* fix calculation of memoryoffset shape in 2 cases: after normalization layer (shape can be read from InputDim in loader) and after affincecomponent layer (shape saved in out-size based on weights shape)
* improve comments
* [MO][TF] Fixed TFSliceToSlice conversion error on Win, replaced int32_max with ShapeOf, minor correction in comments
* review apply: added create_op_with_const_inputs
* review apply: renamed variables, updated typehints for int64_array, float_array, float32_array
* renamed to correct_ends
* returned back check_op_attrs=True
* Added script that check IE existance
* Updated install_prerequisites.sh to check and insall IE python dependency
* Execute MOC transformation pipeline in subprocess
* Updated path to offline_transformations.py
* Updated IE dependency search; added libs search support
* Updated install_prerequisites.bat to check IE dependency
* Print warning if MO and IE versions do not match
* Set env before subprocess run
* Add mean and meta info to serialized IR
* Fix pylin import issue
* Update BOM file; added intel headers
* use default serialization; code style fix
* Codestyle
* Added subprocess timeout
* Check e2e status
* Update install_prerequisites.sh logic
* Update MO version to be generated even without cmake execution
* Update install_prereq to extract release version from python
* Simplify pyhton code
* Reduce memory consumtion to its original value
* Added OV find and search logic for windows batch script
* Remove model reading to avoid excess memory consumtption
* IMproved logging messages; simplified code
* Improved warnign message incase when MO and IE versions mismatch
* Fix test import
* Check IE bindings in the beginnig of MO pipeline
* Changed warning message; added RelWithDebInfo path
* Recomendation to build IE from source
* Resolve PR comments
* Apply review comments; Added CheckAPI pass
* Added path to IE local libs
* ModelOptimizer -> Model Optimizer (+IE)
* OpenVINO -> OpenVINO (TM) Toolkit
* Updated install_prerequisites.bat with new logic
* Move offline_transformations.py to back folder; improve warning mesages experience
* Update install_prerequisites.bat
* Move back some unnecessary changes
* Fix BOM
* Disable import errors for pylint
* Fixed grammar in messages
* pylint disable import error
* Final grammar fixes in bat and sh files
* 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>
* 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
* Added result rename operation
* Optimize imports
* Added ResultRename to package_BOM
* ResultRename moved to the end of back phase, code refactoring
* Revert incorrect changes
* Optimize imports
* Added comments and optimized imports.
* Draft implementation of the telemetry sender utility
* Examples of sending telemetry from the MO
* More statistic about the model.
* Intentional broken file to fail Mask-RCNN ONNX model conversion
* Added joined list of ops used
* Added requests to the requrements file and update BOM to include necessary files related to telemetry
* Send telemetry alwasys
* Refactored usage of GUID usage in the telemetry
* Enabled sending telemetry always
* Simplified function "TelemetryBackend.send"
* Use other approach to send information about session to GA
* Added automatic registration of the telemetry backends and allow to choose it during the telemetry class instantiation
* Added "requests" as a requirement. Wrapped usage of requests module to not crash the app
* Added timeout for sending data to GA. Increased the queue size to 1000
* Finalize Telemetry class implementation
* Do not fail MO if non-critical component is not installed and updated Telemetry GA with the default property
* Added sending version to a separate event
* Use default TID to send the data
* Set lower bound for the requests module which does not contain vulnerabilities
Co-authored-by: Evgeny Lazarev <elazarev.nnov@gmail.com>
* Refactored infer function and function supported_attrs for the layer Interpolate.
* Small change.
* Deleted unneeded checks in transformations ResizeToInterpolate2D and ResizeToInterpolate3D.
* Small fix in the extractor of ONNX Resize.
* Now the extractor of TF ResizeBilinear generates Interpolate-1 again, because 'axis' in final version of Interpolate-4 specification is an input but is not attribute.
* Now the extractor of TF ResizeNearest generates Interpolate-1 again, because 'axis' in final version of Interpolate-4 specification is an input but is not attribute.
* Added static method get_axis into class Interpolate.
* Refactored class CanBeFused in the transformation InterpolateSequenceToInterpolate.
* Fixed transformation InterpolateSequenceToInterpolate according to the last version of the specification of Interpolate-4.
* Started to write support of Interpolate-4 in the transformation InterpolateWithConcat.
* Added support for Interpolate-4 into the transformation InterpolateWithConcat.
* Added support for Interpolate-4 into the transformation InterpolateConcat.
* Added support for Interpolate-4 into the transformation InterpolateReshapeWA.
* Added support for Interpolate-4 into the transformation InterpolateTranspose.
* Started to add test for opset4 case of the transformation InterpolateSequenceToInterpolate.
* Added test for InterpolateSequenceToInterpolate (test_2d_interpolate_sequence_1_opset4_case).
* Added test for InterpolateSequenceToInterpolate (test_2d_interpolate_sequence_4_opset4_case).
* Added another test for InterpolateSequenceToInterpolate (test_2d_interpolate_sequence_5_opset4_case).
* Added another test for InterpolateSequenceToInterpolate (test_3d_interpolate_sequence_1_opset4_case).
* Finished addition of tests for opset4 case of InterpolateSequenceToInterpolate.
* Small change.
* Now opset is only opset1 or opset4 in the transformation InterpolateTranspose.
* Small fixes in transformations ResizeToInterpolate2D and ResizeToInterpolate3D.
* Deleted reading of unused ONNX attributes.
* Fixed docstring of the transformation InterpolateV1ToInterpolateV4.
* Added node name in assert about axes input.
* Fixes in the definition of the operation ONNXResize11.
* Now Interpolate-4 cannot have 'extension' as opset.
* Now the transformation InterpolateV1ToInterpolateV4 uses find_and_replace_pattern but not replace_sub_graph.
* Fixed tests for transformations InterpolateReshapeWA and InterpolateConcat.
* Fixed some tests.
* Rewritten operation Interpolate-4 class according to new variant of documentation.
* Some fixes in ONNXResize11 operation class.
* Now the transformation ONNXResize11ToInterpolate generates Interpolate-4 with 4 inputs.
* Now the transformation UpsampleToResample generates Interpolate-4 with 4 inputs.
* Now the transformation NearestNeighborUpsampling generates Interpolate-4 with 4 inputs.
* Now transformations ResizeToInterpolate2D and ResizeToInterpolate3D generate Interpolate-4 with 4 inputs.
* Now the transformation SplitConcatPairToInterpolate generates Interpolate-4 with 4 inputs.
* Now the transformation UnsqueezeTileReshapeBlockToInterpolate generates Interpolate-4 with 4 inputs.
* Now the transformation InterpolateV1ToInterpolateV4 generates Interpolate-4 with 4 inputs.
* Some fixes.
* Fixed the transformation InterpolateSequenceToInterpolate according to new variant of Interpolate-4 specification.
* Fixed typos.
* Added shape_calculation_mode to supported_attrs.
* Small fixes.
* Added operation ONNXResize10 and the transformation ONNXResize10ToInterpolate4.
* Fixed function correct_scales_using_dst_shape.
* Some fixes in InterpolateSequenceToInterpolate.
* Fixed bug in the method __call__ of the class CanBeFused: now self.accumulated_axes is correctly cleared in all cases.
* Small change.
* Fixed tests for the transformation SplitConcatPairToInterpolate.
* Now transformations InterpolateWithConcat, InterpolateReshapeWA, InterpolateConcat support Interpolate-4.
* Fixed the transformation InterpolateTranspose for the case of Interpolate-4.
* Written the back transformation InterpolateV4AxesCorrection to convert 'axes' input of Interpolate-4 from NHWC to NCHW layout.
* Added PermuteInput in Interpolate-4 infer.
* Fixed typos.
* Deleted the transformation InterpolateAxesCorrection.
* Now Interpolate-4 permutes axis, not shape in input port 3.
* Small fix.
* Some fix.
* Fixed bug in the transformation UpsampleToResample.
* Added some debug prints.
* Added more debug prints.
* Now ONNX Upsample-9 operation is read as ONNXResize10.
* Small fix.
* Small fixes.
* Fixed tests for the transformation SplitConcatPairToInterpolate.
* Deleted debug prints.
* Deleted some debug prints.
* Fixes in the transformation UnsqueezeTileReshapeBlockToInterpolate and its tests.
* Small fix in the transformation InterpolateSequenceToInterpolate.
* Started to write nGraph transformation to convert Interpolate-1 to Interpolate-4.
* Deleted redundant files.
* Small fixes.
* Small fix.
* Written draft of the transformation Interpolate-1 -> Interpolate-4.
* Small fix.
* Now ONNX Importer reads Resize-10 as Interpolate-4.
* Fixes in the test onnx_model_resize10_import_only.
* Small fix in the test for the conversion Interpolate-1 -> Interpolate-4.
* Small fixes.
* Fixed NGraphReaderTests for Interpolate.
* Some fixes.
* Deleted class for Resample operation.
* Fix in the transformation NearestNeighborUpsampling: fixed precision of the input 'scales' of generated Interpolate-4.
* Fixed typo.
* Now the TF operations ResizeBilinear is readed as internal MO operation TFResizeBilinear. This internal operation is converted into Interpolate-4.
* Small fix in BOM-file.
* Added checks of existence of attributes of TF ResizeBilinear operation.
* Small fixes in the conversion of the internal MO operation TFResizeBilinear to Interpolate-4.
* Small fixes.
* Small fixes.
* Now the transformation ONNXResize10ToInterpolateV4 calculates sizes input as input_shape * (scales + epsilon).
* Added the internal MO operation TFResizeNearestNeighbor.
* Fixes in the transformation SplitConcatPairToInterpolate and its tests.
* Fixes in the transformation UnsqueezeTileReshapeBlockToInterpolate and its tests.
* Written the transformation that converts the internal operation TFResizeNearestNeighbor into Interpolate-4.
* Now MO reads the TF operation ResizeNearestNeighbor as the internal MO operation TFResizeNearestNeighbor.
* Small fix.
* Now the specification of Interpolate-4 clarifies that the mode linear_onnx supports only 2D or 4D input tensors.
* Small fix.
* Some fixes.
* Moved the transformation ONNXResize10ToInterpolateV4 to the front stage.
* Deleted infer function and function supported_attrs for ONNXResize10 operation.
* Deleted supported_attrs() for TFResizeBilinear and TFResizeNearestNeighbor.
* Some fixes.
* Fixes in the shape infer function of the nGraph operation Interpolate-4. Now 'axes' input can be non-constant. In the such case, all elements of the output shape are Dimension::dynamic().
* Deleted corner cases processing in transformations TFResizeBilinearToInterpolateV4 and TFResizeNearestNeighborToInterpolateV4.
* Rewritten the function replace_resize_bilinear.
* Written inner MO operation TFResize that covers TF operations ResizeBilinear and ResizeNearestNeighbor.
* Now TF operations ResizeBilinear and ResizeNearestNeighbor are read as an internal operation TFResize in MO. Transformations TFResizeNearestNeighborToInterpolateV4 and TFResizeBilinearToInterpolateV4 are fused into one transformation TFResizeToInterpolateV4.
* Some changes in the shape infer function of nGraph op Interpolate-4.
* Small fix.
* Some changes.
* The transformation TFResizeToInterpolateV4 is moved to the front stage.
* Deleted redundant assert.
* Deleted transformations ResizeToInterpolate2D and ResizeToInterpolate3D.
* Some renaming.
* Small change.
* Deleted .copy() in the shape infer function of the internal operation TFResize.
* Small fix.
* Small fixes.
* Added comment about the case when the input 'axes' of Interpolate-4 is non-constant.
* Written test for Interpolate-4 shape infer, for the case when the input 'axes' is non-constant and shape_calculation_mode = scales.
* Some fixes.
* Small fixes.
* Small fix.
* Added yet another test for the case of non-constant 'axes' input of Interpolate-4 (when shape_calculation_mode = sizes).
* Added some comment.
* Small fix.
* Reverted changes for InterpolateWithConcat.
* Added type checks for all inputs of nGraph operation Interpolate-4.
* Added u32 and u64 to supported element types of sizes and axes inputs of nGraph operation Interpolate-4.
* Fixed some functional tests.
* Some changes.
* Added helper function float32_array.
* Now the MO transformation InterpolateV1ToInterpolate preserves names of layers.
* Small fix.
* Small fix.
* Reverted some change.
* Small fixes.
* Small fix.
* Small fix.
* Small fix.
* Small fix.
* Reverted changes in the nGraph reader tests for Interpolate-1.
* Some revert.
* Fixed some copyright year.
* [MO] Implement TensorFlow 2 While support in MO
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Add extractors for both While and StatelessWhile and do minor changes
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Improve update_body_graph function and manage graph names properly
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix a map for original name of parameters from body and cond
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Implement draft version of support of TF2 Keras RNN
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Implement Keras LSTM and GRU support in MO
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Improve code for Keras RNN support
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Finalize implementation of TF2 Keras RNN support in MO
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Apply the first part of the comments after review #1
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Avoid use of explicit values of port indices in the transformation
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Finalize code after the first-round review
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Apply comments after the second-round review
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Commit.
* Written the header file of the nGraph operation ExperimentalDetectronROIFeatureExtractor.
* Started to write cpp-file for the nGraph operation ExperimentalDetectronROIFeatureExtractor.
* Deleted in_ports_count attribute for the MO operation ExperimentalDetectronROIFeatureExtractor.
* Written validate_and_infer_type() method of ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor.
* Code style fixes.
* Code style fixes.
* Small fixes.
* Code style fixes.
* Now operation ExperimentalDetectronROIFeatureExtractor is read as nGraph operation ExperimentalDetectronROIFeatureExtractor.
* Implemented op::v6::ExperimentalDetectronROIFeatureExtractor::clone_with_new_inputs().
* Added macro NGRAPH_OP_SCOPE to the cpp-file of the nGraph operation ExperimentalDetectronROIFeatureExtractor.
* Fixes in some tests.
* Code style fix.
* Fixed yet another test for ExperimentalDetectronROIFeatureExtractor.
* Added tests for reading ExperimentalDetectronROIFeatureExtractor as operation from opset6.
* Added more test for reading ExperimentalDetectronROIFeatureExtractor as operation from opset6.
* Started to write shape infer tests for the nGraph operation ExperimentalDetectronROIFeatureExtractor.
* Corrected ngraph/test/CMakeLists.txt.
* Small changes.
* Code style fix.
* Small fixes.
* Added ctor of ExperimentalDetectronROIFeatureExtractor with NodeVector as argument.
* Added setting the attribute in_ports_count when the MO operation ExperimentalDetectronROIFeatureExtractor is creating in the MO transformation ONNXMaskRCNNTransformation.
* Added shape infer for the second output of the nGraph operation ExperimentalDetectronROIFeatureExtractor.
* Written shape infer tests for nGraph operation ExperimentalDetectronROIFeatureExtractor (case when input shapes are partially dynamic).
* Small fixes.
* Code style fix.
* Deleted redundant &expected_channels.
* Code style fix.
* Small refactoring.
* Small fixes.
* Small changes.
* Small fixes.
* Deleted attribute distribute_rois_between_levels of ExperimentalDetectronROIFeatureExtractoe.
* Deleted attribute preserve_rois_order of ExperimentalDetectronROIFeatureExtractoe.
* Deleted attribute image_id of ExperimentalDetectronROIFeatureExtractoe.
* Now MO generates attribute 'aligned' of ExperimentalDetectronROIFeatureExtractor only with values 'true' or 'false'.
* Small fix.
* Fix in the conversion of the attribute 'aligned' of MO operation ExperimentalDetectronROIFeatureExtractor to string.
* Tabs were replaced by spaces in some XMLs.
* Tabs were replaced by spaces in ngraph_reshape_tests.cpp.
* Fixed copyrights.
* Applied small patch to IREngine from PR https://github.com/openvinotoolkit/openvino/pull/3814.
* Tabs were replaced by spaces in cnn_ngraph_impl_tests.cpp.
* op::v6::ExperimentalDetectronROIFeatureExtractor::validate_and_infer_types() was rewritten using operator & for channels.
* Added tests for input shapes of op::v6::ExperimentalDetectronROIFeatureExtractor in the case when inputs shapes consist of intervals.
* Fixes in test type_prop.detectron_roi_feature_extractor_intervals.
* [MO] Implement support of TensorFlow 2 Keras Embedding operation in MO
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Update another requirements files
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Config for TF 2.0 Faster R-CNN models, refactored subgraph_between_nodes to use graph API
* Added support for new type of Preprocessing block in the TF 2.0 OD API models. Various fixes to enable the Faster R-CNN ResNet 50
* Updated text comments
* Fixed sub_graph_between_nodes for TensorIteratorMerge. Added support for the TF 2.X EfficientDet models (not yet reshape-able)
* Fixed unit tests
* Fixed regression for TF 1.X OD API SSD model, enabled TF 2.0 OD API SSD models
* Code clean up
* Switched TF 2.0 OD API Faster R-CNN to preprocessor replacement type 2
* Refactored ObjectDetectionAPIPreprocessorReplacement and ObjectDetectionAPIPreprocessor2Replacement
* Fixed bug in the Div transformation to Mul when input is integer.
* Added support for the TF 2.0 OD API Mask R-CNN
* Added unit tests for Div operation. Updated incorrectly modified mask_rcnn_support_api_v1.14.json
* Updated document with list of supported configuration files for TF OD API models
* Review comments
* Added tests for control flow edges for the sub_graph_between_nodes function
* Two more tests
* Fix missed/redundant attrs for some operations
* Align auto_pad attr values in spec
* Update MO IR Reader extenders for appropriate operations
* Allign auto_pad attr values for appropriate operations
* Remove changes in extenders
* Update backend_attrs for some operations
* Changes in shape_infer functions to correct work with explicit mode
* Apply offline comments
* fix MO cli_parser when input contains substring with matching scale/mean values
* some additions to cli_parser unit-tests
* fixed numpy array comparisons -- added assert_ prefix
* more general solution for mean/scale cli_parser, names with only digit values are processed correctly
* minor corrections
* Started to write equality comparator for StridedSlice layers.
* Now considered only unique StridedSlice consumers of non-constant data nodes.
* Fixed test for the transformation ConvertGroupedStridedSlice.
* Deleted commented code.
* Small fixes.
* Moved functions unique_by and group_by_with_binary_predicate to mo/utils/utils.py.
* Deleted function collect_sequences.
* Added asserts into the constructor of StridedSlice.
* Written test for the case when 1) there are 4 StridedSlice operations; 2) 2 of StridedSlice have the same data; 3) 2 others StridedSlice have the same data; 4) all StridedSlice operations outputs are consumed by different operations.
* Added some comments.
* Fix ElementwiseInputReshape transformation
Reshape node always needs to be inserted
in order to preserve ShapeOf nodes (reshapability of a model) that can potentially be above
elementwise node.
Refactor EltwiseInputReshape_test and EltwiseInputNormalization_test since the logic of maintaining reshape for eltwise has been changed.
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Merge EltwiseInputNormalization and EltwiseInputReshape transformations
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Remove Unsqueeze from Fused_op
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix code after code review #1
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix code after review #2
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix code review #4
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Perform full normalization based on shapes of all inputs to eltwise
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Refactor much to avoid old API and edges with unsqueeze_dims attribute
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix code after review
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Added transformation config to support automl efficientdet-4 model
* Added configuration file to convert Automl EfficientDet model
* Updated unit test for Pack
* Added instruction on how to convert EfficientDet Tensorflow model
* Updated documentation on how to convert EfficientDet model
* Updated a documentation with instruction on how to convert Automl EfficientDet.
* [MO] Add CMake install for Model Optimizer
* [MO] Update test for version.py
* [MO] Add CMake install for Model Optimizer
* [MO] Update test for version.py
* [MO] Add CMake install for Model Optimizer
* [MO] Update test for version.py
* [MO] fix file permissions for install location
* Generate TensorIterator without back edges from TensorFlow models
* Added a check in the MarkSubgraphsWithCorrectLayout to not fail when port is not connected
* Updated the 'protobuf2nx' to consume the graph protobuf message
* Cleanup TI from the IRv7 specific code
* Do not run some front transformations recursively
* Draft support for the ONNX Loop operation when 'cond' = True
* LoopToTI transformation changes
* Added draft of Loop operation and parser for ONNX Loop operation body
* Updated Loop body parser + added shape and type infer for the Loop operation
* Fixes for ONNX Loop operation parser
* Moved Loop parsing to Loop op extractor. Added generation of external edges for the Loop body ops
* Added support for ThresholdedRelu using decomposition
* Added support for Min ONNX operation
* Draft fixes for port_map generation for the Loop
* Rename transformation file and fix BOM
* Fixed shape inference for Loop scan outputs (axis is not None)
* Fixed shape inference for ONNX Loop operation
* Refactor checks in the TensorIteratorMerge transformation
* Code refactoring. Enabled commented transformations
* Documentation update for ONNX Loop, ThresholdedRelu and Min
* Fixed typo in the Loop front transformation where execution condition input is connected. Other refactorings
* Fixed in the Loop extractor
* Added printing 'internal_layer_id' attribute in the graph dumper
* Updated calculation of iterations number for the Loop
* Added missing code
* Fixed output port shapes and types generation for Loop operation
* Update function names and variable names in the Loop operation
* Fixed type inference for iteration count input
* Added removal of input/output ports of the Loop if they are not used
* Fixed renumbering Loop operations input/output ports to keep mandatory
* Fixed ThresholdedReluDecomposition transformation
* Updated MO IR Reader to know about Loop operation. But it is still not supported by the MO IR Reader
* Added unit test for Slice op shape infer (reverse the sequence of elements)
* Reverted changes in the ONNX loader function call to protobuf2nx
* Enable Reshape0DToSqueeze transformation recursively
* Refactored Loop operation support implementation
* Changed ThresholdedReluDecomposition to generate Const with shape [1] instead of scalar
* Code style and wording fixes
* Restored accidentally removed 'return' statement in the TI shape infer function
* Fixed comments
* Fixed comment
Co-authored-by: Evgeny Lazarev <elazarev.nnov@gmail.com>
