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- // Tencent is pleased to support the open source community by making ncnn available.
- //
- // Copyright (C) 2022 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 "testutil.h"
-
- static int test_deconvolution3d(int w, int h, int d, int c, int outch, int kernel, int dilation, int stride, int pad, int bias, int output_pad_right, int output_pad_bottom, int output_pad_behind, int output_w, int output_h, int output_d)
- {
- ncnn::Mat a = RandomMat(w, h, d, c);
-
- if (output_w > 0 && output_h > 0 && output_d > 0 && pad != -233 && pad != -234)
- {
- pad = -233;
- }
-
- 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 * kernel);
-
- int activation_type = RAND() % 5; // 0 1 2 3 4
- ncnn::Mat activation_params(2);
- activation_params[0] = RandomFloat(-1, 0); // alpha
- activation_params[1] = RandomFloat(0, 1); // beta
- pd.set(9, activation_type);
- pd.set(10, activation_params);
-
- pd.set(18, output_pad_right);
- pd.set(19, output_pad_bottom);
- pd.set(20, output_pad_behind);
- pd.set(25, output_w);
- pd.set(26, output_h);
- pd.set(27, output_d);
-
- std::vector<ncnn::Mat> weights(2);
- weights[0] = RandomMat(outch * c * kernel * kernel * kernel);
- weights[1] = RandomMat(outch);
-
- int ret = test_layer("Deconvolution3D", pd, weights, a);
- if (ret != 0)
- {
- fprintf(stderr, "test_deconvolution3d failed w=%d h=%d d=%d c=%d outch=%d kernel=%d dilation=%d stride=%d pad=%d bias=%d act=%d actparams=[%f,%f] output_pad_right=%d output_pad_bottom=%d output_pad_behind=%d output_w=%d output_h=%d output_d=%d\n", w, h, d, c, outch, kernel, dilation, stride, pad, bias, activation_type, activation_params[0], activation_params[1], output_pad_right, output_pad_bottom, output_pad_behind, output_w, output_h, output_d);
- }
-
- return ret;
- }
-
- static int test_deconvolution3d_0()
- {
- static const int kdsp[7][4] = {
- {1, 1, 1, 0},
- {1, 1, 2, 0},
- {2, 1, 1, 1},
- {2, 1, 2, -233},
- {3, 1, 1, 1},
- {3, 1, 2, 1},
- {3, 2, 1, -234},
- };
-
- for (int i = 0; i < 7; 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_deconvolution3d(9, 8, 7, 1, 1, k, d, s, p, 1, 0, 0, 0, 0, 0, 0)
- || test_deconvolution3d(9, 8, 7, 4, 13, k, d, s, p, 0, 1, 1, 1, 7, 6, 5)
- || test_deconvolution3d(9, 8, 7, 13, 4, k, d, s, p, 1, 1, 0, 0, 0, 0, 0)
- || test_deconvolution3d(9, 8, 7, 4, 8, k, d, s, p, 0, 0, 1, 0, 0, 0, 0)
- || test_deconvolution3d(9, 8, 7, 8, 4, k, d, s, p, 1, 0, 0, 0, 7, 6, 5)
- || test_deconvolution3d(9, 8, 7, 8, 13, k, d, s, p, 0, 2, 2, 2, 0, 0, 0)
- || test_deconvolution3d(9, 8, 7, 13, 8, k, d, s, p, 1, 2, 0, 2, 0, 0, 0)
- || test_deconvolution3d(9, 8, 7, 16, 16, k, d, s, p, 0, 0, 2, 0, 7, 6, 5);
-
- if (ret != 0)
- return -1;
- }
-
- return 0;
- }
-
- int main()
- {
- SRAND(7767517);
-
- return test_deconvolution3d_0();
- }
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