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| // 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. | |
| 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<ncnn::Mat> 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<ncnn::Mat> 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<ncnn::DeformableConv2D>("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<ncnn::DeformableConv2D>("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<ncnn::DeformableConv2D>("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 = 0; i < 4; 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 | |
| || test_deformableconv2d(7, 5, 24, 32, 4, 2, 2, 2, 1) | |
| || test_deformableconv2d(7, 5, 32, 24, 4, 2, 2, 2, 1) | |
| || test_deformableconv2d(7, 5, 28, 32, 4, 2, 2, 2, 1) | |
| || test_deformableconv2d(7, 5, 32, 28, 4, 2, 2, 2, 1) | |
| || test_deformableconv2d(7, 5, 26, 32, 4, 2, 2, 2, 1) | |
| || test_deformableconv2d(7, 5, 32, 26, 4, 2, 2, 2, 1); | |
| } | |
| int main() | |
| { | |
| SRAND(7767517); | |
| return test_deformableconv2d_0(); | |
| } | |