* interpolate improvement
* JITTED cubic mode
* fix 'code is too big' when JIT
* extend test to cover tail code path
* transformation of interpolate1 to interpolate4
* add low precision transformation for interpolate4
* sequences to ti transformations, support for seq_lengths input, update reference implemetations, add new tests
* fix python api, update sequences to ti transformation
* fix sequences to ti transformation
* Update sequences to TI transformation: fix reverse sequence support
* update single layer tests, fix TI reference impl, fix Sequences to TI transformations
* ngraph code style
* fix build
* fix ngraph python api
* resolver review comments, refactoring
* Resolve review remarks
* delete xfail
* [IE TESTS][IE CMAKE] Add cmake option for configuration to skip tests
* [IE TESTS] Remove extra dependency from IE tests shared lib
* Revert to add flag
* Fix ElementwiseInputReshape transformation
Reshape node always needs to be inserted
in order to preserve ShapeOf nodes (reshapability of a model) that can potentially be above
elementwise node.
Refactor EltwiseInputReshape_test and EltwiseInputNormalization_test since the logic of maintaining reshape for eltwise has been changed.
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Merge EltwiseInputNormalization and EltwiseInputReshape transformations
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Remove Unsqueeze from Fused_op
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix code after code review #1
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix code after review #2
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix code review #4
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Perform full normalization based on shapes of all inputs to eltwise
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Refactor much to avoid old API and edges with unsqueeze_dims attribute
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix code after review
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* [VPU][NGraph] Support ShapeOf and Gather in TopK K propagation
* [VPU] Save calculated K value
* [VPU][Tests] Introduces tests
* [Tests] Review fixes
* QueryState moved to InferRequest
* deprecate ExecutableNetwork::QueryState,chaged tests (without any check yet)
* fix build
* review fixes + build fix
* build fix + review changes
* remove blank line
* style fixes
* test build fixes
* style fix
* style fix
* fixed build of tests
* fix
* mac build fix
* hddl plugin build fix
* clean up unneeded implementation for method
* fixed tests build
* add implementation for getstate, correct getName for MklDNN
* fixed description of state API in comments
* lint fixes
* Rename MemoryState to VariableState
* added tests for cpu for VariableStates, several small fixes in tests and code
* merge fix
* lint fix
* remove whitespaces
* spaces fix
* fix in test to make it workable for all plugins
* fix typo
* fix test for gna
* remove extra comment
* fix test for gna
* Initial summary dumper implementation
* Handle Tensoriterator body + add parser script
* Add support of XML reports merging + report OP names with versions
* Remove debug device name change
* Fix windows building issue
* Add --disable_test_skips command line option
* Gtest failure with logging
* Change skipping logic and resolve linkage errors caused by extern
* Get graph body from Loop
* Fix disable_tests_skipping symbol redefinition
* Fix inline for currentTestIsDisabled
* Rollback get_body for Loop
* Handle cases with skip in test SetUp
* Report Loop and TI ops along with ops in subgraph body
* Resolve some PR comments
* Dummy commit to kick pre-commit validation
Co-authored-by: Efode, Irina <irina.efode@intel.com>
* We need to convert ExtractImagePatches op to ReorgYolo to restore the working capacity of myriad plugin while compiling Yolo-v2 models.
* It was previously removed in #2687
* Fix dynamic output case in interpreterFunction. For dynamic output cases, we can't call get_shape on the result because it's shape is dynamic, instead, we should take the real output shape from output HostTensor
* Fix outputs naming as it's done in other DTS transformation for operations with multiple outputs (Split, TopK, etc).
Ticket - #-42421
* Loop op ngraph implementation, update IE IR Reader and ngraph to cnn converter
* refactoring SubGraphOp class
* type prop unit tests
* ngraph code style
* update comment
* single layer tests for Loop operation
* fix file name
* Add SpecialBodyPorts attribute in Loop op, update single layer tests
* first debug version
* more tests
* missing test file
* removed not needed shapes from test data
* move test data to new folder
* shape infer tests
* Added execution tests
* add several new tests cases, strict checks in Loop impl, temporary disable single layer tests
* ngraph codestyle, refactoring, clone_new_args test
* resolve review remarks
* fix build
* fix tests
* more execution tests
* add a new constructor of Loop op, resolve review remarks
* execution tests
* synchro with current version
* handle scalars and more tests
* scalar test enabled
* loop reference impl
* bug fixes in tests, onnx importer part and in the ref implementation of the Loop op
* applied remarks
* handle unsupported cases
* rewrite unit tests
* update INTERPRETER manifest
* is_termination_condition_always_true simplification
* [TEST] update python models tests
* review remarks
* added xfail to tiny_yolov3
* missing model test
* revert test data
* fixed numbers of failing tests
* fixed failed test description
* fix test message
* fix xfail test
* reference implementation for ngraph::function
* update loop reference implementation
* Refactor loop reference implementation
* ngraph codestyle
* Refactoring
* Submodule update
* Skip check for Reduce ops in mkl for scalar cases, support for yolov3
* fix ngraph reader tests
* revert ceiling op, renaming
* Add allias(Ceiling) for Ceil op in mkl
* delete xfails
* fix build
* single layer tests for tensor iterarator
* Refactor TensorIterator and Loop ref impls
* revert dynamic tensor creation, disable some dynamic test cases
* fix warning
* Resolve review remarks
* revert Predefined values in Loop tests
Co-authored-by: Mateusz Bencer <mateusz.bencer@intel.com>
* change tile reference implementation
* remove tile tests from interpreter manifest
* add repeats parameter to tile
* improve tile reference implementation
* add repeats parameter to tile reference call in tile evaluate method
* style apply
* include <numeric>
* add unnamed namespace to helper functions. Change stdio.h to cstdio. Change input_rank to be constant int
* add const reference to parameter repeats in tile reference function
* change createPitches function to use partial_sum instead of accumulate
* change a little bit createPitches function
* style-apply
* fix function naming
* style-apply
* fix calling functions name bug
* Add description of create_pitches function
* first version with debug logs
* reduce footprint
* single layer tests
* added more tests
* fixed handling bool type
* styles applied
* fix tile
* [ONLY DEBUG] print error scenario message
* fixed problem with e2e tests
* fixed casting of start_axis for numpy mode
Co-authored-by: pszmel <piotr.szmelczynski@intel.com>
* Generate unique output file names in CheckExecGraphInfoSerialization testcase.
When multiple instances of this test were executed in parallel the same
file was accessed by multiple threads which was the cause of flakiness.
* Enable ExecGraphTests.CheckExecGraphInfoSerialization on GPU
* [IE] Add batched blob support
New `class BatchedBlob : public CompoundBlob` defined to allow to pass multiple blobs as 1 InferRequest input.
Motivation: There is the special user case when a number of plain images (e.g. `NV12Blob`) should be passed as one input for network which batch size > 1.
`class CompoundBlob` is not applicable for such cases due to:
1. `NV12Blob` is `CompoundBlob` which prevents to combine multiple NV12 images to a CompoundBlob
2. The default behavior in most of plugins - do not accept generic CompoundBlob as `SetBlob()` argument
Adding `SetBlob(name, vector<Blob::Ptr>...)` to `class IInferRequest`, `class InferRequest`, `class IInferRequestInternal`, ... - is not effective solution due to limited and specific use cases for `batched inputs`.
+ Apply rule-of-zero to CompoundBlob and inherited classes.
* Add "BATCHED_BLOB" optimization capability metric
* Add BatchedBlob usage to hello_nv12_input_classification
* Apply offline code review outcome:
1. Revert CompoundBlob public .ctors signatures
2. Remove 'workaround' .ctor for `BatchedBlob`
3. Revert tensor descriptors of `I420Blob` `NV12Blob` back to the 'fake' value.
* Code review fix
* Add functional tests for CPU, GPU, MULTI, HETERO
* update doc comment
* Apply code review change requests.
Chenhu Wang