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https://github.com/ggerganov/llama.cpp.git
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llama-bench : add model sizes (#2771)
* llama-bench : add model sizes * more compact markdown output * back to GiB * adjust column sizes
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slaren
GitHub
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12e2e33a97
commit
154725c543
@ -441,6 +441,8 @@ struct test {
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static const std::string gpu_info;
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std::string model_filename;
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std::string model_type;
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uint64_t model_size;
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uint64_t model_n_params;
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int n_batch;
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int n_threads;
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bool f32_kv;
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@ -457,8 +459,10 @@ struct test {
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test(const cmd_params_instance & inst, const llama_model * lmodel, const llama_context * ctx) {
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model_filename = inst.model;
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char buf[128];
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llama_model_type(lmodel, buf, sizeof(buf));
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llama_model_desc(lmodel, buf, sizeof(buf));
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model_type = buf;
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model_size = llama_model_size(lmodel);
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model_n_params = llama_model_n_params(lmodel);
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n_batch = inst.n_batch;
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n_threads = inst.n_threads;
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f32_kv = inst.f32_kv;
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@ -524,7 +528,7 @@ struct test {
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"build_commit", "build_number",
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"cuda", "opencl", "metal", "gpu_blas", "blas",
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"cpu_info", "gpu_info",
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"model_filename", "model_type",
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"model_filename", "model_type", "model_size", "model_n_params",
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"n_batch", "n_threads", "f16_kv",
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"n_gpu_layers", "main_gpu", "mul_mat_q", "low_vram", "tensor_split",
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"n_prompt", "n_gen", "test_time",
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@ -538,6 +542,7 @@ struct test {
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static field_type get_field_type(const std::string & field) {
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if (field == "build_number" || field == "n_batch" || field == "n_threads" ||
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field == "model_size" || field == "model_n_params" ||
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field == "n_gpu_layers" || field == "main_gpu" ||
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field == "n_prompt" || field == "n_gen" ||
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field == "avg_ns" || field == "stddev_ns") {
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@ -573,7 +578,7 @@ struct test {
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build_commit, std::to_string(build_number),
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std::to_string(cuda), std::to_string(opencl), std::to_string(metal), std::to_string(gpu_blas), std::to_string(blas),
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cpu_info, gpu_info,
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model_filename, model_type,
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model_filename, model_type, std::to_string(model_size), std::to_string(model_n_params),
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std::to_string(n_batch), std::to_string(n_threads), std::to_string(!f32_kv),
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std::to_string(n_gpu_layers), std::to_string(main_gpu), std::to_string(mul_mat_q), std::to_string(low_vram), tensor_split_str,
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std::to_string(n_prompt), std::to_string(n_gen), test_time,
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@ -709,8 +714,15 @@ struct markdown_printer : public printer {
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return -30;
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}
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if (field == "t/s") {
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return 15;
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return 16;
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}
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if (field == "size" || field == "params") {
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return 10;
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}
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if (field == "n_gpu_layers") {
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return 3;
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}
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int width = std::max((int)field.length(), 10);
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if (test::get_field_type(field) == test::STRING) {
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@ -719,9 +731,28 @@ struct markdown_printer : public printer {
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return width;
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}
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static std::string get_field_display_name(const std::string & field) {
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if (field == "n_gpu_layers") {
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return "ngl";
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}
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if (field == "n_threads") {
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return "threads";
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}
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if (field == "mul_mat_q") {
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return "mmq";
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}
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if (field == "tensor_split") {
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return "ts";
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}
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return field;
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}
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void print_header(const cmd_params & params) override {
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// select fields to print
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fields = { "model", "backend" };
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fields.push_back("model");
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fields.push_back("size");
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fields.push_back("params");
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fields.push_back("backend");
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bool is_cpu_backend = test::get_backend() == "CPU" || test::get_backend() == "BLAS";
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if (!is_cpu_backend) {
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fields.push_back("n_gpu_layers");
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@ -752,7 +783,7 @@ struct markdown_printer : public printer {
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fprintf(fout, "|");
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for (const auto & field : fields) {
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fprintf(fout, " %*s |", get_field_width(field), field.c_str());
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fprintf(fout, " %*s |", get_field_width(field), get_field_display_name(field).c_str());
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}
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fprintf(fout, "\n");
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fprintf(fout, "|");
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@ -769,12 +800,26 @@ struct markdown_printer : public printer {
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fprintf(fout, "|");
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for (const auto & field : fields) {
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std::string value;
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char buf[128];
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if (field == "model") {
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value = t.model_type;
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} else if (field == "size") {
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if (t.model_size < 1024*1024*1024) {
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snprintf(buf, sizeof(buf), "%.2f MiB", t.model_size / 1024.0 / 1024.0);
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} else {
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snprintf(buf, sizeof(buf), "%.2f GiB", t.model_size / 1024.0 / 1024.0 / 1024.0);
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}
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value = buf;
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} else if (field == "params") {
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if (t.model_n_params < 1000*1000*1000) {
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snprintf(buf, sizeof(buf), "%.2f M", t.model_n_params / 1e6);
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} else {
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snprintf(buf, sizeof(buf), "%.2f B", t.model_n_params / 1e9);
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}
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value = buf;
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} else if (field == "backend") {
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value = test::get_backend();
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} else if (field == "test") {
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char buf[128];
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if (t.n_prompt > 0 && t.n_gen == 0) {
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snprintf(buf, sizeof(buf), "pp %d", t.n_prompt);
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} else if (t.n_gen > 0 && t.n_prompt == 0) {
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@ -785,7 +830,6 @@ struct markdown_printer : public printer {
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}
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value = buf;
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} else if (field == "t/s") {
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char buf[128];
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snprintf(buf, sizeof(buf), "%.2f ± %.2f", t.avg_ts(), t.stdev_ts());
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value = buf;
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} else if (vmap.find(field) != vmap.end()) {
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18
llama.cpp
18
llama.cpp
@ -5297,13 +5297,29 @@ int llama_model_n_embd(const struct llama_model * model) {
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return model->hparams.n_embd;
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}
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int llama_model_type(const struct llama_model * model, char * buf, size_t buf_size) {
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int llama_model_desc(const struct llama_model * model, char * buf, size_t buf_size) {
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return snprintf(buf, buf_size, "%s %s %s",
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model->name.c_str(),
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llama_model_type_name(model->type),
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llama_model_ftype_name(model->ftype).c_str());
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}
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uint64_t llama_model_size(const struct llama_model * model) {
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uint64_t size = 0;
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for (const auto & it : model->tensors_by_name) {
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size += ggml_nbytes(it.second);
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}
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return size;
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}
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uint64_t llama_model_n_params(const struct llama_model * model) {
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uint64_t nparams = 0;
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for (const auto & it : model->tensors_by_name) {
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nparams += ggml_nelements(it.second);
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}
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return nparams;
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}
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int llama_model_quantize(
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const char * fname_inp,
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const char * fname_out,
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6
llama.h
6
llama.h
@ -254,7 +254,11 @@ extern "C" {
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LLAMA_API int llama_model_n_embd (const struct llama_model * model);
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// Get a string describing the model type
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LLAMA_API int llama_model_type(const struct llama_model * model, char * buf, size_t buf_size);
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LLAMA_API int llama_model_desc(const struct llama_model * model, char * buf, size_t buf_size);
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// Returns the total size of all the tensors in the model in bytes
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LLAMA_API uint64_t llama_model_size(const struct llama_model * model);
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// Returns the total number of parameters in the model
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LLAMA_API uint64_t llama_model_n_params(const struct llama_model * model);
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// Returns 0 on success
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LLAMA_API int llama_model_quantize(
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