mirror of
https://github.com/ggml-org/llama.cpp.git
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53ff6b9b9f
* GGUF: C++ refactor, backend support, misc fixes remove ggml_tensor.backend update CODEOWNERS [no ci] remove gguf_get_data from API revise GGUF API data types
266 lines
8.2 KiB
C++
266 lines
8.2 KiB
C++
#include "ggml.h"
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#include "gguf.h"
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#include <cstdio>
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#include <string>
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#include <sstream>
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#include <vector>
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#undef MIN
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#undef MAX
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#define MIN(a, b) ((a) < (b) ? (a) : (b))
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#define MAX(a, b) ((a) > (b) ? (a) : (b))
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template <typename T>
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static std::string to_string(const T & val) {
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std::stringstream ss;
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ss << val;
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return ss.str();
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}
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static bool gguf_ex_write(const std::string & fname) {
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struct gguf_context * ctx = gguf_init_empty();
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gguf_set_val_u8 (ctx, "some.parameter.uint8", 0x12);
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gguf_set_val_i8 (ctx, "some.parameter.int8", -0x13);
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gguf_set_val_u16 (ctx, "some.parameter.uint16", 0x1234);
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gguf_set_val_i16 (ctx, "some.parameter.int16", -0x1235);
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gguf_set_val_u32 (ctx, "some.parameter.uint32", 0x12345678);
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gguf_set_val_i32 (ctx, "some.parameter.int32", -0x12345679);
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gguf_set_val_f32 (ctx, "some.parameter.float32", 0.123456789f);
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gguf_set_val_u64 (ctx, "some.parameter.uint64", 0x123456789abcdef0ull);
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gguf_set_val_i64 (ctx, "some.parameter.int64", -0x123456789abcdef1ll);
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gguf_set_val_f64 (ctx, "some.parameter.float64", 0.1234567890123456789);
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gguf_set_val_bool(ctx, "some.parameter.bool", true);
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gguf_set_val_str (ctx, "some.parameter.string", "hello world");
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gguf_set_arr_data(ctx, "some.parameter.arr.i16", GGUF_TYPE_INT16, std::vector<int16_t>{ 1, 2, 3, 4, }.data(), 4);
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gguf_set_arr_data(ctx, "some.parameter.arr.f32", GGUF_TYPE_FLOAT32, std::vector<float>{ 3.145f, 2.718f, 1.414f, }.data(), 3);
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gguf_set_arr_str (ctx, "some.parameter.arr.str", std::vector<const char *>{ "hello", "world", "!" }.data(), 3);
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struct ggml_init_params params = {
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/*.mem_size =*/ 128ull*1024ull*1024ull,
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/*.mem_buffer =*/ NULL,
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/*.no_alloc =*/ false,
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};
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struct ggml_context * ctx_data = ggml_init(params);
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const int n_tensors = 10;
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// tensor infos
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for (int i = 0; i < n_tensors; ++i) {
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const std::string name = "tensor_" + to_string(i);
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int64_t ne[GGML_MAX_DIMS] = { 1 };
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int32_t n_dims = rand() % GGML_MAX_DIMS + 1;
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for (int j = 0; j < n_dims; ++j) {
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ne[j] = rand() % 10 + 1;
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}
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struct ggml_tensor * cur = ggml_new_tensor(ctx_data, GGML_TYPE_F32, n_dims, ne);
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ggml_set_name(cur, name.c_str());
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{
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float * data = (float *) cur->data;
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for (int j = 0; j < ggml_nelements(cur); ++j) {
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data[j] = 100 + i;
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}
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}
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gguf_add_tensor(ctx, cur);
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}
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gguf_write_to_file(ctx, fname.c_str(), false);
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printf("%s: wrote file '%s;\n", __func__, fname.c_str());
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ggml_free(ctx_data);
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gguf_free(ctx);
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return true;
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}
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// just read tensor info
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static bool gguf_ex_read_0(const std::string & fname) {
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struct gguf_init_params params = {
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/*.no_alloc = */ false,
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/*.ctx = */ NULL,
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};
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struct gguf_context * ctx = gguf_init_from_file(fname.c_str(), params);
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if (!ctx) {
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fprintf(stderr, "%s: failed to load '%s'\n", __func__, fname.c_str());
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return false;
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}
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printf("%s: version: %d\n", __func__, gguf_get_version(ctx));
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printf("%s: alignment: %zu\n", __func__, gguf_get_alignment(ctx));
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printf("%s: data offset: %zu\n", __func__, gguf_get_data_offset(ctx));
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// kv
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{
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const int n_kv = gguf_get_n_kv(ctx);
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printf("%s: n_kv: %d\n", __func__, n_kv);
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for (int i = 0; i < n_kv; ++i) {
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const char * key = gguf_get_key(ctx, i);
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printf("%s: kv[%d]: key = %s\n", __func__, i, key);
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}
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}
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// find kv string
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{
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const char * findkey = "some.parameter.string";
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const int keyidx = gguf_find_key(ctx, findkey);
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if (keyidx == -1) {
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printf("%s: find key: %s not found.\n", __func__, findkey);
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} else {
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const char * key_value = gguf_get_val_str(ctx, keyidx);
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printf("%s: find key: %s found, kv[%d] value = %s\n", __func__, findkey, keyidx, key_value);
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}
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}
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// tensor info
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{
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const int n_tensors = gguf_get_n_tensors(ctx);
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printf("%s: n_tensors: %d\n", __func__, n_tensors);
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for (int i = 0; i < n_tensors; ++i) {
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const char * name = gguf_get_tensor_name (ctx, i);
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const size_t size = gguf_get_tensor_size (ctx, i);
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const size_t offset = gguf_get_tensor_offset(ctx, i);
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printf("%s: tensor[%d]: name = %s, size = %zu, offset = %zu\n", __func__, i, name, size, offset);
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}
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}
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gguf_free(ctx);
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return true;
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}
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// read and create ggml_context containing the tensors and their data
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static bool gguf_ex_read_1(const std::string & fname, bool check_data) {
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struct ggml_context * ctx_data = NULL;
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struct gguf_init_params params = {
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/*.no_alloc = */ false,
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/*.ctx = */ &ctx_data,
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};
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struct gguf_context * ctx = gguf_init_from_file(fname.c_str(), params);
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printf("%s: version: %d\n", __func__, gguf_get_version(ctx));
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printf("%s: alignment: %zu\n", __func__, gguf_get_alignment(ctx));
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printf("%s: data offset: %zu\n", __func__, gguf_get_data_offset(ctx));
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// kv
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{
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const int n_kv = gguf_get_n_kv(ctx);
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printf("%s: n_kv: %d\n", __func__, n_kv);
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for (int i = 0; i < n_kv; ++i) {
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const char * key = gguf_get_key(ctx, i);
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printf("%s: kv[%d]: key = %s\n", __func__, i, key);
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}
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}
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// tensor info
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{
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const int n_tensors = gguf_get_n_tensors(ctx);
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printf("%s: n_tensors: %d\n", __func__, n_tensors);
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for (int i = 0; i < n_tensors; ++i) {
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const char * name = gguf_get_tensor_name (ctx, i);
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const size_t size = gguf_get_tensor_size (ctx, i);
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const size_t offset = gguf_get_tensor_offset(ctx, i);
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printf("%s: tensor[%d]: name = %s, size = %zu, offset = %zu\n", __func__, i, name, size, offset);
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}
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}
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// data
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{
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const int n_tensors = gguf_get_n_tensors(ctx);
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for (int i = 0; i < n_tensors; ++i) {
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printf("%s: reading tensor %d data\n", __func__, i);
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const char * name = gguf_get_tensor_name(ctx, i);
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struct ggml_tensor * cur = ggml_get_tensor(ctx_data, name);
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printf("%s: tensor[%d]: n_dims = %d, ne = (%d, %d, %d, %d), name = %s, data = %p\n",
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__func__, i, ggml_n_dims(cur), int(cur->ne[0]), int(cur->ne[1]), int(cur->ne[2]), int(cur->ne[3]), cur->name, cur->data);
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// print first 10 elements
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const float * data = (const float *) cur->data;
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printf("%s data[:10] : ", name);
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for (int j = 0; j < MIN(10, ggml_nelements(cur)); ++j) {
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printf("%f ", data[j]);
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}
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printf("\n\n");
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// check data
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if (check_data) {
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const float * data = (const float *) cur->data;
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for (int j = 0; j < ggml_nelements(cur); ++j) {
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if (data[j] != 100 + i) {
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fprintf(stderr, "%s: tensor[%d], data[%d]: found %f, expected %f\n", __func__, i, j, data[j], float(100 + i));
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gguf_free(ctx);
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return false;
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}
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}
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}
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}
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}
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printf("%s: ctx_data size: %zu\n", __func__, ggml_get_mem_size(ctx_data));
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ggml_free(ctx_data);
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gguf_free(ctx);
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return true;
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}
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int main(int argc, char ** argv) {
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if (argc < 3) {
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printf("usage: %s data.gguf r|w [n]\n", argv[0]);
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printf("r: read data.gguf file\n");
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printf("w: write data.gguf file\n");
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printf("n: no check of tensor data\n");
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return -1;
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}
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bool check_data = true;
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if (argc == 4) {
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check_data = false;
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}
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srand(123456);
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const std::string fname(argv[1]);
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const std::string mode (argv[2]);
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GGML_ASSERT((mode == "r" || mode == "w") && "mode must be r or w");
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if (mode == "w") {
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GGML_ASSERT(gguf_ex_write(fname) && "failed to write gguf file");
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} else if (mode == "r") {
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GGML_ASSERT(gguf_ex_read_0(fname) && "failed to read gguf file");
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GGML_ASSERT(gguf_ex_read_1(fname, check_data) && "failed to read gguf file");
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}
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return 0;
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}
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