* [IE Samples] Activating new parameter is compact mode(memory_reuse) in speech sample
* changed format
* renamed the option to memory_reuse
* renamed the option
* DynamicShapeResolver is able to save information about dynamic output in order to pass it in INFER_DYNAMIC_SHAPE mode. Previously, it propagated fully dynamic output shape (however ranks were equal) and dynamic Convolutions and Poolings were performed incorrectly. Now in the case of dynamic batch, DSR propagates only dynamic batch and Convolutions and Poolings are performed properly as a Loop of single-batch operations.
* Fixed dynamicToStaticShapeTranspose transformation. There was a bug: transposition indices could not be applied with Scatter because the formula is not applicable for this. Replaced with Gather.
i.e. Shape of output tensor of Transpose with transition [0,3,1,2] indices (NHWC [1, 224, 224, 3]->NCHW [1, 3, 224, 224]) was calculated by ScatterElementsUpdate. So output_shape[transposition[i]] = input_shape[i] and the result was output_shape=[1, 224, 3, 224] which was wrong. Vise-versa Gather does output_shape[i] = input_shape[transposition[i]] and the result is [1, 3, 224, 224] which is right.
* MaxPool and AvgPool can be sliced for loop in case of dynamic batch
* Convert stage for inputs is not inserted in the VPU model in the case of OV API 2.0. It did not cause a problem with non-dynamic functions because Graph Transformer has a pass to eliminate redundant converts (u8->f16, ~f16->f16~). In the case of dynamic inputs, yet another inserted Convert breaks data<->shape relations.
* 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
* [MO] Support TensorFlow Grouped Conv2DBackpropInput
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Correct computation of group number for ConvBackpropInput operation
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix get_conv_backprop_groups function
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Add unit-tests for Deconvolution shape inference
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
Compilation with ENABLE_CPU_DEBUG_CAPS was fixed.
Previous to this change it failed due to undefined dnnl::impl::md2dim_str
(since DNNL_VERBOSE was disabled in the scope of PR #11244).
* Removed a redundant image
* Fixed ops specifications and other issues
* converted html links to anchor links
* converted html links to anchor links
* Fixed a link
* Fixed a link
* Changed anchor links according to dev review
# Conflicts:
# docs/OV_Runtime_UG/Operations_specifications.md
* Right fill in the values of the inputs
* Using create_and_fill_tensor_unique_sequence() instead of create_and_fill_tensor()
* Fixing a problem with a missing parameter when calling the create_and_fill_tensor method
* Fix Bucketize Conformance tests inputs generation for Template plugin
* Correct filling of the first port (data)
* Correct the order of passing arguments to the InputGenerateData constructor
* Full range correction for random numbers
* Refactoring the argument sequence of the InputGenerateData class constructor
* A small imperfection
* Rollback changes that are related to range
PR for 22.1 made, now porting to release...
some discrepancy between this version and the 22.1 branch seems to exist, so I adjusted the conflicting link to avoid build check errors...
the overview has been merged, the remaining articles are reviewed here
* Paddle FasterRCNN Ops Conversion: roi_align, strided_slice, where
* add check for 'aligned' feature of 'roi_align' op; use common function for idx_node in 'striede_slice' op
* Apply suggestions from code review
* use common funciton for stride_slice and slice, OP_CHECK for 'where' op conversion
* Apply suggestions from code review
* Fix batchability check of MAX_BATCH_SIZE
* Applied review comment
* clonenetwork in auto
Signed-off-by: fishbell <bell.song@intel.com>
* clone in correct way
Signed-off-by: fishbell <bell.song@intel.com>
Co-authored-by: Taylor Yeonbok Lee <taylor.lee@intel.com>
* Frontend exception safety
Every call to frontend's API (except Places) can throw exception. If during exception handling, FrontEndManager is destroyed and calls 'dlclose' for plugin - call stack will be corrupted and crash will occur.
Solution is to wrap 'plugins' calls with try/catch and throw new exception in 'openvino' context
TODO: currently "Place" objects don't have 'actual' wrappers, so exception in 'place' objects will potentially cause such crash (if exception handler destroys FrontEndManager). Workaround for user would be to try/catch any calls of Place API on their side.
We're not expecting users to use Place API directly, so this workaround looks acceptable
* Add check for exception message
* Keep type of frontend exception during rethrow
* IR FE tests: don't expect InferenceEngine::exception as it be not propagated as is by FrontEndManager
* [Python API] Remove old api class from the new api
* start working on refactoring of OVAny
* fix tests
* fix code-style
* remove tuple test
* fix test
* fix omz hash
* one more overload
* fix pyfloat
* move from_ov_any to utils
* code-style
* move function from common to utils
