* Enable a custom build output folder
* Add the option to set a sample install directory
* Fix code style issues
* Exclude samples_bin from default build
* Make an installation directory dependent on a build type
Co-authored-by: Vladimir Dudnik <vladimir.dudnik@intel.com>
* Remove old msbuild version support
* Use cmake to build samples
* Use targets to install samples
* Use targets to install dlls: `format_reader` and `opencv_c_wrapper`
* Add `LIBRARY DESTINATION` for `format_reader` and `opencv_c_wrapper` install commands
Co-authored-by: Vladimir Dudnik <vladimir.dudnik@intel.com>
* Migrate POC for TensorFlow frontend
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Refactor InputModelTensorFlow API
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Repack POC to official API
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Remove tensorflow API from public include
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Make TF frontend work from MO and clean-up code
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Apply codestyle
* Fix win biuld
* Fix Linux build
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Implement Place class
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Determine outputs from graph
* Implement all Place classes
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Make small clean-up
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Apply code-style corrections
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Determine cut nodes
* Apply codestyle
* Rework to use places
* Fix conversion issue
* Fix build
* Fix conversion
* Small fixes
* Add test for tf frontend
* Add tests
* Implement partial conversion
* Use dynamic type in TFFrameworkNode
* Fix build on Linux
* Implement InputModelTF class
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix code by replacing InputModelTensorFlow to InputModelTF
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix to pass getPlaceByTensorName test
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Refactor and clean the code
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Finalize refactoring code
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Support freezing inputs
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Add support for pruning input ports as new model output
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Apply code-style fixes
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* move op convertors to separate files, refactoring
* openvino codestyle
* openvino codestyle
* fix crash of layer tests
* fix missprint
* Implement TensorFlow NodeContext and DecoderTFProto classes
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Switch to new NodeContext
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Remove ngraph_builder class and node_context_impl class
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Move decoder/graph_iterator to separate files and remove old files
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Document Decoder, GraphIterator, and NodeContext classes
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Apply code style
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Remove empty file graph_iterator_proto.cpp and redundant comments
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Use base class for GraphIterator in model class and correct exception class
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Use ends_with from util library
* Remain only InputModelTF constructor with GraphIterator and adopt other code
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Correct code after merge
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Apply code style
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix code based on feedback: delete extra namespace usage, etc.
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* refactoring of tf FrontEnd: rename namespaces, delete default opset
* codestyle
* fix e2e tests
* change namespaces of external classes
* resolve review comment
* codestyle
* Enable translators for Size,Shape,Rank,Range,Reshape ops
* Add translators for MatMul,Reciprocal,Square,XdivY ops
* enable Translators for Where,Log1p, Transpose, ZerosLike, Pack ops
* Enable Split,IsFinite,Tile ops, refactor Reduce ops
* Add Reverse,Round ops
* fix codestyle
* Enable Unpack, L2Loss ops
* Add LRN, GatherND, TopK ops, fix Reduce ops
* codestyle
* Revising of StridedSlice,SplitV,SpaceToDepth ops
* Add Concat,FusedBatchNormEx,Slice,SpaceToDepth ops
* Add Interpolate,BatchToSpaceNd,SpaceToBatchNd,NonMaxSuppression ops support
* codestyle
* Port CropAndResize,FakeQuantMinMaxVars,FusedDepthwiseConv2d
* fix translators
* codestyle
* Resolve review remarks
* fix wrong merge
* fix incorrect merge, refactoring
* add LeakyRelu op
* codestyle
* Add LogicalXor operation
* Add support for Swish op, set correct tensor names, refactoring
* fix incorrect merge
* codestyle
* fix unit tests
* fix build
* Refactoring
* codestyle
* fix win build
* fix reduce op
* Investigate failures on Windows
* add debug prints
* debug prints
* debug prints
* Delete debug prints
* clean up
* clean up
* codestyle
* delete debug changes
* Delete redandant comments
* rename utils functions
* rename translators
* rename layout convertors
* resolve review comments
* resolve review comments:
* codestyle
* rename NodeContext methods
* add todo comment
* Remove internal tf ops from op_table
* fix decode
Co-authored-by: Roman Kazantsev <roman.kazantsev@intel.com>
Co-authored-by: Maxim Vafin <maxim.vafin@intel.com>
* New approach to offline transformations
* Include paths fix
* Imports fix
* offline_transformations target dependency simplification
* MakeStatefulTransformation exposed to python
* Python bindings build configuration fix
* Test variable name refactor
* Stop crying (snow)flake
* Snake cased offline transformations API
* Removal of old offline transformations from python
* Imports adaptation to new code style
* offline_transformations as a part of the common wheel
* Cmake simplification and refactor
* Correct transform invocation
* CI fix
* Proper dependency check in MO
* _pyngraph as a dependency of MO in cmake
* IR serialization fix in MO
* POT adaptation to the new API
* Revert "Removal of old offline transformations from python"
This reverts commit f9a0551ead.
* Merge of old& new bindings for offline_transformations
* Revert "POT adaptation to the new API"
This reverts commit 499554e68c.
* Obsolete cmake line removal
* Missing comma and merge conflict fix
* Offline transformations tests fix
* IE imports removal from check_ie_bindings
* Installation of opevino/__init__.py fix
* Obsolete line removal
* MO serialization switched to the new API
* Revert of preliminary MO adaptation to the new API
* Another magic spell that will hopefully make CI pass
* Python api cmake dependencies reorg
* Temporary solution for the CI/cpack errors
* Installation fix and code formatting
* ie_api & pyopenvino dependency removal
* Explicit cpack configuration for the new API
* cpack configuration adaptation
* Revert of obsolete cpack changes
Co-authored-by: Alexander Zhogov <alexander.zhogov@intel.com>
* enable itt trace for AUTO
Signed-off-by: fishbell <bell.song@intel.com>
* set itt to real loadnetwork path
Signed-off-by: fishbell <bell.song@intel.com>
* refine itt tracing
Signed-off-by: fishbell <bell.song@intel.com>
* formatting
Signed-off-by: fishbell <bell.song@intel.com>
* [LPT] optimize Subtract with zero_point == 0 when it's not a direct Constant
zero_point may be a Constant, but also it may come in form of
Constant->Convert(from low to high precision) subgraph.
If we handle both cases, we can reduce redundant Subtract node
e.g. between weights and Convolution which makes Convolution
to work fully on low precision inputs which significantly improves
performance.
* don't round shift if it's already in low precision
* Fix 'cannot estimate element if precision is UNSPECIFIED' error caused by LPT
In some models after ConvMulFusion and FakeQuantizeMulFusion, output_low contains
denorms. That is problematic since LayerTransformation::getPrecisionDetails function checks
if output_low is close to zero and if it is - the function sets 'signedPrecision' flag to false.
In that case, both 'signedPrecision' and 'unsignedPrecision' are set to false and that makes
getPrecisionDetails return element::undefined.
This patch changes zeroThreshold to handle denorms.
Ticket: 65375
* fix FakeQuantizeTransformation tests
* Add test cases for PReLU in cpu plugin
* For case when slope is vector
* Add Constant template plugin reference tests
* Update CMakeLists.txt and delete constant.in.cpp
* Add tests of tensor_2constant and constant_multi_use
* Add test of constant_equality_bool
* Remove wrong comments
* Remove some of strange if
* Merge to one CreateFunction
* Remove test names and update test for types
* Add bf16 and f64 tests
* Add missing type tests
* Clear actualOutData to allow multiple use of Validate()
* Update SetUp and CreateFunction to support CentOS CI
* Remove inputData = {}
