Merge pull request #23614 from Abdurrahheem:lstm_layout_attribute

LSTM ONNX Layout Attribute Support #23614 

### Explanation

This PR contains necessary changes to support `layout` attribute. This attributes is present in [ONNX](https://github.com/onnx/onnx/blob/main/docs/Operators.md#lstm) and [Torch](https://pytorch.org/docs/stable/generated/torch.nn.LSTM.html#lstm) (in touch it is name as `batch_first=True`) libraries. When `layout = 1` input to LSTM layer is expected to have batch dimension first -> `[batch_size, sequence_length, features]` vs `layout = 0` - default `[sequence_length, batch_size, features]`

### Test Data

Test data and data generator for PR located here [#1063](https://github.com/opencv/opencv_extra/pull/1063)

### 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

@@ -1393,6 +1393,20 @@ TEST_P(Test_ONNX_layers, LSTM_init_h0_c0)
         applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA);
     testONNXModels("lstm_init_h0_c0", npy, 0, 0, false, false, 3);
 }
+// epsilon is larger because onnx does not match with torch/opencv exactly
+TEST_P(Test_ONNX_layers, LSTM_layout_seq)
+{
+    if(backend == DNN_BACKEND_CUDA)
+        applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA);
+    testONNXModels("lstm_layout_0", npy, 0.005, 0.005, false, false, 3);
+}
+// epsilon is larger because onnx does not match with torch/opencv exactly
+TEST_P(Test_ONNX_layers, LSTM_layout_batch)
+{
+    if(backend == DNN_BACKEND_CUDA)
+        applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA);
+    testONNXModels("lstm_layout_1", npy, 0.005, 0.005, false, false, 3);
+}
 
 TEST_P(Test_ONNX_layers, Pad2d_Unfused)
 {