* BinaryConvolution specification refactoring.
* Aligh tensor types to current CPU implementation.
* Remove !D & 3D case becuase CPU plugin supports only 2D case.
* Add pad_value to the example.
* Add computation algorithm for mode 'xnor-popcount'.
* Computation formula refactoring.
* Fix typo in the description.
* Added attributes save modes
* Added tensor names to IR
* Reformat code
* Add support for tensor names in MO IR Reader
* Unit tests and code refactoring
* Fixed error
* Code refactoring
* Code refactoring
* Code refactoring
* Error fixed
* Error fixed
* Bug fixed
* Bug fixed
* Additional unit tests and comments
* Small update
* Update fake infer function
* Update names restoring
* optimize imports
* Add support for old-style constants and for commas in reader
* Added dest mode in Fuse Mul
* Update default values
* Fix missed debug info in some specific cases
* Fix a lot of issues with missedand wrong names provoding
* Resolve review comments
* Update test IR's
* Refactor and simplify code
* More simplification
* Remove unneccessary changes
* model-optimizer/mo/utils/ir_reader/layer_to_class_test.py
* Add separate tests for names restoring
* Update copyright year
* Apply review comments
Co-authored-by: Anastasia Popova <anastasia.popova@intel.com>
* Redirect StageDependencies from injected stage to the parent of the injection.
* Change StageDependencyEdge to be Stage<->Stage connection. In fact, it affects only stages order, so it would be more natural (also more convenient) to represent it so.
* Add injectedStageDependencies to InjectionEdge to be able to distinguish those dependencies that were added to hwStage during the injection process and make the revertion correct.
* Changed check for dimension size to be non-negative
* Added unit test for reading model with ShapeOf from scalar and fixed IE IR parser
* Added comment to the test
* Fixed ShapeOfFromScalar test
* Fixed incorrect merge
* Added test for a negative value of "dim" in IR
* fix ss
* successfully converted
* successfully run moved infer and normalizer unit-tests
* successfully rewritten StridedSlice infer unittests
* int64 array
* Successfully converter crash-when-loading, xj_feauture and toy nets (cherry-picked maxpoolV4 and tf_broadcast_ext)
* successfully moved PermuteAttrs to general mechanism
* successfully converted xj_feauture and crash when loading with the new rewritten SS infer
* fixed get_shape_from_slice and moved to common utils
* fixed extending masks and some other
* some refactoring
* fixed extending masks in extractor, fixed licence year and some other code clearing
* corrected a couple of unittests
* fox permute for 5 rank slice and 4 rank inputs/
* WIP
* Added comments
* fixed StridedSlice in ProposalMutation.py
* rechecked shape_infer unittests added some new cases
* added shape_infer unit-tests after StridedSliceNormalizer pass and Permute unit-tests
* corrected unittests
* Applied review comments
* general permutations for inputs implemented, corrected ellipsis unrolling when shrink_axis is at the beginning, some other corrections
* removed code duplication in infer and normalizer, moved 'slices' attr normalizing to StridedSliceNormalizer.py
* removed some code duplication and other minor improvements
* Added tests
* minor corrections
* wider range of unittests added (froze the number)
* review comments applied
* enabled skipped unit-test
* comment corrections
* applied review comments: changed op -> type, added some asserts, corrected comments and other minor corrections
* sorted inputs, updated Supported_Frameworks_Layers.md, some minor
* Refactoring FunctionsComparator - extract node comparison part
* try to fix logic and CentOS bulids
* Add negative test for precision
* Use fixed ngraph::descriptor::Tensor type instead template type
* reorganize ngraph_test_utils.cpp
* Cleanup after merge master into branch
Co-authored-by: Patryk Elszkowski <patryk.elszkowki@intel.com>
* Reformulated, intermediate. No positive indices.
* Indices >= 0, depth > 0.
* Added the Types section and a more complicated example.
* Behavior for negative indices is undefined
* Wrap T1 & T2 with *
* Revert mkl-dnn to cae1e0b83
* T1: int32 or int64 only
