diff options
Diffstat (limited to 'examples')
-rw-r--r-- | examples/llama-bench/llama-bench.cpp | 111 | ||||
-rw-r--r-- | examples/quantize-stats/quantize-stats.cpp | 1 | ||||
-rw-r--r-- | examples/server/server.cpp | 4 |
3 files changed, 91 insertions, 25 deletions
diff --git a/examples/llama-bench/llama-bench.cpp b/examples/llama-bench/llama-bench.cpp index 9bd82d56..6617c050 100644 --- a/examples/llama-bench/llama-bench.cpp +++ b/examples/llama-bench/llama-bench.cpp @@ -53,6 +53,13 @@ static std::vector<T> split(const std::string & str, char delim) { return values; } +template<typename T, typename F> +static std::vector<std::string> transform_to_str(const std::vector<T> & values, F f) { + std::vector<std::string> str_values; + std::transform(values.begin(), values.end(), std::back_inserter(str_values), f); + return str_values; +} + template<typename T> static T avg(const std::vector<T> & v) { if (v.empty()) { @@ -126,7 +133,8 @@ struct cmd_params { std::vector<int> n_prompt; std::vector<int> n_gen; std::vector<int> n_batch; - std::vector<bool> f32_kv; + std::vector<ggml_type> type_k; + std::vector<ggml_type> type_v; std::vector<int> n_threads; std::vector<int> n_gpu_layers; std::vector<int> main_gpu; @@ -142,7 +150,8 @@ static const cmd_params cmd_params_defaults = { /* n_prompt */ {512}, /* n_gen */ {128}, /* n_batch */ {512}, - /* f32_kv */ {false}, + /* type_k */ {GGML_TYPE_F16}, + /* type_v */ {GGML_TYPE_F16}, /* n_threads */ {get_num_physical_cores()}, /* n_gpu_layers */ {99}, /* main_gpu */ {0}, @@ -162,7 +171,8 @@ static void print_usage(int /* argc */, char ** argv) { printf(" -p, --n-prompt <n> (default: %s)\n", join(cmd_params_defaults.n_prompt, ",").c_str()); printf(" -n, --n-gen <n> (default: %s)\n", join(cmd_params_defaults.n_gen, ",").c_str()); printf(" -b, --batch-size <n> (default: %s)\n", join(cmd_params_defaults.n_batch, ",").c_str()); - printf(" --memory-f32 <0|1> (default: %s)\n", join(cmd_params_defaults.f32_kv, ",").c_str()); + printf(" -ctk <t>, --cache-type-k <t> (default: %s)\n", join(transform_to_str(cmd_params_defaults.type_k, ggml_type_name), ",").c_str()); + printf(" -ctv <t>, --cache-type-v <t> (default: %s)\n", join(transform_to_str(cmd_params_defaults.type_v, ggml_type_name), ",").c_str()); printf(" -t, --threads <n> (default: %s)\n", join(cmd_params_defaults.n_threads, ",").c_str()); printf(" -ngl, --n-gpu-layers <n> (default: %s)\n", join(cmd_params_defaults.n_gpu_layers, ",").c_str()); printf(" -mg, --main-gpu <i> (default: %s)\n", join(cmd_params_defaults.main_gpu, ",").c_str()); @@ -173,9 +183,32 @@ static void print_usage(int /* argc */, char ** argv) { printf(" -v, --verbose (default: %s)\n", cmd_params_defaults.verbose ? "1" : "0"); printf("\n"); printf("Multiple values can be given for each parameter by separating them with ',' or by specifying the parameter multiple times.\n"); +} +static ggml_type ggml_type_from_name(const std::string & s) { + if (s == "f16") { + return GGML_TYPE_F16; + } + if (s == "q8_0") { + return GGML_TYPE_Q8_0; + } + if (s == "q4_0") { + return GGML_TYPE_Q4_0; + } + if (s == "q4_1") { + return GGML_TYPE_Q4_1; + } + if (s == "q5_0") { + return GGML_TYPE_Q5_0; + } + if (s == "q5_1") { + return GGML_TYPE_Q5_1; + } + + return GGML_TYPE_COUNT; } + static cmd_params parse_cmd_params(int argc, char ** argv) { cmd_params params; std::string arg; @@ -224,13 +257,38 @@ static cmd_params parse_cmd_params(int argc, char ** argv) { } auto p = split<int>(argv[i], split_delim); params.n_batch.insert(params.n_batch.end(), p.begin(), p.end()); - } else if (arg == "--memory-f32") { + } else if (arg == "-ctk" || arg == "--cache-type-k") { if (++i >= argc) { invalid_param = true; break; } - auto p = split<int>(argv[i], split_delim); - params.f32_kv.insert(params.f32_kv.end(), p.begin(), p.end()); + auto p = split<std::string>(argv[i], split_delim); + std::vector<ggml_type> types; + for (const auto & t : p) { + ggml_type gt = ggml_type_from_name(t); + if (gt == GGML_TYPE_COUNT) { + invalid_param = true; + break; + } + types.push_back(gt); + } + params.type_k.insert(params.type_k.end(), types.begin(), types.end()); + } else if (arg == "-ctv" || arg == "--cache-type-v") { + if (++i >= argc) { + invalid_param = true; + break; + } + auto p = split<std::string>(argv[i], split_delim); + std::vector<ggml_type> types; + for (const auto & t : p) { + ggml_type gt = ggml_type_from_name(t); + if (gt == GGML_TYPE_COUNT) { + invalid_param = true; + break; + } + types.push_back(gt); + } + params.type_v.insert(params.type_v.end(), types.begin(), types.end()); } else if (arg == "-t" || arg == "--threads") { if (++i >= argc) { invalid_param = true; @@ -321,7 +379,8 @@ static cmd_params parse_cmd_params(int argc, char ** argv) { if (params.n_prompt.empty()) { params.n_prompt = cmd_params_defaults.n_prompt; } if (params.n_gen.empty()) { params.n_gen = cmd_params_defaults.n_gen; } if (params.n_batch.empty()) { params.n_batch = cmd_params_defaults.n_batch; } - if (params.f32_kv.empty()) { params.f32_kv = cmd_params_defaults.f32_kv; } + if (params.type_k.empty()) { params.type_k = cmd_params_defaults.type_k; } + if (params.type_v.empty()) { params.type_v = cmd_params_defaults.type_v; } if (params.n_gpu_layers.empty()) { params.n_gpu_layers = cmd_params_defaults.n_gpu_layers; } if (params.main_gpu.empty()) { params.main_gpu = cmd_params_defaults.main_gpu; } if (params.mul_mat_q.empty()) { params.mul_mat_q = cmd_params_defaults.mul_mat_q; } @@ -336,7 +395,8 @@ struct cmd_params_instance { int n_prompt; int n_gen; int n_batch; - bool f32_kv; + ggml_type type_k; + ggml_type type_v; int n_threads; int n_gpu_layers; int main_gpu; @@ -365,7 +425,8 @@ struct cmd_params_instance { cparams.n_ctx = n_prompt + n_gen; cparams.n_batch = n_batch; - cparams.f16_kv = !f32_kv; + cparams.type_k = type_k; + cparams.type_v = type_v; cparams.mul_mat_q = mul_mat_q; return cparams; @@ -380,7 +441,8 @@ static std::vector<cmd_params_instance> get_cmd_params_instances_int(const cmd_p for (const auto & mg : params.main_gpu) for (const auto & ts : params.tensor_split) for (const auto & nb : params.n_batch) - for (const auto & fk : params.f32_kv) + for (const auto & tk : params.type_k) + for (const auto & tv : params.type_v) for (const auto & mmq : params.mul_mat_q) for (const auto & nt : params.n_threads) { cmd_params_instance instance = { @@ -388,7 +450,8 @@ static std::vector<cmd_params_instance> get_cmd_params_instances_int(const cmd_p /* .n_prompt = */ n_prompt, /* .n_gen = */ n_gen, /* .n_batch = */ nb, - /* .f32_kv = */ fk, + /* .type_k = */ tk, + /* .type_v = */ tv, /* .n_threads = */ nt, /* .n_gpu_layers = */ nl, /* .main_gpu = */ mg, @@ -410,7 +473,8 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param for (const auto & mg : params.main_gpu) for (const auto & ts : params.tensor_split) for (const auto & nb : params.n_batch) - for (const auto & fk : params.f32_kv) + for (const auto & tk : params.type_k) + for (const auto & tv : params.type_v) for (const auto & mmq : params.mul_mat_q) for (const auto & nt : params.n_threads) { for (const auto & n_prompt : params.n_prompt) { @@ -422,7 +486,8 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param /* .n_prompt = */ n_prompt, /* .n_gen = */ 0, /* .n_batch = */ nb, - /* .f32_kv = */ fk, + /* .type_k = */ tk, + /* .type_v = */ tv, /* .n_threads = */ nt, /* .n_gpu_layers = */ nl, /* .main_gpu = */ mg, @@ -441,7 +506,8 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param /* .n_prompt = */ 0, /* .n_gen = */ n_gen, /* .n_batch = */ nb, - /* .f32_kv = */ fk, + /* .type_k = */ tk, + /* .type_v = */ tv, /* .n_threads = */ nt, /* .n_gpu_layers = */ nl, /* .main_gpu = */ mg, @@ -489,7 +555,8 @@ struct test { uint64_t model_n_params; int n_batch; int n_threads; - bool f32_kv; + ggml_type type_k; + ggml_type type_v; int n_gpu_layers; int main_gpu; bool mul_mat_q; @@ -508,7 +575,8 @@ struct test { model_n_params = llama_model_n_params(lmodel); n_batch = inst.n_batch; n_threads = inst.n_threads; - f32_kv = inst.f32_kv; + type_k = inst.type_k; + type_v = inst.type_v; n_gpu_layers = inst.n_gpu_layers; main_gpu = inst.main_gpu; mul_mat_q = inst.mul_mat_q; @@ -571,7 +639,7 @@ struct test { "cuda", "opencl", "metal", "gpu_blas", "blas", "cpu_info", "gpu_info", "model_filename", "model_type", "model_size", "model_n_params", - "n_batch", "n_threads", "f16_kv", + "n_batch", "n_threads", "type_k", "type_v", "n_gpu_layers", "main_gpu", "mul_mat_q", "tensor_split", "n_prompt", "n_gen", "test_time", "avg_ns", "stddev_ns", @@ -621,7 +689,7 @@ struct test { std::to_string(cuda), std::to_string(opencl), std::to_string(metal), std::to_string(gpu_blas), std::to_string(blas), cpu_info, gpu_info, model_filename, model_type, std::to_string(model_size), std::to_string(model_n_params), - std::to_string(n_batch), std::to_string(n_threads), std::to_string(!f32_kv), + std::to_string(n_batch), std::to_string(n_threads), ggml_type_name(type_k), ggml_type_name(type_v), std::to_string(n_gpu_layers), std::to_string(main_gpu), std::to_string(mul_mat_q), tensor_split_str, std::to_string(n_prompt), std::to_string(n_gen), test_time, std::to_string(avg_ns()), std::to_string(stdev_ns()), @@ -805,8 +873,11 @@ struct markdown_printer : public printer { if (params.n_batch.size() > 1 || params.n_batch != cmd_params_defaults.n_batch) { fields.push_back("n_batch"); } - if (params.f32_kv.size() > 1 || params.f32_kv != cmd_params_defaults.f32_kv) { - fields.push_back("f16_kv"); + if (params.type_k.size() > 1 || params.type_k != cmd_params_defaults.type_k) { + fields.push_back("type_k"); + } + if (params.type_v.size() > 1 || params.type_v != cmd_params_defaults.type_v) { + fields.push_back("type_v"); } if (params.main_gpu.size() > 1 || params.main_gpu != cmd_params_defaults.main_gpu) { fields.push_back("main_gpu"); diff --git a/examples/quantize-stats/quantize-stats.cpp b/examples/quantize-stats/quantize-stats.cpp index 27128247..77302416 100644 --- a/examples/quantize-stats/quantize-stats.cpp +++ b/examples/quantize-stats/quantize-stats.cpp @@ -321,7 +321,6 @@ int main(int argc, char ** argv) { auto cparams = llama_context_default_params(); cparams.n_ctx = 256; cparams.seed = 1; - cparams.f16_kv = false; ctx = llama_new_context_with_model(model, cparams); diff --git a/examples/server/server.cpp b/examples/server/server.cpp index 369f81a8..895f751c 100644 --- a/examples/server/server.cpp +++ b/examples/server/server.cpp @@ -2108,10 +2108,6 @@ static void server_params_parse(int argc, char **argv, server_params &sparams, } params.yarn_beta_slow = std::stof(argv[i]); } - else if (arg == "--memory-f32" || arg == "--memory_f32") - { - params.memory_f16 = false; - } else if (arg == "--threads" || arg == "-t") { if (++i >= argc) |