| 1 | // Unit tests for quantization specific functions - quantize, dequantize and dot product |
| 2 | |
| 3 | #include "ggml.h" |
| 4 | #include "ggml-cpu.h" |
| 5 | |
| 6 | #undef NDEBUG |
| 7 | #include <assert.h> |
| 8 | #include <math.h> |
| 9 | #include <stdio.h> |
| 10 | #include <string> |
| 11 | #include <vector> |
| 12 | |
| 13 | #if defined(_MSC_VER) |
| 14 | #pragma warning(disable: 4244 4267) // possible loss of data |
| 15 | #endif |
| 16 | |
| 17 | constexpr float MAX_QUANTIZATION_REFERENCE_ERROR = 0.0001f; |
| 18 | constexpr float MAX_QUANTIZATION_TOTAL_ERROR = 0.002f; |
| 19 | constexpr float MAX_QUANTIZATION_TOTAL_ERROR_TERNARY = 0.01f; |
| 20 | constexpr float MAX_QUANTIZATION_TOTAL_ERROR_2BITS = 0.0075f; |
| 21 | constexpr float MAX_QUANTIZATION_TOTAL_ERROR_3BITS = 0.0040f; |
| 22 | constexpr float MAX_QUANTIZATION_TOTAL_ERROR_3BITS_XXS = 0.0050f; |
| 23 | constexpr float MAX_DOT_PRODUCT_ERROR = 0.02f; |
| 24 | constexpr float MAX_DOT_PRODUCT_ERROR_LOWBIT = 0.04f; |
| 25 | constexpr float MAX_DOT_PRODUCT_ERROR_TERNARY = 0.15f; |
| 26 | |
| 27 | static const char* RESULT_STR[] = {"ok" , "FAILED" }; |
| 28 | |
| 29 | |
| 30 | // Generate synthetic data |
| 31 | static void generate_data(float offset, size_t n, float * dst) { |
| 32 | for (size_t i = 0; i < n; i++) { |
| 33 | dst[i] = 0.1 + 2*cosf(x: i + offset); |
| 34 | } |
| 35 | } |
| 36 | |
| 37 | // Calculate RMSE between two float arrays |
| 38 | static float array_rmse(const float * a1, const float * a2, size_t n) { |
| 39 | double sum = 0; |
| 40 | for (size_t i = 0; i < n; i++) { |
| 41 | double diff = a1[i] - a2[i]; |
| 42 | sum += diff * diff; |
| 43 | } |
| 44 | return sqrtf(x: sum) / n; |
| 45 | } |
| 46 | |
| 47 | // Total quantization error on test data |
| 48 | 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) { |
| 49 | std::vector<uint8_t> tmp_q(2*test_size); |
| 50 | std::vector<float> tmp_out(test_size); |
| 51 | |
| 52 | qfns_cpu->from_float(test_data, tmp_q.data(), test_size); |
| 53 | qfns->to_float(tmp_q.data(), tmp_out.data(), test_size); |
| 54 | return array_rmse(a1: test_data, a2: tmp_out.data(), n: test_size); |
| 55 | } |
| 56 | |
| 57 | // Total quantization error on test data |
| 58 | 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) { |
| 59 | std::vector<uint8_t> tmp_q(2*test_size); |
| 60 | std::vector<float> tmp_out(test_size); |
| 61 | std::vector<float> tmp_out_ref(test_size); |
| 62 | |
| 63 | // FIXME: why is done twice? |
| 64 | qfns_cpu->from_float(test_data, tmp_q.data(), test_size); |
| 65 | qfns->to_float(tmp_q.data(), tmp_out.data(), test_size); |
| 66 | |
| 67 | qfns->from_float_ref(test_data, tmp_q.data(), test_size); |
| 68 | qfns->to_float(tmp_q.data(), tmp_out_ref.data(), test_size); |
| 69 | |
| 70 | return array_rmse(a1: tmp_out.data(), a2: tmp_out_ref.data(), n: test_size); |
| 71 | } |
| 72 | |
| 73 | static float dot_product(const float * a1, const float * a2, size_t test_size) { |
| 74 | double sum = 0; |
| 75 | for (size_t i = 0; i < test_size; i++) { |
| 76 | sum += a1[i] * a2[i]; |
| 77 | } |
| 78 | return sum; |
| 79 | } |
| 80 | |
| 81 | // Total dot product error |
| 82 | 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) { |
| 83 | GGML_UNUSED(qfns); |
| 84 | |
| 85 | std::vector<uint8_t> tmp_q1(2*test_size); |
| 86 | std::vector<uint8_t> tmp_q2(2*test_size); |
| 87 | |
| 88 | const auto * vdot = ggml_get_type_traits_cpu(type: qfns_cpu->vec_dot_type); |
| 89 | |
| 90 | qfns_cpu->from_float(test_data1, tmp_q1.data(), test_size); |
| 91 | vdot->from_float(test_data2, tmp_q2.data(), test_size); |
| 92 | |
| 93 | float result = INFINITY; |
| 94 | qfns_cpu->vec_dot(test_size, &result, 0, tmp_q1.data(), 0, tmp_q2.data(), 0, 1); |
| 95 | |
| 96 | const float dot_ref = dot_product(a1: test_data1, a2: test_data2, test_size); |
| 97 | |
| 98 | return fabsf(x: result - dot_ref) / test_size; |
| 99 | } |
| 100 | |
| 101 | int main(int argc, char * argv[]) { |
| 102 | bool verbose = false; |
| 103 | const size_t test_size = 32 * 128; |
| 104 | |
| 105 | std::string arg; |
| 106 | for (int i = 1; i < argc; i++) { |
| 107 | arg = argv[i]; |
| 108 | |
| 109 | if (arg == "-v" ) { |
| 110 | verbose = true; |
| 111 | } else { |
| 112 | fprintf(stderr, format: "error: unknown argument: %s\n" , arg.c_str()); |
| 113 | return 1; |
| 114 | } |
| 115 | } |
| 116 | |
| 117 | std::vector<float> test_data(test_size); |
| 118 | std::vector<float> test_data2(test_size); |
| 119 | |
| 120 | generate_data(offset: 0.0, n: test_data.size(), dst: test_data.data()); |
| 121 | generate_data(offset: 1.0, n: test_data2.size(), dst: test_data2.data()); |
| 122 | |
| 123 | ggml_cpu_init(); |
| 124 | |
| 125 | int num_failed = 0; |
| 126 | bool failed = false; |
| 127 | |
| 128 | for (int i = 0; i < GGML_TYPE_COUNT; i++) { |
| 129 | ggml_type type = (ggml_type) i; |
| 130 | const auto * qfns = ggml_get_type_traits(type); |
| 131 | const auto * qfns_cpu = ggml_get_type_traits_cpu(type); |
| 132 | |
| 133 | // deprecated - skip |
| 134 | if (qfns->blck_size == 0) { |
| 135 | continue; |
| 136 | } |
| 137 | |
| 138 | const ggml_type ei = (ggml_type)i; |
| 139 | |
| 140 | printf(format: "Testing %s\n" , ggml_type_name(type: (ggml_type) i)); |
| 141 | ggml_quantize_init(type: ei); |
| 142 | |
| 143 | if (qfns_cpu->from_float && qfns->to_float) { |
| 144 | const float total_error = total_quantization_error(qfns, qfns_cpu, test_size, test_data: test_data.data()); |
| 145 | const float max_quantization_error = |
| 146 | type == GGML_TYPE_TQ1_0 ? MAX_QUANTIZATION_TOTAL_ERROR_TERNARY : |
| 147 | type == GGML_TYPE_TQ2_0 ? MAX_QUANTIZATION_TOTAL_ERROR_TERNARY : |
| 148 | type == GGML_TYPE_Q2_K ? MAX_QUANTIZATION_TOTAL_ERROR_2BITS : |
| 149 | type == GGML_TYPE_IQ2_S ? MAX_QUANTIZATION_TOTAL_ERROR_2BITS : |
| 150 | type == GGML_TYPE_Q3_K ? MAX_QUANTIZATION_TOTAL_ERROR_3BITS : |
| 151 | type == GGML_TYPE_IQ3_S ? MAX_QUANTIZATION_TOTAL_ERROR_3BITS : |
| 152 | type == GGML_TYPE_IQ3_XXS ? MAX_QUANTIZATION_TOTAL_ERROR_3BITS_XXS : MAX_QUANTIZATION_TOTAL_ERROR; |
| 153 | failed = !(total_error < max_quantization_error); |
| 154 | num_failed += failed; |
| 155 | if (failed || verbose) { |
| 156 | printf(format: "%5s absolute quantization error: %s (%f)\n" , ggml_type_name(type), RESULT_STR[failed], total_error); |
| 157 | } |
| 158 | |
| 159 | const float reference_error = reference_quantization_error(qfns, qfns_cpu, test_size, test_data: test_data.data()); |
| 160 | failed = !(reference_error < MAX_QUANTIZATION_REFERENCE_ERROR); |
| 161 | num_failed += failed; |
| 162 | if (failed || verbose) { |
| 163 | printf(format: "%5s reference implementation error: %s (%f)\n" , ggml_type_name(type), RESULT_STR[failed], reference_error); |
| 164 | } |
| 165 | |
| 166 | const float vec_dot_error = dot_product_error(qfns, qfns_cpu, test_size, test_data1: test_data.data(), test_data2: test_data2.data()); |
| 167 | const float max_allowed_error = type == GGML_TYPE_Q2_K || type == GGML_TYPE_IQ2_XS || type == GGML_TYPE_IQ2_XXS || |
| 168 | type == GGML_TYPE_IQ3_XXS || type == GGML_TYPE_IQ3_S || type == GGML_TYPE_IQ2_S |
| 169 | ? MAX_DOT_PRODUCT_ERROR_LOWBIT |
| 170 | : type == GGML_TYPE_TQ1_0 || type == GGML_TYPE_TQ2_0 |
| 171 | ? MAX_DOT_PRODUCT_ERROR_TERNARY |
| 172 | : MAX_DOT_PRODUCT_ERROR; |
| 173 | failed = !(vec_dot_error < max_allowed_error); |
| 174 | num_failed += failed; |
| 175 | if (failed || verbose) { |
| 176 | printf(format: "%5s dot product error: %s (%f)\n" , ggml_type_name(type), RESULT_STR[failed], vec_dot_error); |
| 177 | } |
| 178 | } |
| 179 | } |
| 180 | |
| 181 | if (num_failed || verbose) { |
| 182 | printf(format: "%d tests failed\n" , num_failed); |
| 183 | } |
| 184 | |
| 185 | return num_failed > 0; |
| 186 | } |
| 187 | |