* Preprocessing API - base classes
Includes API definition for trivial mean/scale operations (which don't require layout)
Mean/scale with 'layout' support will be done under separate task together
with Layout
Current test code coverage: 100%
* Python bindings for base preprocessing API
* remove pre_post_process directory from ngraph/core
* remove files from ngraph/python dir
* move pyngraph pre_post_process files from ngraph/python to runtime
* remove pre_post_process test from CMakeList
* move include to the header
* update include path for pre_post_process
* style fix
* bind InputTensorInfo::set_layout
* cleaned test_preprocess
* fix test expected output
* remove duplicate test
* update description of set_element_type
* fix style
* move preprocess from pyngraph to pyopenvino/graph
* update test_preprocess imports and remove unnecessary test
* remove duplicate import
* update custom method
* update test
* update test
* create decorator that changes Node into Output<Node>
* create function that cast Node to Output<Node>
* update test_preprocess to use decorator for custom function
* change _cast_to_output -> _from_node
* move frontend folder to pyopenvino
* rename includes and add compile options
* include frontend to pyopenvino
* move __init__.py
* move tests
* remove mock from tests_compatibility
* rename import module
* Fix code style cpp
* refactor a few lines
* style fix
* update few lines in mo
* add tests fro scale and mean with vector input
* style fix
* add docstring for custom_preprocess_function
* bind InputInfo network method
* style fix
* Add pyopenvino to dependencies
* bind OutputInfo
* fix description of preprocess submodule
* fix style
* update copyright year
* Fix mock
* update docstring
* bind OutputTensorInfo
* bind OutputNetworkInfo and InputNetworkInfo
* bind ColorFormat and ResizeAlgorithm
* clean imports
* fix typo
* add PostProcessSteps to init
* bind PreProcessSteps
* create additional tests
* Fix mo test
* remove module local
* fix code style
* update comment
* fix return type
* update docs
* fix code style
* change ngraph.Type to ov.Type
* fix typo
* move _from_node to node_output.hpp
* add read_model from buffer
* update imports
* add new line
* remove bad quotes
* update imports
* style fix
* add new line
* rename functin args
* remove Type import
* update tests
* style fix
* test clean
* remove blank line
* update PrePostProcessor init and build methods
* create test with model update tests with new PrePostProcessor init and build
* # Conflicts:
# inference-engine/ie_bridges/python/src/openvino/offline_transformations/offline_transformations_api.pyx
# inference-engine/ie_bridges/python/src/openvino/offline_transformations/offline_transformations_api_impl.cpp
# inference-engine/ie_bridges/python/src/openvino/offline_transformations/offline_transformations_api_impl.hpp
# inference-engine/ie_bridges/python/src/openvino/offline_transformations/offline_transformations_api_impl_defs.pxd
# inference-engine/tests/ie_test_utils/common_test_utils/ngraph_test_utils.cpp
# inference-engine/tests/ie_test_utils/common_test_utils/ngraph_test_utils.hpp
# model-optimizer/mo/moc_frontend/serialize.py
# thirdparty/gflags/gflags
# thirdparty/gtest/gtest
* Stash
* move preprocess module from openvino.impl to openvino
* fix building
* fix code style
* try to move MO to use new api
* Intermediate commit
* try to move MO to use new api
* Test pybind11 custom holder for Preprocessing types (InputInfo and PreProcessingSteps)
* Initial code for source_target layout handling for preprocessing
Initial implementation of reverse input channels
* Use input's tensor names instead of friendly names
* Skeleton for guessing layouts and clearing it after preprocessing
* updated package_BOM.txt
* Use reference_wrapper for preprocess bindings
* Update tests
* Layout::find_permutation - support of dynamic layouts
Covered case for 'trivial convert' where no permutation is needed
It is needed for Model Optimizer for logic which will guess model's layout, like "?c??"
* Stash
* add bindings to I420_SINGLE_PLANE and I420_THREE_PLANES
* remove init from all classes except PrePostProcessor and add RGBX and BGRX to ColorFormat enum
* Guess layout so that existing mean/scale tests passed
* update test name
* Draft to guess layout for 'reverse_input_channels'
* More unit tests (error cases)
* pylint & flake8
* pylint - ignore import error
* Stash
* Moved preprocessing to 'back' folder
* More tests
* Update package_BOM
* Support layout_values with no names
Support layout set for 'outputs'
Tests
* Export more enum names from nrgaph
* Basic --layout parsing
* removed debug prints
* Further updates after rebase
* Update imports
* Removed part from 8829
* Fix imports in test code
* Minor cosmetics
* Don't guess 'C' if layout is already set by model
Expose 'Layout::empty' method
* Style fix
* Apply review comments
Restricted 'heuristics'
C++: Added 'fp16', 'fp64' support to mean/scale
* Applied review comments
* Added some dynamic test cases
* Move call of 'apply_preprocessing' to 'serialize.py'
* Unnecessary change
* Added more comments to code
Co-authored-by: pszmel <piotr.szmelczynski@intel.com>
Co-authored-by: Alexey Lebedev <alexey.lebedev@intel.com>
Co-authored-by: bszmelcz <bartosz.szmelczynski@intel.com>
Co-authored-by: Anastasia Kuporosova <anastasia.kuporosova@intel.com>
Co-authored-by: y <ilya.lavrenov@intel.com>
Co-authored-by: Vafin, Maxim <maxim.vafin@intel.com>
* Implement MO part for DetectionOutput-8
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Implement nGraph part for DetectionOutput-8
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Implement deduction of a number of classes method
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix build
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Implement nGraph tests to check shape inference for DetectionOutput-8 with deduction of num_classes
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Implement attributes tests for DetectionOutput-8
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Remove DetectionOutput-1 from opset8
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Add python bindings for DetectionOutput-8 and tests
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Implement downgrading and upgrading transformations for DetectionOutput
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Implement tests for downgrading and upgrading transformations for DetectionOutput
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Adopt existing reference for DetectionOutput-8
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix DetectionOutput-8 reference
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Add tests for DetectionOutput-8 reference
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Finish resolving merge conflict
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix python bindings after re-structuring
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix BOM package list
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix multibox_detection_test
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix python bindings for DetectionOutput-8
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Insert blank line between summary and description for python binding
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Apply review comments: identation, for loop
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix formatting in python bindings
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix supported_attrs for DetectionOutput from opset1
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Add missed imports for python if_op
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Apply feedback and fix Win build
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Use the same test suite name for test mixture
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix transformation tests
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Recover BWDCMP_RTTI for legacy use and remove unused variables in tests
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Remove unused variables in type_prop tests
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Recover legacy referenceDetectionOutput constructor
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix python binding for DetectionOutput
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* move frontend folder to pyopenvino
* rename includes and add compile options
* include frontend to pyopenvino
* move __init__.py
* move tests
* remove mock from tests_compatibility
* rename import module
* Fix code style cpp
* refactor a few lines
* update few lines in mo
* Add pyopenvino to dependencies
* Fix mock
* update docstring
* Fix mo test
* remove module local
* fix code style
* update comment
* fix return type
* update docs
* fix code style
* fix building
* fix code style
* try to move MO to use new api
* Export more enum names from nrgaph
* [Python API] quick fix of packaging
* update tests
* fix setup.py
* small fix
* small fixes according to comments
* skip mo frontend tests
* update mo to new imports
* try to fix win wheel
* fix win wheel
* fix code style
Co-authored-by: Anastasia Kuporosova <anastasia.kuporosova@intel.com>
Co-authored-by: y <ilya.lavrenov@intel.com>
* dynamic shape calculation for GatherElements
* dynamic shape calculation for sparse_reshape, corrections for sparse_segment_mean/sqrtn/sum
* corrected dynamic_dimension_value, added two unit-test cases
* simplified solution, added missing Nones
* some corrections
* added a couple of more unit-tests
* Fix in the MO infer function of Gather.
* Added comment about done fix.
* Added more tests.
* Now Gather and AttributedGather are always marked as reinterp_shape=True.
* add subgraph instead of constant with fixed shape to allow model have undefined batch
* updated transformation (not checked yet)
* changed ReverseV2ToReverseSequence to support dynamic shapes/reshape;
added transformation to reverse_tensor_iterator to support new subgraph got from ReverseV2ToReverseSequence
* remove changes that should not be on this branch
* added tests;
fixed old transformation
* added delete of reversesequences to avoid run of transformation twice
* fixed pattern check for case with dynamic value for input of reversesequence
* Revert "fixed pattern check for case with dynamic value for input of reversesequence"
This reverts commit 0c04164e
* Revert "added delete of reversesequences to avoid run of transformation twice"
This reverts commit fcb7de9c
* reversed changes in reverse_tensorr_iterator for Squeeze case;
update reverse_tensor_iterator with shapeof subgraph
added permutations for attributes to pass layer test
* minor fix for dynamic shape
* updated test;
fixed backward compatibility in reverse_tensor_iterator transformation
* revew comments fixed:
added comments;
refactoring done;
fixed framework name saving for rank = 1
* minor review fixes
* small fix
* Separated old_api_map into old_api_map_order and old_api_element_type.
* Clang format, small fix.
* Corrected comment.
* Removed OldApiMapOrderAttr class.
* Renaming all frontends from "*_ngraph_frontend*" to "_ov_frontend*"
Also Debug builds on Windows release frontends without "d" suffix will not be loaded
* Fix review comments and add wheels test debug prints
* More debug prints
* Load by absolute path and remove debug prints
* [MO, TF] Support Custom Wide and Deep CTR model by MO
It implements implicit support of EmbeddingSegmentsMean operation through decomposition.
Also, this extends the current transformation to fuse TensorFlow sub-graph (for Wide and Deep model family)
containing SparseSegmentSum and SparseSegmentMean operations into EmbeddingSegmentsSum or EmbeddingSegmentsMean.
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix unit-tests after modifications of SparseToDense and EmbeddingSegmentsOperationFusing
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Document SparseSegmentMean support
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Add computation scheme for normalization coeffs and correct documentation
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* add performance hint to time infer
* move unit_tests to tests pkg
* change unit_tests path in azure lin
* change path to mo in bom test
* fix tests_path
* change mo dir path
* initial version of transformation workable for loop
* moved transformation to back + minor changes in result names
* fixed mistake: to concatenate results of all iterations Unsqueeze should be added
* added shape inference for new nodes and extend test
* added support of TensorIterator
* If support + test;
fix to save model with TI after transformation
* fix code and tests according to run with ir_reader
* added finding max internal_layer_id in sub-graph + added comments to code
* turn off transformation because it should not be used in MO scenarios
* refactor code to find out iterations count for TensorIterator
* chenged name of final result to srtucture loop1.loop2.node for path [loop1, loop2, node]
* change port number to index of added output
* return list of new nodes
* change naming of output to standard way;
return result node as output of transformation
* refactor transformation, add more comments; fine up tests
* review fixes: add more comments, refactoring of infer function, fix in iterations count calculation
* added processing of dynamic iterations count + tests
* moved iterations count calculation to TI
* fixed bug in iterations count calculation
* fix bug with adding iterations count to wrong dimension + test
* review fixes: minor renaming + fixed bug with unset stride for TI
* move logic with output record outside function calculation iteration count;
fix case with negative start/end;
fix case when division result is not integer;
added tests for such cases
* review fixes: refactoring of toerations count calculation
* added IteratorGetNextCut, some improvements in graph.py
* added allowed types check
* reused new graph API for ports
* returned back old API 'out_nodes', removed soft-getting name from base class, changed run_after -> []
* correctly used new port API
* corrected IteratorGetNext message
* Changed namespace from ngraph to ov for OV Frontends
* Fixed python
* Fixed ONNX Editor for windows
* Try to fix centos
* Fixed code style
* Revert frontend loader
* Add GatherND_8 operation
* Update shape infer function and tests
* Initial commit for nGraph GatherND_8 operation
* Add GatherNDBase class implementation
* Fix base class errors
* Add missrd header
* Update base class
* Update GatherND_8 implementation
* Fix codestyle
* Fix wrong rank
* Implement tests for gatherND_8 shape inference function
* fix codestyle
* Add limitation to doc
* Siplyfy check in shape inference
* Add more test cases
* Update shape inference function
* Add more test cases to cover all case with dynamic input shapes
* Update shape inference function
* Refactor tests
* Add visitor tests for gatherND_8 operation
* Correct comment
* Add additional check is shape inference function
* Update shape inference implementation for gathernd operartion
* Fix codestyle
* Remove restriction for data is fully defined
* Update shape inference functon
* Fix missed check for nonetype
* Remove redundant checks for batch_dims
* Fix codestyle
* [IE Transformations] Disable pull_transpose_through_fq transformation for activations path
* Update MO part
* Replace TEST to TEST_F
* Fix tests with fixture.
Remove dynamic shapes tests due to the fact that there is always a constant at the input
* MO update for MaxPool-8
* using attrs in op constructor
* remove pads_value attr and pad fusing
* added axis and index_element_type parameters
* updated mo maxpool-8
* added maxpool-8->maxpool-1 transformation, disabled Pad to MaxPool fusing
* added remove_values_output to pooling extractors
* moved remove_values_output attribute to pooling infer function
* fixed ir_comparator tests
* disabled pad to maxpool fusing test
* added downgrade transformation test
* downgrade transformation update
* updated ir reader and tf pooling layer tests
* updated onnx pooling layer tests and MO infer unit test
* updated ir reader extender
* uncommented layer tests code
* disabled MaxPool-8 python binding test
* comment resolving, removed PadMaxPool fusing
* removed test
* downgrade transformation fix, MO codestyle changes
* removed axis check from downgrade transformation
* mark max_pool_test as xfail
* updated downgrade transformation test
* using OPENVINO_RTTI
* Added transposes insertion for Parameter and Result.
* Separated into several transformations.
* Corrected runtime_info format.
* Fixed runtime info serialization.
* Code refactoring.
* Corrected checks.
* Added debug output.
* Added check.
* Fixed unit tests.
* Changed old api map format, removed debug output.
* Moved serialize to rt_info property, code corrections.
* Refactored RTInfo class.
* Small corrections.
* Small corrections.
* Removed redurant import.
* Added tests, added undefined default type.
* Code reformat.
* Fixed serialization unit tests.
* Added comment.
* Added comment.
* Small test correction.
* Changed default values of old_api_map to values from old API IR.
* np.array -> int64_array
* Update MO to use FE to read IR; Swith MO IR version to 11
* Preserve output node name when inserting Transpose
* Codestyle
* Fix layer tests
* Pylint fix
* Disable ref_graphs comparision in layer tests
* codestyle
* Updated MO IR reader.
* Moved version initialization to constructor of OldApiMap.
* Added shape infer after transpose insertion.
* Fixed Pylint
* Removed wrong attribute removal.
* Added transposes insertion for Parameter and Result.
* Separated into several transformations.
* Corrected runtime_info format.
* Fixed runtime info serialization.
* Code refactoring.
* Corrected checks.
* Added debug output.
* Added check.
* Fixed unit tests.
* Changed old api map format, removed debug output.
* Moved serialize to rt_info property, code corrections.
* Refactored RTInfo class.
* Small corrections.
* Small corrections.
* Removed redurant import.
* Added tests, added undefined default type.
* Code reformat.
* Fixed serialization unit tests.
* Added comment.
* Added comment.
* Small test correction.
* Changed default values of old_api_map to values from old API IR.
* np.array -> int64_array
* Update MO to use FE to read IR; Swith MO IR version to 11
* Preserve output node name when inserting Transpose
* Codestyle
* Fix layer tests
* Pylint fix
* Disable ref_graphs comparision in layer tests
* codestyle
* Updated MO IR reader.
* Moved version initialization to constructor of OldApiMap.
* Added shape infer after transpose insertion.
* Fixed Pylint
* Removed wrong attribute removal.
* Serialize fix.
Co-authored-by: Gleb Kazantaev <gleb.kazantaev@intel.com>
* 1. Removed explicit SHARED from libraries
2. Fixed double definition for ie_layer_validators
* Fixed SEG in unit-test: order of initialization for global vars
* Added an ability to find plugins.xml from static IE
* Fixes in unit-test
* Migrated to new macro for import / export
* Minimized number of custom dllexport
* Don't use IR v7 for static libraries
* Revert for merge
* Don't enable tests with dlopen for static libraries
* Code style
* Added condition for export
* Revert format_reader
* Removed forward decalaration with external linkage
* Fixed IE linkage on Windows
* Reverted back 2 flags
* fixed dealing with None values in then/else branches of Select
* generalized solution when condition is non one elemental
* fix when both branches are None
* minor corrections
* rewritten Select unit-tests; fixed for condition with [True] mask
* removed mutable default arg from build_graph, added a few more test cases with masked condition, other minor corrections
* corrected output_shape calculation when broadcasting is off
* layer tests fixed: relaxed assert for condition shape to let pass TF Select
* corrected shape calculation when condition is not elementwise equal, calculated calculation for TF, corrected calculation of shape when values are not set
* fixed a typo for Select from TF Where
* Initial change to allow saving graphto IR without meta_info
* Update saving and restoring functions, add more comments
* Add unit tests for define_data_type() function
* Fix wrong name
* Update condition
* Update meta_data checks
* Update data_type restoretion and missed outpurt ports handling
* Update and add new test
* Update comments
* Remove commented code
* Rename function
* Update temporary Result operations processing
* Remove define_data_type function
* Move node_normalize_output function to Op class methods
* Update comments
* Update comments
* added Kaldi dropoutmask extraction and Kaldi lstmNonlinearity replacer extended for dropout case
(cherry picked from commit 0dd05f8053)
* fixed frame time calculation for Kaldi models with shapeof branches
* fix bug in frame time calculation for Kaldi models with shapeOf paths
* remove incorrect attribute from transformation
* refactoring based on review, couple more checks
* minor review fixes
* Change sort functions to fix incorrect order
* Add separate sorts for different cases
* Update sort function to correct control flow edges handling
* Refactor all sorts for dictionary ordering
* Update build_graph function for correct control_flow edges creation
* Add tests for nodes and ports sort equality
* Fix wrong port value
* Add direct conversion from bool to int
* Use .replace instead of .strip
* Add test with both control_flow and ordinary edges, refactored edges lists filling
* Refactored nodes dict filling
* Delete unused test code
* Fix return valuese for lift_up_through func
* Update unit test
* Refactoring code according to code review
* Fix revers outputs
* Fix unit test
* Fix comment
* Add multioutput support
* Add unit test for cace with several output from ReverseChannel op
* Fix distinantion connect
* Refactored code, updated comments and documentation related to TF OD API models pre-processing.
* Improved MO messages related to pre-processor block removal during conversion of the TD OD API models. Remove mean/scale if padding is used and mean/scale is applied before resize
* Updated TF OD API transformation and documentation for SSD models
* Updated comments and documentation for the ObjectDetectionAPIMaskRCNNSigmoidReplacement transformation
* Updated comments and documentation for the ObjectDetectionAPIMaskRCNNROIPoolingSecondReplacement transformation
* Updated comments and documentation for the ObjectDetectionAPIPSROIPoolingReplacement transformation
* Updated comments and documentation for the ObjectDetectionAPIProposalReplacement transformation
* Updated comments and documentation for the ObjectDetectionAPIDetectionOutputReplacement transformation
* Minor code style fixes
* Fixed unit tests for ObjectDetectionAPIPreprocessor2Replacement transformation
* Improved unit test for pipeline.config parser. Fixed very long bug with incorrect test data for the PipelineConfig parser class
* Code style fixes
* Get rid of "coordinates_swap_method" parameter in the JSON configuration file for TF OD API models
* Code style fixes and minor refactoring
* Simplied code related to swapping Proposal coordinates
* Removed incorrectly removed code
* Fixed code review comments about the code comments
* Allow MO to generate IR with -1 in dimensions
* Some fixes to support -1 for StridedSlice operation
* Updated TensorArrayGatherV3 shape infer to support dynamic output shape
* Several fixes to support undefined dimensions in the Broadcast,Reshape,Slice and Tile
* Fixed bug in the normalization transformation of TF NMS to opset NMS
* Updated shape infer functions related to StridedSlice and NMS
* Updated Select shape inference function to use common shape broadcasting function supporting dynamism
* Fixed operation TFResize shape infer function to work correctly for case when model is converted with --disable_nhwc_to_nchw
* Dynamic Range and update asserts in NMS
* Changed the way how dynamic dimensions are specified. Refactored shape inference functions and common places to use new approach
* More fixes to support dynamic shapes
* More fixes for support of dynamic shapes
* Fixed generation of IR with dynamic dimensions
* Allow reading IRs with undefined dimensions
* More changes in the IE to support dynamic dimensions
* Fixes for Switch, Merge, Concat shape and value infer related to dynamism
* Fixed TensorArray related ops to properly handle dynamic dimensions. Fixed StridedSlice infer for case with new_axis
* Fixed shape_for_layout function to generate masked array
* Fixed shape inference for Convolution and Poolings to support dynamic spatial dimensions
* Updated shape infer functions for CTCGreedyDecotder, CTCLoss and Enter
* Fixed shape inference with dynamic dimensions for MatMul, Split, Upsample, SpaceToBatch, some fixes for the TI
* Fixes for undefined dimensions support for Proposal and DetectionOutput
* Fixed ExtractImagePatches, DepthToSpace and RegionYolo shape infer functions to work with partially dynamic dimensions
* Changes in tf_window_op_pad_infer to better work with dynamic dimensions
* Fixed output shape calculation for StridedSlice operation
* More StridedSlice fixes
* Fixed resolve_convolution_with_group
* Fixed unit tests
* Fixed unit tests
* Fixed Switch op unit tests
* Fixed shape inference for Upsample operation
* Updated unit tests for the Concat operation
* Fixed eltwise shape infer unit tests
* Fixed shape infer tests for Convolution and DetectionOutput ops
* Fixed Crop shape infer function tests
* Fixed Slice op unit test and minor fix in the shape inference. Fixed emitter
* Updated unit test for telemetry and match_shape function for dynamism
* Fixed unit test for the DetectionOutput
* Added support for the TF ClipByValue operation
* Fixed GatherND shape inference for dynamic shapes support
* Dynamic shapes support for the MO IR Reader
* Fixed BlockLSTM operation to not work as an extractor
* Allow to serialize IRs with partially defined shapes
* Updated SelectBroadcast transformation to not check shape values
* Fixed MO IR comparator
* Fixed SS value propagation when slices are dynamic
* Do not re-run graph clean-up for ProposalMutation
* Fixed InterpolateSequenceToInterpolate transformation to support dynamic dimensions
* Fixed Loop iteration count calculation and reading IteratorGetNext shapes
* Fixed unit test for serialization
* Fixed serialization test
* Fixed RandomUniform shape infer
* Fixed several transformations related to RNN to respect dynamic output shapes
* Fixed Deconvolutin shape calculation for dynamic batch. Eltwise shape infer improvements
* Fixed shape infer functions for ExperimentalDetectron ops, reverted changes for NonZero and removed debug prints
* Fixed check for dynamism of a list, fixed value propagation for Concat op and remove redundant shape infer for reshape
* Update Eltwise value propagation to use np.ma
* Fixed ExpandDims shape infer function
* Shape infer functions fixes and improvements
* Remove Accum op from the MO
* Updated activation functions shape infer
* Removed unsupported operation Correlation
* Fixed shape infers for several functions
* Removed unsupported DataAugmentation operation
* Fixed shape infer functions for several ops in extensions directory
* Removed not-support operation PowerFile
* Removed unsupported SpatialTransformer,SimplerNMS and PredictionHeatmap operations
* More shape infer functions updates
* Merge shape infer fix
* Fixed typo
* Fixed TensorArraySize shape infer function
* Fixed VariadicSplit and Squeeze shape infer
* Fixed ONNX models Parameter extractor
* Updated Select value propagation for the dynamic case
* Fixed ReorgYolo shape infer and test
* Removed unnecessary tests
* Fixed Tile shape infer
* Fixed SparseFillEmptryRows unit tests
* Fixed package bom
* Added extractor for the TF operation Mod
* Fixed value propagation for MatMul operation
* Updated Parameter extender to generate shape_array when shape is partially defined only
* Fixed BOM file
* Fixed issue with the TF OD API models and DetectionOutput op. Now the shape infer function for the DO do not re-infer "num_classes" attribute value if it is already known
* Fixed unit test for the DO infer
* Fixed num classes calculation for the DO generation for Faster/Mask-RCNN models
* Changed NMS op to produce static output shape
* Restore dynamic output shape calculation for the NMS for NMS-5
* Fixed CellNormalizer transformation. It should work for static shapes only
* RNNCell Op class fixes
* Revert some changes
* Updated documentation with a list of supported operations
* Revert changes
* Fixes for the ConstantFill op
* Removed redundant SequenceLengthToMask transformation
* TensorArray* ops shape infer code style and refactoring
* Reverse some unnecessary changes in the ConvolutionNormalizer
* Fixes and unit tests for shape_array, compare_shapes, is_fully_defined functions
* Implemented shape_insert, shape_delete functions and tests for them
* Modified code to use shape_delete function
* Added usage of shape_insert function where necessary
* Use shape_insert function in many places
* Some fixes in shape inference for various ops
* Updated shape_delete function to support negative indices
* Changes and unit tests for the MatMul infer function
* Removed strange code from the TF Merge infer function
* Merge op shape infer fixes
* Fixed value propagation in the transformation EltwiseInputReshape.py for the dynamic dimension case
* Code cleanup
* Updated GatherND to support dynamic dimensions
* Minor fixes
* Fixed shape_insert and shape_delete to support np.int64 and np.int32 types
* Updated Upsample operation unit tests with dynamic input shapes
* Minor change in the extensions/back/ConvolutionNormalizer.py to make sure that input dimensions are static
* Fixed ConvertGroupedStridedSlice transformation and added unit tests
* Revert debug changes
* Fixed value propagation for Unsqueeze to work with partially defined input values
* Typo fix
* Added unit tests for the Unsqueeze op shape infer
* broadcasting functions changes and unit tests
* Fixed Tile value inference for partially defined input tensor
* Unit tests for Split and VariadicSplit ops
* Fixes for the Concat infer + unit tests
* Removed redundant tf_pack shape infer
* Fixed Concat value infer and added unit tests
* Fixed StridedSlice shape inference for case with dynamic slices
* Fixes related to StridedSlice shape infer, changes in tests
* Unit tests for the eltwise shape and value infer
* Fixed Pad op value propagation to allow dynamic input values to be propagated
* Unit test for Pooling dynamic input shape infer
* Squeeze op unit tests for dynamic input shape
* Added assert to the Squeeze op shape infer for case when squeeze dimension is dynamic value
* Added message to the MO when input shapes are dynamic
* Convolution dynamic unit test
* Removed redundant transformation GroupedConvWeightsNormalize
* Removed non-ascii character from the message
* Fixed typo in the BOM file
* Code style and comment fixes
* Fixed copy-paste issue in the DO shape infer function
* Fixed setting dynamic shape in the MO command line
* Added function to compare tensor with dynamic values. Fixes in the unit tests and shape infer functions
* Improved Reshape shape infer + added unit tests
* Fixed value propagation for Select op
* Renamed several internal functions, minor code fixes.
* Code style fixes
* Modified condition in the _set_shape method of the Port class to not check shape if the "override_output_shape" attribute is specified
* Fixed constant value propagation for ReduceOps when inputs have dynamic values. Added unit test
* Fixed shape infer for the Loop for dynamic dimensions case
* Fix in the NMS shape infer to avoid ragged numpy array generation. Fixed Scatter shape infer validation
* Improved shapes infer for eltwise ops with respect to dynamic dimensions
* Changed code comments
* Renamed tensor names in the ClipByValueTFTransformation
* Changed np.ma.allequal to strict_compare_tensors in the Merge op infer
* Chanded np.ma.allequal with strict_compare_tensor.
* Fixed Merge op value infer
* Fixed debug code
* Removed commented line
* Updated condition to check for dynamic shapes in the Partial infer to not fail for MxNet models
* Improvements to the get_shape_from_slice and is_dynamic_slice functions
* Reverted change in the `normalize_slices_attr` for ellipsis mask case
* Updated shape conditions in the ScatterNDBase op to support dynamic dimensions
* Crop op file refactoring
* Set "type" attribute to None for SparseFillEmptyRows op which is not from any opset
* Removed unnecessary extractor test
* Restored Crop operation type
* Removed "type" attribute from the Crop operation and updated the MO code to find Crop by "op" attribute
* Fixed If shape infer function to produce dynamic dimensions
* Updated If shape and value infer to properly work when condition is static
* Fixed fusing transformation check to work with dynamic dimensions. Change comparison in the shape_inference function to not use strict shapes comparison
* Optimize imports in the LayerNorm
* ConvertGroupedStridedSlice minor fixes related to dynamism support
* Fixed ConvertGroupedStridedSlice to properly check if the dimension is sliced
* Add transformation for single CTCGreedyDecoder operation
* Fix style in op specification
* Update transformation logic
* refactor old tests and add tests for new transformation
* Move tf specific front transformations to tf folder
* Update transformation logic and comments
* Add run_after function and update comments
* Add output_sparse_format attribute to extractor
* Update transformation conditions and tests
* Fix incorrect comment
* Move sparse_to_dense_replacer to front/tf folder to fix problems with class registration
* Update import
* Update output ports handling in transformation
* Update test
* Fix BOM file
* Update pattern for ctcloss transformation
* Fix and refactor tests for ctcloss transform
* Update transformation conditions
* added reinterp_shape parameter to tf ss extractor
* removed reinterp_shape
* added transformation to replace ss
* updated bom
* fix for e2e tests
* updated a case when shrink_axis_mask and new_axis_mask are both initialized
* unittests
* added comments
* updated graph_condition
* comments resolving
* updated the case, when shrink_axis_mask and new_axis_mask are both initialized
* added layer tests for squeeze/unsqueeze cases
* remove case when shrink and new axis masks are both set
