CS348Project/llama.cpp
5
0
Fork 0
mirror of https://github.com/ggml-org/llama.cpp.git synced 2025-10-31 08:51:55 +00:00
Code Issues Packages Projects Releases Wiki Activity

llama : sync gguf-llama.cpp with latest llama.cpp (#2608)

Browse Source 
* llama : sync gguf-llama.cpp with latest llama.cpp

* minor : indentation + assert

* llama : refactor gguf_buffer and gguf_ctx_buffer

* llama : minor
This commit is contained in:
Georgi Gerganov
2023-08-14 16:28:44 +03:00
committed by GitHub
parent 6f64b6c0f8
commit f00780b2ee
6 changed files with 692 additions and 463 deletions
Download Patch File Download Diff File Expand all files Collapse all files

23
examples/gguf/gguf.cpp
View File

@@ -8,14 +8,19 @@
#include <sstream>
#include <fstream>
#include <vector>
/*
#undef MIN
#undef MAX
#define MIN(a, b) ((a) < (b) ? (a) : (b))
#define MAX(a, b) ((a) > (b) ? (a) : (b))
template<typename T>
static std::string to_string(const T & val) {
std::stringstream ss;
ss << val;
return ss.str();
}
*/
void gguf_ex_write_str(std::ofstream & fout, const std::string & val) {
const int32_t n = val.size();
fout.write((const char *) &n, sizeof(n));
@@ -377,28 +382,28 @@ bool gguf_ex_read_2(const std::string & fname) {
struct gguf_file file(fname.c_str(), "rb");
gguf_mmap data_mmap(&file, 0, false);
const int n_tensors = gguf_get_n_tensors(ctx);
for (int i = 0; i < n_tensors; ++i) {
const char * name = gguf_get_tensor_name(ctx, i);
const size_t offset = gguf_get_data_offset(ctx) + gguf_get_tensor_offset(ctx, i);
const char * name = gguf_get_tensor_name(ctx, i);
const size_t offset = gguf_get_data_offset(ctx) + gguf_get_tensor_offset(ctx, i);
struct ggml_tensor * cur = ggml_get_tensor(ctx_data, name);
cur->data = static_cast<char *>(data_mmap.addr) + offset;
// print first 10 elements
const float * data = (const float *) cur->data;
const float * data = (const float *) cur->data;
printf("%s data[:10] : ", name);
for (int j = 0; j < 10; ++j) {
for (int j = 0; j < MIN(10, ggml_nelements(cur)); ++j) {
printf("%f ", data[j]);
}
printf("\n\n");
}
fprintf(stdout, "%s: ctx_data size: %zu\n", __func__, ggml_get_mem_size(ctx_data));
fprintf(stdout, "%s: ctx_data size: %zu\n", __func__, ggml_get_mem_size(ctx_data));
ggml_free(ctx_data);
gguf_free(ctx);

3
ggml-metal.h
View File

@@ -38,6 +38,9 @@ struct ggml_metal_context;
struct ggml_metal_context * ggml_metal_init(int n_cb);
void ggml_metal_free(struct ggml_metal_context * ctx);
void * ggml_metal_host_malloc(size_t n);
void ggml_metal_host_free (void * data);
// set the number of command buffers to use
void ggml_metal_set_n_cb(struct ggml_metal_context * ctx, int n_cb);

15
ggml-metal.m
View File

@@ -224,6 +224,21 @@ void ggml_metal_free(struct ggml_metal_context * ctx) {
free(ctx);
}
void * ggml_metal_host_malloc(size_t n) {
void * data = NULL;
const int result = posix_memalign((void **) &data, getpagesize(), n);
if (result != 0) {
fprintf(stderr, "%s: error: posix_memalign failed\n", __func__);
return NULL;
}
return data;
}
void ggml_metal_host_free(void * data) {
free(data);
}
void ggml_metal_set_n_cb(struct ggml_metal_context * ctx, int n_cb) {
ctx->n_cb = n_cb;
}

989
gguf-llama.cpp
View File

File diff suppressed because it is too large Load Diff

28
gguf-llama.h
View File

@@ -41,10 +41,6 @@
#define LLAMA_SUPPORTS_GPU_OFFLOAD
#endif
#ifndef LLAMA_DEFAULT_RMS_EPS
#define LLAMA_DEFAULT_RMS_EPS 5e-6f
#endif
#ifdef __cplusplus
extern "C" {
#endif
@@ -74,12 +70,23 @@ extern "C" {
typedef void (*llama_progress_callback)(float progress, void *ctx);
struct llama_context_params {
enum llama_log_level {
LLAMA_LOG_LEVEL_ERROR = 2,
LLAMA_LOG_LEVEL_WARN = 3,
LLAMA_LOG_LEVEL_INFO = 4
};
// Signature for logging events
// Note that text includes the new line character at the end for most events.
// If your logging mechanism cannot handle that, check if the last character is '\n' and strip it
// if it exists.
// It might not exist for progress report where '.' is output repeatedly.
typedef void (*llama_log_callback)(enum llama_log_level level, const char * text, void * user_data);
struct llama_context_params {
uint32_t seed; // RNG seed, -1 for random
int32_t n_ctx; // text context
int32_t n_batch; // prompt processing batch size
int32_t n_gqa; // grouped-query attention (TEMP - will be moved to model hparams)
float rms_norm_eps; // rms norm epsilon (TEMP - will be moved to model hparams)
int32_t n_gpu_layers; // number of layers to store in VRAM
int32_t main_gpu; // the GPU that is used for scratch and small tensors
@@ -96,6 +103,7 @@ extern "C" {
// Keep the booleans together to avoid misalignment during copy-by-value.
bool low_vram; // if true, reduce VRAM usage at the cost of performance
bool mul_mat_q; // if true, use experimental mul_mat_q kernels
bool f16_kv; // use fp16 for KV cache
bool logits_all; // the llama_eval() call computes all logits, not just the last one
bool vocab_only; // only load the vocabulary, no weights
@@ -129,7 +137,7 @@ extern "C" {
// model quantization parameters
typedef struct llama_model_quantize_params {
int 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 llama_ftype ftype; // quantize to this llama_ftype
bool allow_requantize; // allow quantizing non-f32/f16 tensors
bool quantize_output_tensor; // quantize output.weight
} llama_model_quantize_params;
@@ -182,6 +190,10 @@ extern "C" {
int32_t n_eval;
};
// Set callback for all future logging events.
// If this is not called, or NULL is supplied, everything is output on stderr.
LLAMA_API void llama_log_set(llama_log_callback log_callback, void * user_data);
LLAMA_API int llama_max_devices();
LLAMA_API struct llama_context_params llama_context_default_params();

97
gguf-util.h
View File

@@ -64,13 +64,6 @@ static std::string format(const char * fmt, ...) {
return std::string(buf.data(), size);
}
template<typename T>
static std::string to_string(const T & val) {
std::stringstream ss;
ss << val;
return ss.str();
}
// TODO: can we merge this one and gguf_context?
struct gguf_file {
// use FILE * so we don't have to re-open the file to mmap
@@ -474,94 +467,4 @@ struct gguf_mlock {
#endif
};
// Replacement for std::vector<uint8_t> that doesn't require zero-initialization.
struct gguf_buffer {
uint8_t * addr = NULL;
size_t size = 0;
gguf_buffer() = default;
void resize(size_t len) {
#ifdef GGML_USE_METAL
free(addr);
int result = posix_memalign((void **) &addr, getpagesize(), len);
if (result == 0) {
memset(addr, 0, len);
}
else {
addr = NULL;
}
#else
delete[] addr;
addr = new uint8_t[len];
#endif
size = len;
}
~gguf_buffer() {
#ifdef GGML_USE_METAL
free(addr);
#else
delete[] addr;
#endif
addr = NULL;
}
// disable copy and move
gguf_buffer(const gguf_buffer&) = delete;
gguf_buffer(gguf_buffer&&) = delete;
gguf_buffer& operator=(const gguf_buffer&) = delete;
gguf_buffer& operator=(gguf_buffer&&) = delete;
};
#ifdef GGML_USE_CUBLAS
#include "ggml-cuda.h"
struct gguf_ctx_buffer {
uint8_t * addr = NULL;
bool is_cuda;
size_t size = 0;
gguf_ctx_buffer() = default;
void resize(size_t size) {
free();
addr = (uint8_t *) ggml_cuda_host_malloc(size);
if (addr) {
is_cuda = true;
}
else {
// fall back to pageable memory
addr = new uint8_t[size];
is_cuda = false;
}
this->size = size;
}
void free() {
if (addr) {
if (is_cuda) {
ggml_cuda_host_free(addr);
}
else {
delete[] addr;
}
}
addr = NULL;
}
~gguf_ctx_buffer() {
free();
}
// disable copy and move
gguf_ctx_buffer(const gguf_ctx_buffer&) = delete;
gguf_ctx_buffer(gguf_ctx_buffer&&) = delete;
gguf_ctx_buffer& operator=(const gguf_ctx_buffer&) = delete;
gguf_ctx_buffer& operator=(gguf_ctx_buffer&&) = delete;
};
#else
typedef gguf_buffer gguf_ctx_buffer;
#endif
#endif