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Open Source Computer Vision Library
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153 lines
5.5 KiB
153 lines
5.5 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 "test_precomp.hpp" |
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namespace opencv_test { namespace { |
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class Test_Graph_Simplifier : public ::testing::Test { |
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public: |
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bool required; |
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Test_Graph_Simplifier() : required(true) {} |
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void test_conformance(const std::string &basename, const std::string &expected_layer) { |
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test(basename + std::string("/model"), std::vector<std::string>{expected_layer}, std::string("dnn/onnx/conformance/node/")); |
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} |
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void test(const std::string &basename, const std::string &expected_layer) { |
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test(basename, std::vector<std::string>{expected_layer}); |
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} |
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void test(const std::string &basename, const std::vector<std::string> &expected_layers, const std::string &model_path_prefix = std::string("dnn/onnx/models/")) { |
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std::string model_path = findDataFile(model_path_prefix + basename + std::string(".onnx"), required); |
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auto net = readNet(model_path); |
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std::vector<std::string> layers; |
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net.getLayerTypes(layers); |
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// remove Const, Identity (output layer), __NetInputLayer__ (input layer) |
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layers.erase(std::remove_if(layers.begin(), layers.end(), [] (const std::string l) { return l == "Const" || l == "Identity" || l == "__NetInputLayer__"; }), layers.end()); |
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EXPECT_EQ(layers, expected_layers); |
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} |
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}; |
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TEST_F(Test_Graph_Simplifier, GeluSubGraph) { |
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test("gelu", "Gelu"); |
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test("bias_gelu", std::vector<std::string>{"Gelu", "NaryEltwise"}); |
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} |
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TEST_F(Test_Graph_Simplifier, GeluApproximationSubGraph) { |
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test("gelu_approximation", "GeluApproximation"); |
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} |
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TEST_F(Test_Graph_Simplifier, LayerNormSubGraph) { |
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test("layer_norm_expanded", "LayerNormalization"); |
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test("layer_norm_expanded_with_initializers", "LayerNormalization"); |
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} |
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TEST_F(Test_Graph_Simplifier, LayerNormNoFusionSubGraph) { |
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test("layer_norm_no_fusion", std::vector<std::string>{"NaryEltwise", "Reduce", "Sqrt"}); |
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} |
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TEST_F(Test_Graph_Simplifier, ResizeSubgraph) { |
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/* Test for 6 subgraphs: |
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- GatherCastSubgraph |
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- MulCastSubgraph |
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- UpsampleSubgraph |
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- ResizeSubgraph1 |
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- ResizeSubgraph2 |
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- ResizeSubgraph3 |
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*/ |
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test("upsample_unfused_torch1.2", std::vector<std::string>{"BatchNorm", "Resize"}); |
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test("resize_nearest_unfused_opset11_torch1.3", std::vector<std::string>{"BatchNorm", "Convolution", "Resize"}); |
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test("resize_nearest_unfused_opset11_torch1.4", std::vector<std::string>{"BatchNorm", "Convolution", "Resize"}); |
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test("upsample_unfused_opset9_torch1.4", std::vector<std::string>{"BatchNorm", "Convolution", "Resize"}); |
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test("two_resizes_with_shared_subgraphs", std::vector<std::string>{"NaryEltwise", "Resize"}); |
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} |
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TEST_F(Test_Graph_Simplifier, SoftmaxSubgraph) { |
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/* Test for 3 subgraphs |
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- SoftMaxSubgraph |
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- SoftMaxSubgraph2 (conformance) |
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- LogSoftMaxSubgraph (conformance) |
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*/ |
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test("softmax_unfused", "Softmax"); |
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test_conformance("test_softmax_example_expanded", "Softmax"); |
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test_conformance("test_softmax_axis_2_expanded", "Softmax"); |
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test_conformance("test_softmax_default_axis_expanded", "Softmax"); |
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test_conformance("test_softmax_axis_0_expanded", "Softmax"); |
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test_conformance("test_softmax_axis_1_expanded", "Softmax"); |
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test_conformance("test_softmax_large_number_expanded", "Softmax"); |
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test_conformance("test_softmax_negative_axis_expanded", "Softmax"); |
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test_conformance("test_logsoftmax_axis_2_expanded", "Softmax"); |
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test_conformance("test_logsoftmax_example_1_expanded", "Softmax"); |
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test_conformance("test_logsoftmax_negative_axis_expanded", "Softmax"); |
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test_conformance("test_logsoftmax_axis_0_expanded", "Softmax"); |
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test_conformance("test_logsoftmax_axis_1_expanded", "Softmax"); |
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test_conformance("test_logsoftmax_large_number_expanded", "Softmax"); |
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test_conformance("test_logsoftmax_default_axis_expanded", "Softmax"); |
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} |
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TEST_F(Test_Graph_Simplifier, HardSwishSubgraph) { |
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test_conformance("test_hardswish_expanded", "HardSwish"); |
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} |
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TEST_F(Test_Graph_Simplifier, CeluSubgraph) { |
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test_conformance("test_celu_expanded", "Celu"); |
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} |
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TEST_F(Test_Graph_Simplifier, NormalizeSubgraph) { |
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/* Test for 6 subgraphs |
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- NormalizeSubgraph1 |
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- NormalizeSubgraph2 |
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- NormalizeSubgraph2_2 |
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- NormalizeSubgraph3 |
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- NormalizeSubgraph4 |
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- NormalizeSubgraph5 |
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*/ |
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test("reduceL2_subgraph_2", "Normalize"); |
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test("reduceL2_subgraph", "Normalize"); |
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test("normalize_fusion", "Normalize"); |
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} |
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TEST_F(Test_Graph_Simplifier, BatchNormalizationSubgraph) { |
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/* Test for 2 subgraphs |
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- BatchNormalizationSubgraph1 |
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- BatchNormalizationSubgraph2 |
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*/ |
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test("frozenBatchNorm2d", "BatchNorm"); |
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test("batch_norm_subgraph", "BatchNorm"); |
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} |
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TEST_F(Test_Graph_Simplifier, ExpandSubgraph) { |
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test("expand_neg_batch", "Expand"); |
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} |
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TEST_F(Test_Graph_Simplifier, MishSubgraph) { |
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/* Test for 2 subgraphs |
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- SoftplusSubgraph |
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- MishSubgraph |
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*/ |
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test("mish_no_softplus", "Mish"); |
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test("mish", "Mish"); |
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} |
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TEST_F(Test_Graph_Simplifier, AttentionSubgraph) { |
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/* Test for 2 subgraphs |
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- AttentionSubgraph |
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- AttentionSingleHeadSubgraph |
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*/ |
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test("attention", "Attention"); |
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test("attention_single_head", "Attention"); |
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} |
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TEST_F(Test_Graph_Simplifier, BiasedMatMulSubgraph) { |
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/* Test for 1 subgraphs |
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- BiasedMatMulSubgraph |
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*/ |
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test("biased_matmul", "MatMul"); |
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} |
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}}
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