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gemma.cpp
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PiperOrigin-RevId: 610498969
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Dan Zheng 2024-02-26 12:54:39 -08:00 committed by Copybara-Service
parent 129e66ada2
commit 8db89304bd
4 changed files with 41 additions and 65 deletions
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18
DEVELOPERS.md
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@ -70,21 +70,3 @@ The implementation code is roughly split into 4 layers, from high to low level:
4. Backend (`highway`) - Low-level hardware interface (SIMD in the case of
highway) supporting the implementations in (3).
## Compile-Time Flags (Advanced)
There are several compile-time flags to be aware of (note these may or may not
be exposed to the build system):
- `GEMMA_WEIGHT_T` : Sets the level of compression for weights (surfaced as
WEIGHT_TYPE in CMakeLists.txt). Currently this should be set to `SfpStream`
(default, if no flag is specified) for 8-bit SFP, or `hwy::bfloat16_t` to
enable for higher-fidelity (but slower) bfloat16 support. This is defined in
`gemma.h`.
- `GEMMA_MAX_SEQ_LEN` : Sets maximum sequence length to preallocate for the KV
Cache. The default is 4096 tokens but can be overridden. This is not exposed
through `CMakeLists.txt` yet.
In the medium term both of these will likely be deprecated in favor of handling
options at runtime - allowing for multiple weight compression schemes in a single
build and dynamically resizes the KV cache as needed.

8
README.md
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@ -114,12 +114,8 @@ convenient directory location (e.g. the `build/` directory in this repo).
The build system uses [CMake](https://cmake.org/). To build the gemma inference
runtime, create a build directory and generate the build files using `cmake`
from the top-level project directory. Note if you previous ran `cmake` and are
re-running with a different setting, be sure to clean out the `build/` directory
with `rm -rf build/*` (warning this will delete any other files in the `build/`
directory.
For the 8-bit switched floating point weights (sfp), run cmake with no options:
from the top-level project directory. For the 8-bit switched floating point
weights (sfp), run cmake with no options:
#### Unix-like Platforms
```sh

21
configs.h
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@ -18,26 +18,21 @@
#ifndef THIRD_PARTY_GEMMA_CPP_CONFIGS_H_
#define THIRD_PARTY_GEMMA_CPP_CONFIGS_H_
// Allow changing pre-allocated kv cache size as a compiler flag
#ifndef GEMMA_MAX_SEQLEN
#define GEMMA_MAX_SEQLEN 4096
#endif // !GEMMA_MAX_SEQLEN
#include <stddef.h>
namespace gcpp {
static constexpr size_t kSeqLen = GEMMA_MAX_SEQLEN;
static constexpr size_t kSeqLen = 7168;
struct ConfigGemma7B {
static constexpr int kSeqLen = gcpp::kSeqLen;
static constexpr int kVocabSize = 256128;
static constexpr int kLayers = 28;
static constexpr int kModelDim = 3072;
static constexpr int kFFHiddenDim = 16 * 3072 / 2; // = 24576
static constexpr int kFFHiddenDim = 16 * 3072 / 2; // = 24576
static constexpr int kHeads = 16;
static constexpr int kKVHeads = 16; // standard MHA
static constexpr int kQKVDim = 256; // query size == key size == value size
static constexpr int kKVHeads = 16; // standard MHA, no GQA or MQA
static constexpr int kQKVDim = 256; // query size == key size == value size
static constexpr int kTopK = 1;
};
@ -46,13 +41,13 @@ struct ConfigGemma2B {
static constexpr int kVocabSize = 256128;
static constexpr int kLayers = 18;
static constexpr int kModelDim = 2048;
static constexpr int kFFHiddenDim = 16 * 2048 / 2; // = 16384
static constexpr int kFFHiddenDim = 16 * 2048 / 2; // = 16384
static constexpr int kHeads = 8;
static constexpr int kKVHeads = 8; // TODO(austinvhuang): add MQA support
static constexpr int kQKVDim = 256; // query size == key size == value size
static constexpr int kQKVDim = 256; // query size == key size == value size
static constexpr int kTopK = 1;
};
} // namespace gcpp
} // namespace gcpp
#endif // THIRD_PARTY_GEMMA_CPP_CONFIGS_H_
#endif // THIRD_PARTY_GEMMA_CPP_CONFIGS_H_

59
gemma.h
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@ -25,14 +25,14 @@
#include <vector>
// copybara:import_next_line:gemma_cpp
#include "compression/compress.h" // SfpStream/NuqStream
#include "compression/compress.h" // SfpStream/NuqStream
// copybara:import_next_line:gemma_cpp
#include "configs.h" // kSeqLen
#include "configs.h" // kSeqLen
// copybara:import_next_line:gemma_cpp
#include "util/args.h" // ArgsBase
#include "hwy/aligned_allocator.h"
#include "hwy/base.h" // hwy::bfloat16_t
#include "hwy/base.h" // hwy::bfloat16_t
#include "hwy/contrib/thread_pool/thread_pool.h"
#include "util/args.h" // ArgsBase
// copybara:import_next_line:sentencepiece
#include "src/sentencepiece_processor.h"
@ -42,7 +42,7 @@ namespace gcpp {
// float, hwy::bfloat16_t, SfpStream, NuqStream
#ifndef GEMMA_WEIGHT_T
#define GEMMA_WEIGHT_T SfpStream
#endif // !GEMMA_WEIGHT_T
#endif // !GEMMA_WEIGHT_T
using WeightT = GEMMA_WEIGHT_T;
using EmbedderInputT = hwy::bfloat16_t;
@ -51,9 +51,9 @@ constexpr bool kSystemPrompt = false;
struct KVCache {
hwy::AlignedFreeUniquePtr<float[]>
key_cache; // batch_size * kSeqLen * kLayers * kKVHeads * kQKVDim
key_cache; // batch_size * kSeqLen * kLayers * kKVHeads * kQKVDim
hwy::AlignedFreeUniquePtr<float[]>
value_cache; // batch_size * kSeqLen * kLayers * kKVHeads * kQKVDim
value_cache; // batch_size * kSeqLen * kLayers * kKVHeads * kQKVDim
};
// Model variants: see configs.h for details.
@ -61,9 +61,9 @@ enum class Model { GEMMA_2B, GEMMA_7B };
enum class ModelTraining { GEMMA_IT, GEMMA_PT };
struct LoaderArgs : public ArgsBase<LoaderArgs> {
LoaderArgs(int argc, char *argv[]) { InitAndParse(argc, argv); }
LoaderArgs(int argc, char* argv[]) { InitAndParse(argc, argv); }
static std::string ToLower(const std::string &text) {
static std::string ToLower(const std::string& text) {
std::string result = text;
std::transform(begin(result), end(result), begin(result),
[](unsigned char c) { return std::tolower(c); });
@ -89,7 +89,7 @@ struct LoaderArgs : public ArgsBase<LoaderArgs> {
}
// Returns error string or nullptr if OK.
const char *Validate() const {
const char* Validate() const {
const std::string model_type_lc = ToLower(model_type);
if (model_type_lc != "2b-pt" && model_type_lc != "7b-pt" &&
model_type_lc != "2b-it" && model_type_lc != "7b-it") {
@ -111,11 +111,12 @@ struct LoaderArgs : public ArgsBase<LoaderArgs> {
}
Path tokenizer;
Path model; // uncompressed weights OR
Path cache; // compressed weights
Path model; // uncompressed weights OR
Path cache; // compressed weights
std::string model_type;
template <class Visitor> void ForEach(const Visitor &visitor) {
template <class Visitor>
void ForEach(const Visitor& visitor) {
visitor(tokenizer, "tokenizer", Path(),
"Path name of tokenizer model file. (required)");
visitor(
@ -138,10 +139,10 @@ struct LoaderArgs : public ArgsBase<LoaderArgs> {
struct GemmaInterface;
struct Gemma {
Gemma(const LoaderArgs &args, hwy::ThreadPool &pool);
~Gemma(); // must be defined after GemmaInterface's dtor is defined.
Gemma(const LoaderArgs& args, hwy::ThreadPool& pool);
~Gemma(); // must be defined after GemmaInterface's dtor is defined.
const sentencepiece::SentencePieceProcessor &Tokenizer() const;
const sentencepiece::SentencePieceProcessor& Tokenizer() const;
std::unique_ptr<GemmaInterface> impl_;
gcpp::ModelTraining model_training;
@ -153,7 +154,7 @@ using StreamFunc = std::function<bool(int, float)>;
using AcceptFunc = std::function<bool(int)>;
struct InferenceArgs : public ArgsBase<InferenceArgs> {
InferenceArgs(int argc, char *argv[]) { InitAndParse(argc, argv); }
InferenceArgs(int argc, char* argv[]) { InitAndParse(argc, argv); }
size_t max_tokens;
size_t max_generated_tokens;
@ -163,7 +164,7 @@ struct InferenceArgs : public ArgsBase<InferenceArgs> {
bool multiturn;
// Returns error string or nullptr if OK.
const char *Validate() const {
const char* Validate() const {
if (max_tokens > gcpp::kSeqLen) {
return "max_tokens is larger than the maximum sequence length (see "
"configs.h).";
@ -175,7 +176,8 @@ struct InferenceArgs : public ArgsBase<InferenceArgs> {
return nullptr;
}
template <class Visitor> void ForEach(const Visitor &visitor) {
template <class Visitor>
void ForEach(const Visitor& visitor) {
visitor(max_tokens, "max_tokens", size_t{3072},
"Maximum number of tokens in prompt + generation.");
visitor(max_generated_tokens, "max_generated_tokens", size_t{2048},
@ -184,21 +186,22 @@ struct InferenceArgs : public ArgsBase<InferenceArgs> {
visitor(temperature, "temperature", 1.0f, "Temperature for top-K", 2);
visitor(deterministic, "deterministic", false,
"Make top-k sampling deterministic", 2);
visitor(multiturn, "multiturn", false,
visitor(multiturn, "multiturn", true,
"Multiturn mode (if 0, this clears the KV cache after every "
"interaction without quitting)\n Default = 0 (conversation resets every turn)");
"interaction without quitting)",
2);
}
};
void GenerateGemma(Gemma &gemma, const InferenceArgs &args,
const std::vector<int> &prompt, size_t start_pos,
hwy::ThreadPool &pool, hwy::ThreadPool &inner_pool,
const StreamFunc &stream_token,
const AcceptFunc &accept_token, std::mt19937 &g,
void GenerateGemma(Gemma& gemma, const InferenceArgs& args,
const std::vector<int>& prompt, size_t start_pos,
hwy::ThreadPool& pool, hwy::ThreadPool& inner_pool,
const StreamFunc& stream_token,
const AcceptFunc& accept_token, std::mt19937& g,
int verbosity);
constexpr int EOS_ID = 1;
} // namespace gcpp
} // namespace gcpp
#endif // THIRD_PARTY_GEMMA_CPP_GEMMA_H_
#endif // THIRD_PARTY_GEMMA_CPP_GEMMA_H_