Pull Request Readiness Checklist

All test data and models for PR are located #1190

This PR fixes issue reised when importing batched vanilla Attention layer from PyTorch via ONNX. Currently batched version of Attention layer in PyTorch has unflatten operation inside. unflatten operation causes issue in reshape layer (see the Reshape_2 in the graph below) due to incorrect output of slice layer. This PR particularly fixes slice and concat layers to handle unflatten operation.

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

• I agree to contribute to the project under Apache 2 License.
• 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
• The PR is proposed to the proper branch
• There is a reference to the original bug report and related work
• There is accuracy test, performance test and test data in opencv_extra repository, if applicable
  Patch to opencv_extra has the same branch name.
• The feature is well documented and sample code can be built with the project CMake