mirror of
https://github.com/Tencent/ncnn.git
synced 2026-10-19 14:32:15 +08:00
102 lines
2.2 KiB
C++
102 lines
2.2 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_softmax(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("Softmax", pd, weights, a);
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if (ret != 0)
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{
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fprintf(stderr, "test_softmax 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_nd(const ncnn::Mat& m)
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{
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const int dims = m.dims;
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for (int i = -dims; i < dims; i++)
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{
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int ret = test_softmax(m, i);
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if (ret != 0)
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return ret;
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}
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return 0;
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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(23, 25, 27, 32);
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ncnn::Mat b = RandomMat(21, 22, 19, 40);
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ncnn::Mat c = RandomMat(24, 27, 29, 28);
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ncnn::Mat d = RandomMat(25, 23, 25, 31);
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return 0
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|| test_softmax_nd(a)
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|| test_softmax_nd(b)
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|| test_softmax_nd(c)
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|| test_softmax_nd(d);
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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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ncnn::Mat b = RandomMat(22, 19, 40);
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ncnn::Mat c = RandomMat(27, 29, 28);
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ncnn::Mat d = RandomMat(23, 25, 31);
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return 0
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|| test_softmax_nd(a)
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|| test_softmax_nd(b)
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|| test_softmax_nd(c)
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|| test_softmax_nd(d);
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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(125, 32);
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ncnn::Mat b = RandomMat(147, 40);
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ncnn::Mat c = RandomMat(127, 28);
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ncnn::Mat d = RandomMat(129, 31);
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return 0
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|| test_softmax_nd(a)
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|| test_softmax_nd(b)
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|| test_softmax_nd(c)
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|| test_softmax_nd(d);
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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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ncnn::Mat b = RandomMat(120);
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ncnn::Mat c = RandomMat(124);
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ncnn::Mat d = RandomMat(127);
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return 0
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|| test_softmax_nd(a)
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|| test_softmax_nd(b)
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|| test_softmax_nd(c)
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|| test_softmax_nd(d);
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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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