* Tensor accessor for shape inference
- as functor for getting data from tensor vector or map.
- as lambda in GPU plugin on tile op
* Make tensor data adapter pure virtual
- function accessor to data returns pointer to interface
* Refactor tensor data accessor and adapter
* Extract memory adapter make it GPU graph internal
- can't be part of GPU runtime memory core dev API not visible there
* Expand IStaticShapeInfer by port map
- update factory map for new infer interface with port map information
- add bit util to generate bit mask use it in PortMask
* Pass tensor accessor as reference not fun object
- Add cldnn data adapter and accessor
- Reduce dynamic allocations in data accessors
* Fix compilation issues
* Use ov::Tensor for data accessor
- remove data adapters are they not required
* Update comments
* Fix build issues
* Fix tile shape infer test
* Add empty null tensor accessor as specialization
* Apply style formatting
* Move data accessor from dev API to shape inference
* Fix linking issues
* Review ROIAlign for shape inference aspects:
- Check interval shape and label propagation
- Check template implementation of shape_infer
- Add unit test for static and dynamic shapes
* Update ROIAlign::evaluate to use ov::Tensor
- remove ngraph namespace from op where possible
* Review PriorBox op for shape inference aspects:
- check interval shape and label propagation
- check preserve interval values and labels on inputs
- add template shape_infer function
- add/update test for dynamic and static shape inference
* Update PriorBox evaluate to use ov::Tensor
- remove ngraph namespace form PriorBox where possible
* Review PriorBoxClustered for shape infer aspects
- check interval dimension and label propagation
- check preserve partial values and labels on inputs
- add template implementation of shape_infer
- add/update test for static and dynamic shapes
* Use correct shape for PriorBox transformation test
* PriorBoxClustered evaluate use ov::Tensor
Remove ngraph namespace from op where possible
* Fix compilation issues
* fix coverity issue in concat
Signed-off-by: Hu Yuan2 <yuan2.hu@intel.com>
* fix coverity issue in graph_optimizer.cpp
Signed-off-by: Hu Yuan2 <yuan2.hu@intel.com>
* fix review issue
Signed-off-by: Hu Yuan2 <yuan2.hu@intel.com>
* fix the mistaken that there are two throw
Signed-off-by: Hu Yuan2 <yuan2.hu@intel.com>
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Signed-off-by: Hu Yuan2 <yuan2.hu@intel.com>
* [CPU] Add CPU plugin specific properties to supported_properties list
* Add tests and move cpu specific tests from shared_tests_instances
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Co-authored-by: Anton Voronov <anton.voronov@intel.com>
* [LPT] reused reference FQ implementation in fold_fake_quantize
* [LPT] Removed legacy parameters
* Added plugin tests with per-channel FQ for GrConv wo reshape
* Apply folding only in the case when FQ data input is constant
* EliminateFQ fix
* add _streams_info_table in Executor config
* change useHyperThreading init value
* restore cmake
* fix comments
* add calling enableCpuPinning property
* fix judgment about number of sockets in init_stream
* fix test case compile issue
* fix ci test case fail issue
* modify GetPerformanceStreams calling position
* add affinity in get_cpu_pinning
* modify ecore judgement
* add no binding core on ADL
* fix ci issue, add get_num_numa_nodes()
* fix code style
* fix StreamsHasHigherPriority issue
* fix according to comments
* fix performance degression
* fix code style
* code style
* fix warning
* fix ci test failed
* fix ImportNetwork issue
* fix ci test case issue
* fix smoke_CachingSupportCase_CPU issue
* add ExportOptimalNumStreamsTest test
* modify test name
* modify ExportOptimalNumStreams test
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Co-authored-by: Chen Peter <peter.chen@intel.com>
* Intermediate state
* Remove old dyn batch path in the new api
* Remove legacy dyn batch support
* Remove dyn batch support field from the config
* Revert changes to the common part
* Revert accidental change in the test file
* Minor fixes
* Fix support for dyn batch without setting current
* Typo fix
Pawel Raasz
Edward Shogulin
Chen Xu
Nikolay Shchegolev
Yuan Hu
Sofya Balandina
Egor Duplenskii
Ilya Lavrenov
Nesterov Alexander
Vladislav Golubev
Chenhu Wang
Alexandra Sidorova
Luwei Zhou
Mateusz Tabaka
Aleksandr Voron
Sun XiaoxiaandChen Peter
Maksim Kutakov