* Remove deprecated v0::TopK
* Remove using SortType and using Mode from TopK
* apply code format
* Revert "Remove using SortType and using Mode from TopK"
This reverts commit ee2f99ea89.
* Reconfigured the layouts with importing the dedicated POT layout and Accuracy Checker and Model Downloader items from the OMZ layout
* updated
* test
* test
* Moved the Model Downloader from ie_docs.xml to openvino_docs.xml
* Renamed optimization_docs.xml --> pot_docs.xml
* Added Model Server to the layout
* Minor fixes
* Generate unique output file names in CheckExecGraphInfoSerialization testcase.
When multiple instances of this test were executed in parallel the same
file was accessed by multiple threads which was the cause of flakiness.
* Enable ExecGraphTests.CheckExecGraphInfoSerialization on GPU
* Fix serialization of execution graph.
* Add exec graph comparison.
* Align execution graph serialization to old aproach.
* Revise error massages.
* Fixed execution graph comparison.
Now only attribute names are compared since values can differ on
different devices.
* Readability refactoring.
* Refactoring regarding readability.
* [IE] Add batched blob support
New `class BatchedBlob : public CompoundBlob` defined to allow to pass multiple blobs as 1 InferRequest input.
Motivation: There is the special user case when a number of plain images (e.g. `NV12Blob`) should be passed as one input for network which batch size > 1.
`class CompoundBlob` is not applicable for such cases due to:
1. `NV12Blob` is `CompoundBlob` which prevents to combine multiple NV12 images to a CompoundBlob
2. The default behavior in most of plugins - do not accept generic CompoundBlob as `SetBlob()` argument
Adding `SetBlob(name, vector<Blob::Ptr>...)` to `class IInferRequest`, `class InferRequest`, `class IInferRequestInternal`, ... - is not effective solution due to limited and specific use cases for `batched inputs`.
+ Apply rule-of-zero to CompoundBlob and inherited classes.
* Add "BATCHED_BLOB" optimization capability metric
* Add BatchedBlob usage to hello_nv12_input_classification
* Apply offline code review outcome:
1. Revert CompoundBlob public .ctors signatures
2. Remove 'workaround' .ctor for `BatchedBlob`
3. Revert tensor descriptors of `I420Blob` `NV12Blob` back to the 'fake' value.
* Code review fix
* Add functional tests for CPU, GPU, MULTI, HETERO
* update doc comment
* Apply code review change requests.
