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https://github.com/opencv/opencv.git
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Hanbin Bae
ca0d47c8e6
optimize(dnn): optimize Slice layer for strided inputs #28447 ## Description This PR optimizes the `SliceLayer` implementation for strided inputs (where `step > 1`). The original implementation used a recursive element-wise copy (`getSliceRecursive`) for any strided slice, which was extremely inefficient. This PR introduces: 1. **Parallelization**: Uses `cv::parallel_for_` to parallelize the outermost dimension of the slice operation. 2. **Memcpy Optimization**: Automatically detects "pseudo-contiguous" blocks in strided slices (e.g., slicing an outer dimension but keeping inner dimensions intact) and uses `std::memcpy` instead of scalar loops. 3. **Refactoring**: Replaces the recursive function with a dedicated `ParallelSlice` loop body. ## Impact Significant performance improvement for strided slice operations (common in detection heads, strided sampling, etc.). **Benchmark Results:** | Test Case | Before (ms) | After (ms) | Speedup | | :--- | :--- | :--- | :--- | | **Strided Axis 0** `[::2, ...]` | 1.10 | **0.02** | **~55x** | | **Strided Axis 2** `[..., ::2]` | 1.10 | **0.06** | **~18x** | | **Contiguous** (Baseline) | 0.10 | 0.10 | 1.0x (Unchanged) | ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [ ] The feature is well documented and sample code can be built with the project CMake
94 lines
2.4 KiB
C++
94 lines
2.4 KiB
C++
// 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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namespace opencv_test {
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struct Layer_Slice : public TestBaseWithParam<tuple<Backend, Target>>
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{
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void test_slice(const std::vector<int>& input_shape, int axis, int begin, int end, int step = 1)
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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 data(input_shape, CV_32FC1);
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randu(data, 0.f, 1.f);
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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("axis", axis);
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std::vector<int> begins(input_shape.size(), 0);
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std::vector<int> ends = input_shape;
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std::vector<int> steps(input_shape.size(), 1);
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begins[axis] = begin;
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ends[axis] = end;
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steps[axis] = step;
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lp.set("begin", DictValue::arrayInt(&begins[0], begins.size()));
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lp.set("end", DictValue::arrayInt(&ends[0], ends.size()));
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if (step != 1) {
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lp.set("steps", DictValue::arrayInt(&steps[0], steps.size()));
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}
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int id = net.addLayerToPrev(lp.name, lp.type, lp);
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net.connect(0, 0, id, 0);
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net.setInputsNames({"data"});
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// warmup
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{
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net.setInput(data, "data");
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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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}
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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, Slice_Contiguous_Axis0)
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{
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test_slice({64, 128, 128}, 0, 10, 54);
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}
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PERF_TEST_P_(Layer_Slice, Slice_Contiguous_Axis2)
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{
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test_slice({64, 128, 128}, 2, 10, 118);
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}
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PERF_TEST_P_(Layer_Slice, Slice_Small_Middle)
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{
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test_slice({32, 64, 32}, 1, 20, 40);
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}
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PERF_TEST_P_(Layer_Slice, Slice_Strided_Axis0_Step2)
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{
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// Strided slice on outer axis.
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// [64, 128, 128] -> [0:64:2, ...]
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test_slice({64, 128, 128}, 0, 0, 64, 2);
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}
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PERF_TEST_P_(Layer_Slice, Slice_Strided_Axis2_Step2)
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{
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// Strided slice on inner axis.
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// [64, 128, 128] -> [..., 0:128:2]
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test_slice({64, 128, 128}, 2, 0, 128, 2);
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}
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INSTANTIATE_TEST_CASE_P(/**/, Layer_Slice, dnnBackendsAndTargets(false, false, true, false, false, false, false, false));
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} // namespace opencv_test
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