ExternalVendorCode/whisper.cpp
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sync : ggml (#2001)

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* sync : update scripts

* sync : ggml

* talk-llama : sync llama.cpp

* make : WHISPER_CUBLAS -> WHISPER_CUDA

* ci : try to fix sycl build

* talk-llama : fix make build
This commit is contained in:
Georgi Gerganov
2024-03-27 18:55:10 +02:00
committed by GitHub
parent 1558ec5a16
commit 2948c740a2
90 changed files with 15702 additions and 12476 deletions
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75
examples/talk-llama/llama.h
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@ -39,7 +39,7 @@
#define LLAMA_FILE_MAGIC_GGSN 0x6767736eu // 'ggsn'
#define LLAMA_SESSION_MAGIC LLAMA_FILE_MAGIC_GGSN
#define LLAMA_SESSION_VERSION 4
#define LLAMA_SESSION_VERSION 5
#ifdef __cplusplus
extern "C" {
@ -117,6 +117,7 @@ extern "C" {
LLAMA_FTYPE_MOSTLY_IQ2_S = 28, // except 1d tensors
LLAMA_FTYPE_MOSTLY_IQ2_M = 29, // except 1d tensors
LLAMA_FTYPE_MOSTLY_IQ4_XS = 30, // except 1d tensors
LLAMA_FTYPE_MOSTLY_IQ1_M = 31, // except 1d tensors
LLAMA_FTYPE_GUESSED = 1024, // not specified in the model file
};
@ -275,13 +276,16 @@ extern "C" {
// model quantization parameters
typedef struct llama_model_quantize_params {
int32_t nthread; // number of threads to use for quantizing, if <=0 will use std::thread::hardware_concurrency()
enum llama_ftype ftype; // quantize to this llama_ftype
bool allow_requantize; // allow quantizing non-f32/f16 tensors
bool quantize_output_tensor; // quantize output.weight
bool only_copy; // only copy tensors - ftype, allow_requantize and quantize_output_tensor are ignored
bool pure; // quantize all tensors to the default type
void * imatrix; // pointer to importance matrix data
int32_t nthread; // number of threads to use for quantizing, if <=0 will use std::thread::hardware_concurrency()
enum llama_ftype ftype; // quantize to this llama_ftype
enum ggml_type output_tensor_type; // output tensor type
enum ggml_type token_embedding_type; // itoken embeddings tensor type
bool allow_requantize; // allow quantizing non-f32/f16 tensors
bool quantize_output_tensor; // quantize output.weight
bool only_copy; // only copy tensors - ftype, allow_requantize and quantize_output_tensor are ignored
bool pure; // quantize all tensors to the default type
void * imatrix; // pointer to importance matrix data
void * kv_overrides; // pointer to vector containing overrides
} llama_model_quantize_params;
// grammar types
@ -388,6 +392,7 @@ extern "C" {
LLAMA_API int32_t llama_n_vocab (const struct llama_model * model);
LLAMA_API int32_t llama_n_ctx_train(const struct llama_model * model);
LLAMA_API int32_t llama_n_embd (const struct llama_model * model);
LLAMA_API int32_t llama_n_layer (const struct llama_model * model);
// Get the model's RoPE frequency scaling factor
LLAMA_API float llama_rope_freq_scale_train(const struct llama_model * model);
@ -435,10 +440,24 @@ extern "C" {
// Returns 0 on success
LLAMA_API int32_t llama_model_apply_lora_from_file(
const struct llama_model * model,
const char * path_lora,
float scale,
const char * path_base_model,
int32_t n_threads);
const char * path_lora,
float scale,
const char * path_base_model,
int32_t n_threads);
// Apply a loaded control vector to a llama_context, or if data is NULL, clear
// the currently loaded vector.
// n_embd should be the size of a single layer's control, and data should point
// to an n_embd x n_layers buffer starting from layer 1.
// il_start and il_end are the layer range the vector should apply to (both inclusive)
// See llama_control_vector_load in common to load a control vector.
LLAMA_API int32_t llama_control_vector_apply(
struct llama_context * lctx,
const float * data,
size_t len,
int32_t n_embd,
int32_t il_start,
int32_t il_end);
//
// KV cache
@ -659,23 +678,29 @@ extern "C" {
LLAMA_API void llama_synchronize(struct llama_context * ctx);
// Token logits obtained from the last call to llama_decode()
// The logits for the last token are stored in the last row
// Logits for which llama_batch.logits[i] == 0 are undefined
// Rows: n_tokens provided with llama_batch
// The logits for which llama_batch.logits[i] != 0 are stored contiguously
// in the order they have appeared in the batch.
// Rows: number of tokens for which llama_batch.logits[i] != 0
// Cols: n_vocab
LLAMA_API float * llama_get_logits(struct llama_context * ctx);
// Logits for the ith token. Equivalent to:
// llama_get_logits(ctx) + i*n_vocab
// llama_get_logits(ctx) + ctx->output_ids[i]*n_vocab
// returns NULL for invalid ids.
LLAMA_API float * llama_get_logits_ith(struct llama_context * ctx, int32_t i);
// Get all output token embeddings
// shape: [n_tokens*n_embd] (1-dimensional)
// Get all output token embeddings.
// when pooling_type == LLAMA_POOLING_TYPE_NONE or when using a generative model,
// the embeddings for which llama_batch.logits[i] != 0 are stored contiguously
// in the order they have appeared in the batch.
// shape: [n_outputs*n_embd]
// Otherwise, returns NULL.
LLAMA_API float * llama_get_embeddings(struct llama_context * ctx);
// Get the embeddings for the ith token
// llama_get_embeddings(ctx) + i*n_embd
// Get the embeddings for the ith token. Equivalent to:
// llama_get_embeddings(ctx) + ctx->output_ids[i]*n_embd
// shape: [n_embd] (1-dimensional)
// returns NULL for invalid ids.
LLAMA_API float * llama_get_embeddings_ith(struct llama_context * ctx, int32_t i);
// Get the embeddings for a sequence id
@ -945,6 +970,16 @@ extern "C" {
int32_t n_past,
int32_t n_predict);
/// @details Build a split GGUF final path for this chunk.
/// llama_split_path(split_path, sizeof(split_path), "/models/ggml-model-q4_0", 2, 4) => split_path = "/models/ggml-model-q4_0-00002-of-00004.gguf"
// Returns the split_path length.
LLAMA_API int llama_split_path(char * split_path, size_t maxlen, const char * path_prefix, int split_no, int split_count);
/// @details Extract the path prefix from the split_path if and only if the split_no and split_count match.
/// llama_split_prefix(split_prefix, 64, "/models/ggml-model-q4_0-00002-of-00004.gguf", 2, 4) => split_prefix = "/models/ggml-model-q4_0"
// Returns the split_prefix length.
LLAMA_API int llama_split_prefix(char * split_prefix, size_t maxlen, const char * split_path, int split_no, int split_count);
// Performance information
LLAMA_API struct llama_timings llama_get_timings(struct llama_context * ctx);