* Enable low precision types for ConvertLike operation
* Migrate backend unit test suite to template plugin reference tests
* Fix typo in naming convention
* Avoid duplication of template plugin tests execution
* Add file to instantiate TEST_P and avoid test execution duplication
* revise tan op
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* update doc
add examples in desciption
add the unit of measure
clear input type
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* add template plugin test case for int type
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* add template plugin test case for uint and float
remove the float test in backend
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* modify document
change type to any supported numeric type
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* fix compile error in openvino-lin
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* Add input image scale flag in benchmark app.
- user set input image scale with -iscale.
input is divided by scale.
Signed-off-by: hyunback <hyunback.kim@intel.com>
* Apply image scale, mean parameter in benchmark APP
Means and sacles values per channel
Signed-off-by: hyunback <hyunback.kim@intel.com>
* Fix clang-format
Signed-off-by: hyunback <hyunback.kim@intel.com>
* fix clang-format issue2.
Signed-off-by: hyunback <hyunback.kim@intel.com>
* Update benchmark tool to align the format of mean and sacle values with MO arguments.
Signed-off-by: hyunback <hyunback.kim@intel.com>
* Remove debug print.
Signed-off-by: hyunback <hyunback.kim@intel.com>
* Refactor NopElimination; Execute NopEliminatoin inside MOC Backend
* Add missing header
* Refactor tests; use weak_ptr to avoid excess consumers for node
* Add test to check number of shared_ptr usages for graph nodes during Manager execution
* Remove AlgebraicSimplification forewer
* [clDNN] Handle negative axis in concat op
That enables following models for onnx importer path:
yolact-resnet50-fpn-pytorch
yolact-resnet101-fpn-pytorch
yolact-darknet53-fpn-pytorch
swin-tiny-patch4-window7-224
action-recognition-mkinetics-res34-mhsa
driver-action-recognition-adas-0002-decoder
horizontal-text-detection-0001
* Add tests for negative axis in Concat op
* Separate executable for paddlepaddle unit tests
* Fix CI
* Move PaddlePaddle-specific python requirements to paddlepaddle test folder
Also produce build time warning when paddle test models generation is disabled
* Renamed back PADDLE_TEST_MODELS_DIRNAME to TEST_PADDLE_MODELS_DIRNAME
* Add dependency on CPU plugin (PaddlePaddle fuzzy tests use CPU plugin for inference)
* Fix code style
* Fix review comments #2
* Code style fix
* Add dependency of 'paddlepaddle_test_models' to 'test_model_zoo'
* update spec, add visitors, backend test
* remove visitors test as it is implemented in another PR
* remove visitors test from CMakeLists
* remove old backend tests, refactor minor parts of the code
* add namespace
* refaactor template test for less_equal op
* update docs
* add host tensors validation
* create type_prop tests
* create serialization single layer test
* create visitor test
* create op_reference test
* add logicalAnd to constants.py
* create additional op_reference tests
* add check for number of visited attributes in visitor test
* update auto_broadcast description
* remoove backend test
* update LogicalNot params name
* remove backend test from CMakeList
* create util function for type_prop tests
* update op_reference tests
* remove typo in docs
* remove unsupported types from evaluate
* fix bug in op_reference test
* refactor visitor test
* update math formula in the spec
* update has_evaluate types
* Moved current IE API to separate folder
* Fix install
* Fix documentation
* Fixed install path
* Try to fix CI
* Changed installation path
* Use ONNXRuntime rel-1.8.1 version
* Initial version of v8::MaxPool op class
* Type instead of Type_t to indicate element type
* Attribute visitor test
* Common MaxPoolBase base class
* More refactoring
* v8::MaxPool cleanup
* Pooling ops inference helper extension - window dilation
* New MaxPool 3D type prop tests
* Common part of MaxPool validation part extracted to the base class
* MaxPool-8 shape inference with base class utils
* infer_batched_pooling_forward arguments reorder to avoid compilation errors
* Align the rounding type attribute name for both MaxPool version
* MaxPool-8 axis attribute
* Missing attributes
* Code formatting
* PR feedback
* MaxPool-1 RTTI definition adjustment
