* Do not run transformations for TF 2.X OD API models recursively (needed for models with Loop operation)
* Added anchor front transformation to group all TF OD API transformations. Added new necessary dependencies from KerasRNN transformations related to While support
* Added JSON configuration files for TF 2.4 OD API SSD and EfficientDet models
* Updated documentation with table of supported TF 2.x OD API models
* Improved visualization of the dependency graph
* Updated version of the pre-processing transformation for TF 2.4 OD API models
* Fixes in the TF 2.x OD API models conversion
* Fixed order of applying mean/scale values for TF 2.X OD API pre-processing
* Updates to the documentation
* Fixes for the preprocessor block transformation for the TF OD API models
* Added code comments
* Fixed bom file
* Unit tests for the TF 2.4 OD API ObjectDetectionAPIPreprocessor2Replacement transformation
* Code cleanup
* Updates to the documentation on how to convert TF OD API models and graph dumper
* Added assert to make sure that operations in the `get_specific_ops_with_const_inputs` has exactly 2 inputs
* Added PreprocessConversionTest tests
* Disabled tests on GPU: CVS-51764
* Disabled some tests on VPU and TEMPLATE
* Support for input layout conversions in TEMPLATE plugin
* [Plugins test] Add functional test for correct import/export support by plugins
Test suite creates number of models with various precisions.
For each model:
- If plugin doesn't support IMPORT_EXPORT_SUPPORT metric - skip the test
- Try LoadNetwork without cache enabled fails - skip the test
- Do one inference
If Load and Infer request is succeeded and plugin has import metric:
- Load network with cache enabled. Infer request and compare outputs with original infer
- Import network, perform inference. Compare outputs with previous ones
* Fix Centos build warnings
Myriad: reset executableNetwork before next load
Myriad: Reduced time consumption for Myriad tests
* Caching test suite - batch size parameter support
* Add F3Net to list of supported models
* Add instruction for F3Net model pytorch->onnx conversion
* Add new file to ie_docs.xml
* Update instruction
* Apply comments
* Apply comments
* Apply review comments
* Refactor specification
* Complete detail description section
* Rewrite mathematical formula
* Fix range of values for min and max attributes
* Add note for conversion policy between float and integral type of input tensor
* Address review comments
* Fix typo in max attribute
* Remove redundant examples
Test:
Use benchmark_app from this PR #4814
Run ./benchmark_app -h
Verify that template plugin is listed in supported caching devices
Run ./benchmark_app -m <model.onnx> -d TEMPLATE -i <file> -cache tmpCache
Verify that tmpCache is created and network is exported to blob
Verify that if model is ONNX (e.g. ResNet50) - that loading of network is performed faster when cache is available
Run several times: ./benchmark_app -m <model.onnx> -d TEMPLATE -i <file> -cache tmpCache -single_load
Verify that if model is ONNX (e.g. ResNet50) - that loading of network is performed faster when cache is available
Verify that in this mode loading of network is faster than without "-single_load" option
* Created opset7.md to add the specification of the operation FFT.
* Started to write the specification of the operation FFT.
* Added link to the specification of the operation FFT.
* Continued to write the specification of the FFT.
* Written about inputs and outputs of FFT.
* Started to write examples.
* Added example when there is no input 'signal_size'.
* Added more example.
* Small fixes.
* Small fix.
* Renamed FFT to DFFT.
* Small fix.
* Small fix.
* Started to write the algorithm of FFT.
* Added asserts.
* Started to write the method __call__ of the class of DFFT calculation.
* Fixed category.
* Continued to write the algorithm of the FFT calculation.
* Continued to write the algorithm of the FFT calculation.
* Continued to write the algorithm of the FFT calculation.
* Continued to write the algorithm of the calculation of DFFT.
* Written the algorithm of the calculation of DFFT.
* Small fix.
* Renamed operation.
* Added examples of 3D input tensors.
* Covered complex number representation.
* Written formulas for FFT.
* Written about start point of trimming.
* Small fixes.
* Small fixes.
* Some fixes.
* Added some note.
* Added a description of the calculation of the output shape.
* Added examples with unsorted axes and with (-1) in signal_size.
* Fixed range of axes indices.
* Small fix.
* Small change.
* Added T_SIZE type.
* Added negative axes support.
* Some fixes.
* Some fixes.
* Written the draft of the specification of the operation IFFT.
* Small fix.
* Renamed the operation IFFT into DIFFT. Deleted attribute.
* Renamed operation to IDFT.
* Deleted int8 type.
* Added examples of 3D input tensors.
* Added formulas and text.
* Fixed ie_docs.xml.
* Fixed sign in the IFFT formula.
* Some fixes.
* Added examples with unsorted axes and with (-1) in signal_size.
* Some fixes.
* Small fix.
* Small fixes.
* Added type T_SIZE.
* Deleted redundant sentence.
* Added support for negative axes.
* Some changes.
* Feature/vpu doc fixes 2021 3 (#4635)
* Documentation fixes and updates for VPU
* minor correction
* minor correction
* Fixed links
* updated supported layers list for vpu
* added draft version of doc for networks with state (#3372)
* added draft version of doc for networks with state
* update code snippet
* update example
* review fixes
* fixed png
* review fixes
* image fix
* minor fix
* LowLatency documentation
* apply review comments
* Apply suggestions from code review
Co-authored-by: Anastasiya Ageeva <anastasiya.ageeva@intel.com>
* review fixes
Co-authored-by: Ivan Tikhonov <ivan.tikhonov@intel.com>
Co-authored-by: Anastasiya Ageeva <anastasiya.ageeva@intel.com>
(cherry picked from commit 99c746f2c3)
* take latest changes from 2021.2
* Document TensorFlow 2* Update: Layers Support and Remove Beta Status
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Update documentation based on latest test results and feedback
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Remove ConvLSTM2D from supported layers list
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Document Dot layer without limitation
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Address feedback upon DenseFeatures and RNN operations
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Do a grammar correction
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Do a grammar correction based on feedback
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Mod operation specification refactoring.
* Add dummy broadcast_rules.md.
* Minor fixes, e.g. capitalize operation names, typos.
* Add comment about division by zero.
* Division by zero update.
Co-authored-by: jdanieck <jozef.daniecki@intel.com>
* Added support for Gelu-6 to the MO
* Adding Gelu-6 to ngraph and python API + some tests
* Fixed typo in the Gelu approximation mode
* Fixed Gelu-6 reference implementation for Tanh mode
* Added transformation to downgrade v6::Gelu to v2::Gelu
* Added specification for the Gelu-6
* Code style fixes
* The Gelu-6 operation specification update
* Fixed compilation issue in reference implementation for Gelu
* Fix compilation issues for some OSs
* Code style fix
* One more cpplint issue fix
* Fixed Gelu6 reference implementation compilation on Windows.
* Code style fix
* Fixed various ngraph unit tests
* Code style check
* Reverted Gelu-2 to be fused op
* Fixed Gelu6 downgrade transformation
* Added unit test for Gelu6Downgrade transformation
* Update copyright year
* Updated copyright year
* Replaced tab characters with 4 spaces in IR reader tests
* Code style fixes
* Added default value for GeluApproximation mode for Gelu-6 op
* Fixed code style for Gelu-6
* Changed order of parameters for the Gelu evaluate to potentially avoid backward compatibility issues with ARM plugin
* Fixed code style
* Introduced opset7. Moved Gelu6 to opset7
* Fixed non-updated transformation
* Fixed opset version in ngraph Python API for Gelu operation
* Fixed typo in the opset number in the documentation
* Reverted some changes related to Gelu6
* Updated MO to produce Gelu7
* Updated unit tests for Gelu
* Updated Gelu7 specification
* Changed gelu reference implementation. Added opset7 to Python packages
* Updated Python API tests for Gelu operation
* Code style fix
* Marked get_approximation_mode function as const
* Added missing "const" qualifier
* Fixed code style issues in tests
* Added extractor for MxNet operation Gelu
* Spelling issues fix
* Updated MxNet supported symbols
* Added NGRAPH_OP_SCOPE for Gelu7 validate_and_infer_types
* Fixed a typo in the comment
* Update spec for ADD operation.
* Change back quote for attribute name and value.
* Update link for auto_broadcast attribute.
* Move detailed description section, add suto_broadcast attribite to examples.
* Remove github link in numpy attribute description and replace it with local link.
* Add brodcast_rules.md for specific broadcast rules.
* Add new line at the end of broadcast_rules.md, modify font for add inputs.
* Change link for Broadcast_1.md
* Add description of broadcast in broadcast_rules.md
* Correct output shape description.
* Add bidirectional broadcast description and new examples.
* Add description for auto_broadcast types: None and PDPD.
* Add examples for pdpd and bidirectional broadcasts, add pdpd attributte for Add, modify Broadcast ops to refer broadcast_rules file.
* Duplicated 'openvino_docs_ops_broadcast_rules' label change.
* Add example with scalar for bidiretional broadcast.
* Add new lines for examples.
Helena Kloosterman
Alexey Suhov
Anton Chetverikov
Evgeny Lazarev
Ilya Lavrenov
Anton Pankratv
Alina Alborova
Patryk ElszkowskiandPatryk Elszkowski
Ivan TikhonovandAnastasiya Ageeva
Katarzyna Mitrus
Pavel EsirandTatiana Savina
Maxim VafinandTatiana Savina
Mikhail Nosov
Jozef Daniecki
Gabriele Galiero Casay
Maksim Derbasov
Vladimir Gavrilov
Andrey Zaytsev
Bartosz Lesniewski
Maxim ShevtsovandAlina Alborova
Anastasia PopovaandAnastasiya Ageeva
Svetlana Dolinina
Ilya Churaev
Roman Kazantsev
