mirror of
https://github.com/Tencent/ncnn.git
synced 2026-10-17 04:41:47 +08:00
57 lines
1.2 KiB
C++
57 lines
1.2 KiB
C++
// Copyright 2024 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_softmax_oom(const ncnn::Mat& a, int axis)
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{
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ncnn::ParamDict pd;
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pd.set(0, axis); // axis
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pd.set(1, 1); // fixbug0
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std::vector<ncnn::Mat> weights(0);
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int ret = test_layer_oom("Softmax", pd, weights, a);
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if (ret != 0)
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{
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fprintf(stderr, "test_softmax_oom failed a.dims=%d a=(%d %d %d %d) axis=%d\n", a.dims, a.w, a.h, a.d, a.c, axis);
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}
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return ret;
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}
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static int test_softmax_0()
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{
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ncnn::Mat a = RandomMat(18, 17, 19, 32);
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return test_softmax_oom(a, 0) || test_softmax_oom(a, 1) || test_softmax_oom(a, 2) || test_softmax_oom(a, 3);
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}
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static int test_softmax_1()
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{
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ncnn::Mat a = RandomMat(25, 27, 32);
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return test_softmax_oom(a, 0) || test_softmax_oom(a, 1) || test_softmax_oom(a, 2);
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}
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static int test_softmax_2()
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{
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ncnn::Mat a = RandomMat(25, 32);
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return test_softmax_oom(a, 0) || test_softmax_oom(a, 1);
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}
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static int test_softmax_3()
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{
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ncnn::Mat a = RandomMat(128);
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return test_softmax_oom(a, 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 0
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|| test_softmax_0()
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|| test_softmax_1()
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|| test_softmax_2()
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|| test_softmax_3();
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}
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