718c41634f
1.项目后端整体迁移至PaddleOCR-NCNN算法，已通过基本的兼容性测试 2.工程改为使用CMake组织，后续为了更好地兼容第三方库，不再提供QMake工程 3.重整权利声明文件，重整代码工程，确保最小化侵权风险 Log: 切换后端至PaddleOCR-NCNN，切换工程为CMake Change-Id: I4d5d2c5d37505a4a24b389b1a4c5d12f17bfa38c
111 lines
3.9 KiB
C++
111 lines
3.9 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) 2020 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 "layer/normalize.h"
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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<ncnn::Normalize>("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) across_spatial=%d across_channel=%d channel_shared=%d eps=%f eps_mode=%d\n", a.dims, a.w, a.h, 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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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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}
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