96 lines
2.6 KiB
C++
96 lines
2.6 KiB
C++
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// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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#include "perf_precomp.hpp"
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#include <opencv2/dnn/shape_utils.hpp>
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namespace opencv_test {
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struct Layer_Slice : public TestBaseWithParam<tuple<Backend, Target> >
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{
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template<int DIMS>
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void test_slice(const int* inputShape, const int* begin, const int* end)
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{
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int backendId = get<0>(GetParam());
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int targetId = get<1>(GetParam());
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Mat input(DIMS, inputShape, CV_32FC1, Scalar::all(0));
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for (int i = 0; i < (int)input.total(); ++i)
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input.ptr<float>()[i] = (float)(i & 4095);
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std::vector<Range> range(DIMS);
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for (int i = 0; i < DIMS; ++i)
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range[i] = Range(begin[i], end[i]);
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Net net;
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LayerParams lp;
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lp.type = "Slice";
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lp.name = "testLayer";
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lp.set("begin", DictValue::arrayInt<int*>((int*)&begin[0], DIMS));
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lp.set("end", DictValue::arrayInt<int*>((int*)&end[0], DIMS));
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net.addLayerToPrev(lp.name, lp.type, lp);
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// warmup
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{
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net.setInput(input);
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net.setPreferableBackend(backendId);
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net.setPreferableTarget(targetId);
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Mat out = net.forward();
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EXPECT_GT(cv::norm(out, NORM_INF), 0);
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#if 0
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//normAssert(out, input(range));
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cout << input(range).clone().reshape(1, 1) << endl;
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cout << out.reshape(1, 1) << endl;
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#endif
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}
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TEST_CYCLE()
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{
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Mat res = net.forward();
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}
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SANITY_CHECK_NOTHING();
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}
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};
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PERF_TEST_P_(Layer_Slice, YOLOv4_tiny_1)
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{
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const int inputShape[4] = {1, 64, 104, 104};
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const int begin[] = {0, 32, 0, 0};
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const int end[] = {1, 64, 104, 104};
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test_slice<4>(inputShape, begin, end);
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}
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PERF_TEST_P_(Layer_Slice, YOLOv4_tiny_2)
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{
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const int inputShape[4] = {1, 128, 52, 52};
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const int begin[] = {0, 64, 0, 0};
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const int end[] = {1, 128, 52, 52};
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test_slice<4>(inputShape, begin, end);
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}
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PERF_TEST_P_(Layer_Slice, YOLOv4_tiny_3)
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{
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const int inputShape[4] = {1, 256, 26, 26};
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const int begin[] = {0, 128, 0, 0};
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const int end[] = {1, 256, 26, 26};
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test_slice<4>(inputShape, begin, end);
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}
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PERF_TEST_P_(Layer_Slice, FastNeuralStyle_eccv16)
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{
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const int inputShape[4] = {1, 128, 80, 100};
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const int begin[] = {0, 0, 2, 2};
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const int end[] = {1, 128, 76, 96};
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test_slice<4>(inputShape, begin, end);
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}
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INSTANTIATE_TEST_CASE_P(/**/, Layer_Slice, dnnBackendsAndTargets(false, false));
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} // namespace
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