vbatts/llama.cpp
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llama : improve printing + log meta data

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Georgi Gerganov 2023-08-16 14:24:04 +03:00
parent f634b292c9
commit e524750a6c
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GPG key ID: 449E073F9DC10735
3 changed files with 62 additions and 18 deletions
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17
ggml.c
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@ -18583,6 +18583,19 @@ static const size_t GGUF_TYPE_SIZE[GGUF_TYPE_COUNT] = {
};
static_assert(GGUF_TYPE_COUNT == 10, "GGUF_TYPE_COUNT != 10");
static const char * GGUF_TYPE_NAME[GGUF_TYPE_COUNT] = {
[GGUF_TYPE_UINT8] = "uint8",
[GGUF_TYPE_INT8] = "int8",
[GGUF_TYPE_UINT16] = "uint16",
[GGUF_TYPE_INT16] = "int16",
[GGUF_TYPE_UINT32] = "uint32",
[GGUF_TYPE_INT32] = "int32",
[GGUF_TYPE_FLOAT32] = "float32",
[GGUF_TYPE_BOOL] = "bool",
[GGUF_TYPE_STRING] = "string",
[GGUF_TYPE_ARRAY] = "array",
};
union gguf_value {
uint8_t uint8;
int8_t int8;
@ -19017,6 +19030,10 @@ void gguf_free(struct gguf_context * ctx) {
GGML_ALIGNED_FREE(ctx);
}
const char * gguf_type_name(enum gguf_type type) {
return GGUF_TYPE_NAME[type];
}
int gguf_get_version(struct gguf_context * ctx) {
return ctx->header.version;
}

2
ggml.h
View file

@ -1740,6 +1740,8 @@ extern "C" {
GGML_API void gguf_free(struct gguf_context * ctx);
GGML_API const char * gguf_type_name(enum gguf_type type);
GGML_API int gguf_get_version (struct gguf_context * ctx);
GGML_API size_t gguf_get_alignment (struct gguf_context * ctx);
GGML_API size_t gguf_get_data_offset(struct gguf_context * ctx);

61
gguf-llama.cpp
View file

@ -101,11 +101,21 @@
#define TN_FFN_DOWN "blk.%d.ffn_down.weight"
#define TN_FFN_UP "blk.%d.ffn_up.weight"
#ifdef __GNUC__
#ifdef __MINGW32__
#define LLAMA_ATTRIBUTE_FORMAT(...) __attribute__((format(gnu_printf, __VA_ARGS__)))
#else
#define LLAMA_ATTRIBUTE_FORMAT(...) __attribute__((format(printf, __VA_ARGS__)))
#endif
#else
#define LLAMA_ATTRIBUTE_FORMAT(...)
#endif
//
// logging
//
static void llama_log_internal(llama_log_level level, const char* format, ...);
LLAMA_ATTRIBUTE_FORMAT(2, 3)
static void llama_log_internal (llama_log_level level, const char* format, ...);
static void llama_log_callback_default(llama_log_level level, const char * text, void * user_data);
#define LLAMA_LOG_INFO(...) llama_log_internal(LLAMA_LOG_LEVEL_INFO , __VA_ARGS__)
@ -130,13 +140,7 @@ static void zeros(std::ofstream & file, size_t n) {
}
}
#ifdef __GNUC__
#ifdef __MINGW32__
__attribute__((format(gnu_printf, 1, 2)))
#else
__attribute__((format(printf, 1, 2)))
#endif
#endif
LLAMA_ATTRIBUTE_FORMAT(1, 2)
static std::string format(const char * fmt, ...) {
va_list ap;
va_list ap2;
@ -991,7 +995,7 @@ static std::string llama_format_tensor_shape(const std::vector<uint32_t> & ne) {
char buf[256];
snprintf(buf, sizeof(buf), "%5u", ne.at(0));
for (size_t i = 1; i < ne.size(); i++) {
snprintf(buf + strlen(buf), sizeof(buf) - strlen(buf), " x %5u", ne.at(i));
snprintf(buf + strlen(buf), sizeof(buf) - strlen(buf), ", %5u", ne.at(i));
}
return buf;
}
@ -999,13 +1003,14 @@ static std::string llama_format_tensor_shape(const std::vector<uint32_t> & ne) {
static std::string llama_format_tensor_shape(const struct ggml_tensor * t) {
char buf[256];
snprintf(buf, sizeof(buf), "%5" PRId64, t->ne[0]);
for (int i = 1; i < t->n_dims; i++) {
snprintf(buf + strlen(buf), sizeof(buf) - strlen(buf), " x %5" PRId64, t->ne[i]);
for (int i = 1; i < GGML_MAX_DIMS; i++) {
snprintf(buf + strlen(buf), sizeof(buf) - strlen(buf), ", %5" PRId64, t->ne[i]);
}
return buf;
}
struct llama_model_loader {
int n_kv = 0;
int n_tensors = 0;
int n_created = 0;
@ -1027,11 +1032,31 @@ struct llama_model_loader {
ctx_gguf = gguf_init_from_file(fname.c_str(), params);
n_kv = gguf_get_n_kv(ctx_gguf);
n_tensors = gguf_get_n_tensors(ctx_gguf);
file_version = (enum llama_file_version) gguf_get_version(ctx_gguf);
LLAMA_LOG_INFO("%s: loaded %d tensors from %s (version %s)\n",
__func__, n_tensors, fname.c_str(), llama_file_version_name(file_version));
// print meta data
// TODO: make optional
{
LLAMA_LOG_INFO("%s: loaded meta data with %d key-value paris and %d tensors from %s (version %s)\n",
__func__, n_kv, n_tensors, fname.c_str(), llama_file_version_name(file_version));
for (int i = 0; i < n_kv; i++) {
const char * name = gguf_get_key(ctx_gguf, i);
const enum gguf_type type = gguf_get_kv_type(ctx_gguf, i);
LLAMA_LOG_INFO("%s: - %3d: %42s %-8s\n", __func__, i, name, gguf_type_name(type));
}
for (int i = 0; i < n_tensors; i++) {
const char * name = gguf_get_tensor_name(ctx_gguf, i);
struct ggml_tensor * meta = ggml_get_tensor(ctx_meta, name);
LLAMA_LOG_INFO("%s: - %3d: %32s %-8s [ %s ]\n", __func__, i, name, ggml_type_name(meta->type), llama_format_tensor_shape(meta).c_str());
}
}
if (!llama_mmap::SUPPORTED) {
LLAMA_LOG_WARN("%s: mmap is not supported on this platform\n", __func__);
@ -1281,7 +1306,7 @@ static void llama_model_load_internal(
if (kid >= 0) { \
enum gguf_type ktype = gguf_get_kv_type(ctx, kid); \
if (ktype != (type)) { \
throw std::runtime_error(format("key %s has wrong type: %d", key, ktype)); \
throw std::runtime_error(format("key %s has wrong type: %s", key, gguf_type_name(ktype))); \
} \
(dst) = func(ctx, kid); \
} else if (req) { \
@ -1325,7 +1350,7 @@ static void llama_model_load_internal(
const auto n_gqa = hparams.n_gqa();
if (model.type == e_model::MODEL_65B && n_gqa == 8) {
fprintf(stderr, "%s: warning: assuming 70B model based on GQA == %d\n", __func__, n_gqa);
LLAMA_LOG_WARN("%s: assuming 70B model based on GQA == %d\n", __func__, n_gqa);
model.type = e_model::MODEL_70B;
}
}
@ -3399,7 +3424,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
return i_layer < num_layers/8 || i_layer >= 7*num_layers/8 || (i_layer - num_layers/8)%3 == 2;
};
size_t idx = 0;
int idx = 0;
std::vector<uint8_t> read_data;
std::vector<uint8_t> work;
@ -3428,7 +3453,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
tensor->data = read_data.data();
model_loader->load_data_for(tensor);
LLAMA_LOG_INFO("[%4zu/%4zu] %36s - [%s], type = %6s, ",
LLAMA_LOG_INFO("[%4d/%4d] %36s - [%s], type = %6s, ",
++idx, model_loader->n_tensors,
ggml_get_name(tensor),
llama_format_tensor_shape(tensor).c_str(),