Weight handling:
- new ModelStore2 supports both pre-2025 multi-file and single-file formats
- simpler ForEachTensor with TensorArgs
- tensors are constructed with their full suffixed name
I/O:
- support mmap and stride
- Simplified SbsWriter, single insert(); add SbsReader
Misc:
- kMockTokenizer: allow creating with unavailable tokenizer
- configs.h: Simpler enum validity checks via kSentinel
- matmul.h: remove unused enable_bind (now in allocator.h)
- tensor_info: single TensorInfoRegistry class, rename from tensor_index.h
Frontends:
- Replace Allocate/CreateGemma with ctor(LoaderArgs, MatMulEnv&)
- Deduce model/weight type, remove --model and parsing
- Replace most common.h includes with configs.h
- Remove --compressed_weights, use --weights instead
- Remove ModelInfo, replaced by ModelConfig.
Backprop:
- Reduce max loss, remove backward_scalar_test (timeout)
- Update thresholds because new RandInit changes rng eval order and thus numerics
PiperOrigin-RevId: 755317484
use new ThreadingContext2 instead of monostate/init in each frontend
Add ThreadingArgs(replaces AppArgs)
backprop: use Packed() accessor and MakePacked factory and row-based access to allow for stride
compress_weights: remove, moving to py-only exporter instead
Move MatPtr to mat.h and revise interface:
- Generic MatOwner
- rename accessors to Packed*
- support stride/row accessors, fix RowPtr stride
Add TypeBits(Type)
Move GenerateMat to test_util-inl for sharing between matmul test/bench
Move internal init to gemma.cc to avoid duplication
Rename GemmaEnv model_ to gemma_ for disambiguating vs upcoming ModelStorage
Remove --compressed_weights, use --weights instead.
tensor_index: add ExtentsFromInfo and TensorIndexLLM/Img
Allocator: use normal unique_ptr for AllocBytes so users can call directly
threading: use -> because AlignedPtr no longer assumes arrays
PiperOrigin-RevId: 745918637
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
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
This changes the command line flags, but the default value retains the previous behavior.
Also add a CreateGemma helper to enable extra args without interface changes.
PiperOrigin-RevId: 641266411
Split common and weights into separate lib
Remove common-inl (does not have to be SIMD code), activations.cc
Centralize switch(Model) to avoid duplication
Move CompressWeightsT to compress_weights.cc
Move LoadWeights to weights.cc
PiperOrigin-RevId: 640869202
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.
Jan Wassenberg
RangerUFO
Phil Culliton
Daniel Keysers
Ray Smith
The gemma.cpp Authors
Zoltan Szabadka