* Added mish layer doc opset
* Refactoring mish spec
* Update mish spec
* Change output description of Mish layer
* Fix Mish according to review
* Refactoring Mish and GELU spec according to code review
* Update formula for ops in spec
* Refactoring spec text
* Update Mish opset
* Change Mish version from 1 to 4
* Sort opset4
Co-authored-by: Your Name <you@example.com>
* Added documentation for Interpolate-3.
* Some fixes.
* Fixed some typos.
* Now Interpolate-3 is Interpolate-4.
* Fixed typo.
* DEleted unused 'mode' 'area'.
* Fixed some typos.
* Now 'axes' attribute is an input of Interpolate.
* Added description of variants of nearest_mode.
* Added descriptions of coordinate transformation modes.
* Now 'axes' is an optional input.
* Fixed typo.
the point is that we should check the ORIGINALLY (largest) list of the devices (actually ExecutableNetworks for them) to see if the device is just added back
* [LPT] FuseFakeQuantizeAndScaleShift transformation for last layer fix
* [LPT] refactoring
* [LPT] FuseFakeQuantizeAndScaleShift test: last layer name validation was added
* [IE][nGraph]: Introduces PartialShape ctor from values vector
Signed-off-by: Gladilov, Gleb <gleb.gladilov@intel.com>
* [IE][VPU][nGraph]: Moves evaluateTargetShape to common utilities
The same functionality - get upper-bound shape estimation for dynamic
input - is needed in dynamic Reshape along with dynamic Broadcast.
Return value type has been changed from PartialShape to vector<int64_t>.
The reason is Reshape encodes special values (0, -1) into input values
that define output shape. Representing those values (which upper-bound
provides evaluateTargetShape) as PartialShape leads to incorrect
representation vector with -1 as dynamic shape - which is not expected.
Signed-off-by: Gladilov, Gleb <gleb.gladilov@intel.com>
* [IE][VPU][nGraph]: Introduces StaticShapeReshape
In comparison with original Reshape StaticShapeReshape propagates
upper-bound shape through a function in case of dynamic input. To do so,
shape inference method gets upper-bound shape from evaluateTargetShape,
decodes special values (0, -1) in it and then propagate the result.
Output shape processing happens only once, because if shape inference
were called after ShapeOf operations have been optimized out on dynamic
path, then evaluateTargetShape will require evaluate method for all
operations that appear in function before current Reshape. Since
evaluate method is implemented not for all operations it lead to
Faster-RCNN compilation error.
Signed-off-by: Gladilov, Gleb <gleb.gladilov@intel.com>
* [IE][VPU][nGraph]: Updates Reshape DTS on StaticShapeReshape
In case of non-const Reshape input that defines output shape DTS uses
StaticShapeReshape which propagates upper-bound shape evaluated from
this input through a function.
Signed-off-by: Gladilov, Gleb <gleb.gladilov@intel.com>
* [IE][VPU][nGraph][Tests]: Refactoring DTS Reshape tests
The only changes are:
* header files include reordering
* indentation/wrapping fixing
Signed-off-by: Gladilov, Gleb <gleb.gladilov@intel.com>
* [IE][VPU][nGraph]: Moves ShapeOf transformation out of DTS scope
In comparison with DTS ShapeOf transformation needs to work on whole
function. Separating these 2 transformations makes testing easier since
now it's possible to call specific DTS without ShapeOf transformation
and vice versa.
Also DynamicToStaticShapeOf has been renamed into
EliminateShapeOfAfterDSR since transformation doesn't introduce new DSR
operations.
Signed-off-by: Gladilov, Gleb <gleb.gladilov@intel.com>
* [VPU][Tests]: Introduces DTS Reshape tests with non-const pattern
New StaticShapeReshape constructor has been added as well, since test
fixture should create it from reshape parameters, not reshape itself.
Signed-off-by: Gladilov, Gleb <gleb.gladilov@intel.com>
* Remove replacement of StridedSlice with other stages and execute it on device as one kernel.
* Refactor strided slice tests to be able to parametrize it by precision.
* Update firmware.
* added support for power layer with non-1 exponents to GNA plugin
* reverted a change caused by merge issue
* fixes for review comments (typo fix - lrelu instead of leru, unnamed structure instead of of named one in union with arguments of activation function, name fix - input instead of inputs),
scale-shift implementation based on affine layer instead of PWL,
* fixed code style
* fixes for coding style in scale_factor_calc.hpp
* added domain for power function
* fixed review comment - power function specific methods
* added check if dynamic casting was successful
* removed I16 as it is not supported by ngraph
* fixed initialization per review comment
SparseToDense used in Wide and Deep model is expressed through ScatterND operation.
ScatterND is more functional than SparseToDense. Hence, it was decided to replace SparseToDense
with ScatterND. ScatterND is more useful for other models.
Remove SparseToDense from the previous opset
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Check equality of shape data for the replaced and replacement input/output data in the model
* Connect data with shape in duplicateData method
* Disconnect shape with data which is being removed as unsued.
* Check that disconnected shape still have child dataToShape edges or consumers
* Refactor cleanUp to use removeUnsuedData and not duplicate code
