mirror of
https://github.com/Tencent/ncnn.git
synced 2026-10-18 13:42:18 +08:00
nihui
706c4d1964
Add 4d Mat handling across generic and optimized backends, extend operator tests, and document supported input and output Mat dimensions.
56 lines
1.5 KiB
C++
56 lines
1.5 KiB
C++
// Copyright 2020 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_instancenorm(const ncnn::Mat& a, float eps, int affine)
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{
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int channels = a.c;
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ncnn::ParamDict pd;
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pd.set(0, affine ? channels : 0);
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pd.set(1, eps);
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pd.set(2, affine);
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std::vector<ncnn::Mat> weights(2);
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weights[0] = RandomMat(channels);
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weights[1] = RandomMat(channels);
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int ret = test_layer("InstanceNorm", pd, weights, a);
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if (ret != 0)
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{
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fprintf(stderr, "test_instancenorm failed a.dims=%d a=(%d %d %d %d) eps=%f affine=%d\n", a.dims, a.w, a.h, a.d, a.c, eps, affine);
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}
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return ret;
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}
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static int test_instancenorm_0()
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{
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return 0
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|| test_instancenorm(RandomMat(6, 4, 2), 0.01f, 0)
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|| test_instancenorm(RandomMat(3, 3, 12), 0.002f, 0)
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|| test_instancenorm(RandomMat(5, 7, 16), 0.02f, 0)
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|| test_instancenorm(RandomMat(6, 4, 2), 0.01f, 1)
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|| test_instancenorm(RandomMat(3, 3, 12), 0.002f, 1)
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|| test_instancenorm(RandomMat(5, 7, 16), 0.02f, 1);
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}
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static int test_instancenorm_1()
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{
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return 0
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|| test_instancenorm(RandomMat(5, 4, 3, 3), 0.01f, 0)
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|| test_instancenorm(RandomMat(3, 3, 2, 8), 0.002f, 0)
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|| test_instancenorm(RandomMat(5, 4, 3, 3), 0.01f, 1)
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|| test_instancenorm(RandomMat(3, 3, 2, 8), 0.002f, 1);
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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 0
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|| test_instancenorm_0()
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|| test_instancenorm_1();
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}
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