From 982937a3337f7e97ef08fd5603f4157575ece7e1 Mon Sep 17 00:00:00 2001 From: Rohanjames1997 Date: Fri, 11 Sep 2026 13:19:37 -0500 Subject: [PATCH] tests: extend test-quantize-fns to test nrc=2 (i8mm) kernels (#16234) * Test for nrc=2 as well | i8mm kernels * Trigger only on supported HW * Remove trailing whitespace * Address review comment * test: properly prepare nrc=2 inputs with independent data per row * tests : make nrc=2 dot product inputs distinct Assisted-by: Kiro * tests : use non-trivial strides in nrc=2 dot product test * tests : fail nrc=2 dot product test on non-finite errors --- tests/test-quantize-fns.cpp | 69 ++++++++++++++++++++++++++++++------- 1 file changed, 56 insertions(+), 13 deletions(-) diff --git a/tests/test-quantize-fns.cpp b/tests/test-quantize-fns.cpp index 9510ac14c..570fca89a 100644 --- a/tests/test-quantize-fns.cpp +++ b/tests/test-quantize-fns.cpp @@ -5,6 +5,8 @@ #undef NDEBUG #include +#include +#include #include #include #include @@ -32,9 +34,9 @@ static const char* RESULT_STR[] = {"ok", "FAILED"}; // Generate synthetic data -static void generate_data(float offset, size_t n, float * dst) { +static void generate_data(float offset, size_t n, float * dst, float amplitude = 2.0f) { for (size_t i = 0; i < n; i++) { - dst[i] = 0.1 + 2*cosf(i + offset); + dst[i] = 0.1 + amplitude*cosf(i + offset); } } @@ -83,23 +85,50 @@ static float dot_product(const float * a1, const float * a2, size_t test_size) { } // 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 tmp_q1(2*test_size); - std::vector tmp_q2(2*test_size); - +static float dot_product_error(const ggml_type_traits_cpu * qfns_cpu, ggml_type src0_type, size_t test_size, + const float * test_data1, const float * test_data2, + const float * test_data3, const float * test_data4, + const int nrc) { const auto * vdot = ggml_get_type_traits_cpu(qfns_cpu->vec_dot_type); + const size_t pad = 64; + const size_t bx = ggml_row_size(src0_type, test_size) + pad; + const size_t by = ggml_row_size(qfns_cpu->vec_dot_type, test_size) + pad; + + std::vector tmp_q1(bx * nrc); + std::vector tmp_q2(by * nrc); 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); + if (nrc == 1) { + 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); + const float dot_ref = dot_product(test_data1, test_data2, test_size); + return fabsf(result - dot_ref) / test_size; + } - return fabsf(result - dot_ref) / test_size; + // nrc == 2: kernel computes a 2x2 dot product matrix + // Output layout: s[0]=dot(vx0,vy0), s[1]=dot(vx1,vy0), s[bs]=dot(vx0,vy1), s[bs+1]=dot(vx1,vy1) + // row and output strides are padded, same as in the mul_mat path + qfns_cpu->from_float(test_data3, tmp_q1.data() + bx, test_size); + vdot->from_float(test_data4, tmp_q2.data() + by, test_size); + + const size_t bs = 16; + std::vector result(bs + 2, INFINITY); + qfns_cpu->vec_dot(test_size, result.data(), bs, tmp_q1.data(), bx, tmp_q2.data(), by, 2); + + const float ref00 = dot_product(test_data1, test_data2, test_size); + const float ref10 = dot_product(test_data3, test_data2, test_size); + const float ref01 = dot_product(test_data1, test_data4, test_size); + const float ref11 = dot_product(test_data3, test_data4, test_size); + + const auto err = [test_size](float val, float ref) { + const float e = fabsf(val - ref) / test_size; + return std::isfinite(e) ? e : INFINITY; + }; + + return std::max({err(result[0], ref00), err(result[1], ref10), err(result[bs], ref01), err(result[bs + 1], ref11)}); } static int test_vec_dot_f32(bool verbose) { @@ -133,9 +162,13 @@ static int test_vec_dot_q(bool verbose) { std::vector test_data(test_size); std::vector test_data2(test_size); + std::vector test_data3(test_size); + std::vector test_data4(test_size); generate_data(0.0, test_data.size(), test_data.data()); generate_data(1.0, test_data2.size(), test_data2.data()); + generate_data(3.0, test_data3.size(), test_data3.data(), 1.0f); + generate_data(4.0, test_data4.size(), test_data4.data(), 1.5f); for (int i = 0; i < GGML_TYPE_COUNT; i++) { ggml_type type = (ggml_type) i; @@ -178,7 +211,7 @@ static int test_vec_dot_q(bool 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 vec_dot_error = dot_product_error(qfns_cpu, type, test_size, test_data.data(), test_data2.data(), nullptr, nullptr, 1); 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 @@ -194,6 +227,16 @@ static int test_vec_dot_q(bool verbose) { if (failed || verbose) { printf("%5s dot product error: %s (%f)\n", ggml_type_name(type), RESULT_STR[failed], vec_dot_error); } + + // Test nrc=2 path for types that support it + if (qfns_cpu->nrows == 2) { + const float vec_dot_error_nrc2 = dot_product_error(qfns_cpu, type, test_size, test_data.data(), test_data2.data(), test_data3.data(), test_data4.data(), 2); + failed = !(vec_dot_error_nrc2 < max_allowed_error); + num_failed += failed; + if (failed || verbose) { + printf("%5s dot product error (nrc=2): %s (%f)\n", ggml_type_name(type), RESULT_STR[failed], vec_dot_error_nrc2); + } + } } }