* Enable CoreThreadingTestsWithIterations tests for GNA
Sync rest of GNA Lib API,
Sync Config for MT tests
Change models in CoreThreadingTestsWithIterations to be compat with GNA
* Use parameter for model set selection
* Fix style
* Disable HETERO CoreThreadingTestsWithIterations tests and create issue 45658
* Initial support of GatherElements in MO and nGraph
* apply_style
* added lost extractor for GatherElements
* Corrected GatherElements::validate_and_infer_types
* updated package_BOM.txt
* Type_t added
* started to implement ngraph shape_type_infer unit-tests
* finally implemented all ngraph shape_inference unit-tests
* updated Supported_Frameworks_Layers.md
* added correct handling of dynamic shapes in nGraph, added unit-tests for dynamic cases, fixed dump typos in MO, replaced axis type from int -> int64_t
* implemented shape infer for dynamic shapes with intervals
* finalized MO implementation
* applied comment from review
* style-apply
* spec correction
* removed conflict
* fixed typos
* removed obsolete comments form type_prop
* significant corrections in validate_and_infer_types
* style-apply
* data_rank check for axis
* Resolved problems with ssd_resnet34_1200
* removed debug code
* Added correct handling onnx nodes from parent graph scope
* removed unnecessary include
* fixed calcution index to replace
* fixed LoopParentParametersUsedInBody test
* added set_friendly_name
* apply Unsqueeze for each concatenated Loop output
* added handling trip count with value max_int
* merge from upstream/master
* update xfail list
* added checking is trip_count is constant
* 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
* Add spec for CTCGreedyDecoder
* Update spec
* Fix spec according to code rewiev
* Update spec
* Update spec
* Update spec according to review
* Update spec
* Update spec
* Update spec
* Update example spec
* Fix space in spec
* Fix spec
* Fix spec according to review
* fix spec
* update spec
* Update spec
* Change format outputs in spec
* Hot fix
* Minor fixes
* Add new attribute for op in spec
* change input
* Add precision to outputs
* Fix input in spec
* Update spec
* Update CTCGreedyDecoderSeqLen_6.md
fix mistakes
* Change first input layout
* fix example
Co-authored-by: Your Name <you@example.com>
* remove avgpool op from layer creator
* remove binaryconvolution op from layer creator
* remove broadcast op from layer creator
* remove ctcgreedydecoder op from layer creator
* remove stridedslice op from layer creator
* remove convolutionbackpropdata op from layer creator
* adjust broadcast op to deduce broadcast mode
* add default strides if not provided when creating stridedslice
* code review comments
* Fixed tests compilation for Android ARM
* Small fixes
* Fixed issues CVS-44775, CVS-34206, CVS-34349
* Disabled KSO tests for Template
* Eliminated invalid subgraphs
* Enabled KSO QueryNetwork tests for Template
* Fixed other plugins as well
* Used NodeTypeInfo instead of std::string
Co-authored-by: apankratovantonp <anton.pankratov@intel.com>
* Revice DetectionOutput reference implementation
Ticket: 37433
* fix test_create_op
* fix test_dyn_attributes
* apply code format
* fix crash on Windows when variance_encoded_in_target == 1
* add more checks for DetectionOutput inputs
* Fix single layer tests
* apply code format
* fix ssd_vgg16_300 inference with batch size > 1
* update types in docs
* fix crash on windows
* apply code style
* fix python tests
* fix setting output type
* change False to false and True to true in docs
* Allow prior boxes to have different type than box logits
Some models work that way
* simplify output shape calculation
* fixes to docs
* initial commit
* initial commit
* move fix to tf conv_extractor
* added 3d case
* fix e2e with 3d conv
* remove 3d case
Co-authored-by: yegor.kruglov <ykruglov@nnlvdp-mkaglins.inn.intel.com>
desired format
changed InferRequestInternal:
- added _deviceInputs member to store plugin desired perprocessing
targets
- added default argument to preProcessingRequired to describe plugin
specific desired preprocessing target
- SetBlob and GetBlob to deal with plugin desired preprocessing targets
(_deviceInputs)
- added addInputPreProcessingFor helper method to avoid code
duplication
changed TEMPLATE plugin to use new functionality:
- removed explicit presicion conversion (to use built-in one of
InferRequestInternal)
- _networkInputBlobs to use InferRequestInternal::_deviceInputs
changed PreprocessingPrecisionConvertTest:
- to force output precision to be same as input (and not FP32 always)
changed TEMPLATE plugin to allow U8 outputs
