mirror of
https://github.com/Tencent/ncnn.git
synced 2026-10-17 04:41:47 +08:00
64 lines
1.9 KiB
C++
64 lines
1.9 KiB
C++
// Copyright 2025 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_deconvolution_oom(int w, int h, int c, int outch, int kernel, int dilation, int stride, int pad, int bias, int output_pad_right, int output_pad_bottom, int output_w, int output_h)
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{
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ncnn::Mat a = RandomMat(w, h, c);
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if (output_w > 0 && output_h > 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);
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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_w);
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pd.set(21, output_h);
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std::vector<ncnn::Mat> weights(bias ? 2 : 1);
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weights[0] = RandomMat(outch * c * kernel * kernel);
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if (bias)
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weights[1] = RandomMat(outch);
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int ret = test_layer_oom("Deconvolution", pd, weights, a);
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if (ret != 0)
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{
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fprintf(stderr, "test_deconvolution_oom failed w=%d h=%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_w=%d output_h=%d\n", w, h, c, outch, kernel, dilation, stride, pad, bias, activation_type, activation_params[0], activation_params[1], output_pad_right, output_pad_bottom, output_w, output_h);
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return ret;
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}
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return ret;
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}
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static int test_deconvolution_0()
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{
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return 0
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|| test_deconvolution_oom(9, 7, 8, 8, 3, 1, 1, 1, 1, 0, 0, 0, 0)
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|| test_deconvolution_oom(9, 7, 16, 16, 3, 1, 1, 1, 1, 0, 0, 0, 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_deconvolution_0();
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}
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