mirror of
https://github.com/Tencent/ncnn.git
synced 2026-10-22 16:55:13 +08:00
nihui
61 lines
1.6 KiB
C++
61 lines
1.6 KiB
C++
// Tencent is pleased to support the open source community by making ncnn available.
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//
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// Copyright (C) 2024 THL A29 Limited, a Tencent company. All rights reserved.
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//
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// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
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// in compliance with the License. You may obtain a copy of the License at
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//
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// https://opensource.org/licenses/BSD-3-Clause
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//
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// Unless required by applicable law or agreed to in writing, software distributed
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// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
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// CONDITIONS OF ANY KIND, either express or implied. See the License for the
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// specific language governing permissions and limitations under the License.
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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) axis=%d\n", a.dims, a.w, a.h, 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(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_1()
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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_2()
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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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}
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