ggml : unit test for quantization functions (#953)
* Unit test for quantization functions Use the ggml_internal_get_quantize_fn function to loop through all quantization formats and run a sanity check on the result. Also add a microbenchmark that times these functions directly without running the rest of the GGML graph. * test-quantize-fns: CI fixes Fix issues uncovered in CI - need to use sizes divisible by 32*8 for loop unrolling - use intrinsic header that should work on Mac * test-quantize: remove Per PR comment, subsumed by test-quantize-fns * test-quantize: fix for q8_0 intermediatespull/1122/head
unbounded
1 year ago
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GitHub
parent
36b4f7e064
commit
5f939498d5
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// Unit tests for quantization specific functions - quantize, dequantize and dot product
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#include "ggml.h"
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#undef NDEBUG
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#include <assert.h>
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#include <math.h>
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#include <stdio.h>
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#include <string>
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#include <vector>
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const float MAX_QUANTIZATION_REFERENCE_ERROR = 0.0001;
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const float MAX_QUANTIZATION_TOTAL_ERROR = 0.002;
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const float MAX_DOT_PRODUCT_ERROR = 0.02;
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const char* RESULT_STR[] = {"ok", "FAILED"};
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// Generate synthetic data
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void generate_data(float offset, size_t n, float * dst) {
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for (size_t i = 0; i < n; i++) {
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dst[i] = 0.1 + 2*cosf(i + offset);
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}
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}
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// Calculate RMSE between two float arrays
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float array_rmse(const float * a1, const float * a2, size_t n) {
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double sum = 0;
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for (size_t i = 0; i < n; i++) {
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double diff = a1[i] - a2[i];
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sum += diff * diff;
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}
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return sqrtf(sum) / n;
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}
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// Total quantization error on test data
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float total_quantization_error(quantize_fns_t & qfns, size_t test_size, const float * test_data) {
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std::vector<uint8_t> tmp_q(test_size);
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std::vector<float> tmp_out(test_size);
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qfns.quantize_row_q(test_data, tmp_q.data(), test_size);
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qfns.dequantize_row_q(tmp_q.data(), tmp_out.data(), test_size);
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return array_rmse(test_data, tmp_out.data(), test_size);
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}
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// Total quantization error on test data
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float reference_quantization_error(quantize_fns_t & qfns, size_t test_size, const float * test_data) {
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std::vector<uint8_t> tmp_q(test_size);
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std::vector<float> tmp_out(test_size);
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std::vector<float> tmp_out_ref(test_size);
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qfns.quantize_row_q(test_data, tmp_q.data(), test_size);
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qfns.dequantize_row_q(tmp_q.data(), tmp_out.data(), test_size);
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qfns.quantize_row_q_reference(test_data, tmp_q.data(), test_size);
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qfns.dequantize_row_q(tmp_q.data(), tmp_out_ref.data(), test_size);
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return array_rmse(tmp_out.data(), tmp_out_ref.data(), test_size);
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}
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float dot_product(const float * a1, const float * a2, size_t test_size) {
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double sum = 0;
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for (size_t i = 0; i < test_size; i++) {
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sum += a1[i] * a2[i];
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}
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return sum;
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}
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// Total dot product error
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float dot_product_error(quantize_fns_t & qfns, size_t test_size, const float * test_data1, const float *test_data2) {
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std::vector<uint8_t> tmp_q1(test_size);
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std::vector<uint8_t> tmp_q2(test_size*2);
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qfns.quantize_row_q(test_data1, tmp_q1.data(), test_size);
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qfns.quantize_row_q_dot(test_data2, tmp_q2.data(), test_size);
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float result = INFINITY;
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qfns.vec_dot_q(test_size, &result, tmp_q1.data(), tmp_q2.data());
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const float dot_ref = dot_product(test_data1, test_data2, test_size);
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return fabsf(result - dot_ref) / test_size;
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}
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int main(int argc, char * argv[]) {
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bool verbose = false;
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const size_t test_size = 32 * 128;
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std::string arg;
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for (int i = 1; i < argc; i++) {
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arg = argv[i];
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if (arg == "-v") {
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verbose = true;
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} else {
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fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
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return 1;
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}
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}
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std::vector<float> test_data(test_size);
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std::vector<float> test_data2(test_size);
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generate_data(0.0, test_data.size(), test_data.data());
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generate_data(1.0, test_data2.size(), test_data2.data());
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// Initialize GGML, ensures float conversion tables are initialized
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struct ggml_init_params ggml_params = {
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/* .mem_size = */ 1*1024,
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/* .mem_buffer = */ NULL,
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/* .no_alloc = */ true,
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};
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struct ggml_context * ctx = ggml_init(ggml_params);
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int num_failed = 0;
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bool failed = false;
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for (int i = 0; i < GGML_TYPE_COUNT; i++) {
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ggml_type type = (ggml_type) i;
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quantize_fns_t qfns = ggml_internal_get_quantize_fn(i);
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if (qfns.quantize_row_q) {
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const float total_error = total_quantization_error(qfns, test_size, test_data.data());
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failed = !(total_error < MAX_QUANTIZATION_TOTAL_ERROR);
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num_failed += failed;
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if (failed || verbose) {
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printf("%5s absolute quantization error: %s (%f)\n", ggml_type_name(type), RESULT_STR[failed], total_error);
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}
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const float reference_error = reference_quantization_error(qfns, test_size, test_data.data());
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failed = !(reference_error < MAX_QUANTIZATION_REFERENCE_ERROR);
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num_failed += failed;
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if (failed || verbose) {
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printf("%5s reference implementation error: %s (%f)\n", ggml_type_name(type), RESULT_STR[failed], reference_error);
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}
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const float vec_dot_error = dot_product_error(qfns, test_size, test_data.data(), test_data2.data());
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failed = !(vec_dot_error < MAX_DOT_PRODUCT_ERROR);
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num_failed += failed;
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if (failed || verbose) {
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printf("%5s dot product error: %s (%f)\n", ggml_type_name(type), RESULT_STR[failed], vec_dot_error);
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}
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}
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}
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if (num_failed || verbose) {
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printf("%d tests failed\n", num_failed);
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}
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ggml_free(ctx);
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return num_failed > 0;
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}
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// Benchmark quantization specific functions on synthetic data
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#include "ggml.h"
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#undef NDEBUG
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#include <algorithm>
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#include <assert.h>
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#include <functional>
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#include <inttypes.h>
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#include <math.h>
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#include <memory>
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#include <stdio.h>
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#include <string>
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#include <vector>
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#define MAX_ALIGNMENT 64
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#define QK 32
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#define WARMUP 5
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#define ITERATIONS 10
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#define L1_SIZE 32*128
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#define L2_SIZE 32*2048
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#define L3_SIZE 32*20480
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#define MEM_SIZE 32*2048000
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struct quantize_perf_params {
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std::vector<std::string> include_types;
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std::vector<size_t> test_sizes;
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size_t alignment_offset = 0;
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bool op_quantize_row_q_reference = false;
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bool op_quantize_row_q = false;
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bool op_dequantize_row_q = false;
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bool op_quantize_row_q_dot = false;
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bool op_vec_dot_q = false;
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};
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#if defined(__x86_64__) || defined(__i386__)
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#include <x86intrin.h>
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inline int64_t cpu_cycles() {
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// Rough way to detect new-ish CPUs
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#ifdef __POPCNT__
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unsigned int dummy;
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return __rdtscp(&dummy);
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#else
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return __rdtsc();
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#endif
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}
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#else
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#define cpu_cycles() 0
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#endif
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// Generate synthetic data
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void generate_data(float offset, size_t n, float * dst) {
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for (size_t i = 0; i < n; i++) {
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dst[i] = 0.1 + 2*cosf(i + offset);
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}
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}
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float gigabytes_per_second(size_t bytes, int64_t usecs) {
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return bytes / (float) usecs * 1000000 / (1024*1024*1024);
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}
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void * align_with_offset(void * ptr, int offset) {
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size_t dummy_size = MAX_ALIGNMENT * 4;
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return (char *) std::align(MAX_ALIGNMENT, MAX_ALIGNMENT, ptr, dummy_size) + offset;
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}
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void benchmark_function(size_t size, size_t q_size, std::function<size_t(void)> function) {
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int64_t min_time_us = INT64_MAX;
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int64_t total_time_us = 0;
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int64_t min_time_cycles = INT64_MAX;
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int64_t total_time_cycles = 0;
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for (int i = 0; i < WARMUP; i++) {
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function();
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}
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for (int i = 0; i < ITERATIONS; i++) {
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const int64_t start_time = ggml_time_us();
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const int64_t start_cycles = cpu_cycles();
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function();
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const int64_t end_cycles = cpu_cycles();
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const int64_t end_time = ggml_time_us();
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total_time_cycles += end_cycles - start_cycles;
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min_time_cycles = std::min(min_time_cycles, end_cycles - start_cycles);
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total_time_us += end_time - start_time;
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min_time_us = std::min(min_time_us, end_time - start_time);
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}
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printf(" min cycles/%d vals : %9.2f\n", QK, QK * min_time_cycles / (float) size);
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printf(" avg cycles/%d vals : %9.2f\n", QK, QK * total_time_cycles / (float) (size * ITERATIONS));
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printf(" float32 throughput : %9.2f GB/s\n", gigabytes_per_second(4 * size * ITERATIONS, total_time_us));
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printf(" quantized throughput : %9.2f GB/s\n", gigabytes_per_second(q_size * ITERATIONS, total_time_us));
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}
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int main(int argc, char * argv[]) {
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quantize_perf_params params {};
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// read command line
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bool invalid_param = false;
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std::string arg;
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for (int i = 1; i < argc; i++) {
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arg = argv[i];
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if (arg == "--size") {
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if (++i >= argc) {
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invalid_param = true;
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break;
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}
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size_t size = std::stoi(argv[i]);
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if (size % 32 != 0) {
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fprintf(stderr, "error: size %zu not divisible by 32\n", size);
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invalid_param = true;
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break;
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}
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params.test_sizes.push_back(size);
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} else if (arg == "-3") {
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// quick select sizes that probably fit in CPU caches
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params.test_sizes.push_back(L1_SIZE);
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params.test_sizes.push_back(L2_SIZE);
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params.test_sizes.push_back(L3_SIZE);
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} else if (arg == "-4") {
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// quick select cache sizes + memory
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params.test_sizes.push_back(L1_SIZE);
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params.test_sizes.push_back(L2_SIZE);
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params.test_sizes.push_back(L3_SIZE);
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params.test_sizes.push_back(MEM_SIZE);
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} else if (arg == "--op") {
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if (++i >= argc) {
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invalid_param = true;
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break;
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}
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std::string op {argv[i]};
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if (op == "quantize_row_q_reference") {
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params.op_quantize_row_q_reference = true;
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} else if (op == "quantize_row_q") {
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params.op_quantize_row_q = true;
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} else if (op == "dequantize_row_q") {
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params.op_dequantize_row_q = true;
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} else if (op == "quantize_row_q_dot") {
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params.op_quantize_row_q_dot = true;
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} else if (op == "vec_dot_q") {
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params.op_vec_dot_q = true;
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} else {
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invalid_param = true;
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break;
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}
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} else if (arg == "--type") {
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if (++i >= argc) {
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invalid_param = true;
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break;
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}
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params.include_types.push_back(argv[i]);
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} else if (arg == "--alignment-offset") {
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if (++i >= argc) {
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invalid_param = true;
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break;
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}
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int alignment = std::stoi(argv[i]);
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if (alignment < 0 || alignment > MAX_ALIGNMENT) {
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fprintf(stderr, "error: aligment-offset must be less than %d\n", MAX_ALIGNMENT);
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invalid_param = true;
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break;
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}
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params.alignment_offset = alignment;
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} else {
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fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
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return 1;
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}
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}
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if (invalid_param) {
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fprintf(stderr, "error: invalid parameter for argument: %s\n", arg.c_str());
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return 1;
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}
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if (params.test_sizes.empty()) {
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params.test_sizes.push_back(L1_SIZE);
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}
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if (!(params.op_quantize_row_q_reference || params.op_quantize_row_q || params.op_dequantize_row_q || params.op_quantize_row_q_dot || params.op_vec_dot_q)) {
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params.op_quantize_row_q_reference = params.op_quantize_row_q = params.op_dequantize_row_q = params.op_quantize_row_q_dot = params.op_vec_dot_q = true;
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}
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std::sort(params.test_sizes.begin(), params.test_sizes.end());
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size_t largest = params.test_sizes.back();
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std::vector<uint8_t> test_data1_v(largest*4 + MAX_ALIGNMENT*2);
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std::vector<uint8_t> test_data2_v(largest*4 + MAX_ALIGNMENT*2);
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std::vector<uint8_t> test_q1_v(largest*4 + MAX_ALIGNMENT*2);
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std::vector<uint8_t> test_q2_v(largest*4 + MAX_ALIGNMENT*2);
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std::vector<uint8_t> test_out_v(largest*4 + MAX_ALIGNMENT*2);
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float * test_data1 = (float *) align_with_offset(test_data1_v.data(), params.alignment_offset);
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float * test_data2 = (float *) align_with_offset(test_data2_v.data(), params.alignment_offset);
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float * test_q1 = (float *) align_with_offset(test_q1_v.data(), params.alignment_offset);
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float * test_q2 = (float *) align_with_offset(test_q2_v.data(), params.alignment_offset);
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float * test_out = (float *) align_with_offset(test_out_v.data(), params.alignment_offset);
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generate_data(0, largest, test_data1);
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generate_data(1, largest, test_data2);
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// Initialize GGML, ensures float conversion tables are initialized
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struct ggml_init_params ggml_params = {
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/* .mem_size = */ 1*1024,
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/* .mem_buffer = */ NULL,
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/* .no_alloc = */ true,
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};
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struct ggml_context * ctx = ggml_init(ggml_params);
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for (int i = 0; i < GGML_TYPE_COUNT; i++) {
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ggml_type type = (ggml_type) i;
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quantize_fns_t qfns = ggml_internal_get_quantize_fn(i);
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if (!params.include_types.empty() && std::find(params.include_types.begin(), params.include_types.end(), ggml_type_name(type)) == params.include_types.end()) {
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continue;
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}
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if (qfns.quantize_row_q) {
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printf("%s\n", ggml_type_name(type));
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if (params.op_quantize_row_q_reference) {
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printf(" quantize_row_q_reference\n");
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for (size_t size : params.test_sizes) {
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printf(" %zu values (%.2f MB)\n", size, 4*size/(float)(1024*1024));
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auto quantize_fn = [&](void ) {
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qfns.quantize_row_q_reference(test_data1, test_q1, size);
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return test_q1[0];
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};
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size_t quantized_size = size / ggml_blck_size(type) * ggml_type_size(type);
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benchmark_function(size, quantized_size, quantize_fn);
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}
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printf("\n");
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}
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if (params.op_quantize_row_q) {
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printf(" quantize_row_q\n");
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for (size_t size : params.test_sizes) {
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printf(" %zu values (%.2f MB)\n", size, 4*size/(float)(1024*1024));
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auto quantize_fn = [&](void ) {
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qfns.quantize_row_q(test_data1, test_q1, size);
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return test_q1[0];
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};
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size_t quantized_size = size / ggml_blck_size(type) * ggml_type_size(type);
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benchmark_function(size, quantized_size, quantize_fn);
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}
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printf("\n");
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}
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if (params.op_dequantize_row_q) {
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printf(" dequantize_row_q\n");
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qfns.quantize_row_q(test_data1, test_q1, largest);
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for (size_t size : params.test_sizes) {
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printf(" %zu values (%.2f MB)\n", size, 4*size/(float)(1024*1024));
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auto quantize_fn = [&](void ) {
|
||||
qfns.dequantize_row_q(test_q1, test_out, size);
|
||||
return test_out[0];
|
||||
};
|
||||
size_t quantized_size = size / ggml_blck_size(type) * ggml_type_size(type);
|
||||
benchmark_function(size, quantized_size, quantize_fn);
|
||||
}
|
||||
printf("\n");
|
||||
}
|
||||
|
||||
if (params.op_quantize_row_q_dot) {
|
||||
printf(" quantize_row_q_dot\n");
|
||||
for (size_t size : params.test_sizes) {
|
||||
printf(" %zu values (%.2f MB)\n", size, 4*size/(float)(1024*1024));
|
||||
auto quantize_fn = [&](void ) {
|
||||
qfns.quantize_row_q_dot(test_data1, test_q1, size);
|
||||
return test_q1[0];
|
||||
};
|
||||
size_t quantized_size = size / ggml_blck_size(type) * ggml_type_size(type);
|
||||
benchmark_function(size, quantized_size, quantize_fn);
|
||||
}
|
||||
printf("\n");
|
||||
}
|
||||
|
||||
if (params.op_vec_dot_q) {
|
||||
printf(" vec_dot_q\n");
|
||||
qfns.quantize_row_q(test_data1, test_q1, largest);
|
||||
qfns.quantize_row_q(test_data2, test_q2, largest);
|
||||
for (size_t size : params.test_sizes) {
|
||||
printf(" %zu values (%.2f MB)\n", size, 4*size/(float)(1024*1024));
|
||||
auto quantize_fn = [&](void ) {
|
||||
float result;
|
||||
qfns.vec_dot_q(size, &result, test_q1, test_q2);
|
||||
return result;
|
||||
};
|
||||
size_t quantized_size = size / ggml_blck_size(type) * ggml_type_size(type);
|
||||
benchmark_function(size, quantized_size, quantize_fn);
|
||||
}
|
||||
printf("\n");
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
ggml_free(ctx);
|
||||
|
||||
return 0;
|
||||
}
|
||||
@ -1,42 +0,0 @@
|
||||
#include "ggml.h"
|
||||
#undef NDEBUG
|
||||
#include <assert.h>
|
||||
#include <math.h>
|
||||
|
||||
int main(void) {
|
||||
#define QK 32
|
||||
float src[QK];
|
||||
uint8_t dst[24];
|
||||
int64_t hist[16];
|
||||
|
||||
for (int i = 0; i < QK; i++) {
|
||||
src[i] = (float)(i + 1);
|
||||
}
|
||||
|
||||
size_t size = ggml_quantize_q4_0(src, dst, QK, QK, hist);
|
||||
assert(size == 20);
|
||||
float max_result = ((float *)dst)[0];
|
||||
float max_expected = src[31] / ((1 << 3) - 1);
|
||||
assert(max_result == max_expected);
|
||||
for (int i = 0; i < QK; i++) {
|
||||
uint8_t q4_result = (i % 2) ? (dst[sizeof(float) + i/2] >> 4) : (dst[sizeof(float) + i/2] & 0xF);
|
||||
uint8_t q4_expected = roundf(src[i] / max_expected) + 8;
|
||||
assert(q4_result == q4_expected);
|
||||
}
|
||||
|
||||
size = ggml_quantize_q4_1(src, dst, QK, QK, hist);
|
||||
assert(size == 24);
|
||||
float delta_result = ((float *)dst)[0];
|
||||
float delta_expected = (src[31] - src[0]) / ((1 << 4) - 1);
|
||||
assert(delta_result == delta_expected);
|
||||
float min_result = ((float *)dst)[1];
|
||||
float min_expected = src[0];
|
||||
assert(min_result == min_expected);
|
||||
for (int i = 0; i < QK; i++) {
|
||||
uint8_t q4_result = (i % 2) ? (dst[sizeof(float)*2 + i/2] >> 4) : (dst[sizeof(float)*2 + i/2] & 0xF);
|
||||
uint8_t q4_expected = roundf((src[i] - min_expected) / delta_expected);
|
||||
assert(q4_result == q4_expected);
|
||||
}
|
||||
|
||||
return 0;
|
||||
}
|
||||
Loading…
Reference in New Issue