* [MO] Clean-up MO cmd-line options
Remove the following Model Optimizer deprecated options that are no longer used for several releases: disable_fusing, disable_gfusing, generate_deprecated_IR_V7,
legacy_ir_generation, keep_shape_ops, move_to_preprocess
Deprecate through CLI the following options for which functionality triggered from POT or automatically: disable_weights_compression, disable_nhwc_to_nchw,
disable_resnet_optimization, finegrain_fusing.
Correct and extend description of each MO option to be printed during model conversion.
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Correct documentation about input shapes
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Perform final corrections in documentation
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Remove legacy_ir_generation overall
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Clean-up tests from deprecated options
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Recover disable_fusing option as deprecated
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix keys for static_shape and extensions
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Remove extension key that does not work
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Apply feedback: remove disable_gfusing, correct docs
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Recover disable_fusing option for unit-tests
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Apply feedback for documentation
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Apply feedback about parameters use_legacy_frontend and use_new_frontend
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* DO minor fixes for indentation of MO logs
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Revert log.error for fallback message
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Revert disable_weights_compression parameter for tests
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* 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
* 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>
* 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.
* 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
* 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.
* changed permutes
* fixed permutes
* fixed kernel
* fix transpose after convolution
* fix for convnet
* insert transposes for all convolutions and poolings
* refactor transformations;
added unit tests;
removed old transformations for addinf permutes/reshapes
* fixed constant types
* fixes after merge
* fixed bug for rm_cnn4a: added correct time_dim for the first convolution
* added fix for timeheightconvolution: in this case we have correct time set in convolution kernel already
* minor review fixes: renamed transformation and file
* rename in test
* rename in test
* sort imports + couplt changes in comments
* review fixes: refactoring
* replaced recursive implementation by nx.topological_sort;
fixed comments
* minor fixes: comment + preserving node names
* Updated requirements for MO and POT with telemetry.
* Added mock telemetry common class for unit tests.
* Used mock telemetry in preprocessing unit tests.
* Small correction.
* Fix in the transformation PreserveRuntimeInfo: now Transpose is inserted before input port 0 of Result only, not after data node of layer before Result layer.
* Deleted commented code.
* Added more tests for the MO transformation PreserveRuntimeInfo.
* cli_parser.py fix to accept scalar value for freezing
* update cli help
* fixed unit-tests, clarified help for specifying data type
* typos correction
* Enable new FP16 format and support mixed precision
* Apply review comments
* Fix issue with fp64 in FakeQuantWithMinMaxVars.py
* Enabme decompression converts fusing for CPU plugin
* Apply review feedback
* Fix code style
* Fix issue with np.full and apply review feedback
* Apply review feedback
* Fix HardSigmoid onnx extractor
* Replace np.arrays that were skipped with mo_array
* Fix compress_quantized_weights_test.py
* Fix import issues
* Apply review feedback and fix type of fusing linops in MO
* Apply review feedback
* Fix types for Mean/Scales and MXNET zeros
* Add RandomUniform_8 to ConvertPrecision
* Fix merge issue
* Fix consts names collision in GPU plugin
* Squashed commit of previous work
* Fix mock tests
* clang
* Fix rebase errors
* remove unnecessary changes
* One more finding
* Copy ov::Model runtime info as well
* Fix review comments
* Commit missing file
* Copy m_shared_object when cloning model
* removed copy_shared_objects and use clone_model(model, NodeMap) as a friend for ov::Model
* Added OPENVINO_API to forward declaration
* add OPENVINO_API to friend function declaration
* Fixes in the infer function of MO operation Select.
* Fixes in the nGraph transformation SharedShapeOf.
* Deleted commented code.
* Added more tests for the infer function of the MO operation Select.
* Started to write tests for the transformation SharedShapeOf.
* Added more tests.
* Now the transformation can correctly process a mix of opset1::ShapeOf and opset8::ShapeOf.
* Small change.
* Used opset1 and opset3 instead of opset1 and opset8.
* Used get_output_element_type(0) instead of checking the version of ShapeOf.
* Remove some legacy targets
* Replace some targets
* Removed inference_engine_plugin_api dependency
* Minor comment for developer config
* Fixed include paths
* Small fixes for static build
* Try to fix build pyopenvino
* Fixed comments
* Try to fix build
* Include OpenVINODeveloperPackage inside InferenceEngineDeveloperPackageConfig
* Try to fix GAPI tests
fixed return of results from transformation for case of not 1 added result (last node with several out ports)
modified test to cover case with several output ports for last node
