Merge pull request #24500 from fengyuentau:test_layer_fusion

dnn (onnx): add subgraph fusion tests #24500

### 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
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake

modules/dnn/test/test_graph_simplifier.cpp

@@ -0,0 +1,131 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+#include "test_precomp.hpp"
+
+namespace opencv_test { namespace {
+
+class Test_Graph_Simplifier : public ::testing::Test {
+ public:
+    bool required;
+
+    Test_Graph_Simplifier() : required(true) {}
+
+    void test_conformance(const std::string &basename, const std::string &expected_layer) {
+        test(basename + std::string("/model"), std::vector<std::string>{expected_layer}, std::string("dnn/onnx/conformance/node/"));
+    }
+
+    void test(const std::string &basename, const std::string &expected_layer) {
+        test(basename, std::vector<std::string>{expected_layer});
+    }
+
+    void test(const std::string &basename, const std::vector<std::string> &expected_layers, const std::string &model_path_prefix = std::string("dnn/onnx/models/")) {
+        std::string model_path = findDataFile(model_path_prefix + basename + std::string(".onnx"), required);
+        auto net = readNet(model_path);
+        std::vector<std::string> layers;
+        net.getLayerTypes(layers);
+
+        // remove Const, Identity (output layer), __NetInputLayer__ (input layer)
+        layers.erase(std::remove_if(layers.begin(), layers.end(), [] (const std::string l) { return l == "Const" || l == "Identity" || l == "__NetInputLayer__"; }), layers.end());
+
+        EXPECT_EQ(layers, expected_layers);
+    }
+};
+
+TEST_F(Test_Graph_Simplifier, GeluSubGraph) {
+    test("gelu", "Gelu");
+}
+
+TEST_F(Test_Graph_Simplifier, GeluApproximationSubGraph) {
+    test("gelu_approximation", "GeluApproximation");
+}
+
+TEST_F(Test_Graph_Simplifier, LayerNormSubGraph) {
+    test("layer_norm_expanded", "LayerNormalization");
+}
+
+TEST_F(Test_Graph_Simplifier, ResizeSubgraph) {
+    /* Test for 6 subgraphs:
+        - GatherCastSubgraph
+        - MulCastSubgraph
+        - UpsampleSubgraph
+        - ResizeSubgraph1
+        - ResizeSubgraph2
+        - ResizeSubgraph3
+    */
+    test("upsample_unfused_torch1.2", std::vector<std::string>{"BatchNorm", "Resize"});
+    test("resize_nearest_unfused_opset11_torch1.3", std::vector<std::string>{"BatchNorm", "Convolution", "Resize"});
+    test("resize_nearest_unfused_opset11_torch1.4", std::vector<std::string>{"BatchNorm", "Convolution", "Resize"});
+    test("upsample_unfused_opset9_torch1.4", std::vector<std::string>{"BatchNorm", "Convolution", "Resize"});
+    test("two_resizes_with_shared_subgraphs", std::vector<std::string>{"NaryEltwise", "Resize"});
+}
+
+TEST_F(Test_Graph_Simplifier, SoftmaxSubgraph) {
+    /* Test for 3 subgraphs
+        - SoftMaxSubgraph
+        - SoftMaxSubgraph2 (conformance)
+        - LogSoftMaxSubgraph (conformance)
+    */
+    test("softmax_unfused", "Softmax");
+    test_conformance("test_softmax_example_expanded", "Softmax");
+    test_conformance("test_softmax_axis_2_expanded", "Softmax");
+    test_conformance("test_softmax_default_axis_expanded", "Softmax");
+    test_conformance("test_softmax_axis_0_expanded", "Softmax");
+    test_conformance("test_softmax_axis_1_expanded", "Softmax");
+    test_conformance("test_softmax_large_number_expanded", "Softmax");
+    test_conformance("test_softmax_negative_axis_expanded", "Softmax");
+    test_conformance("test_logsoftmax_axis_2_expanded", "Softmax");
+    test_conformance("test_logsoftmax_example_1_expanded", "Softmax");
+    test_conformance("test_logsoftmax_negative_axis_expanded", "Softmax");
+    test_conformance("test_logsoftmax_axis_0_expanded", "Softmax");
+    test_conformance("test_logsoftmax_axis_1_expanded", "Softmax");
+    test_conformance("test_logsoftmax_large_number_expanded", "Softmax");
+    test_conformance("test_logsoftmax_default_axis_expanded", "Softmax");
+}
+
+TEST_F(Test_Graph_Simplifier, HardSwishSubgraph) {
+    test_conformance("test_hardswish_expanded", "HardSwish");
+}
+
+TEST_F(Test_Graph_Simplifier, CeluSubgraph) {
+    test_conformance("test_celu_expanded", "Celu");
+}
+
+TEST_F(Test_Graph_Simplifier, NormalizeSubgraph) {
+    /* Test for 6 subgraphs
+        - NormalizeSubgraph1
+        - NormalizeSubgraph2
+        - NormalizeSubgraph2_2
+        - NormalizeSubgraph3
+        - NormalizeSubgraph4
+        - NormalizeSubgraph5
+    */
+    test("reduceL2_subgraph_2", "Normalize");
+    test("reduceL2_subgraph", "Normalize");
+    test("normalize_fusion", "Normalize");
+}
+
+TEST_F(Test_Graph_Simplifier, BatchNormalizationSubgraph) {
+    /* Test for 2 subgraphs
+        - BatchNormalizationSubgraph1
+        - BatchNormalizationSubgraph2
+    */
+    test("frozenBatchNorm2d", "BatchNorm");
+    test("batch_norm_subgraph", "BatchNorm");
+}
+
+TEST_F(Test_Graph_Simplifier, ExpandSubgraph) {
+    test("expand_neg_batch", "Expand");
+}
+
+TEST_F(Test_Graph_Simplifier, MishSubgraph) {
+    /* Test for 2 subgraphs
+        - SoftplusSubgraph
+        - MishSubgraph
+    */
+    test("mish_no_softplus", "Mish");
+    test("mish", "Mish");
+}
+
+}}