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| author | Mitja Felicijan <mitja.felicijan@gmail.com> | 2026-02-12 20:57:17 +0100 |
|---|---|---|
| committer | Mitja Felicijan <mitja.felicijan@gmail.com> | 2026-02-12 20:57:17 +0100 |
| commit | b333b06772c89d96aacb5490d6a219fba7c09cc6 (patch) | |
| tree | 211df60083a5946baa2ed61d33d8121b7e251b06 /llama.cpp/tests/test-quantize-fns.cpp | |
| download | llmnpc-b333b06772c89d96aacb5490d6a219fba7c09cc6.tar.gz | |
Engage!
Diffstat (limited to 'llama.cpp/tests/test-quantize-fns.cpp')
| -rw-r--r-- | llama.cpp/tests/test-quantize-fns.cpp | 186 |
1 files changed, 186 insertions, 0 deletions
diff --git a/llama.cpp/tests/test-quantize-fns.cpp b/llama.cpp/tests/test-quantize-fns.cpp new file mode 100644 index 0000000..037c058 --- /dev/null +++ b/llama.cpp/tests/test-quantize-fns.cpp @@ -0,0 +1,186 @@ +// Unit tests for quantization specific functions - quantize, dequantize and dot product + +#include "ggml.h" +#include "ggml-cpu.h" + +#undef NDEBUG +#include <assert.h> +#include <math.h> +#include <stdio.h> +#include <string> +#include <vector> + +#if defined(_MSC_VER) +#pragma warning(disable: 4244 4267) // possible loss of data +#endif + +constexpr float MAX_QUANTIZATION_REFERENCE_ERROR = 0.0001f; +constexpr float MAX_QUANTIZATION_TOTAL_ERROR = 0.002f; +constexpr float MAX_QUANTIZATION_TOTAL_ERROR_TERNARY = 0.01f; +constexpr float MAX_QUANTIZATION_TOTAL_ERROR_2BITS = 0.0075f; +constexpr float MAX_QUANTIZATION_TOTAL_ERROR_3BITS = 0.0040f; +constexpr float MAX_QUANTIZATION_TOTAL_ERROR_3BITS_XXS = 0.0050f; +constexpr float MAX_DOT_PRODUCT_ERROR = 0.02f; +constexpr float MAX_DOT_PRODUCT_ERROR_LOWBIT = 0.04f; +constexpr float MAX_DOT_PRODUCT_ERROR_TERNARY = 0.15f; + +static const char* RESULT_STR[] = {"ok", "FAILED"}; + + +// Generate synthetic data +static void generate_data(float offset, size_t n, float * dst) { + for (size_t i = 0; i < n; i++) { + dst[i] = 0.1 + 2*cosf(i + offset); + } +} + +// Calculate RMSE between two float arrays +static float array_rmse(const float * a1, const float * a2, size_t n) { + double sum = 0; + for (size_t i = 0; i < n; i++) { + double diff = a1[i] - a2[i]; + sum += diff * diff; + } + return sqrtf(sum) / n; +} + +// Total quantization error on test data +static float total_quantization_error(const ggml_type_traits * qfns, const ggml_type_traits_cpu * qfns_cpu, size_t test_size, const float * test_data) { + std::vector<uint8_t> tmp_q(2*test_size); + std::vector<float> tmp_out(test_size); + + qfns_cpu->from_float(test_data, tmp_q.data(), test_size); + qfns->to_float(tmp_q.data(), tmp_out.data(), test_size); + return array_rmse(test_data, tmp_out.data(), test_size); +} + +// Total quantization error on test data +static float reference_quantization_error(const ggml_type_traits * qfns, const ggml_type_traits_cpu * qfns_cpu, size_t test_size, const float * test_data) { + std::vector<uint8_t> tmp_q(2*test_size); + std::vector<float> tmp_out(test_size); + std::vector<float> tmp_out_ref(test_size); + + // FIXME: why is done twice? + qfns_cpu->from_float(test_data, tmp_q.data(), test_size); + qfns->to_float(tmp_q.data(), tmp_out.data(), test_size); + + qfns->from_float_ref(test_data, tmp_q.data(), test_size); + qfns->to_float(tmp_q.data(), tmp_out_ref.data(), test_size); + + return array_rmse(tmp_out.data(), tmp_out_ref.data(), test_size); +} + +static float dot_product(const float * a1, const float * a2, size_t test_size) { + double sum = 0; + for (size_t i = 0; i < test_size; i++) { + sum += a1[i] * a2[i]; + } + return sum; +} + +// Total dot product error +static float dot_product_error(const ggml_type_traits * qfns, const ggml_type_traits_cpu * qfns_cpu, size_t test_size, const float * test_data1, const float * test_data2) { + GGML_UNUSED(qfns); + + std::vector<uint8_t> tmp_q1(2*test_size); + std::vector<uint8_t> tmp_q2(2*test_size); + + const auto * vdot = ggml_get_type_traits_cpu(qfns_cpu->vec_dot_type); + + qfns_cpu->from_float(test_data1, tmp_q1.data(), test_size); + vdot->from_float(test_data2, tmp_q2.data(), test_size); + + float result = INFINITY; + qfns_cpu->vec_dot(test_size, &result, 0, tmp_q1.data(), 0, tmp_q2.data(), 0, 1); + + const float dot_ref = dot_product(test_data1, test_data2, test_size); + + return fabsf(result - dot_ref) / test_size; +} + +int main(int argc, char * argv[]) { + bool verbose = false; + const size_t test_size = 32 * 128; + + std::string arg; + for (int i = 1; i < argc; i++) { + arg = argv[i]; + + if (arg == "-v") { + verbose = true; + } else { + fprintf(stderr, "error: unknown argument: %s\n", arg.c_str()); + return 1; + } + } + + std::vector<float> test_data(test_size); + std::vector<float> test_data2(test_size); + + generate_data(0.0, test_data.size(), test_data.data()); + generate_data(1.0, test_data2.size(), test_data2.data()); + + ggml_cpu_init(); + + int num_failed = 0; + bool failed = false; + + for (int i = 0; i < GGML_TYPE_COUNT; i++) { + ggml_type type = (ggml_type) i; + const auto * qfns = ggml_get_type_traits(type); + const auto * qfns_cpu = ggml_get_type_traits_cpu(type); + + // deprecated - skip + if (qfns->blck_size == 0) { + continue; + } + + const ggml_type ei = (ggml_type)i; + + printf("Testing %s\n", ggml_type_name((ggml_type) i)); + ggml_quantize_init(ei); + + if (qfns_cpu->from_float && qfns->to_float) { + const float total_error = total_quantization_error(qfns, qfns_cpu, test_size, test_data.data()); + const float max_quantization_error = + type == GGML_TYPE_TQ1_0 ? MAX_QUANTIZATION_TOTAL_ERROR_TERNARY : + type == GGML_TYPE_TQ2_0 ? MAX_QUANTIZATION_TOTAL_ERROR_TERNARY : + type == GGML_TYPE_Q2_K ? MAX_QUANTIZATION_TOTAL_ERROR_2BITS : + type == GGML_TYPE_IQ2_S ? MAX_QUANTIZATION_TOTAL_ERROR_2BITS : + type == GGML_TYPE_Q3_K ? MAX_QUANTIZATION_TOTAL_ERROR_3BITS : + type == GGML_TYPE_IQ3_S ? MAX_QUANTIZATION_TOTAL_ERROR_3BITS : + type == GGML_TYPE_IQ3_XXS ? MAX_QUANTIZATION_TOTAL_ERROR_3BITS_XXS : MAX_QUANTIZATION_TOTAL_ERROR; + failed = !(total_error < max_quantization_error); + num_failed += failed; + if (failed || verbose) { + printf("%5s absolute quantization error: %s (%f)\n", ggml_type_name(type), RESULT_STR[failed], total_error); + } + + const float reference_error = reference_quantization_error(qfns, qfns_cpu, test_size, test_data.data()); + failed = !(reference_error < MAX_QUANTIZATION_REFERENCE_ERROR); + num_failed += failed; + if (failed || verbose) { + printf("%5s reference implementation error: %s (%f)\n", ggml_type_name(type), RESULT_STR[failed], reference_error); + } + + const float vec_dot_error = dot_product_error(qfns, qfns_cpu, test_size, test_data.data(), test_data2.data()); + const float max_allowed_error = type == GGML_TYPE_Q2_K || type == GGML_TYPE_IQ2_XS || type == GGML_TYPE_IQ2_XXS || + type == GGML_TYPE_IQ3_XXS || type == GGML_TYPE_IQ3_S || type == GGML_TYPE_IQ2_S + ? MAX_DOT_PRODUCT_ERROR_LOWBIT + : type == GGML_TYPE_TQ1_0 || type == GGML_TYPE_TQ2_0 + ? MAX_DOT_PRODUCT_ERROR_TERNARY + : MAX_DOT_PRODUCT_ERROR; + failed = !(vec_dot_error < max_allowed_error); + num_failed += failed; + if (failed || verbose) { + printf("%5s dot product error: %s (%f)\n", ggml_type_name(type), RESULT_STR[failed], vec_dot_error); + } + } + } + + if (num_failed || verbose) { + printf("%d tests failed\n", num_failed); + } + + return num_failed > 0; +} |
