ExternalVendorCode/whisper.cpp
1
0
Fork 0
mirror of https://github.com/ggerganov/whisper.cpp.git synced 2025-06-17 14:28:07 +00:00
Code Issues Actions 4 Packages Projects Releases Wiki Activity

talk-llama : sync llama.cpp

Browse Source
This commit is contained in:
Georgi Gerganov
2024-03-08 11:55:50 +02:00
parent 05d1b61af4
commit 8e409d1113
3 changed files with 1890 additions and 827 deletions
Download Patch File Download Diff File Expand all files Collapse all files

158
examples/talk-llama/llama.h
View File

@ -64,6 +64,15 @@ extern "C" {
LLAMA_VOCAB_TYPE_WPM = 2, // WordPiece
};
// note: these values should be synchronized with ggml_rope
// TODO: maybe move this enum to ggml.h (ggml_rope_type)
enum llama_rope_type {
LLAMA_ROPE_TYPE_NONE = -1,
LLAMA_ROPE_TYPE_NORM = 0,
LLAMA_ROPE_TYPE_NEOX = 2,
LLAMA_ROPE_TYPE_GLM = 4,
};
enum llama_token_type {
LLAMA_TOKEN_TYPE_UNDEFINED = 0,
LLAMA_TOKEN_TYPE_NORMAL = 1,
@ -98,32 +107,38 @@ extern "C" {
LLAMA_FTYPE_MOSTLY_IQ2_XXS = 19, // except 1d tensors
LLAMA_FTYPE_MOSTLY_IQ2_XS = 20, // except 1d tensors
LLAMA_FTYPE_MOSTLY_Q2_K_S = 21, // except 1d tensors
LLAMA_FTYPE_MOSTLY_Q3_K_XS = 22, // except 1d tensors
LLAMA_FTYPE_MOSTLY_IQ3_XS = 22, // except 1d tensors
LLAMA_FTYPE_MOSTLY_IQ3_XXS = 23, // except 1d tensors
LLAMA_FTYPE_MOSTLY_IQ1_S = 24, // except 1d tensors
LLAMA_FTYPE_MOSTLY_IQ4_NL = 25, // except 1d tensors
LLAMA_FTYPE_MOSTLY_IQ3_S = 26, // except 1d tensors
LLAMA_FTYPE_MOSTLY_IQ3_M = 27, // except 1d tensors
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_GUESSED = 1024, // not specified in the model file
};
enum llama_rope_scaling_type {
LLAMA_ROPE_SCALING_UNSPECIFIED = -1,
LLAMA_ROPE_SCALING_NONE = 0,
LLAMA_ROPE_SCALING_LINEAR = 1,
LLAMA_ROPE_SCALING_YARN = 2,
LLAMA_ROPE_SCALING_MAX_VALUE = LLAMA_ROPE_SCALING_YARN,
LLAMA_ROPE_SCALING_TYPE_UNSPECIFIED = -1,
LLAMA_ROPE_SCALING_TYPE_NONE = 0,
LLAMA_ROPE_SCALING_TYPE_LINEAR = 1,
LLAMA_ROPE_SCALING_TYPE_YARN = 2,
LLAMA_ROPE_SCALING_TYPE_MAX_VALUE = LLAMA_ROPE_SCALING_TYPE_YARN,
};
enum llama_pooling_type {
LLAMA_POOLING_NONE = 0,
LLAMA_POOLING_MEAN = 1,
LLAMA_POOLING_CLS = 2,
LLAMA_POOLING_TYPE_UNSPECIFIED = -1,
LLAMA_POOLING_TYPE_NONE = 0,
LLAMA_POOLING_TYPE_MEAN = 1,
LLAMA_POOLING_TYPE_CLS = 2,
};
enum llama_split_mode {
LLAMA_SPLIT_NONE = 0, // single GPU
LLAMA_SPLIT_LAYER = 1, // split layers and KV across GPUs
LLAMA_SPLIT_ROW = 2, // split rows across GPUs
LLAMA_SPLIT_MODE_NONE = 0, // single GPU
LLAMA_SPLIT_MODE_LAYER = 1, // split layers and KV across GPUs
LLAMA_SPLIT_MODE_ROW = 2, // split rows across GPUs
};
typedef struct llama_token_data {
@ -148,7 +163,7 @@ extern "C" {
// - embd : token embeddings (i.e. float vector of size n_embd) (used when token is NULL)
// - pos : the positions of the respective token in the sequence
// - seq_id : the sequence to which the respective token belongs
// - logits : if zero, the logits for the respective token will not be output
// - logits : if zero, the logits (and/or the embeddings) for the respective token will not be output
//
typedef struct llama_batch {
int32_t n_tokens;
@ -158,7 +173,7 @@ extern "C" {
llama_pos * pos;
int32_t * n_seq_id;
llama_seq_id ** seq_id;
int8_t * logits;
int8_t * logits; // TODO: rename this to "output"
// NOTE: helpers for smooth API transition - can be deprecated in the future
// for future-proof code, use the above fields instead and ignore everything below
@ -171,9 +186,9 @@ extern "C" {
} llama_batch;
enum llama_model_kv_override_type {
LLAMA_KV_OVERRIDE_INT,
LLAMA_KV_OVERRIDE_FLOAT,
LLAMA_KV_OVERRIDE_BOOL,
LLAMA_KV_OVERRIDE_TYPE_INT,
LLAMA_KV_OVERRIDE_TYPE_FLOAT,
LLAMA_KV_OVERRIDE_TYPE_BOOL,
};
struct llama_model_kv_override {
@ -222,7 +237,10 @@ extern "C" {
uint32_t n_batch; // prompt processing maximum batch size
uint32_t n_threads; // number of threads to use for generation
uint32_t n_threads_batch; // number of threads to use for batch processing
int32_t rope_scaling_type; // RoPE scaling type, from `enum llama_rope_scaling_type`
enum llama_rope_scaling_type rope_scaling_type; // RoPE scaling type, from `enum llama_rope_scaling_type`
enum llama_pooling_type pooling_type; // whether to pool (sum) embedding results by sequence id
// (ignored if no pooling layer)
// ref: https://github.com/ggerganov/llama.cpp/pull/2054
float rope_freq_base; // RoPE base frequency, 0 = from model
@ -232,6 +250,7 @@ extern "C" {
float yarn_beta_fast; // YaRN low correction dim
float yarn_beta_slow; // YaRN high correction dim
uint32_t yarn_orig_ctx; // YaRN original context size
float defrag_thold; // defragment the KV cache if holes/size > thold, < 0 disabled (default)
ggml_backend_sched_eval_callback cb_eval;
void * cb_eval_user_data;
@ -240,11 +259,15 @@ extern "C" {
enum ggml_type type_v; // data type for V cache
// Keep the booleans together to avoid misalignment during copy-by-value.
bool mul_mat_q; // if true, use experimental mul_mat_q kernels (DEPRECATED - always true)
bool logits_all; // the llama_eval() call computes all logits, not just the last one (DEPRECATED - set llama_batch.logits instead)
bool embedding; // embedding mode only
bool logits_all; // the llama_decode() call computes all logits, not just the last one (DEPRECATED - set llama_batch.logits instead)
bool embeddings; // if true, extract embeddings (together with logits)
bool offload_kqv; // whether to offload the KQV ops (including the KV cache) to GPU
bool do_pooling; // whether to pool (sum) embedding results by sequence id (ignored if no pooling layer)
// Abort callback
// if it returns true, execution of llama_decode() will be aborted
// currently works only with CPU execution
ggml_abort_callback abort_callback;
void * abort_callback_data;
};
// model quantization parameters
@ -349,15 +372,13 @@ extern "C" {
LLAMA_API bool llama_supports_mlock (void);
LLAMA_API bool llama_supports_gpu_offload(void);
LLAMA_API DEPRECATED(bool llama_mmap_supported (void), "use llama_supports_mmap() instead");
LLAMA_API DEPRECATED(bool llama_mlock_supported(void), "use llama_supports_mlock() instead");
LLAMA_API const struct llama_model * llama_get_model(const struct llama_context * ctx);
LLAMA_API uint32_t llama_n_ctx (const struct llama_context * ctx);
LLAMA_API uint32_t llama_n_batch (const struct llama_context * ctx);
LLAMA_API enum llama_vocab_type llama_vocab_type(const struct llama_model * model);
LLAMA_API enum llama_rope_type llama_rope_type (const struct llama_model * model);
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);
@ -407,14 +428,6 @@ extern "C" {
// The model needs to be reloaded before applying a new adapter, otherwise the adapter
// will be applied on top of the previous one
// Returns 0 on success
LLAMA_API DEPRECATED(int32_t llama_apply_lora_from_file(
struct llama_context * ctx,
const char * path_lora,
float scale,
const char * path_base_model,
int32_t n_threads),
"use llama_model_apply_lora_from_file instead");
LLAMA_API int32_t llama_model_apply_lora_from_file(
const struct llama_model * model,
const char * path_lora,
@ -512,10 +525,12 @@ extern "C" {
llama_seq_id seq_id);
// Adds relative position "delta" to all tokens that belong to the specified sequence and have positions in [p0, p1)
// If the KV cache is RoPEd, the KV data is updated accordingly
// If the KV cache is RoPEd, the KV data is updated accordingly:
// - lazily on next llama_decode()
// - explicitly with llama_kv_cache_update()
// p0 < 0 : [0, p1]
// p1 < 0 : [p0, inf)
LLAMA_API void llama_kv_cache_seq_shift(
LLAMA_API void llama_kv_cache_seq_add(
struct llama_context * ctx,
llama_seq_id seq_id,
llama_pos p0,
@ -523,7 +538,9 @@ extern "C" {
llama_pos delta);
// Integer division of the positions by factor of `d > 1`
// If the KV cache is RoPEd, the KV data is updated accordingly
// If the KV cache is RoPEd, the KV data is updated accordingly:
// - lazily on next llama_decode()
// - explicitly with llama_kv_cache_update()
// p0 < 0 : [0, p1]
// p1 < 0 : [p0, inf)
LLAMA_API void llama_kv_cache_seq_div(
@ -533,6 +550,20 @@ extern "C" {
llama_pos p1,
int d);
// Returns the largest position present in the KV cache for the specified sequence
LLAMA_API llama_pos llama_kv_cache_seq_pos_max(
struct llama_context * ctx,
llama_seq_id seq_id);
// Defragment the KV cache
// This will be applied:
// - lazily on next llama_decode()
// - explicitly with llama_kv_cache_update()
LLAMA_API void llama_kv_cache_defrag(struct llama_context * ctx);
// Apply the KV cache updates (such as K-shifts, defragmentation, etc.)
LLAMA_API void llama_kv_cache_update(struct llama_context * ctx);
//
// State / sessions
//
@ -552,7 +583,7 @@ extern "C" {
// Returns the number of bytes read
LLAMA_API size_t llama_set_state_data(
struct llama_context * ctx,
uint8_t * src);
const uint8_t * src);
// Save/load session file
LLAMA_API bool llama_load_session_file(
@ -572,27 +603,6 @@ extern "C" {
// Decoding
//
// Run the llama inference to obtain the logits and probabilities for the next token(s).
// tokens + n_tokens is the provided batch of new tokens to process
// n_past is the number of tokens to use from previous eval calls
// Returns 0 on success
// DEPRECATED: use llama_decode() instead
LLAMA_API DEPRECATED(int llama_eval(
struct llama_context * ctx,
llama_token * tokens,
int32_t n_tokens,
int32_t n_past),
"use llama_decode() instead");
// Same as llama_eval, but use float matrix input directly.
// DEPRECATED: use llama_decode() instead
LLAMA_API DEPRECATED(int llama_eval_embd(
struct llama_context * ctx,
float * embd,
int32_t n_tokens,
int32_t n_past),
"use llama_decode() instead");
// Return batch for single sequence of tokens starting at pos_0
//
// NOTE: this is a helper function to facilitate transition to the new batch API - avoid using it
@ -631,7 +641,10 @@ extern "C" {
// n_threads_batch is the number of threads used for prompt and batch processing (multiple tokens)
LLAMA_API void llama_set_n_threads(struct llama_context * ctx, uint32_t n_threads, uint32_t n_threads_batch);
// Token logits obtained from the last call to llama_eval()
// Set abort callback
LLAMA_API void llama_set_abort_callback(struct llama_context * ctx, ggml_abort_callback abort_callback, void * abort_callback_data);
// 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
@ -642,14 +655,20 @@ extern "C" {
// llama_get_logits(ctx) + i*n_vocab
LLAMA_API float * llama_get_logits_ith(struct llama_context * ctx, int32_t i);
// Get the embeddings for the input
// shape: [n_embd] (1-dimensional)
// Get all output token embeddings
// shape: [n_tokens*n_embd] (1-dimensional)
LLAMA_API float * llama_get_embeddings(struct llama_context * ctx);
// Get the embeddings for the ith sequence
// Get the embeddings for the ith token
// llama_get_embeddings(ctx) + i*n_embd
// shape: [n_embd] (1-dimensional)
LLAMA_API float * llama_get_embeddings_ith(struct llama_context * ctx, int32_t i);
// Get the embeddings for a sequence id
// Returns NULL if pooling_type is LLAMA_POOLING_TYPE_NONE
// shape: [n_embd] (1-dimensional)
LLAMA_API float * llama_get_embeddings_seq(struct llama_context * ctx, llama_seq_id seq_id);
//
// Vocab
//
@ -708,7 +727,7 @@ extern "C" {
/// Apply chat template. Inspired by hf apply_chat_template() on python.
/// Both "model" and "custom_template" are optional, but at least one is required. "custom_template" has higher precedence than "model"
/// NOTE: This function only support some known jinja templates. It is not a jinja parser.
/// NOTE: This function does not use a jinja parser. It only support a pre-defined list of template. See more: https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template
/// @param tmpl A Jinja template to use for this chat. If this is nullptr, the model’s default chat template will be used instead.
/// @param chat Pointer to a list of multiple llama_chat_message
/// @param n_msg Number of llama_chat_message in this chat
@ -766,13 +785,6 @@ extern "C" {
float * logits_guidance,
float scale);
LLAMA_API DEPRECATED(void llama_sample_classifier_free_guidance(
struct llama_context * ctx,
llama_token_data_array * candidates,
struct llama_context * guidance_ctx,
float scale),
"use llama_sample_apply_guidance() instead");
/// @details Sorts candidate tokens by their logits in descending order and calculate probabilities based on logits.
LLAMA_API void llama_sample_softmax(
struct llama_context * ctx,
@ -826,12 +838,6 @@ extern "C" {
llama_token_data_array * candidates,
float temp);
LLAMA_API DEPRECATED(void llama_sample_temperature(
struct llama_context * ctx,
llama_token_data_array * candidates,
float temp),
"use llama_sample_temp instead");
/// @details Apply constraints from grammar
LLAMA_API void llama_sample_grammar(
struct llama_context * ctx,