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
- Added prompt flag to InferenceArgs for non-interactive mode
- Set user-facing options to verbosity level 1
- Fixed prompt_size declaration and variable ordering in run.cc
- Properly set prompt_size after WrapAndTokenize calls
- Moved kVerboseLogTokens block after prompt_size is set
This change adds a --prompt command-line option that allows users to
provide prompts directly without entering interactive mode, which is
useful for scripting and automation.
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
Jan Wassenberg
prajwalc22