mirror of
https://github.com/Tencent/ncnn.git
synced 2026-10-19 06:21:39 +08:00
nihui
706c4d1964
Add 4d Mat handling across generic and optimized backends, extend operator tests, and document supported input and output Mat dimensions.
114 lines
3.7 KiB
C++
114 lines
3.7 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_normalize(const ncnn::Mat& a, int across_spatial, int across_channel, int channel_shared, float eps, int eps_mode)
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{
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int scale_data_size = channel_shared ? 1 : a.c;
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ncnn::ParamDict pd;
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pd.set(0, across_spatial);
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pd.set(4, across_channel);
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pd.set(1, channel_shared);
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pd.set(2, eps);
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pd.set(3, scale_data_size);
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pd.set(9, eps_mode);
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std::vector<ncnn::Mat> weights(1);
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weights[0] = RandomMat(scale_data_size);
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int ret = test_layer("Normalize", pd, weights, a);
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if (ret != 0)
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{
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fprintf(stderr, "test_normalize failed a.dims=%d a=(%d %d %d %d) across_spatial=%d across_channel=%d channel_shared=%d eps=%f eps_mode=%d\n", a.dims, a.w, a.h, a.d, a.c, across_spatial, across_channel, channel_shared, eps, eps_mode);
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}
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return ret;
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}
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static int test_normalize_0()
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{
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ncnn::Mat a = RandomMat(6, 4, 2);
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ncnn::Mat b = RandomMat(5, 7, 8);
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return 0
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|| test_normalize(a, 1, 0, 0, 0.01f, 0)
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|| test_normalize(a, 1, 0, 0, 0.001f, 1)
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|| test_normalize(a, 1, 0, 0, 0.002f, 2)
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|| test_normalize(a, 1, 0, 1, 0.01f, 0)
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|| test_normalize(a, 1, 0, 1, 0.001f, 1)
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|| test_normalize(a, 1, 0, 1, 0.002f, 2)
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|| test_normalize(b, 1, 0, 0, 0.01f, 0)
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|| test_normalize(b, 1, 0, 0, 0.001f, 1)
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|| test_normalize(b, 1, 0, 0, 0.002f, 2)
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|| test_normalize(b, 1, 0, 1, 0.01f, 0)
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|| test_normalize(b, 1, 0, 1, 0.001f, 1)
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|| test_normalize(b, 1, 0, 1, 0.002f, 2);
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}
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static int test_normalize_1()
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{
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ncnn::Mat a = RandomMat(5, 6, 3);
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ncnn::Mat b = RandomMat(3, 4, 8);
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return 0
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|| test_normalize(a, 0, 1, 0, 0.01f, 0)
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|| test_normalize(a, 0, 1, 0, 0.001f, 1)
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|| test_normalize(a, 0, 1, 0, 0.002f, 2)
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|| test_normalize(a, 0, 1, 1, 0.01f, 0)
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|| test_normalize(a, 0, 1, 1, 0.001f, 1)
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|| test_normalize(a, 0, 1, 1, 0.002f, 2)
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|| test_normalize(b, 0, 1, 0, 0.01f, 0)
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|| test_normalize(b, 0, 1, 0, 0.001f, 1)
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|| test_normalize(b, 0, 1, 0, 0.002f, 2)
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|| test_normalize(b, 0, 1, 1, 0.01f, 0)
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|| test_normalize(b, 0, 1, 1, 0.001f, 1)
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|| test_normalize(b, 0, 1, 1, 0.002f, 2);
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}
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static int test_normalize_2()
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{
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ncnn::Mat a = RandomMat(2, 3, 5);
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ncnn::Mat b = RandomMat(4, 6, 8);
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return 0
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|| test_normalize(a, 1, 1, 0, 0.01f, 0)
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|| test_normalize(a, 1, 1, 0, 0.001f, 1)
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|| test_normalize(a, 1, 1, 0, 0.002f, 2)
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|| test_normalize(a, 1, 1, 1, 0.01f, 0)
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|| test_normalize(a, 1, 1, 1, 0.001f, 1)
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|| test_normalize(a, 1, 1, 1, 0.002f, 2)
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|| test_normalize(b, 1, 1, 0, 0.01f, 0)
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|| test_normalize(b, 1, 1, 0, 0.001f, 1)
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|| test_normalize(b, 1, 1, 0, 0.002f, 2)
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|| test_normalize(b, 1, 1, 1, 0.01f, 0)
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|| test_normalize(b, 1, 1, 1, 0.001f, 1)
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|| test_normalize(b, 1, 1, 1, 0.002f, 2);
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}
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static int test_normalize_3()
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{
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ncnn::Mat a = RandomMat(5, 4, 3, 3);
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ncnn::Mat b = RandomMat(3, 3, 2, 8);
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return 0
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|| test_normalize(a, 1, 0, 0, 0.01f, 0)
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|| test_normalize(a, 1, 0, 1, 0.001f, 1)
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|| test_normalize(b, 0, 1, 0, 0.002f, 2)
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|| test_normalize(b, 0, 1, 1, 0.01f, 0)
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|| test_normalize(a, 1, 1, 0, 0.001f, 1)
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|| test_normalize(b, 1, 1, 1, 0.002f, 2);
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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_normalize_0()
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|| test_normalize_1()
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|| test_normalize_2()
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|| test_normalize_3();
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}
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