* [GNA] Move tests to plugin dir
* reverted temporary fix
* Added linux specific compiler flags
Co-authored-by: Adam Tumialis <adam.tumialis@intel.com>
* Remove deprecated and not used functions:
- ngraph::is_valid_permutation
- ngraph::apply_permutation
* Use not blocking assertion in transpose test,
type prop
* Set 'UNDEFINED' as the performancehint default value. Update benchmark app to pass performance hint with none value to MULTI/AUTO plugin.
Signed-off-by: Wang, Yang <yang4.wang@intel.com>
* Using 'UNDEFINED' as the default value of hint in AUTO/MULTI plugin.
Signed-off-by: Wang, Yang <yang4.wang@intel.com>
* Adding a flag instead of adding a default value of hint to check if user configures the performance hint to AUTO/MULTI plugin.
Signed-off-by: Wang, Yang <yang4.wang@intel.com>
* Update benchmark python version.
Signed-off-by: Wang, Yang <yang4.wang@intel.com>
Signed-off-by: Wang, Yang <yang4.wang@intel.com>
* add static_output attribute to enable GPU implementation of GenerateProposals.
This change may be reverted when dynamic shapes support will be implemented
in GPU plugin.
* - add GPU single layer test;
- add normalized attribute to SLT.
* add GPU primitive for GenerateProposals
* add kernel for GenerateProposals
* add unit test for GenerateProposals
* add blocked layouts support
* tidy up
* support blocked layouts also for 2nd and 3d outputs
* Transformation to deal with dynamic output in GPU
- revert changes in GenerateProposals interface and shape inferenece;
- add transformation;
- custom compare method in single-layer test.
* address review comments
* fix after rebase
* fix after rebase
* review comment: added nms_eta to testcase name generation
* - added input types combination to functional tests;
- fix float16 comparison.
* fix after rebase
* use vector for input ids
* fix after rebase
* [TF FE] Support DynamicPartition operation
Add support for DynamicPartition operation and validate it with the layer tests
Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>
* Add implementation
* Rescale partition indices to provide stable sorting
Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>
* Test to interval shape propagated by transpose
* Test to propagate labels by transpose
* Add template transpose shape inference
* Fixes to transpose shape inference
* Update names for shapes:
input -> input_shape
order -> order_shape
* Not fill output shape for dynamic range
* Add constexpr to SeqGen and Between comparator
* Correct StaticShape creation in test
* Tests check partial value propagate in arg input
* Add evaluate upper, lower, label to transpose
- add test
* Add common methods for inference and evaluate
* Move helpers to shape_inference
* Move transpose attribute to transpose op
* Fix include in transpose operator
* Correct label generation and type
* Fix null conversion
* Use uint64_t for labels tensor
* Fix compare labels
* Use order length as output rank
* Update transpose transformation test
* Move helpers to validation_util
* Correct test assertion for expected shape
* Transpose evaluate use common function
for output calculation
* Remove redundant helpers from transpose test
* fix Performance inefficiencies issue caused by previous PR.
Signed-off-by: Wang, Yang <yang4.wang@intel.com>
* Update.
Signed-off-by: Wang, Yang <yang4.wang@intel.com>
Signed-off-by: Wang, Yang <yang4.wang@intel.com>
Co-authored-by: River Li <river.li@intel.com>
* marks tf2 keras tests as precommit for new FE
* adds tf2 layers tests for new FE in precommit
* removes redundant tabulations
* review changes
* fix field name
* fix syntax error
* removes failing tests
* removes failed test
* removes failed test
* Fix benchmark_app commandline parsing
Object 'str' does not have a contains() method. Replaced by
"searchstring in object" query.
* Fix perf counter output and use consistent units
When ProfilingInfo was bound by pybind11, those entries turned into
Python timedelta objects. This caused two problems:
1. There was a division by 1000 to go to milliseconds. This caused a lot
of precision lost, because `timedelta(microseconds=2300)/1000.0 =
timedelta(2)` and `timedelta(microseconds=33) = timedelta(0)`.
2. When converting those timedelta objects to str, the output is in the
form of (HH:MM:SS.XXXXXX). This is not very useful microsecond based
performance counters.
This change simply reverts everything to printing plain microsecond
based integers.
* Align counter output to ms between Python/C++
