* Added nGraph Python API for operations DFT and IDFT.
* Written tests for the DFT Python API.
* Written tests for IDFT nGraph Python API.
* Small fixes.
* Started to add tests for the signal_size case.
* Written tests for signal_size case of DFT.
* Written tests for signal_size case of IDFT.
* Some code style fixes in IDFT nGraph Python API tests.
* Code style fixes in tests for DFT nGraph Python API.
* Now DFT nGraph Python API tests are used numpy FFT ressults as expected results of tests.
* Now IDFT nGraph Python API tests without signal_size are used numpy FFT result as input data.
* Now IDFT nGraph Python API tests use numpy IFFT as expected results for signal_size cases.
* Deleted redundant function.
* Formatting fix.
* Now test data for DFT and IDFT nGraph Python API are randomly generated.
* Added seed initialization.
* update tanh v1 spec
* Apply review suggestions
* add rounding info
* Move Tanh to activation functions
* reorganize spec and add rounding rule for integers
* back to arithemtic functions
* Update `short description` to adjust with new EW description template
Co-authored-by: Patryk Elszkowski <patryk.elszkowki@intel.com>
* Removed transformation which removes Const->Result sub-graphs
* Removed one more MO transformation which removes Const->Result sub-graph during the front phase
* Use Serialization as a default engine in MO
* Added cmd option to use old serialization
* Added mapping file generation
* Test mapping file generation
* Fix setBatchsize parameters order; fix mapping file generation
* Added FrameworkNode; added method to read models with custom ops but without extensions
* Added python API for read_network_without_extensions function; updated mo not to use IECore
* Added read_model_without_extensions to IReader and IParser
* Fix V7 IR reader
* Fix pword value
* Fix dllexport macro usage
* Add metainfo to IR
* Fix nGraph code style
* Fix license header
* Restore prepare_emit_ir behaviour
* Fix compare_function to resolve situation when Result input port has multiple names
* Update Compare Functions
* Fix FrameworkNode validation
* Self-review
* CodeStyle check
* --use_fallback -> --use_legacy_ir_generation
* Sort imports in main.py
* --path_to_model -> --input_model
* Use logging instead of print
* Code simplifucation&cleanup
* Fix offline_Transformations key
* Fix GeneraeMappingFile comments
* Use Extension approach to work with custom ops
* Fix versions check
* Code clean-up
* Moved FrameworkNode to inference_engine_transformations library
* Fix FrameworkNode includes
* Code clean-up
* Extend blobs dumping with filtering by environment variables
The idea is to dump blogs without rebuilding
We cannot just use environment variables without compile-time flag
because of security flaws.
Instead, it is expected that developers just always set additional
macro (BLOB_DUMP_PATH) which is not set for the production builds:
export CXXFLAGS="-DBLOB_DUMP_PATH=\\\"mkldnn_dump\\\""
This macro activates blob dump filtering using environment variables.
To prevent unnecessary dumping, blobs are not dumped by default even
if macro is defined.
* Extend nGraph Python API and test IE IR reader for Einsum
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Format description for test auxiliary function
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Remove print from the python test
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* [cldnn] Add initial fused conv eltw POC
- Add cldnn unit test
- Add fused dependency list to the fused_primitive_desc
- fuse_nodes update for saving fusing history and depenecies
- Modify Jitter to create jit constants using fused dependencies
- Add cldnn unit-test cases for multiple serial and parallel eltwise fuse pattern
- Modify Jitter and add default values in sum input
Signed-off-by: Ahn, Paul Y <paul.y.ahn@intel.com>
Co-authored-by: Andrew Kwangwoong Park <andrew.kwangwoong.park@intel.com>
* [cldnn] Update fused_conv_eltwise cldnn unit test
- Add execute and compare function
- Add cldnn unit-test case for multiple parallel eltwise and additional eltwise
- Add cldnn unit-test case for combination of multiple parallel eltw
- Add cldnn unit-test cases for serial and diverged quantize and eltwise
Signed-off-by: Andrew Kwangwoong Park <andrew.kwangwoong.park@intel.com>
* [cldnn] Modify checking fusibility of eltwise fusing
- Add new checking fusibility rule in prepare_primitive_fusing
- Move cldnn eltwise fusing test to fusing_gpu_test.cpp
- Modify method to get input var name in jitter
Signed-off-by: Ahn, Paul Y <paul.y.ahn@intel.com>
* [cldnn] Fix fusing item type and activation fusibility checking condition
- Extract input_data_supports_fusings from fuse_activaion_f
- Fix checking supported mode bug
Co-authored-by: Andrew Kwangwoong Park <andrew.kwangwoong.park@intel.com>
* Fixed preprocessing for template plugin
* Added more tests instances
* Split common transformation to smaller ones which can be used by plugins
* Moved preprocessing transformation to Plugin API
* Added PreprocessConversionTest tests
* Disabled tests on GPU: CVS-51764
* Disabled some tests on VPU and TEMPLATE
* Support for input layout conversions in TEMPLATE plugin
* Improvements in Template Plugin
* Fixed compilation
* Fixes
* Disables some tests
* Fixed compilation on Windows
* Fixed docs
* Small refactoring in TEMPLATE plugin
* Fixed compilation on Windows
* Fixed code style
* Hide CALL_STATUS_FNC helpers to private API
* Moved some base classes to private place from plugin_api
* Updates for VariableState creation
* Take Jane's changes for Demension names
* Revert "Take Jane's changes for Demension names"
This reverts commit 9f6c8fa5a6.
* Removed ICNNNetwork include
* removed more icnnnetwork includes
* Added missed include with ie_input_info.hpp
* Fixed GNA plugin to provide names w/o \0
In linux, without malloc_trim, some freed memories are not being returned to system.
Current hypothesis is that a large allocation for compilation is not completely freeed, thought mostly freed.
This does not happendin Windows.
So, added malloc_trim for linux build until we figure out a better solution.
* initial changes (IR not generated)
* extractor fix
* convert tdnnf (with correct infer)
* refactoring + comments in code
* added unit tests + couple fixes based on tests
* change order for old convolutions
* fix pylint
* small refactoring
* added if to remove changes in old irs
* doc updated
* fix layout and kernel shapes for old convolutions
* fixed test
* moved test
* fix import in test
* fixed backward compatibility
* review fixes
* [PP] FLuid level tests for mean value preprocessing
* PP] Fluid operations for mean value preprocessing
* * Relaxed tolerance and fix for issue.
* * Fix for issue.
* * Applied comments.
Co-authored-by: Anton Potapov <anton.potapov@intel.com>
