In one of the network it was the following pipeline:
```
FullyConnected -> Reshape -> FullyConnected
```
And the output of Reshape wasn't in the same order as input for this
layer. I found that the problem was connected with format of the layers.
During optimization passes this pipeline was transformed to the
following:
```
FullyConnected -> Reorder -> Reshape -> Reorder -> FullyConnected
```
Both `FullyConnected` layers works with `yxfb` format. This is why
Reorder layer after the Reshape has output layout with format `yxfb` and
`reshape_in_layout.format` returns `yxfb` format. But in this case we
have to convert Reshape to `bfyx` format because in this case we won't
change the order of elements.
I replaced `reshape_in_layout.format` (which returns `yxfb`) and
explicitly set `bfyx` format.
JIRA: 35288
* Draft version of the Swish nGraph operation and fusing transformations for different approaches to express the operation
* Swish fusing transformation refactoring
* Added Swish operation and extractor for TF. Removed unfolding transformation for the operation.
* Added SwishIE. Implemented transformation to convert Swish to SwishIE.
* Code style fixes
* Updated Swish reference implementation. Added tests for shape and value inference
* Fixed code style for Python API
* Fixed unit test
* Apply review comments
* Use matcher_pass_callback
* Make m_alpha attribute protected in the SwishIE operation
* Fixed Swish op PythonAPI test
* Added Caffe Slice_ext
* Added TFSlice, AttributedSlice (both with extractors and replacers), corrected SliceConverter and added unittests for all cases
* added comments to each type of Slice operation; optimized shape inference; moved mxlice inside of slice.py; renamed slice_replacers
* removed type annotation for get_shape_after_slice routine
* replaced zeros_like with zeros
* Corrected preserving node names, renamed attributes names, added tests fro slice_replacer onnx phase
* Renamed slice_replacers.py
* added more unittest cases
* added type annotations, moved to more relevant place routines for shape calculation, and some other minor corrections
* corrected a typo `normalize_slice_indices` comment
* corrected shape calculation for Nonconstant inputs
* corrected a few typos
* corrected type declarations
* corrected shape inference with rounding
* refactored unit-tests for front transforms of Slice
* added error raising for negative and zero shapes
* removed magic_num
* corrected AttributedSlice, clarified comments
* fixed unit-test for AttributedSliceToSlice
* typo in type hints corrected
* removed supported_attrs
* returned back default None for attrs of Slice
* Updated ConvertPrecision transformation to be executed for TI Body
* Added type fusion for GenericIE operation
* Added test for TensorIterator body precision conversion
This extends resample optimization for 8-bit types that uses feature
packed to mode to process multiple features in one work-item to features
not being multiple of packing factor.
For nearest resampling it is safe to copy extra feature padding for
blocked formats, so this change only removes this condition.
* Minimized ngraph headers inclusion
* Added compilation of plugin api headers with strict flags
* Fixed -WPedantic issue in ngraph headers
* Fixed compilation
* Trying to fix Windows
* Fixed GNA unit tests compilation
* Disabled WX test on Windows
* Enable ngraph python tests
* Refactor and unify ngraph with onnx python tests
* Revert deprecated test cases
* Set ngraph and onnx python tests as a one test suite execution
* Change unstrict Xfails to strict ones
* Update after review:
- add model zoo to onnx tests,
- improvements of tests
* Revert mounting zoo models dir
Co-authored-by: Michał Karzyński <4430709+postrational@users.noreply.github.com>
