* Add Parallelize*Range helpers and partitioning helpers
* Refactor Pinning class, store original affinity (required to construct another NestedPools after pinning happened)
Compress:
* prevent Compress printing stats in tests
* zero-pad tensors
Matmul:
* add matmul_unit_test (TODO) and bench_matmul
* matmul_test: change norm to row vectors (that is what is added) and include bf16 rounding error
* Prepare for L2/L3 retrieval
PiperOrigin-RevId: 700603811
Add Extents2D, Range2D vocab types
Matmul uses ConstMat for inputs and RowPtr for output
Move RowVectorBatch to basics.h
Separate threading.cc
Fix topology string: report cores not LPs, and #HT
Move QStride/IsMHA into LayerConfig
ImageTokens does not require make_unique.
matmul_test: no longer require template args
PiperOrigin-RevId: 692963605
Use ModelConfig values for ImageTokens.
Output timing info for image token generation.
Add a method to copy image data into Image class directly.
Minor changes: pipe ModelTraining to more places.
PiperOrigin-RevId: 690572283
Improved threading.h, fix thread counts for single package/cluster systems
Temporarily forces to a single socket. Prefill 29.28 tps, decode 6.92.
Also fix benchmarks.cc build, update tensor allocator to Allocator
PiperOrigin-RevId: 687307167
Changed CompressedLayer and CompressedWeights to be constructed with an instance of a LayerConfig and WeightsConfig respectively.
Added CompressedModel to remove ByteStorageT and get rid of most of the type casting, as well as allowing the default destructor to be used and work properly.
Adjusted WeightsWrapper and ForwardLayer etc to match.
The only remaining template arg is the weight type.
This enables all the instantiations to be deleted, apart from one per type.
It also enables (but not yet done) the config to be stored in the blob file instead of having to be specified separately.
Reduces the size of the gemma_lib and weights shared libraries by a factor of 4.3 and 3.2 respectively.
PiperOrigin-RevId: 686870060
add app.h comment
compress-inl: remove unused typedef
gemma-inl: add missing HWY_ATTR and cast
separate sum-inl.h and basics.h headers
replace more hwy::bfloat16_t with BF16
update include pragmas
update dot_test thresholds
update Highway version in Bazel for HWY_RCAST_ALIGNED fix
PiperOrigin-RevId: 684464326
Definition of array size is moved to the constructor.
Allocation is separate and parallelized.
All users of weights_raw.h migrated to CompressedWeights and weights_raw.h deleted.
Replaced all previous ForEachTensor functions with a single unified function.
PiperOrigin-RevId: 684451604
See https://arxiv.org/abs/2407.07726 for a description of the model.
Because PaliGemma operates as a prefix-LM on the image+prompt, add support for that.
PiperOrigin-RevId: 677841119
This can affect generation results after a few hundred tokens.
Also remove profiler from DecompressAndCall, use Add instead of +=,
use PackedSpan for args and remove alignment requirement.
Changing accumulation order in AssimilateCascadedSums updates dot_test thresholds.
PiperOrigin-RevId: 676891797
Compression:
* Implement {any packed} x {bf16, f32} 'Load2' and DecompressAndZeroPad
* New compression test for all packed formats, add to GEMMA_TEST_FILES, remove from sfp/nuq_test
* Decompress->DecompressAndZeroPad, use PackedSpan for args with bounds checking
* NUQ: support arbitrary-length enc/dec
* New compression/shared, remove sfp.h and nuq.h
* Move Store2 into Traits and provide Compress2 wrapper
* Remove unused Decompress()-with-pool overload
* Simplify CompressedArrayLen, rename to CompressedArrayElements
* Remove unused DistortionStats b_l1_
Misc:
* Add compensated and Kahan dot, support any length
* Use same Dot function everywhere
* Move exact arithmetic functions into fp_arith
* use FloatPtr and MatPtr typedefs in tests; less stack usage
* Rename args to packed/raw
* Remove Traits::Name, instead TypeName<T>()
* Move kMaxSFP and kClusters/kGroupSize into Sfp/NuqStream
PiperOrigin-RevId: 672868468
Supports converting all weight/activation formats to native MulT (bf16/f32)
Also:
- ConstMat/MutableMat for const correctness
- Move RowVectorBatch to allocator.h so it can be used from Matmul
- Add matmul.h so MatMulEnv can be used from Activations
- Remove kMaxThreads, detect from PerClusterPools
- Build fix: -inl.h files must be textual_hdrs, and highway.h should precede -inl.h
```
zen4 new
64, 24576, 3072, add=0, MatTA=bf16, MatTB=sfp: 616.6 GFLOPS.
64, 3072, 24576, add=0, MatTA=bf16, MatTB=sfp: 460.7 GFLOPS.
64, 24576, 3072, add=0, MatTA=f32, MatTB=sfp: 598.6 GFLOPS.
64, 3072, 24576, add=0, MatTA=f32, MatTB=sfp: 435.6 GFLOPS.
zen4 old
64, 24576, 3072, add=0, MatTA=f32, MatTB=sfp: 257.5 GFLOPS.
64, 3072, 24576, add=0, MatTA=f32, MatTB=sfp: 231.9 GFLOPS.
```
PiperOrigin-RevId: 663729812
Slower because we now init tiles of C and accumulate into them.
Also remove unused var in optimize_test and use BF16 typedef.
PiperOrigin-RevId: 662115916
SfpCodec::Dec2F and ComressTraits<T>::Decompress2 for all supported types. It also allows to remove one of the specializations of GEMM_4x4_Tile, handling compressed MatB with one function. As before even when MatA is bf16 it is using 32-bit registers for computations.
Measurements for a 2b-it sfp-encoded model on a AMD Ryzen Threadripper PRO 3945WX 12-Cores:
baseline:
```
32.6254 prefill tokens / sec
8.91429 tokens / sec
115 milliseconds time to first token
```
this change:
```
54.3045 prefill tokens / sec
16.8191 tokens / sec
56 milliseconds time to first token
```
PiperOrigin-RevId: 651369694
Helper functions to tokenize/wrap
Move LayersOutputFunc into RuntimeConfig
AcceptFunc passes the probability
Implement StringFromType using the parser, and verify results match
PiperOrigin-RevId: 643255119
This is still in progress / experimental, currently it is only
implemented for normal gemma MQA attention layers, and no
parallelism is added yet for backward pass.
Since we need to remember all activations from all layers, the
forward pass was also reimplemented with a new activation data
structure.
Remove extra Dot() overload
MatVecAdd always adds, use MatVecT<kAdd> if conditional.
Remove ununsed MatVecAddLoop and MatVecLoop
No longer tsan-verify even_odd
PiperOrigin-RevId: 631377279
Move Path into io.h and use for opening files.
Removes dependency of gemma_lib on args.
Separate Windows codepath instead of emulating POSIX functions.
Plus lint fixes.
PiperOrigin-RevId: 626279004
- Allow scaling of SFP weights
- Allow using uncompressed weights
- Do not try to compress weights in the main model calls
- Reduce code duplication in weight handling with some macros
Co-authored-by: Eugene Kliuchnikov <eustas@google.com>
Co-authored-by: Thomas Fischbacher <tfish@google.com>
Co-authored-by: Zoltan Szabadka <szabadka@google.com>
--
19694e1f2e by Silvio Traversaro <silvio@traversaro.it>:
Do not pass explicitly -O2 flag to compiler in Release build
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/gemma.cpp/pull/3 from traversaro:patch-1 19694e1f2e
PiperOrigin-RevId: 610096914
It's not possible to build `gemma.cpp` with the standard MSVC front-end
as it doesn't support arrays more than `0x7ffffffff` bytes (see Compiler Error C2148),
however this isn't a problem with the optional Visual Studio Clang/LLVM frontend.
This can be specified using the `-T` flag when running CMake:
```
$ cmake -B build -T ClangCL
$ cmake --build build --config Release
```
Windows doesn't provide `pread`/`pwrite` so this must be emulated using
the `ReadFile`/`WriteFile` Win32 APIs.
`_CRT_SECURE_NO_WARNINGS` is defined to prevent a large number of warnings
about using "depricated" function names (e.g. `close` instead of `_close`).
`NOMINMAX` is defined to prevent the `min`/`max` macros from `windows.h`
from conflicting with expressions like `std::min`. Generally libraries should
avoid including `windows.h` in their public headers or define `WIN32_LEAN_AND_MEAN`
before including the `windows.h` header, but this unfortunately isn't always the case.
Ray Smith
Jan Wassenberg
Paul Chang
Daniel Keysers
RangerUFO
Copybara-Service
The gemma.cpp Authors
Thomas Fischbacher
Andrey Vlasov
Kan Wu
Zoltan Szabadka
Sam Kaufman
Luca Versari
Eric Ye
enum-class
Dan Zheng
Silvio Traversaro
Austin Huang
Ikko Eltociear Ashimine
David Coles