// Copyright 2022 Google LLC // // This source code is licensed under the BSD-style license found in the // LICENSE file in the root directory of this source tree. #include #include #include #include TEST(COMPUTE_CONVOLUTION_OUTPUT_DMENSION, compute) { ASSERT_EQ(xnn_compute_convolution_output_dimension(5, 3, 1, 1), 3); ASSERT_EQ(xnn_compute_convolution_output_dimension(10, 3, 2, 1), 6); ASSERT_EQ(xnn_compute_convolution_output_dimension(5, 3, 1, 2), 2); } namespace { // A dummy, nop microkernel for testing. void dummy_gemm(size_t mr, size_t nr, size_t k, const void *a, size_t a_stride, const void *w, void *c, size_t cm_stride, size_t cn_stride, const void *params) {} xnn_hmp_gemm_ukernel empty_gemm_ukernel = {}; xnn_hmp_gemm_ukernel dummy_gemm_ukernel = xnn_init_hmp_gemm_ukernel(dummy_gemm); void dummy_igemm(size_t mr, size_t nr, size_t kc, size_t ks, const void **a, const void *w, void *c, size_t cm_stride, size_t cn_stride, size_t a_offset, const void *zero, const void *params) {} xnn_hmp_igemm_ukernel empty_igemm_ukernel = {}; xnn_hmp_igemm_ukernel dummy_igemm_ukernel = xnn_init_hmp_igemm_ukernel(dummy_igemm); } // namespace TEST(HEURISTIC_MR, batch_size_same_as_mr) { gemm_parameters params = { .minmax = { .gemm = { dummy_gemm_ukernel, dummy_gemm_ukernel, }, .igemm = { dummy_igemm_ukernel, dummy_igemm_ukernel, }, }, .mr = 2, .nr = 8, }; ASSERT_EQ(2, xnn_get_heuristic_mr_gemm(2, params.mr, params.nr, params.minmax.gemm)); ASSERT_EQ(2, xnn_get_heuristic_mr_igemm(2, params.mr, params.nr, params.minmax.igemm)); params = (gemm_parameters) { .minmax = { .gemm = { dummy_gemm_ukernel, dummy_gemm_ukernel, empty_gemm_ukernel, dummy_gemm_ukernel }, .igemm = { dummy_igemm_ukernel, dummy_igemm_ukernel, empty_igemm_ukernel, dummy_igemm_ukernel }, }, .mr = 4, .nr = 8, }; ASSERT_EQ(4, xnn_get_heuristic_mr_gemm(4, params.mr, params.nr, params.minmax.gemm)); ASSERT_EQ(4, xnn_get_heuristic_mr_igemm(4, params.mr, params.nr, params.minmax.igemm)); } TEST(HEURISTIC_MR, batch_size_smaller_than_mr) { gemm_parameters params = { .minmax = { .gemm = { dummy_gemm_ukernel, dummy_gemm_ukernel, dummy_gemm_ukernel, dummy_gemm_ukernel, }, .igemm = { dummy_igemm_ukernel, dummy_igemm_ukernel, dummy_igemm_ukernel, dummy_igemm_ukernel, }, }, .mr = 4, .nr = 8, }; // batch size == 3 < mr == 4, pick smallest available kernel to minimize clamps. ASSERT_EQ(3, xnn_get_heuristic_mr_gemm(3, params.mr, params.nr, params.minmax.gemm)); ASSERT_EQ(3, xnn_get_heuristic_mr_igemm(3, params.mr, params.nr, params.minmax.igemm)); params = (gemm_parameters) { .minmax = { .gemm = { dummy_gemm_ukernel, empty_gemm_ukernel, empty_gemm_ukernel, dummy_gemm_ukernel, }, .igemm = { dummy_igemm_ukernel, empty_igemm_ukernel, empty_igemm_ukernel, dummy_igemm_ukernel, }, }, .mr = 4, .nr = 8, }; // The only kernel with mr < 2 is mr == 1, which is too inefficient for this batch size 2. ASSERT_EQ(4, xnn_get_heuristic_mr_gemm(2, params.mr, params.nr, params.minmax.gemm)); ASSERT_EQ(4, xnn_get_heuristic_mr_igemm(2, params.mr, params.nr, params.minmax.igemm)); ASSERT_EQ(1, xnn_get_heuristic_mr_gemm(1, params.mr, params.nr, params.minmax.gemm)); ASSERT_EQ(1, xnn_get_heuristic_mr_igemm(1, params.mr, params.nr, params.minmax.igemm)); params = (gemm_parameters) { .minmax = { .gemm = { dummy_gemm_ukernel, empty_gemm_ukernel, empty_gemm_ukernel, dummy_gemm_ukernel, dummy_gemm_ukernel, dummy_gemm_ukernel, }, .igemm = { dummy_igemm_ukernel, empty_igemm_ukernel, empty_igemm_ukernel, dummy_igemm_ukernel, dummy_igemm_ukernel, dummy_igemm_ukernel, }, }, .mr = 6, .nr = 8, }; ASSERT_EQ(5, xnn_get_heuristic_mr_gemm(5, params.mr, params.nr, params.minmax.gemm)); ASSERT_EQ(5, xnn_get_heuristic_mr_igemm(5, params.mr, params.nr, params.minmax.igemm)); ASSERT_EQ(4, xnn_get_heuristic_mr_gemm(4, params.mr, params.nr, params.minmax.gemm)); ASSERT_EQ(4, xnn_get_heuristic_mr_igemm(4, params.mr, params.nr, params.minmax.igemm)); ASSERT_EQ(4, xnn_get_heuristic_mr_gemm(2, params.mr, params.nr, params.minmax.gemm)); ASSERT_EQ(4, xnn_get_heuristic_mr_igemm(2, params.mr, params.nr, params.minmax.igemm)); ASSERT_EQ(1, xnn_get_heuristic_mr_gemm(1, params.mr, params.nr, params.minmax.gemm)); ASSERT_EQ(1, xnn_get_heuristic_mr_igemm(1, params.mr, params.nr, params.minmax.igemm)); } TEST(HEURISTIC_MR, batch_size_larger_than_mr) { gemm_parameters params = { .minmax = { .gemm = { dummy_gemm_ukernel, empty_gemm_ukernel, dummy_gemm_ukernel, dummy_gemm_ukernel, }, .igemm = { dummy_igemm_ukernel, empty_igemm_ukernel, dummy_igemm_ukernel, dummy_igemm_ukernel, }, }, .mr = 4, .nr = 8, }; ASSERT_EQ(3, xnn_get_heuristic_mr_gemm(5, params.mr, params.nr, params.minmax.gemm)); ASSERT_EQ(3, xnn_get_heuristic_mr_igemm(5, params.mr, params.nr, params.minmax.igemm)); params = (gemm_parameters) { .minmax = { .gemm = { dummy_gemm_ukernel, dummy_gemm_ukernel, dummy_gemm_ukernel, dummy_gemm_ukernel, dummy_gemm_ukernel, dummy_gemm_ukernel, }, .igemm = { dummy_igemm_ukernel, dummy_igemm_ukernel, dummy_igemm_ukernel, dummy_igemm_ukernel, dummy_igemm_ukernel, dummy_igemm_ukernel, }, }, .mr = 6, .nr = 8, }; ASSERT_EQ(4, xnn_get_heuristic_mr_gemm(7, params.mr, params.nr, params.minmax.gemm)); ASSERT_EQ(4, xnn_get_heuristic_mr_igemm(7, params.mr, params.nr, params.minmax.igemm)); ASSERT_EQ(6, xnn_get_heuristic_mr_gemm(11, params.mr, params.nr, params.minmax.gemm)); ASSERT_EQ(6, xnn_get_heuristic_mr_igemm(11, params.mr, params.nr, params.minmax.igemm)); ASSERT_EQ(6, xnn_get_heuristic_mr_gemm(22, params.mr, params.nr, params.minmax.gemm)); ASSERT_EQ(6, xnn_get_heuristic_mr_igemm(22, params.mr, params.nr, params.minmax.igemm)); ASSERT_EQ(5, xnn_get_heuristic_mr_gemm(50, params.mr, params.nr, params.minmax.gemm)); ASSERT_EQ(5, xnn_get_heuristic_mr_igemm(50, params.mr, params.nr, params.minmax.igemm)); ASSERT_EQ(5, xnn_get_heuristic_mr_gemm(50, params.mr, params.nr, params.minmax.gemm)); ASSERT_EQ(5, xnn_get_heuristic_mr_igemm(50, params.mr, params.nr, params.minmax.igemm)); // Tests some MobiletNet params. ASSERT_EQ(6, xnn_get_heuristic_mr_gemm(112*112, params.mr, params.nr, params.minmax.gemm)); ASSERT_EQ(6, xnn_get_heuristic_mr_igemm(112*112, params.mr, params.nr, params.minmax.igemm)); ASSERT_EQ(6, xnn_get_heuristic_mr_gemm(56*56, params.mr, params.nr, params.minmax.gemm)); ASSERT_EQ(6, xnn_get_heuristic_mr_igemm(56*56, params.mr, params.nr, params.minmax.igemm)); ASSERT_EQ(6, xnn_get_heuristic_mr_gemm(14 * 14, params.mr, params.nr, params.minmax.gemm)); ASSERT_EQ(6, xnn_get_heuristic_mr_igemm(14 * 14, params.mr, params.nr, params.minmax.igemm)); ASSERT_EQ(5, xnn_get_heuristic_mr_gemm(7*7, params.mr, params.nr, params.minmax.gemm)); ASSERT_EQ(5, xnn_get_heuristic_mr_igemm(7*7, params.mr, params.nr, params.minmax.igemm)); } TEST(HEURISTIC_MR, max_mr_without_mr1_kernel) { gemm_parameters params = { .minmax = { .gemm = { empty_gemm_ukernel, empty_gemm_ukernel, empty_gemm_ukernel, dummy_gemm_ukernel, }, .igemm = { empty_igemm_ukernel, empty_igemm_ukernel, empty_igemm_ukernel, dummy_igemm_ukernel, }, }, .mr = 4, .nr = 8, }; // batch size == 3 < mr == 4, pick smallest available kernel to minimize clamps. ASSERT_EQ(4, xnn_get_heuristic_mr_gemm(3, params.mr, params.nr, params.minmax.gemm)); }