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