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https://github.com/Tencent/ncnn.git
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* runtime cpu dispatch * force thread one * disable openmp for coverage * simplify test layer * print NCNN_TARGET_ARCH * less ci build variants * weight fp16 storage option * test convdw int8 * apple a12 a13 * ncnn_add_layer ncnn_add_shader cmake macro
194 lines
6.3 KiB
C++
194 lines
6.3 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/crop.h"
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#include "testutil.h"
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static int test_crop(const ncnn::Mat& a, int woffset, int hoffset, int coffset, int outw, int outh, int outc, int woffset2, int hoffset2, int coffset2)
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{
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ncnn::ParamDict pd;
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pd.set(0, woffset); // woffset
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pd.set(1, hoffset); // hoffset
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pd.set(2, coffset); // coffset
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pd.set(3, outw); // outw
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pd.set(4, outh); // outh
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pd.set(5, outc); // outc
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pd.set(6, woffset2); // woffset2
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pd.set(7, hoffset2); // hoffset2
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pd.set(8, coffset2); // coffset2
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std::vector<ncnn::Mat> weights(0);
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int ret = test_layer<ncnn::Crop>("Crop", pd, weights, a);
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if (ret != 0)
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{
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fprintf(stderr, "test_crop failed a.dims=%d a=(%d %d %d) woffset=%d hoffset=%d coffset=%d outw=%d outh=%d outc=%d woffset2=%d hoffset2=%d coffset2=%d\n", a.dims, a.w, a.h, a.c, woffset, hoffset, coffset, outw, outh, outc, woffset2, hoffset2, coffset2);
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}
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return ret;
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}
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static ncnn::Mat IntArrayMat(int a0)
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{
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ncnn::Mat m(1);
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int* p = m;
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p[0] = a0;
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return m;
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}
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static ncnn::Mat IntArrayMat(int a0, int a1)
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{
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ncnn::Mat m(2);
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int* p = m;
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p[0] = a0;
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p[1] = a1;
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return m;
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}
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static ncnn::Mat IntArrayMat(int a0, int a1, int a2)
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{
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ncnn::Mat m(3);
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int* p = m;
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p[0] = a0;
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p[1] = a1;
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p[2] = a2;
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return m;
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}
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static void print_int_array(const ncnn::Mat& a)
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{
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const int* pa = a;
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fprintf(stderr, "[");
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for (int i = 0; i < a.w; i++)
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{
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fprintf(stderr, " %d", pa[i]);
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}
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fprintf(stderr, " ]");
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}
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static int test_crop(const ncnn::Mat& a, const ncnn::Mat& starts, const ncnn::Mat& ends, const ncnn::Mat& axes)
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{
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ncnn::ParamDict pd;
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pd.set(9, starts); // starts
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pd.set(10, ends); // ends
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pd.set(11, axes); // axes
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std::vector<ncnn::Mat> weights(0);
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int ret = test_layer<ncnn::Crop>("Crop", pd, weights, a);
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if (ret != 0)
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{
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fprintf(stderr, "test_crop failed a.dims=%d a=(%d %d %d)", a.dims, a.w, a.h, a.c);
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fprintf(stderr, " starts=");
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print_int_array(starts);
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fprintf(stderr, " ends=");
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print_int_array(ends);
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fprintf(stderr, " axes=");
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print_int_array(axes);
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fprintf(stderr, "\n");
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}
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return ret;
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}
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static int test_crop_0()
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{
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ncnn::Mat a = RandomMat(13, 11, 16);
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return 0
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|| test_crop(a, 0, 0, 0, -233, -233, -233, 0, 0, 0)
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|| test_crop(a, 0, 3, 0, 10, -233, -233, 0, 0, 0)
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|| test_crop(a, 5, 0, 0, -233, 6, -233, 0, 0, 0)
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|| test_crop(a, 5, 3, 0, -233, -233, 12, 0, 0, 0)
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|| test_crop(a, 0, 3, 4, 7, -233, 8, 0, 0, 0)
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|| test_crop(a, 5, 0, 5, 4, -233, 4, 0, 0, 0)
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|| test_crop(a, 5, 3, 6, 2, 7, 9, 0, 0, 0)
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|| test_crop(a, 0, 3, 4, -233, 4, 5, 0, 0, 0)
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|| test_crop(a, 5, 0, 5, 6, 6, 8, 0, 0, 0)
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|| test_crop(a, 5, 3, 6, 4, 4, 4, 0, 0, 0);
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}
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static int test_crop_1()
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{
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ncnn::Mat a = RandomMat(13, 11, 16);
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return 0
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|| test_crop(a, 0, 0, 0, -233, -233, -233, 3, 4, 6)
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|| test_crop(a, 0, 3, 0, 10, -233, -233, 0, 3, 4)
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|| test_crop(a, 5, 0, 0, -233, 6, -233, 5, 0, 2)
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|| test_crop(a, 5, 3, 0, -233, -233, 12, 2, 1, 1)
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|| test_crop(a, 0, 3, 4, 7, -233, 8, 3, 4, 4)
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|| test_crop(a, 5, 0, 5, 4, -233, 4, 0, 3, 0)
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|| test_crop(a, 5, 3, 6, 2, 7, 9, 1, 2, 3)
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|| test_crop(a, 0, 3, 4, -233, 4, 5, 3, 2, 1);
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}
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static int test_crop_2()
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{
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ncnn::Mat a = RandomMat(13, 11, 17);
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return 0
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|| test_crop(a, 0, 0, 0, -233, -233, -233, 3, 4, 6)
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|| test_crop(a, 0, 3, 0, 10, -233, -233, 0, 3, 4)
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|| test_crop(a, 5, 0, 0, -233, 6, -233, 5, 0, 2)
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|| test_crop(a, 5, 3, 0, -233, -233, 12, 2, 1, 1)
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|| test_crop(a, 0, 3, 4, 7, -233, 8, 3, 4, 4)
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|| test_crop(a, 5, 0, 5, 4, -233, 4, 0, 3, 0)
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|| test_crop(a, 5, 3, 6, 2, 7, 9, 1, 2, 3)
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|| test_crop(a, 0, 3, 4, -233, 4, 5, 3, 2, 1);
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}
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static int test_crop_3()
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{
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ncnn::Mat a = RandomMat(13, 11, 16);
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return 0
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|| test_crop(a, IntArrayMat(0, 0, 0), IntArrayMat(100, 100, 100), IntArrayMat(0, 1, 2))
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|| test_crop(a, IntArrayMat(4), IntArrayMat(8), IntArrayMat(0))
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|| test_crop(a, IntArrayMat(2), IntArrayMat(7), IntArrayMat(1))
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|| test_crop(a, IntArrayMat(3), IntArrayMat(5), IntArrayMat(2))
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|| test_crop(a, IntArrayMat(2, 1), IntArrayMat(4, -2), IntArrayMat(0, 1))
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|| test_crop(a, IntArrayMat(1, 4), IntArrayMat(-5, 7), IntArrayMat(1, -3))
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|| test_crop(a, IntArrayMat(2, 1), IntArrayMat(4, -2), IntArrayMat(-1, -2))
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|| test_crop(a, IntArrayMat(1, 2, 3), IntArrayMat(-3, -2, -1), IntArrayMat(-3, -2, -1));
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}
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static int test_crop_4()
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{
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ncnn::Mat a = RandomMat(13, 11, 17);
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return 0
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|| test_crop(a, IntArrayMat(0, 0, 0), IntArrayMat(100, 100, 100), IntArrayMat(0, 1, 2))
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|| test_crop(a, IntArrayMat(4), IntArrayMat(8), IntArrayMat(0))
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|| test_crop(a, IntArrayMat(2), IntArrayMat(7), IntArrayMat(1))
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|| test_crop(a, IntArrayMat(3), IntArrayMat(5), IntArrayMat(2))
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|| test_crop(a, IntArrayMat(2, 1), IntArrayMat(4, -2), IntArrayMat(0, 1))
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|| test_crop(a, IntArrayMat(1, 4), IntArrayMat(-5, 7), IntArrayMat(1, -3))
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|| test_crop(a, IntArrayMat(2, 1), IntArrayMat(4, -2), IntArrayMat(-1, -2))
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|| test_crop(a, IntArrayMat(1, 2, 3), IntArrayMat(-3, -2, -1), IntArrayMat(-3, -2, -1));
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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_crop_0()
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|| test_crop_1()
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|| test_crop_2()
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|| test_crop_3()
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|| test_crop_4();
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}
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