Merge pull request #23501 from Abdurrahheem:additional_lstm_tests

Added LSTM and GRU tests for various batch and input length sizes #23501

Added tests with various sequence length and batch sizes
Test data: https://github.com/opencv/opencv_extra/pull/1057

### 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
- [ ] 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_onnx_importer.cpp

@@ -1287,6 +1287,48 @@ TEST_P(Test_ONNX_layers, GRU)
     testONNXModels("gru", npy, 0, 0, false, false);
 }
 
+TEST_P(Test_ONNX_layers, gru_cell_batchsize_50_seqlen_1)
+{
+#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
+    // IE exception: Node GRU_22 was not assigned on any pointed device
+    if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
+        applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16,
+            CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION
+        );
+#endif
+    if(backend == DNN_BACKEND_CUDA)
+        applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA);
+    testONNXModels("gru_cell_batchsize_50_seqlen_1", npy, 0, 0, false, false);
+}
+
+TEST_P(Test_ONNX_layers, gru_cell_batchsize_5_seqlen_5)
+{
+#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
+    // IE exception: Node GRU_22 was not assigned on any pointed device
+    if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
+        applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16,
+            CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION
+        );
+#endif
+    if(backend == DNN_BACKEND_CUDA)
+        applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA);
+    testONNXModels("gru_cell_batchsize_5_seqlen_5", npy, 0, 0, false, false);
+}
+
+TEST_P(Test_ONNX_layers, gru_cell_batchsize_1_seqlen_50)
+{
+#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
+    // IE exception: Node GRU_22 was not assigned on any pointed device
+    if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
+        applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16,
+            CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION
+        );
+#endif
+    if(backend == DNN_BACKEND_CUDA)
+        applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA);
+    testONNXModels("gru_cell_batchsize_1_seqlen_50", npy, 0, 0, false, false);
+}
+
 TEST_P(Test_ONNX_layers, GRU_bidirectional)
 {
     testONNXModels("gru_bi", npy, 0, 0, false, false);
@@ -1323,6 +1365,27 @@ TEST_P(Test_ONNX_layers, LSTM_cell_with_peepholes)
     testONNXModels("lstm_cell_with_peepholes", npy, 0, 0, false, false);
 }
 
+TEST_P(Test_ONNX_layers, LSTM_cell_batchsize_50_seqlen_1)
+{
+    if(backend == DNN_BACKEND_CUDA)
+        applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA);
+    testONNXModels("lstm_cell_batchsize_50_seqlen_1", npy, 0, 0, false, false);
+}
+
+TEST_P(Test_ONNX_layers, LSTM_cell_batchsize_1_seqlen_50)
+{
+    if(backend == DNN_BACKEND_CUDA)
+        applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA);
+    testONNXModels("lstm_cell_batchsize_1_seqlen_50", npy, 0, 0, false, false);
+}
+
+TEST_P(Test_ONNX_layers, LSTM_cell_batchsize_5_seqlen_5)
+{
+    if(backend == DNN_BACKEND_CUDA)
+        applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA);
+    testONNXModels("lstm_cell_batchsize_5_seqlen_5", npy, 0, 0, false, false);
+}
+
 TEST_P(Test_ONNX_layers, Pad2d_Unfused)
 {
     testONNXModels("ReflectionPad2d");