diff options
Diffstat (limited to 'examples')
| -rw-r--r-- | examples/quantize-stats/quantize-stats.cpp | 135 | ||||
| -rw-r--r-- | examples/quantize/quantize.cpp | 7 |
2 files changed, 105 insertions, 37 deletions
diff --git a/examples/quantize-stats/quantize-stats.cpp b/examples/quantize-stats/quantize-stats.cpp index cd973e8..4e6c2c8 100644 --- a/examples/quantize-stats/quantize-stats.cpp +++ b/examples/quantize-stats/quantize-stats.cpp @@ -15,6 +15,8 @@ #include <string> #include <unordered_map> #include <vector> +#include <thread> +#include <mutex> struct quantize_stats_params { std::string model = "models/7B/ggml-model-f16.bin"; @@ -27,7 +29,6 @@ struct quantize_stats_params { std::vector<enum ggml_type> include_types; }; -const int64_t SCRATCH_ELEMENTS = 32*32; const size_t HISTOGRAM_BUCKETS = 150; const double HISTOGRAM_RANGE = 0.03; @@ -90,6 +91,13 @@ void update_error_stats(int64_t nelements, const float * input, const float * ou stats.num_samples += nelements; } +void combine_error_stats(error_stats & into, const error_stats & from) { + into.num_samples += from.num_samples; + into.total_error += from.total_error; + if (from.max_error > into.max_error) into.max_error = from.max_error; + for (size_t i=0; i<HISTOGRAM_BUCKETS; ++i) into.error_histogram[i] += from.error_histogram[i]; +} + double find_quantile(const error_stats & stats, double quantile) { double sum = std::accumulate(std::begin(stats.error_histogram), std::end(stats.error_histogram), 0.0); @@ -130,6 +138,36 @@ static bool tensor_is_contiguous(const struct ggml_tensor * tensor) { tensor->nb[3] == tensor->nb[2]*tensor->ne[2]; } +void test_roundtrip_on_chunk( + const ggml_tensor * layer, + int64_t offset, + int64_t chunk_size, + const quantize_fns_t & qfns, + bool use_reference, + float * input_scratch, + char * quantized_scratch, + float * output_scratch, + error_stats & stats) { + + if (layer->type == GGML_TYPE_F16) { + for (int i = 0; i < chunk_size; i++) { + input_scratch[i] = ggml_get_f32_1d(layer, i + offset); + } + } else { + input_scratch = ggml_get_data_f32(layer) + offset; + } + + if (use_reference) { + qfns.quantize_row_q_reference(input_scratch, quantized_scratch, chunk_size); + } else { + qfns.quantize_row_q(input_scratch, quantized_scratch, chunk_size); + } + qfns.dequantize_row_q(quantized_scratch, output_scratch, chunk_size); + + update_error_stats(chunk_size, input_scratch, output_scratch, stats); +} + + // Run quantization function for a single layer and update error stats void test_roundtrip_on_layer( std::string & name, @@ -137,40 +175,61 @@ void test_roundtrip_on_layer( const quantize_fns_t & qfns, bool use_reference, const ggml_tensor * layer, - float * input_scratch, - char *quantized_scratch, - float * output_scratch, - error_stats & total_error) { + std::vector<float> & input_scratch, + std::vector<char> & quantized_scratch, + std::vector<float> & output_scratch, + error_stats & total_error, + int max_thread = 0) { assert(tensor_is_contiguous(layer)); error_stats layer_error {}; - int64_t nelements = ggml_nelements(layer); - - for (int64_t offset = 0; offset < nelements; offset += SCRATCH_ELEMENTS) { - int64_t chunk_size = std::min(SCRATCH_ELEMENTS, nelements - offset); + uint64_t nelements = ggml_nelements(layer); - if (layer->type == GGML_TYPE_F16) { - for (int i = 0; i < chunk_size; i++) { - input_scratch[i] = ggml_get_f32_1d(layer, i + offset); + float* input_scratch_ptr = nullptr; + if (layer->type == GGML_TYPE_F16) { + if (input_scratch.size() < nelements) input_scratch.resize(nelements); + input_scratch_ptr = input_scratch.data(); + } + if (quantized_scratch.size() < 4*nelements) quantized_scratch.resize(4*nelements); + if (output_scratch.size() < nelements) output_scratch.resize(nelements); + + if (max_thread < 1) max_thread = std::thread::hardware_concurrency(); + int chunk_size = 32*512; + int num_chunks = (nelements + chunk_size - 1)/chunk_size; + + if (num_chunks < 2 || max_thread < 2) { + test_roundtrip_on_chunk(layer, 0, nelements, qfns, use_reference, input_scratch_ptr, quantized_scratch.data(), + output_scratch.data(), print_layer_stats ? layer_error : total_error); + } else { + auto & stats = print_layer_stats ? layer_error : total_error; + std::mutex mutex; + uint64_t counter = 0; + auto compute = [&mutex, &counter, &stats, &qfns, nelements, layer, use_reference, input_scratch_ptr, + &quantized_scratch, &output_scratch, chunk_size] () { + error_stats local_stats {}; + while (true) { + std::unique_lock<std::mutex> lock(mutex); + uint64_t offset = counter; counter += chunk_size; + if (offset >= nelements) { + combine_error_stats(stats, local_stats); + break; + } + lock.unlock(); + uint64_t chunk = offset + chunk_size < nelements ? chunk_size : nelements - offset; + test_roundtrip_on_chunk(layer, offset, chunk, qfns, use_reference, input_scratch_ptr + offset, + quantized_scratch.data() + 4*offset, output_scratch.data() + offset, local_stats); } - } else { - input_scratch = ggml_get_data_f32(layer) + offset; - } - - if (use_reference) { - qfns.quantize_row_q_reference(input_scratch, quantized_scratch, chunk_size); - } else { - qfns.quantize_row_q(input_scratch, quantized_scratch, chunk_size); - } - qfns.dequantize_row_q(quantized_scratch, output_scratch, chunk_size); - - update_error_stats(chunk_size, input_scratch, output_scratch, total_error); - if (print_layer_stats) { - update_error_stats(chunk_size, input_scratch, output_scratch, layer_error); - } + }; + int nthread = std::min(num_chunks, max_thread); + std::vector<std::thread> workers(nthread-1); + for (auto& w : workers) w = std::thread(compute); + compute(); + for (auto& w : workers) w.join(); } + if (print_layer_stats) { print_error_stats(name, layer_error, false); + combine_error_stats(total_error, layer_error); } } @@ -181,6 +240,7 @@ int main(int argc, char ** argv) { // read command line + int max_thread = 0; bool invalid_param = false; std::string arg; for (int i = 1; i < argc; i++) { @@ -230,6 +290,12 @@ int main(int argc, char ** argv) { fprintf(stderr, "error: %s not in list of types\n", argv[i]); invalid_param = true; } + } else if (arg == "-n" || arg == "--num-threads") { + if (++i >= argc) { + invalid_param = true; + break; + } + max_thread = atoi(argv[i]); } else { fprintf(stderr, "error: unknown argument: %s\n", arg.c_str()); quantize_stats_print_usage(argc, argv); @@ -295,9 +361,9 @@ int main(int argc, char ** argv) { } printf("testing %d layers with max size %" PRId64 "\n", included_layers, max_nelements); // allocate scratch space - std::vector<float> input_scratch(SCRATCH_ELEMENTS); - std::vector<char> quantized_scratch(SCRATCH_ELEMENTS*4); - std::vector<float> output_scratch(SCRATCH_ELEMENTS); + std::vector<float> input_scratch; + std::vector<char> quantized_scratch; + std::vector<float> output_scratch; // loop throught quantization types for (int i = 0; i < GGML_TYPE_COUNT; i++) { @@ -328,10 +394,11 @@ int main(int argc, char ** argv) { qfns, params.reference, kv_tensor.second, - input_scratch.data(), - quantized_scratch.data(), - output_scratch.data(), - global_stats + input_scratch, + quantized_scratch, + output_scratch, + global_stats, + max_thread ); } diff --git a/examples/quantize/quantize.cpp b/examples/quantize/quantize.cpp index 49a33a8..5b4812c 100644 --- a/examples/quantize/quantize.cpp +++ b/examples/quantize/quantize.cpp @@ -10,8 +10,8 @@ int main(int argc, char ** argv) { ggml_time_init(); - if (argc != 4) { - fprintf(stderr, "usage: %s model-f32.bin model-quant.bin type\n", argv[0]); + if (argc < 4) { + fprintf(stderr, "usage: %s model-f32.bin model-quant.bin type [nthread]\n", argv[0]); fprintf(stderr, " type = %d - q4_0\n", LLAMA_FTYPE_MOSTLY_Q4_0); fprintf(stderr, " type = %d - q4_1\n", LLAMA_FTYPE_MOSTLY_Q4_1); fprintf(stderr, " type = %d - q4_2\n", LLAMA_FTYPE_MOSTLY_Q4_2); @@ -30,6 +30,7 @@ int main(int argc, char ** argv) { const std::string fname_out = argv[2]; const enum llama_ftype ftype = (enum llama_ftype)atoi(argv[3]); + int nthread = argc > 4 ? atoi(argv[4]) : 0; const int64_t t_main_start_us = ggml_time_us(); @@ -39,7 +40,7 @@ int main(int argc, char ** argv) { { const int64_t t_start_us = ggml_time_us(); - if (llama_model_quantize(fname_inp.c_str(), fname_out.c_str(), ftype)) { + if (llama_model_quantize(fname_inp.c_str(), fname_out.c_str(), ftype, nthread)) { fprintf(stderr, "%s: failed to quantize model from '%s'\n", __func__, fname_inp.c_str()); return 1; } |