Merge pull request #23401 from fengyuentau:fix_cann_layer_support

dnn: Support more operators in CANN backend #23401

This PR adds the support of following layers:

- [x] Sub
- [x] PRelu
- [x] DeConv
- [x] Also warn users if backend is switched back to default if some of the layers are not supported.
- [ ] [Dropped] LSTM: some hacks (adding layers) were introduced which makes it even harder to build the graph for CANN backend.

### 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/src/net_cann.cpp

@@ -117,7 +117,7 @@ void NetImplCann::initBackend(const std::vector<LayerPin>& blobsToKeep_)
             if (ld.id != 0 && !layer->supportBackend(preferableBackend))
             {
                 newWasSupported = false;
-                CV_LOG_INFO(NULL, "DNN/CANN: layer (name=" << ld.name << ", type=" << ld.type << ") is not supported by CANN backend. Going back to CPU backend");
+                CV_LOG_ONCE_WARNING(NULL, "DNN/CANN: layer (name=" << ld.name << ", type=" << ld.type << ") is not supported by CANN backend. Going back to default backend on CPU target");
             }
         }
     }
@@ -202,7 +202,7 @@ void NetImplCann::initBackend(const std::vector<LayerPin>& blobsToKeep_)
             }
 
             CV_LOG_INFO(NULL, "DNN/CANN: converting layer " << ld.name << "@" << ld.type << "@" << ld.id << " to CANN operator");
-            auto backendNode = layer->initCann(ld.inputBlobsWrappers, layerInputNodes); // it's ok if ld.name is empty
+            auto backendNode = layer->initCann(ld.inputBlobsWrappers, ld.outputBlobsWrappers, layerInputNodes); // it's ok if ld.name is empty
 
             // collect outputs
             bool isOutputNode = ld.consumers.size() == 0 ? true : false;