compute_forward_dup_flt(params, dst); + else if (dst->type == GGML_TYPE_BF16) ggml_compute_forward_dup_flt(params, dst); + else if (dst->type == GGML_TYPE_F32) ggml_compute_forward_dup_flt(params, dst); + else ggml_compute_forward_dup_to_q(params, dst); } break; case GGML_TYPE_BF16: { - ggml_compute_forward_dup_bf16(params, dst); + /**/ if (dst->type == GGML_TYPE_F16) ggml_compute_forward_dup_flt(params, dst); + else if (dst->type == GGML_TYPE_BF16) ggml_compute_forward_dup_flt(params, dst); + else if (dst->type == GGML_TYPE_F32) ggml_compute_forward_dup_flt(params, dst); + else ggml_compute_forward_dup_to_q(params, dst); } break; case GGML_TYPE_F32: { - ggml_compute_forward_dup_f32(params, dst); + /**/ if (dst->type == GGML_TYPE_F16) ggml_compute_forward_dup_flt(params, dst); + else if (dst->type == GGML_TYPE_BF16) ggml_compute_forward_dup_flt(params, dst); + else if (dst->type == GGML_TYPE_F32) ggml_compute_forward_dup_flt(params, dst); + else if (dst->type == GGML_TYPE_I32) ggml_compute_forward_dup_flt(params, dst); + else ggml_compute_forward_dup_to_q(params, dst); } break; case GGML_TYPE_I32: { - ggml_compute_forward_dup_i32(params, dst); + if (dst->type == GGML_TYPE_F32) ggml_compute_forward_dup_flt(params, dst); + else GGML_ABORT("not implemented"); } break; default: { if (ggml_is_quantized(src0->type) && dst->type == GGML_TYPE_F32) { - ggml_compute_forward_dup_q(params, dst); + ggml_compute_forward_dup_from_q(params, dst); break; } GGML_ABORT("fatal error"); diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp index 01cbf87533..507b691dc9 100644 --- a/tests/test-backend-ops.cpp +++ b/tests/test-backend-ops.cpp @@ -6629,9 +6629,11 @@ static std::vector> make_test_cases_perf() { test_cases.emplace_back(new test_bin_bcast(ggml_add, GGML_TYPE_F32, {4096, 1, 1, 1}, {1, 1, 1, 1})); test_cases.emplace_back(new test_bin_bcast(ggml_add, GGML_TYPE_F32, {4096, 1, 1, 1}, {1, 512, 1, 1})); - test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F16, {512, 3072, 1, 1})); - test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {8192, 512, 2, 1}, {0, 2, 1, 3})); - test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {3072, 512, 2, 1}, {0, 2, 1, 3})); + test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F16, {512, 3072, 1, 1})); + test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {8192, 512, 2, 1}, {0, 2, 1, 3})); + test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {3072, 512, 2, 1}, {0, 2, 1, 3})); + test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_Q4_0, {8192, 512, 2, 1})); + test_cases.emplace_back(new test_cpy(GGML_TYPE_Q4_0, GGML_TYPE_F32, {8192, 512, 2, 1})); test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {4096, 4096, 5, 1}, false, false, GGML_TYPE_F32, {1, 1}, 1.0f, 0.0f)); test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {12888, 256, 5, 1}, false, false, GGML_TYPE_F32, {1, 1}, 1.0f, 0.0f)); From 4b8560ab56fdd9819358b47c338bbc8ec357c57e Mon Sep 17 00:00:00 2001 From: Xuan-Son Nguyen Date: Fri, 19 Sep 2025 13:02:51 +0700 Subject: [PATCH 44/52] chat : fix build on arm64 (#16101) --- common/chat.cpp | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/common/chat.cpp b/common/chat.cpp index 4707c4fef4..5ac57f1e80 100644 --- a/common/chat.cpp +++ b/common/chat.cpp @@ -1741,10 +1741,12 @@ static void common_chat_parse_gpt_oss(common_chat_msg_parser & builder) { static common_chat_params common_chat_params_init_firefunction_v2(const common_chat_template & tmpl, const struct templates_params & inputs) { LOG_DBG("%s\n", __func__); common_chat_params data; - data.prompt = apply(tmpl, inputs, /* messages_override =*/ std::nullopt, /* tools_override= */ json(), json { + const std::optional tools_override = json(); + const std::optional additional_context = json { {"datetime", format_time(inputs.now, "%b %d %Y %H:%M:%S GMT")}, {"functions", json(inputs.tools.empty() ? "" : inputs.tools.dump(2))}, - }); + }; + data.prompt = apply(tmpl, inputs, /* messages_override =*/ std::nullopt, tools_override, additional_context); if (inputs.tools.is_array() && !inputs.tools.empty()) { data.grammar_lazy = inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_REQUIRED; data.grammar = build_grammar([&](const common_grammar_builder & builder) { From 4067f07fc5aa5722b87db303b561597004696f6c Mon Sep 17 00:00:00 2001 From: Aleksander Grygier Date: Fri, 19 Sep 2025 09:52:27 +0200 Subject: [PATCH 45/52] feat: Improve mobile UI for Settings Dialog (#16084) * feat: Improve mobile UI for Settings Dialog * chore: update webui build output * fix: Linting errors * chore: update webui build output --- tools/server/public/index.html.gz | Bin 842295 -> 843352 bytes .../server/webui/scripts/install-git-hooks.sh | 16 +- tools/server/webui/src/app.css | 12 + .../ChatSettings/ChatSettingsDialog.svelte | 275 +++++++++--------- .../ChatSettings/ChatSettingsFields.svelte | 145 +++++++++ .../ChatSettings/ChatSettingsFooter.svelte | 13 +- .../ChatSettings/ChatSettingsSection.svelte | 23 -- .../webui/src/lib/components/app/index.ts | 2 +- 8 files changed, 313 insertions(+), 173 deletions(-) create mode 100644 tools/server/webui/src/lib/components/app/chat/ChatSettings/ChatSettingsFields.svelte delete mode 100644 tools/server/webui/src/lib/components/app/chat/ChatSettings/ChatSettingsSection.svelte diff --git a/tools/server/public/index.html.gz b/tools/server/public/index.html.gz index 909fa1cceb81d4030c5a11b475304ba206a8d95b..c6d8258d7f81499c0317e6a32c3f89227ac875c4 100644 GIT binary patch delta 842424 zcmV((K;XZ(v@_VeGmsX4@t)kZ9FiuRq#pD*XB5kEG#kosERRQya&joLMYhD(vPny% zuI^{QzbZT$=te(C$ur69Om;0cP$(1%g+c)+6#o2GrShjz>2w%`CH!Bv6b6&Q$S++6 z_~&97jQXYNWoa=)%6vLm_>+DW;KvIFUM{BN?jq=QN266~;7|O2d3WLWOBX9HAWF~X z)1DuORO)D2noJiZzaK0B00dk~KbZTy#b`wkr_<87d+nEc!|r6@hvm}Tzx3y&#gq{~ z`RHGiJ{&(Og(whAC#7J*=|8_dJnFoz{;5*=_D_HQsz2>5Rx`geT#QHfraz?-(7k-( 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a/tools/server/webui/scripts/install-git-hooks.sh b/tools/server/webui/scripts/install-git-hooks.sh index 740075e281..a2a3ca76f5 100755 --- a/tools/server/webui/scripts/install-git-hooks.sh +++ b/tools/server/webui/scripts/install-git-hooks.sh @@ -1,7 +1,7 @@ #!/bin/bash # Script to install pre-commit and post-commit hooks for webui -# Pre-commit: formats code and builds, stashes unstaged changes +# Pre-commit: formats, lints, checks, and builds code, stashes unstaged changes # Post-commit: automatically unstashes changes REPO_ROOT=$(git rev-parse --show-toplevel) @@ -44,6 +44,18 @@ if git diff --cached --name-only | grep -q "^tools/server/webui/"; then exit 1 fi + # Run the lint command + npm run lint + + # Check if lint command succeeded + if [ $? -ne 0 ]; then + echo "Error: npm run lint failed" + if [ $STASH_CREATED -eq 0 ]; then + echo "You can restore your unstaged changes with: git stash pop" + fi + exit 1 + fi + # Run the check command npm run check @@ -112,7 +124,7 @@ if [ $? -eq 0 ]; then echo " Post-commit: $POST_COMMIT_HOOK" echo "" echo "The hooks will automatically:" - echo " • Format and build webui code before commits" + echo " • Format, lint, check, and build webui code before commits" echo " • Stash unstaged changes during the process" echo " • Restore your unstaged changes after the commit" echo "" diff --git a/tools/server/webui/src/app.css b/tools/server/webui/src/app.css index d05a422f02..a9ac80ab9c 100644 --- a/tools/server/webui/src/app.css +++ b/tools/server/webui/src/app.css @@ -121,3 +121,15 @@ @apply bg-background text-foreground; } } + +@layer utilities { + .scrollbar-hide { + /* Hide scrollbar for Chrome, Safari and Opera */ + &::-webkit-scrollbar { + display: none; + } + /* Hide scrollbar for IE, Edge and Firefox */ + -ms-overflow-style: none; + scrollbar-width: none; + } +} diff --git a/tools/server/webui/src/lib/components/app/chat/ChatSettings/ChatSettingsDialog.svelte b/tools/server/webui/src/lib/components/app/chat/ChatSettings/ChatSettingsDialog.svelte index 6752f06636..0d9cca0589 100644 --- a/tools/server/webui/src/lib/components/app/chat/ChatSettings/ChatSettingsDialog.svelte +++ b/tools/server/webui/src/lib/components/app/chat/ChatSettings/ChatSettingsDialog.svelte @@ -1,15 +1,20 @@ - -

    -
    + +
    + + - -
    - - {#each currentSection.fields as field (field.key)} -
    - {#if field.type === 'input'} - + +
    +
    + Settings - (localConfig[field.key] = e.currentTarget.value)} - placeholder={`Default: ${SETTING_CONFIG_DEFAULT[field.key] || 'none'}`} - class="max-w-md" - /> - {#if field.help || SETTING_CONFIG_INFO[field.key]} -

    - {field.help || SETTING_CONFIG_INFO[field.key]} -

    - {/if} - {:else if field.type === 'textarea'} - + +
    + -

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