mirror of https://github.com/google/gemma.cpp.git
Merge pull request #58 from google:dev-cleanup
PiperOrigin-RevId: 610942948
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BasedOnStyle: Google
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@ -71,6 +71,18 @@ The implementation code is roughly split into 4 layers, from high to low level:
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4. Backend (`highway`) - Low-level hardware interface (SIMD in the case of
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highway) supporting the implementations in (3).
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Besides these layers, supporting utilities are:
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- `compression/` - model compression operations. The 8-bit switched floating
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point model conversion is here.
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- `util/` - command line argument handling and any other utilities.
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## Style and Formatting
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A `.clang-format` configuration is provided with our defaults, please run source
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files through `clang-format` (or a formatter that produces equivalent behavior)
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before finalizing PR for submission.
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## Compile-Time Flags (Advanced)
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There are several compile-time flags to be aware of (note these may or may not
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13
gemma.h
13
gemma.h
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@ -26,15 +26,19 @@
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// copybara:import_next_line:gemma_cpp
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#include "compression/compress.h" // SfpStream/NuqStream
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// copybara:end
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// copybara:import_next_line:gemma_cpp
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#include "configs.h" // kSeqLen
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// copybara:end
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// copybara:import_next_line:gemma_cpp
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#include "util/args.h" // ArgsBase
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// copybara:end
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#include "hwy/aligned_allocator.h"
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#include "hwy/base.h" // hwy::bfloat16_t
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#include "hwy/contrib/thread_pool/thread_pool.h"
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// copybara:import_next_line:sentencepiece
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#include "src/sentencepiece_processor.h"
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// copybara:end
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namespace gcpp {
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@ -115,7 +119,8 @@ struct LoaderArgs : public ArgsBase<LoaderArgs> {
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Path cache; // compressed weights
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std::string model_type;
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template <class Visitor> void ForEach(const Visitor &visitor) {
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template <class Visitor>
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void ForEach(const Visitor& visitor) {
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visitor(tokenizer, "tokenizer", Path(),
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"Path name of tokenizer model file. (required)");
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visitor(
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@ -175,7 +180,8 @@ struct InferenceArgs : public ArgsBase<InferenceArgs> {
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return nullptr;
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}
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template <class Visitor> void ForEach(const Visitor &visitor) {
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template <class Visitor>
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void ForEach(const Visitor& visitor) {
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visitor(max_tokens, "max_tokens", size_t{3072},
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"Maximum number of tokens in prompt + generation.");
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visitor(max_generated_tokens, "max_generated_tokens", size_t{2048},
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@ -186,7 +192,8 @@ struct InferenceArgs : public ArgsBase<InferenceArgs> {
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"Make top-k sampling deterministic", 2);
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visitor(multiturn, "multiturn", false,
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"Multiturn mode (if 0, this clears the KV cache after every "
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"interaction without quitting)\n Default = 0 (conversation resets every turn)");
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"interaction without quitting)\n Default = 0 (conversation "
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"resets every turn)");
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}
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};
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