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Open Source Computer Vision Library
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109 lines
3.4 KiB
109 lines
3.4 KiB
// 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 EinsumParams { |
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int inputSize; |
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int outputSize; |
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std::string equation; |
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std::vector<MatShape> einsumInpShapes; |
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EinsumParams(std::string equation_, std::vector<MatShape> einsumInpShapes_ = std::vector<MatShape>()) |
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{ |
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inputSize = einsumInpShapes_.size(); |
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equation = equation_; |
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einsumInpShapes = einsumInpShapes_; |
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} |
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}; |
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static inline void PrintTo(const EinsumParams& params, ::std::ostream* os) { |
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(*os) << "Equation=" << params.equation << " "; |
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(*os) << "InputShape={"; |
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for(int i = 0; i < params.einsumInpShapes.size(); i++) |
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{ |
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(*os) << "{"; |
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for(int j = 0; j < params.einsumInpShapes[i].size(); j++) |
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{ |
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(*os) << params.einsumInpShapes[i][j] << ((j < params.einsumInpShapes[i].size() - 1) ? ", " : ""); |
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} |
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(*os) << ((i < params.einsumInpShapes.size() - 1) ? "}, " : "}"); |
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} |
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(*os) << "}"; |
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} |
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// test cases |
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static const EinsumParams testEinsumConfigs[] = { |
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// TODO: Add tests with one input after ellips merge |
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{"ij, jk -> ik", {{2, 3}, {3, 2}}}, |
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{"ij, jk -> ik", {{20, 30}, {30, 20}}}, |
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{"ij, jk -> ik", {{113, 127}, {127, 113}}}, |
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{"imkj, injs -> imnks", {{1, 4, 7, 9}, {1, 5, 9, 8}}}, |
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{"imkj, injs -> imnks", {{1, 4, 70, 90}, {1, 5, 90, 80}}}, |
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{"imkj, injs -> imnks", {{1, 4, 73, 91}, {1, 5, 91, 57}}}, |
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{"ij -> i", {{30, 40}}}, |
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{"ij -> i", {{113, 374}}}, |
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{"...ij -> ...i", {{30, 40}}}, |
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{"...ij -> ...i", {{113, 374}}}, |
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{"...ij, ...jk -> ...ik", {{40, 50}, {50, 80}}}, |
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{"...ij, ...jk -> ...ik", {{47, 51}, {51, 83}}}, |
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}; |
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class Layer_Einsum: public TestBaseWithParam<EinsumParams> {}; |
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PERF_TEST_P_(Layer_Einsum, einsum) { |
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const EinsumParams& params = GetParam(); |
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LayerParams lp; |
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lp.type = "Einsum"; |
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lp.name = "testEinsum"; |
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lp.set("equation", params.equation); |
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lp.set("inputSize", params.inputSize); |
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lp.set("outputSize", 1); |
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CV_CheckFalse(params.einsumInpShapes.empty(), "ERROR no inputs shapes provided"); |
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for (int i = 0; i < params.einsumInpShapes.size(); i++) { |
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lp.set("inputShapes" + cv::format("%d", i), DictValue::arrayInt(params.einsumInpShapes[i].begin(), params.einsumInpShapes[i].size())); |
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} |
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Net net; |
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std::vector<Mat> inputs; |
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std::vector<std::string> input_names; |
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int id = net.addLayer(lp.name, lp.type, lp); |
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for (int i = 0; i < params.inputSize; ++i) { |
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// create inputs |
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inputs.emplace_back(Mat(params.einsumInpShapes[i].size(), params.einsumInpShapes[i].data(), CV_32FC1)); |
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// connect each input to the layer |
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net.connect(0, i, id, i); |
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// create input names dynamically, assuming input naming follows a consistent pattern |
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input_names.emplace_back("input" + std::to_string(i + 1)); |
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} |
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//warm up |
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std::vector<Mat> outputs; |
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net.setInputsNames(input_names); |
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for (int i = 0; i < input_names.size(); i++){ |
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net.setInput(inputs[i], input_names[i]); |
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} |
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net.forward(outputs, "testEinsum"); |
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TEST_CYCLE() |
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{ |
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net.forward(outputs, "testEinsum"); |
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} |
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SANITY_CHECK_NOTHING(); |
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} |
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INSTANTIATE_TEST_CASE_P(/**/, Layer_Einsum, testing::ValuesIn(testEinsumConfigs)); |
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}; //namespace
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