// Tencent is pleased to support the open source community by making ncnn available. // // Copyright (C) 2019 THL A29 Limited, a Tencent company. All rights reserved. // // Licensed under the BSD 3-Clause License (the "License"); you may not use this file except // in compliance with the License. You may obtain a copy of the License at // // https://opensource.org/licenses/BSD-3-Clause // // Unless required by applicable law or agreed to in writing, software distributed // under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR // CONDITIONS OF ANY KIND, either express or implied. See the License for the // specific language governing permissions and limitations under the License. #include "layer/deformableconv2d.h" #include "testutil.h" static int test_deformableconv2d(int w, int h, int c, int outch, int kernel, int dilation, int stride, int pad, int bias) { const int kernel_extent_w = dilation * (kernel - 1) + 1; const int kernel_extent_h = dilation * (kernel - 1) + 1; const int out_w = (w + pad + pad - kernel_extent_w) / stride + 1; const int out_h = (h + pad + pad - kernel_extent_h) / stride + 1; std::vector a(3); a[0] = RandomMat(w, h, c); a[1] = RandomMat(out_w, out_h, kernel * kernel * 2); a[2] = RandomMat(out_w, out_h, kernel * kernel); ncnn::ParamDict pd; pd.set(0, outch); pd.set(1, kernel); pd.set(2, dilation); pd.set(3, stride); pd.set(4, pad); pd.set(5, bias); pd.set(6, outch * c * kernel * kernel); int activation_type = RAND() % 7; // 0 1 2 3 4 5 6 ncnn::Mat activation_params(2); activation_params[0] = (activation_type == 6) ? RandomFloat(0, 1) : RandomFloat(-1, 0); // alpha activation_params[1] = RandomFloat(0, 1); // beta pd.set(9, activation_type); pd.set(10, activation_params); std::vector weights(bias ? 2 : 1); weights[0] = RandomMat(outch * c * kernel * kernel); if (bias) weights[1] = RandomMat(outch); float epsilon = 0.001; int ret = test_layer("DeformableConv2D", pd, weights, a, 1, epsilon); if (ret != 0) { fprintf(stderr, "test_deformableconv2d failed w=%d h=%d c=%d outch=%d kernel=%d dilation=%d stride=%d pad=%d bias=%d act=%d actparams=[%f,%f]\n", w, h, c, outch, kernel, dilation, stride, pad, bias, activation_type, activation_params[0], activation_params[1]); } { ncnn::Option opt; opt.num_threads = 1; opt.use_packing_layout = true; opt.use_fp16_packed = false; opt.use_fp16_storage = false; opt.use_fp16_arithmetic = false; opt.use_bf16_storage = false; opt.use_shader_pack8 = false; opt.use_image_storage = false; opt.use_sgemm_convolution = false; opt.use_winograd_convolution = false; ret = test_layer_opt("DeformableConv2D", pd, weights, opt, a, 1, epsilon); if (ret != 0) { fprintf(stderr, "test_deformableconv2d failed w=%d h=%d c=%d outch=%d kernel=%d dilation=%d stride=%d pad=%d bias=%d act=%d actparams=[%f,%f]\n", w, h, c, outch, kernel, dilation, stride, pad, bias, activation_type, activation_params[0], activation_params[1]); } } { ncnn::Option opt; opt.num_threads = 1; opt.use_packing_layout = true; opt.use_fp16_packed = true; opt.use_fp16_storage = true; opt.use_fp16_arithmetic = true; opt.use_bf16_storage = true; opt.use_shader_pack8 = true; opt.use_image_storage = true; opt.use_sgemm_convolution = false; opt.use_winograd_convolution = false; ret = test_layer_opt("DeformableConv2D", pd, weights, opt, a, 1, epsilon); if (ret != 0) { fprintf(stderr, "test_deformableconv2d failed w=%d h=%d c=%d outch=%d kernel=%d dilation=%d stride=%d pad=%d bias=%d act=%d actparams=[%f,%f]\n", w, h, c, outch, kernel, dilation, stride, pad, bias, activation_type, activation_params[0], activation_params[1]); } } return ret; } static int test_deformableconv2d_0() { static const int kdsp[10][4] = { {1, 1, 1, 0}, {1, 1, 2, 0}, {2, 1, 1, 1}, {2, 1, 2, 0}, {3, 1, 1, 1}, {3, 1, 2, 1}, {3, 2, 1, 1}, {4, 1, 2, 1}, {5, 1, 2, 2}, {5, 2, 2, 2}, }; for (int i = 8; i < 10; i++) { const int k = kdsp[i][0]; const int d = kdsp[i][1]; const int s = kdsp[i][2]; const int p = kdsp[i][3]; int ret = 0 || test_deformableconv2d(9, 7, 1, 1, k, d, s, p, 1) || test_deformableconv2d(9, 7, 4, 13, k, d, s, p, 0) || test_deformableconv2d(9, 7, 13, 4, k, d, s, p, 1) || test_deformableconv2d(9, 7, 4, 8, k, d, s, p, 0) || test_deformableconv2d(9, 7, 8, 4, k, d, s, p, 1) || test_deformableconv2d(9, 7, 8, 13, k, d, s, p, 0) || test_deformableconv2d(9, 7, 13, 8, k, d, s, p, 1) || test_deformableconv2d(9, 7, 16, 16, k, d, s, p, 0) || test_deformableconv2d(16, 16, 1 * 3, 1 * 3, k, d, s, p, 1) || test_deformableconv2d(16, 16, 1 * 3, 4 * 3, k, d, s, p, 1) || test_deformableconv2d(16, 16, 1 * 3, 8 * 3, k, d, s, p, 1) || test_deformableconv2d(16, 16, 1 * 3, 16 * 3, k, d, s, p, 1) || test_deformableconv2d(16, 16, 4 * 3, 1 * 3, k, d, s, p, 1) || test_deformableconv2d(16, 16, 4 * 3, 4 * 3, k, d, s, p, 1) || test_deformableconv2d(16, 16, 4 * 3, 8 * 3, k, d, s, p, 1) || test_deformableconv2d(16, 16, 4 * 3, 16 * 3, k, d, s, p, 1) || test_deformableconv2d(16, 16, 8 * 3, 1 * 3, k, d, s, p, 1) || test_deformableconv2d(16, 16, 8 * 3, 4 * 3, k, d, s, p, 1) || test_deformableconv2d(16, 16, 8 * 3, 8 * 3, k, d, s, p, 1) || test_deformableconv2d(16, 16, 8 * 3, 16 * 3, k, d, s, p, 1) || test_deformableconv2d(16, 16, 16 * 3, 1 * 3, k, d, s, p, 1) || test_deformableconv2d(16, 16, 16 * 3, 4 * 3, k, d, s, p, 1) || test_deformableconv2d(16, 16, 16 * 3, 8 * 3, k, d, s, p, 1) || test_deformableconv2d(16, 16, 16 * 3, 16 * 3, k, d, s, p, 1); if (ret != 0) return -1; } return 0; } int main() { SRAND(7767517); return test_deformableconv2d_0(); }