mirror of
https://github.com/Tencent/ncnn.git
synced 2026-10-19 23:03:17 +08:00
93 lines
3.1 KiB
C++
93 lines
3.1 KiB
C++
// Copyright 2022 Tencent
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// SPDX-License-Identifier: BSD-3-Clause
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#include "testutil.h"
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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)
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{
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ncnn::Mat a = RandomMat(w, h, d, c);
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if (output_w > 0 && output_h > 0 && output_d > 0 && pad != -233 && pad != -234)
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{
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pad = -233;
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}
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ncnn::ParamDict pd;
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pd.set(0, outch);
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pd.set(1, kernel);
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pd.set(2, dilation);
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pd.set(3, stride);
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pd.set(4, pad);
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pd.set(5, bias);
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pd.set(6, outch * c * kernel * kernel * kernel);
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int activation_type = RAND() % 5; // 0 1 2 3 4
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ncnn::Mat activation_params(2);
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activation_params[0] = RandomFloat(-1, 0); // alpha
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activation_params[1] = RandomFloat(0, 1); // beta
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pd.set(9, activation_type);
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pd.set(10, activation_params);
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pd.set(18, output_pad_right);
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pd.set(19, output_pad_bottom);
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pd.set(20, output_pad_behind);
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pd.set(25, output_w);
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pd.set(26, output_h);
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pd.set(27, output_d);
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std::vector<ncnn::Mat> weights(2);
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weights[0] = RandomMat(outch * c * kernel * kernel * kernel);
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weights[1] = RandomMat(outch);
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int ret = test_layer("Deconvolution3D", pd, weights, a);
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if (ret != 0)
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{
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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);
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}
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return ret;
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}
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static int test_deconvolution3d_0()
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{
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static const int kdsp[7][4] = {
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{1, 1, 1, 0},
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{1, 1, 2, 0},
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{2, 1, 1, 1},
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{2, 1, 2, -233},
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{3, 1, 1, 1},
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{3, 1, 2, 1},
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{3, 2, 1, -234},
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};
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for (int i = 0; i < 7; i++)
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{
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const int k = kdsp[i][0];
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const int d = kdsp[i][1];
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const int s = kdsp[i][2];
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const int p = kdsp[i][3];
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int ret = 0
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|| test_deconvolution3d(9, 8, 7, 1, 1, k, d, s, p, 1, 0, 0, 0, 0, 0, 0)
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|| test_deconvolution3d(9, 8, 7, 4, 13, k, d, s, p, 0, 1, 1, 1, 7, 6, 5)
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|| test_deconvolution3d(9, 8, 7, 13, 4, k, d, s, p, 1, 1, 0, 0, 0, 0, 0)
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|| test_deconvolution3d(9, 8, 7, 4, 8, k, d, s, p, 0, 0, 1, 0, 0, 0, 0)
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|| test_deconvolution3d(9, 8, 7, 8, 4, k, d, s, p, 1, 0, 0, 0, 7, 6, 5)
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|| test_deconvolution3d(9, 8, 7, 8, 13, k, d, s, p, 0, 2, 2, 2, 0, 0, 0)
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|| test_deconvolution3d(9, 8, 7, 13, 8, k, d, s, p, 1, 2, 0, 2, 0, 0, 0)
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|| test_deconvolution3d(9, 8, 7, 16, 16, k, d, s, p, 0, 0, 2, 0, 7, 6, 5);
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if (ret != 0)
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return -1;
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}
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return 0;
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}
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int main()
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{
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SRAND(7767517);
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return test_deconvolution3d_0();
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}
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