* Revert "Fixed 3 naming issue"
This reverts commit a92d3cfff5.
* Revert "Fix CC issues for transformation and snippets"
This reverts commit d08a3f5aac.
* Fix NGRAPH_PASS_CALLBACK issue to make it can work
* Fix matcher name missing issue
* multiclass_nms opset9 spec, api, reference, paddle fe mapper, paddle fe unittest.
* multiclass_nms opset9 cpu node impl.
* multiclass_nms opset9 shape infer fix.
* multiclass_nms opset9: add transform ConvertMulticlassNms8ToMulticlassNms9.
* ConvertMulticlassNmsToMulticlassNmsIE: to MulticlassNmsIEInternal
* add test dependency package paddledet==2.1.0
* 1. fix for roisnum overflow. 2. common shape_infer private function.
Signed-off-by: jialipen <cecilia.peng@intel.com>
* 1. use common infer_shape helper. 2. fix roisnum overflow issue. 3. fix for nmsWithEta.
* test suite for opset9 multiclass_nms smoke tests pass, with both static and dynamic shapes.
code clean for unit test.
* decouple specification from this PR.
* op fuzzy: dynamic input/output
* reference impl refactor
* multiclass_nms_base no need clone_inputs.
* code clean
* restrict ppdet import
* fix clang format error
* change ppdet import to resolve CI fail issue related to its dependency.
* fix CI
* refactor: multiclass_nms_shape_inference for opset9 and reference impl.
TODO: could be applied to opset8 and even matrix_nms.
* fix CI build failure.
* CI fix for ambiguous namespace reference issue when
building static libs.
* update nms save_model python scripts.
* dynamic inputs for NMS with CPU plugin.
* copyright header for test scripts.
* op comformance test for multiclass_nms_9.
* minor update: is_type
* python opset9 and multiclass_nms
* flake8 CI fix
flake8 CI fix
flake8 CI fix
* remove NmsBase. stage1.
flake8 CI fix
remove NmsBase. stage 1 fix.
* rm NmsBase. stage2.
* more multiclass_nms prop tests and fix.
* remove unchanged ops from binding opset9.
* dependcy of paddle_tests.
* fix: add MulticlassNms to op mapper.
* clang format fix
* fix merge error.
* roi_align_9: ov_core, transformations, template_plugin
* roi_align_9: CPU Plugin
* keep only constructor with enums which is aligned with spec
* remove evaluate function for ROIAlign_9
* Add op check test for operation ROIAlign-9
* Apply suggestions from code review
* fix version name from 'v0' to 'v3' in transform part
* use common shape_infer function for v3 and v9
* remove'tf_' prefix for ROIAlign::AlignedMode to avoid misleading for models from different platforms
* Try to improve gflags
* Try to improve gflags: part 2
* Tried to use dependencies on system
* Use nlohmann_jsonConfig from system
* Enabled nlohmann_json from system
* Improvements
* handle system gflags in developer package
* Simplifications
* Simplify dependency management
* Corrected package names
* Fixed subgraphsDumper configure stage
* Try to fix rhel8
* Try to fix macosx
* Fixed VPUX build
* Fixed aliasing issues
* Suppress some wanrings
* export gflags when build it
* Fixed some LTO
* Try to fix Mac
* revert
* use gflags as private dependency
* Aligned targets in developer package
* Fixed frontends tests build on U20 with LTO
* PAssed
* Don't use pkg_search_module(zlib ..) during cross-compilation
* Removed unused variables
* Fixed finding of zlib during cross-compilation
* added recursive run for transformation to fix fp16 IR with Interpolate inside If
* added test for interpolate inside If
* remove useless variable
* fixed transformaion for divide
* fix code style
* commit auto change
* review fix
* add test for recursive call of divide marks
* removed empty line
* revert previous version of convert_seq_to_ti transformation
* try to check that outputs of TI are connected to Result nodes
* add unit tests
* fix codestyle
* fix Memory tests
* revert local change
* revert local change
* replace duplicated code with lambda
The change fixes FQ fusions for subgraphs like 'Const weights'->FQ->Transpose->Multiply.
After PullTransposeThroughFQUp transformation, we end up with following:
'Const weights'->Transpose->FQ->Multiply. Because of the Transpose on first
FakeQuantize inputs, Multiply could not be fused since FakeQuantizeMulFusion
expected that weights is a Constant node.
Ticket: 77785
Transformation insert Transpose for MatMul's weights and
sets its transpose_b attribute to true.
If executed by MO, it helps to reduce LoadNetwork time on CPU plugin,
since ConvertMatMulToFC doesn't have to insert Transpose by itself.
Ticket: 78635
* [CPU] Add transformation that aligns elementwise input ranks
* fix tests - check also aBcd16b format
* add support for fq
* add test for sqr diff
* move to moc transformations
* fix tests
* align only for numpy autobroadcast type
* fix fetching autob from fq
* [CPU] Eltwise tests corrected & callback for CPU removed
* remove transformation callback call
* revert changes to getMKLDNNOutputMemoryFormats
* remove comment
* use single wrap_type
Co-authored-by: Vladislav Golubev <vladislav.golubev@intel.com>
Tomasz Dołbniak
River Li
Ilya Lavrenov
Mateusz Bencer
Tingqian Li
Chenhu Wang
Tetiana Gubanova
Artur Kulikowski
Katarzyna Mitrus
cecilia peng
Tomasz Jankowski
Jan Iwaszkiewicz
Bo Liu
Mateusz Tabaka
Vladislav Volkov
Svetlana Dolinina
Gleb Kazantaev
Vladislav Golubev
Ivan Tikhonov
Ilya Churaev
Nadezhda Ageeva
Mikhail Nosov
Evgenya Stepyreva
Pavel Esir
Vladimir Zinoviev
Maksim Derbasov