* [MO] Upgrade TensorFlow version dependency due to SNYK hits
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Still use 2.5.0 TensorFlow for Python 3.6 and older
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* handle 'and' marker in requirements
* Revert "handle 'and' marker in requirements"
This reverts commit 952bb949ca.
* moved importlib-metadata from requirements.txt into setup.py
* fixed version comparison: for comparsion extracted hashes are used
* shortened 7 -> 11 to match the current version fromat from nightly
* corrected regex, added comparing by minimal hash len
* forced split argument dtype to int
* added unit-test
* fixed typo in split_test.py
* set explicitly np.int64 instead of np.int
* use split_length's dtype
* Update LSTMSequence backend_attrs
* Add missed attribute clip
* Update backend_attrs for all *sequence operations
* Add extender for GRUSequence
* Add GRUSequence to custom ops list
* use has_and_set instead if direct acces to attributes
* Add sqrt extender
* Update check to not use default infer in infer was set before
* Update comment
* Fix comment
* Remove Sqrt extender
* Remove unnecessary changes
* Add MO implementation of SQRT operation
* Added compatibility check of layout with partial shape
E.g. layout "NC" in not compatible with PartialShape{1,3,224,224}
Check is added:
- For parameter set_layout
- For parameter set_partial_shape
- For result set_layout
- Checked also compatibility for all results after 'validate_and_infer_types'
* Fix incorrect tests
* Fix of more incorrect tests
* Removed couple of obsoleted error-handling tests - these are catched now on earlier stages
Co-authored-by: Ilya Lavrenov <ilya.lavrenov@intel.com>
* Check the selected frontend to correspond use_new/legacy_frontend options
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix a default case when no frontend is found
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Added op names to tensor names for MaskRCNN replacement transformation. Fixed output layout for MaskRCNN.
* Applied commentes left from PR with tensor names fix.
* Added tests for remove_tensor_names().
* Added checks in emitter.
* Removed debug output.
* Small fix.
* Small fix.
* Fixed tensor names setting in InputCut, fixed tensor names losing in AutomlEfficientDet.
* Changed op name adding to tensor names in InputCut for output port case only.
* change order of transformations to work correctly with Convolutions in Kaldi LSTM networks
* removed unneeded changes and add unit tests
* remove comment
* remove changes from memory_offset_adjustment, move all fixes inside add_reshape_transpose_around_conv_pool to avoid new bugs
* removed test for deleted changes
* replace -1 by None
* Correct Loaders for TensorFlow StridedSlice and Pack operations
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Supress INFO and WARNING messages from TensorFlow
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Detect casting node inside preprocessing block and leave it
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix unit-test for ObjectDetectionAPI
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* grouped convolution resolver fix
* add reverse_infer for Transpose, Elementwise, Identity and some fixes to successfully OOB convert MXNet models
* add reverse_infer for BatchNorms, dynamic groups fix, multi_box_prior.py fix
* add reverse infer for trivial cases
* input rank setting for image detection ops
* reverse_infer for Gather, AttributedGather add todo comment for Parameter
* reverse infer for LSTM, swapaxis; fixes and unit-tests for Elementwise, Gather, Transpose; also generalized Parameter reverse_infer; fixed DetectionOutput and partial reverse_infer
* clarified comment for LSTM reverse_infer
* detalized Elementwise reverse_infer, added several more unit-tests, Split reverse_infer fix, IteratorGetNext_ext.py fix
* generalized group convolution resolver
* specified in_ports explicitly
* clarified Split, Concat, Parameter, other minor typos
* relaxed compatibility check for elementwise; simplified scalar extracting for convolution.py and gather.py, fixed replacer order for ConvolutionNormalizer.py
* added routine set_input_shapes for image detection ops
* fixed typos to pass locally E2E, slightly changed LSTM reverse_infer
* VariadicSplit reverse_infer bugfix
* IteratorGetNextCut.py added check if port is connected
* explicitly specified in_port, added asserts, improved Split reverse infer
* sorted imports
* reverse_infer for ONNX and MXNet LSTM, GRU, RNN operations
* replaced Error raising with red warning
* added missing return for defined input shapes, fixed getting num groups for tf conv
* added mandatory attributes; fixed failing unit-tests, fixed typo with scalar group in ConvolutionNormalizer
* removed priorbox reverse_infer; Parameter reverse_infer corrected to use the only one existing out_port
* fixed clarify_partial_shape_test
* Preserve outputs order TF.
* Preserve of input/output indices for MxNet.
* Small fix.
* Added check.
* Small fix.
* Corrected Keras model importing.
* Fixed Keras model loading.
* Small correction.
* Corrected model loading.
* Small fix.
* Comment corrected.
* Removed unnecessary import.
* Preserving of input/output indices for ONNX.
* Fixed checks.
* Fixed for case of multiple outputs of node before Result.
* Added test for multiple tensor names before Result.
* Multiple tensor names before Result fix.
* Added order alignment for user input/output.
* Extended for case of input names in Parameter tensor list.
* Fixed unit tests.
* Corrected help.
* Small correction.
* Code refactoring.
* Temporarily reverted refactor.
* Fixed wrong changes.
* Fixed wrong changes.
* Returned reverted refactoring.
* Removed inputs_list from serializing.
