// Copyright 2021 Tencent // SPDX-License-Identifier: BSD-3-Clause #include "testutil.h" #include "layer_type.h" static int test_requantize(const ncnn::Mat& a, int scale_in_data_size, int scale_out_data_size, int bias_data_size, int activation_type, float alpha, float beta) { ncnn::ParamDict pd; pd.set(0, scale_in_data_size); pd.set(1, scale_out_data_size); pd.set(2, bias_data_size); ncnn::Mat activation_params(2); activation_params[0] = alpha; activation_params[1] = beta; pd.set(3, activation_type); pd.set(4, activation_params); std::vector weights(bias_data_size ? 3 : 2); weights[0] = RandomMat(scale_in_data_size); weights[1] = RandomMat(scale_out_data_size); if (bias_data_size) weights[2] = RandomMat(bias_data_size); Randomize(weights[0], 0.0001, 0.001); Randomize(weights[1], 10, 100); int flag = TEST_LAYER_DISABLE_AUTO_INPUT_CASTING; int ret = test_layer("Requantize", pd, weights, a, 1, flag); if (ret != 0) { fprintf(stderr, "test_requantize failed a.dims=%d a=(%d %d %d %d) scale_in_data_size=%d scale_out_data_size=%d bias_data_size=%d act=%d actparams=[%f,%f]\n", a.dims, a.w, a.h, a.d, a.c, scale_in_data_size, scale_out_data_size, bias_data_size, activation_type, activation_params[0], activation_params[1]); } return ret; } static int test_requantize(const ncnn::Mat& a, int scale_in_data_size, int scale_out_data_size, int bias_data_size) { return 0 || test_requantize(a, scale_in_data_size, scale_out_data_size, bias_data_size, 0, 0.f, 0.f) || test_requantize(a, scale_in_data_size, scale_out_data_size, bias_data_size, 1, 0.f, 0.f) || test_requantize(a, scale_in_data_size, scale_out_data_size, bias_data_size, 2, RandomFloat(0, 1), 0.f) || test_requantize(a, scale_in_data_size, scale_out_data_size, bias_data_size, 3, RandomFloat(-1, 0), RandomFloat(0, 1)) || test_requantize(a, scale_in_data_size, scale_out_data_size, bias_data_size, 4, 0.f, 0.f) || test_requantize(a, scale_in_data_size, scale_out_data_size, bias_data_size, 5, 0.f, 0.f); } static int test_requantize_relu_empty_activation_params(const ncnn::Mat& a) { ncnn::ParamDict pd; pd.set(0, 1); pd.set(1, 1); pd.set(2, 0); pd.set(3, 1); std::vector weights(2); weights[0] = RandomMat(1); weights[1] = RandomMat(1); Randomize(weights[0], 0.0001, 0.001); Randomize(weights[1], 10, 100); int flag = TEST_LAYER_DISABLE_AUTO_INPUT_CASTING | TEST_LAYER_DISABLE_AUTO_INPUT_PACKING; int ret = test_layer("Requantize", pd, weights, a, 1, flag); if (ret != 0) { fprintf(stderr, "test_requantize_relu_empty_activation_params failed a.dims=%d a=(%d %d %d %d)\n", a.dims, a.w, a.h, a.d, a.c); } return ret; } static int test_requantize_pack1(const ncnn::Mat& a, int scale_in_data_size, int scale_out_data_size, int bias_data_size, int activation_type, float alpha, float beta) { ncnn::ParamDict pd; pd.set(0, scale_in_data_size); pd.set(1, scale_out_data_size); pd.set(2, bias_data_size); ncnn::Mat activation_params(2); activation_params[0] = alpha; activation_params[1] = beta; pd.set(3, activation_type); pd.set(4, activation_params); std::vector weights(bias_data_size ? 3 : 2); weights[0] = RandomMat(scale_in_data_size); weights[1] = RandomMat(scale_out_data_size); if (bias_data_size) weights[2] = RandomMat(bias_data_size); Randomize(weights[0], 0.0001, 0.001); Randomize(weights[1], 10, 100); int flag = TEST_LAYER_DISABLE_AUTO_INPUT_CASTING | TEST_LAYER_DISABLE_AUTO_INPUT_PACKING; int ret = test_layer("Requantize", pd, weights, a, 1, flag); if (ret != 0) { fprintf(stderr, "test_requantize_pack1 failed a.dims=%d a=(%d %d %d %d) scale_in_data_size=%d scale_out_data_size=%d bias_data_size=%d act=%d actparams=[%f,%f]\n", a.dims, a.w, a.h, a.d, a.c, scale_in_data_size, scale_out_data_size, bias_data_size, activation_type, activation_params[0], activation_params[1]); } return ret; } static int test_requantize_pack1(const ncnn::Mat& a, int scale_in_data_size, int scale_out_data_size, int bias_data_size) { return 0 || test_requantize_pack1(a, scale_in_data_size, scale_out_data_size, bias_data_size, 0, 0.f, 0.f) || test_requantize_pack1(a, scale_in_data_size, scale_out_data_size, bias_data_size, 1, 0.f, 0.f) || test_requantize_pack1(a, scale_in_data_size, scale_out_data_size, bias_data_size, 2, RandomFloat(0, 1), 0.f) || test_requantize_pack1(a, scale_in_data_size, scale_out_data_size, bias_data_size, 3, RandomFloat(-1, 0), RandomFloat(0, 1)) || test_requantize_pack1(a, scale_in_data_size, scale_out_data_size, bias_data_size, 4, 0.f, 0.f) || test_requantize_pack1(a, scale_in_data_size, scale_out_data_size, bias_data_size, 5, 0.f, 0.f); } static int test_requantize_pack8(const ncnn::Mat& a, int scale_in_data_size, int scale_out_data_size, int bias_data_size, int activation_type, float alpha, float beta) { ncnn::ParamDict pd; pd.set(0, scale_in_data_size); pd.set(1, scale_out_data_size); pd.set(2, bias_data_size); ncnn::Mat activation_params(2); activation_params[0] = alpha; activation_params[1] = beta; pd.set(3, activation_type); pd.set(4, activation_params); std::vector weights(bias_data_size ? 3 : 2); weights[0] = RandomMat(scale_in_data_size); weights[1] = RandomMat(scale_out_data_size); if (bias_data_size) weights[2] = RandomMat(bias_data_size); Randomize(weights[0], 0.0001, 0.001); Randomize(weights[1], 10, 100); int flag = TEST_LAYER_DISABLE_AUTO_INPUT_CASTING; // ordinary cases cover dims=1/2/3; retain the packed dims=4 cases if (a.dims != 4) flag |= TEST_LAYER_DISABLE_GPU_TESTING; #if !__riscv flag |= TEST_LAYER_ENABLE_FORCE_INPUT_PACK8; #endif int ret = test_layer("Requantize", pd, weights, a, 1, flag); if (ret != 0) { fprintf(stderr, "test_requantize_pack8 failed a.dims=%d a=(%d %d %d %d) scale_in_data_size=%d scale_out_data_size=%d bias_data_size=%d act=%d actparams=[%f,%f]\n", a.dims, a.w, a.h, a.d, a.c, scale_in_data_size, scale_out_data_size, bias_data_size, activation_type, activation_params[0], activation_params[1]); } return ret; } static int test_requantize_pack8(const ncnn::Mat& a, int scale_in_data_size, int scale_out_data_size, int bias_data_size) { return 0 || test_requantize_pack8(a, scale_in_data_size, scale_out_data_size, bias_data_size, 0, 0.f, 0.f) || test_requantize_pack8(a, scale_in_data_size, scale_out_data_size, bias_data_size, 1, 0.f, 0.f) || test_requantize_pack8(a, scale_in_data_size, scale_out_data_size, bias_data_size, 2, RandomFloat(0, 1), 0.f) || test_requantize_pack8(a, scale_in_data_size, scale_out_data_size, bias_data_size, 3, RandomFloat(-1, 0), RandomFloat(0, 1)) || test_requantize_pack8(a, scale_in_data_size, scale_out_data_size, bias_data_size, 4, 0.f, 0.f) || test_requantize_pack8(a, scale_in_data_size, scale_out_data_size, bias_data_size, 5, 0.f, 0.f); } static int test_requantize_0() { return 0 || test_requantize_pack1(RandomIntMat(3, 3, 32), 32, 32, 0) || test_requantize_pack1(RandomIntMat(3, 3, 64), 1, 1, 64) || test_requantize_pack1(RandomIntMat(3, 3, 128), 128, 1, 128) || test_requantize_pack1(RandomIntMat(7, 9, 12), 1, 1, 12) || test_requantize_pack1(RandomIntMat(7, 9, 12), 1, 1, 1) || test_requantize_pack1(RandomIntMat(7, 9, 12), 1, 1, 0) || test_requantize_pack1(RandomIntMat(7, 9, 12), 12, 12, 12) || test_requantize_pack1(RandomIntMat(7, 9, 12), 12, 12, 1) || test_requantize_pack1(RandomIntMat(7, 9, 12), 12, 12, 0) || test_requantize_pack1(RandomIntMat(7, 9, 12), 1, 12, 12) || test_requantize_pack1(RandomIntMat(7, 9, 12), 1, 12, 1) || test_requantize_pack1(RandomIntMat(7, 9, 12), 1, 12, 0) || test_requantize_pack1(RandomIntMat(7, 9, 12), 12, 1, 12) || test_requantize_pack1(RandomIntMat(7, 9, 12), 12, 1, 1) || test_requantize_pack1(RandomIntMat(7, 9, 12), 12, 1, 0) || test_requantize_pack1(RandomIntMat(3, 5, 13), 1, 1, 13) || test_requantize_pack1(RandomIntMat(3, 5, 13), 1, 1, 1) || test_requantize_pack1(RandomIntMat(3, 5, 13), 1, 1, 0) || test_requantize_pack1(RandomIntMat(3, 5, 13), 13, 13, 13) || test_requantize_pack1(RandomIntMat(3, 5, 13), 13, 13, 1) || test_requantize_pack1(RandomIntMat(3, 5, 13), 13, 13, 0) || test_requantize_pack1(RandomIntMat(3, 5, 13), 1, 13, 13) || test_requantize_pack1(RandomIntMat(3, 5, 13), 1, 13, 1) || test_requantize_pack1(RandomIntMat(3, 5, 13), 1, 13, 0) || test_requantize_pack1(RandomIntMat(3, 5, 13), 13, 1, 13) || test_requantize_pack1(RandomIntMat(3, 5, 13), 13, 1, 1) || test_requantize_pack1(RandomIntMat(3, 5, 13), 13, 1, 0); } static int test_requantize_1() { return 0 || test_requantize_pack1(RandomIntMat(9, 32), 32, 32, 0) || test_requantize_pack1(RandomIntMat(9, 64), 1, 1, 64) || test_requantize_pack1(RandomIntMat(9, 128), 128, 1, 128) || test_requantize_pack1(RandomIntMat(17, 12), 1, 1, 12) || test_requantize_pack1(RandomIntMat(17, 12), 1, 1, 1) || test_requantize_pack1(RandomIntMat(17, 12), 1, 1, 0) || test_requantize_pack1(RandomIntMat(17, 12), 12, 12, 12) || test_requantize_pack1(RandomIntMat(17, 12), 12, 12, 1) || test_requantize_pack1(RandomIntMat(17, 12), 12, 12, 0) || test_requantize_pack1(RandomIntMat(17, 12), 1, 12, 12) || test_requantize_pack1(RandomIntMat(17, 12), 1, 12, 1) || test_requantize_pack1(RandomIntMat(17, 12), 1, 12, 0) || test_requantize_pack1(RandomIntMat(17, 12), 12, 1, 12) || test_requantize_pack1(RandomIntMat(17, 12), 12, 1, 1) || test_requantize_pack1(RandomIntMat(17, 12), 12, 1, 0) || test_requantize_pack1(RandomIntMat(19, 15), 1, 1, 15) || test_requantize_pack1(RandomIntMat(19, 15), 1, 1, 1) || test_requantize_pack1(RandomIntMat(19, 15), 1, 1, 0) || test_requantize_pack1(RandomIntMat(19, 15), 15, 15, 15) || test_requantize_pack1(RandomIntMat(19, 15), 15, 15, 1) || test_requantize_pack1(RandomIntMat(19, 15), 15, 15, 0) || test_requantize_pack1(RandomIntMat(19, 15), 1, 15, 15) || test_requantize_pack1(RandomIntMat(19, 15), 1, 15, 1) || test_requantize_pack1(RandomIntMat(19, 15), 1, 15, 0) || test_requantize_pack1(RandomIntMat(19, 15), 15, 1, 15) || test_requantize_pack1(RandomIntMat(19, 15), 15, 1, 1) || test_requantize_pack1(RandomIntMat(19, 15), 15, 1, 0); } static int test_requantize_2() { return 0 || test_requantize_pack1(RandomIntMat(124), 1, 1, 1) || test_requantize_pack1(RandomIntMat(124), 1, 1, 0) || test_requantize_pack1(RandomIntMat(127), 1, 1, 1) || test_requantize_pack1(RandomIntMat(127), 1, 1, 0) || test_requantize_pack1(RandomIntMat(127), 1, 1, 0, 2, 0.f, 0.f) || test_requantize_pack1(RandomIntMat(127), 1, 1, 0, 2, RandomFloat(-1, 0), 0.f) || test_requantize_relu_empty_activation_params(RandomIntMat(127)); } static int test_requantize_3() { return 0 #ifndef __riscv || test_requantize_pack8(RandomIntMat(5, 7, 24), 1, 1, 24) || test_requantize_pack8(RandomIntMat(5, 7, 24), 1, 1, 1) || test_requantize_pack8(RandomIntMat(5, 7, 24), 1, 1, 0) || test_requantize_pack8(RandomIntMat(5, 7, 24), 24, 24, 24) || test_requantize_pack8(RandomIntMat(5, 7, 24), 24, 24, 1) || test_requantize_pack8(RandomIntMat(5, 7, 24), 24, 24, 0) || test_requantize_pack8(RandomIntMat(5, 7, 24), 1, 24, 24) || test_requantize_pack8(RandomIntMat(5, 7, 24), 1, 24, 1) || test_requantize_pack8(RandomIntMat(5, 7, 24), 1, 24, 0) || test_requantize_pack8(RandomIntMat(5, 7, 24), 24, 1, 24) || test_requantize_pack8(RandomIntMat(5, 7, 24), 24, 1, 1) || test_requantize_pack8(RandomIntMat(5, 7, 24), 24, 1, 0) || test_requantize_pack8(RandomIntMat(15, 24), 1, 1, 24) || test_requantize_pack8(RandomIntMat(15, 24), 1, 1, 1) || test_requantize_pack8(RandomIntMat(15, 24), 1, 1, 0) || test_requantize_pack8(RandomIntMat(15, 24), 24, 24, 24) || test_requantize_pack8(RandomIntMat(15, 24), 24, 24, 1) || test_requantize_pack8(RandomIntMat(15, 24), 24, 24, 0) || test_requantize_pack8(RandomIntMat(15, 24), 1, 24, 24) || test_requantize_pack8(RandomIntMat(15, 24), 1, 24, 1) || test_requantize_pack8(RandomIntMat(15, 24), 1, 24, 0) || test_requantize_pack8(RandomIntMat(15, 24), 24, 1, 24) || test_requantize_pack8(RandomIntMat(15, 24), 24, 1, 1) || test_requantize_pack8(RandomIntMat(15, 24), 24, 1, 0) || test_requantize_pack8(RandomIntMat(128), 1, 1, 1) || test_requantize_pack8(RandomIntMat(128), 1, 1, 0); #else || test_requantize(RandomIntMat(5, 7, 24), 1, 1, 24) || test_requantize(RandomIntMat(5, 7, 24), 1, 1, 1) || test_requantize(RandomIntMat(5, 7, 24), 1, 1, 0) || test_requantize(RandomIntMat(5, 7, 24), 24, 24, 24) || test_requantize(RandomIntMat(5, 7, 24), 24, 24, 1) || test_requantize(RandomIntMat(5, 7, 24), 24, 24, 0) || test_requantize(RandomIntMat(5, 7, 24), 1, 24, 24) || test_requantize(RandomIntMat(5, 7, 24), 1, 24, 1) || test_requantize(RandomIntMat(5, 7, 24), 1, 24, 0) || test_requantize(RandomIntMat(5, 7, 24), 24, 1, 24) || test_requantize(RandomIntMat(5, 7, 24), 24, 1, 1) || test_requantize(RandomIntMat(5, 7, 24), 24, 1, 0) || test_requantize(RandomIntMat(15, 24), 1, 1, 24) || test_requantize(RandomIntMat(15, 24), 1, 1, 1) || test_requantize(RandomIntMat(15, 24), 1, 1, 0) || test_requantize(RandomIntMat(15, 24), 24, 24, 24) || test_requantize(RandomIntMat(15, 24), 24, 24, 1) || test_requantize(RandomIntMat(15, 24), 24, 24, 0) || test_requantize(RandomIntMat(15, 24), 1, 24, 24) || test_requantize(RandomIntMat(15, 24), 1, 24, 1) || test_requantize(RandomIntMat(15, 24), 1, 24, 0) || test_requantize(RandomIntMat(15, 24), 24, 1, 24) || test_requantize(RandomIntMat(15, 24), 24, 1, 1) || test_requantize(RandomIntMat(15, 24), 24, 1, 0) || test_requantize(RandomIntMat(128), 1, 1, 1) || test_requantize(RandomIntMat(128), 1, 1, 0) || test_requantize(RandomIntMat(127), 1, 1, 0, 2, RandomFloat(1, 2), 0.f); #endif // __riscv } static int test_requantize_4() { return 0 || test_requantize_pack1(RandomIntMat(3, 3, 1, 32), 32, 32, 0) || test_requantize_pack1(RandomIntMat(3, 3, 1, 64), 1, 1, 64) || test_requantize_pack1(RandomIntMat(3, 3, 1, 128), 128, 1, 128) || test_requantize_pack8(RandomIntMat(5, 3, 2, 24), 1, 1, 24) || test_requantize_pack8(RandomIntMat(5, 3, 2, 24), 24, 24, 0) || test_requantize_pack1(RandomIntMat(5, 3, 2, 12), 1, 1, 12) || test_requantize_pack1(RandomIntMat(5, 3, 2, 12), 12, 12, 0) || test_requantize_pack1(RandomIntMat(3, 5, 3, 13), 1, 13, 13) || test_requantize_pack1(RandomIntMat(3, 5, 3, 13), 13, 1, 0); } static int test_requantize_activation_params_text() { #if NCNN_STRING const char* params[] = {"0=1 1=1 3=3 -23304=2,-1,2", "0=1 1=1 3=3 -23304=2,-1.0,2.0"}; for (int i = 0; i < 2; i++) { TestParamDict pd; if (pd.load_param(params[i]) != 0 || pd.type(4) != 5 + i) return -1; std::vector weights(2); weights[0].create(1); weights[0][0] = 1.f; weights[1].create(1); weights[1][0] = 1.f; ncnn::Mat a(2); int* p = a; p[0] = -3; p[1] = 3; ncnn::Mat reference(2); reference[0] = -1.f; reference[1] = 2.f; ncnn::Mat b; int ret = test_layer_naive(ncnn::LayerType::Requantize, pd, weights, a, b, 0); if (ret == 0) ret = CompareMat(reference, b, 0.f); if (ret != 0) { fprintf(stderr, "test_requantize_activation_params_text failed params=%s ret=%d\n", params[i], ret); return ret; } const ncnn::Mat original = pd.get(4, ncnn::Mat()); const int* q = original; if (i == 0 ? (q[0] != -1 || q[1] != 2) : (original[0] != -1.f || original[1] != 2.f)) { fprintf(stderr, "test_requantize_activation_params_text modified params=%s\n", params[i]); return -1; } } #endif return 0; } #if NCNN_VALIDATION static int test_requantize_load_param_activation(const ncnn::ParamDict& base, int activation_type, const ncnn::Mat& activation_params, int expected_ret) { ncnn::ParamDict pd = base; pd.set(3, activation_type); pd.set(4, activation_params); return test_layer_param(ncnn::LayerType::Requantize, pd, expected_ret); } static int test_requantize_load_param() { ncnn::ParamDict base; base.set(0, 1); base.set(1, 1); if (test_layer_param(ncnn::LayerType::Requantize, base, 0) != 0) return -1; ncnn::Mat params(2); params[0] = 0.1f; params[1] = 0.5f; int ret = 0 || test_requantize_load_param_activation(base, 0, ncnn::Mat(), 0) || test_requantize_load_param_activation(base, 0, ncnn::Mat(0), 0) || test_requantize_load_param_activation(base, 0, params, 0) || test_requantize_load_param_activation(base, 0, params.range(0, 1), 0) || test_requantize_load_param_activation(base, 1, ncnn::Mat(), 0) || test_requantize_load_param_activation(base, 1, ncnn::Mat(0), 0) || test_requantize_load_param_activation(base, 1, params, 0) || test_requantize_load_param_activation(base, 1, params.range(0, 1), 0) || test_requantize_load_param_activation(base, 2, ncnn::Mat(), -1) || test_requantize_load_param_activation(base, 2, ncnn::Mat(0), -1) || test_requantize_load_param_activation(base, 2, params, 0) || test_requantize_load_param_activation(base, 2, params.range(0, 1), 0) || test_requantize_load_param_activation(base, 3, ncnn::Mat(), -1) || test_requantize_load_param_activation(base, 3, ncnn::Mat(0), -1) || test_requantize_load_param_activation(base, 3, params, 0) || test_requantize_load_param_activation(base, 3, params.range(0, 1), -1) || test_requantize_load_param_activation(base, 4, ncnn::Mat(), 0) || test_requantize_load_param_activation(base, 4, ncnn::Mat(0), 0) || test_requantize_load_param_activation(base, 4, params, 0) || test_requantize_load_param_activation(base, 4, params.range(0, 1), 0) || test_requantize_load_param_activation(base, 5, ncnn::Mat(), 0) || test_requantize_load_param_activation(base, 5, ncnn::Mat(0), 0) || test_requantize_load_param_activation(base, 5, params, 0) || test_requantize_load_param_activation(base, 5, params.range(0, 1), 0) || test_requantize_load_param_activation(base, 6, ncnn::Mat(), -1) || test_requantize_load_param_activation(base, 6, ncnn::Mat(0), -1) || test_requantize_load_param_activation(base, 6, params, 0) || test_requantize_load_param_activation(base, 6, params.range(0, 1), -1) || test_requantize_load_param_activation(base, 7, ncnn::Mat(), -1); if (ret != 0) return ret; if (test_layer_param(ncnn::LayerType::Requantize, base, 4, 1, -1) || test_layer_param(ncnn::LayerType::Requantize, base, 4, 1.f, -1)) return -1; ncnn::Mat missing_data(0); missing_data.w = 1; const ncnn::Mat bad[] = {ncnn::Mat(2, (size_t)1u), ncnn::Mat(2, (size_t)2u), ncnn::Mat(2, 2), ncnn::Mat(2, (size_t)16u, 4), missing_data}; for (int i = 0; i < 5; i++) { if (test_layer_param(ncnn::LayerType::Requantize, base, 4, bad[i], -1) != 0) return -1; } return 0; } static int test_requantize_load_param_text() { #if NCNN_STRING const char* params[] = {"0=1 1=1 3=3 -23304=2,-1,2", "0=1 1=1 3=3 -23304=2,-1.0,2.0"}; for (int i = 0; i < 2; i++) { TestParamDict pd; if (pd.load_param(params[i]) != 0 || pd.type(4) != 5 + i) return -1; if (test_layer_param(ncnn::LayerType::Requantize, pd, 0) != 0) return -1; } #endif return 0; } #endif // NCNN_VALIDATION int main() { SRAND(7767517); return 0 || test_requantize_4() || test_requantize_0() || test_requantize_1() || test_requantize_2() || test_requantize_3() || test_requantize_activation_params_text() #if NCNN_VALIDATION || test_requantize_load_param() || test_requantize_load_param_text() #endif // NCNN_VALIDATION ; }