* [ONNX] Add new ConstatntOfShape operator

* Fix a bug in op implementation

* Modify downgrade pass to support broadcast scalars

* Style-fix

* Use at instead of []

* Use onnx helper instead of ngraph builder

* Add some UT

* Style fix

* Limit range of DynBroadcast in downgrade pass

* Move tests to better location

* Rewrite tests to test_case

* Add check if arg_pshape is static

* Style

* Trigger CI
Co-authored-by: Michał Karzyński <postrational@users.noreply.github.com>
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>

* Switch to PartialShape in onnx_importer ValueInfo

* Construct dynamic dimensions out of ONNX dimensions defined as dim_param

* Validate the PartialShape of inputs created from an ONNX model with dynamic shapes

* Validate the output shape inference for a dynamic ONNX model

* Test the execution of an ONNX model with dynamic dimensions

* Test the Ax+B with more than one batch size

* Provenance tagging adjustments - PartialShape instead of Shape

* Correct translation of ONNX shapes to nG shapes

* Test the shape of Constant produced by scalar initializers

* Review comments & more strict assertions in UT

* UT checking a dynamic rank input

* Fully dynamic input inference test

* first dynamic version

* modified UTs

* Added assert checks

* Added specialised methods

* first verion of AvgPool

* code review remarks introduced

* Changed tests to use default BackendMode value

* Reverted not related changes

* first verion of AvgPool

code review remarks introduced

Changed tests to use default BackendMode value

* first version of maxpool

* Changed PoolingFactory to support dynamic shapes

* fixed Pad op

* Added Uts to global ops

* Code review remarks introduced

* code review remarks introduced

* Code refactor

* Code review remarks introduced
Co-authored-by: Tomasz Dołbniak <tomasz.dolbniak@intel.com>
Co-authored-by: Sang Ik Lee <sang.ik.lee@intel.com>

* Added Round op to onnx importer.

* Added a new line.

* Excluded test from plaidml.

* Code formatting.

* Added header.

* Unabled test on gpu.
Co-authored-by: Chris Sullivan <chris.sullivan@intel.com>
Co-authored-by: Sang Ik Lee <sang.ik.lee@intel.com>

* Constify the onnx importer conv

* Extract and fix the groups attribute validation for Conv

* Check if the convolution's data input rank is static

* Validate the groups attribute against channels and filters

* Validate the conv operation in a separate function

* Dynamically broadcast the conv bias if needed

* Import a test model with dynamic batch conv op

* Run a conv test with dynamic batch

* Cleanup of conv bias handling code

* Use a proper Broadcast constructor for bias in onnx conv

* Handle dynamic ReduceMean with statically defined rank

* Use the target shape rank to construct the default output shape for Broadcast

* Handle ONNX Squeeze with dynamic input and static rank

* Handle ONNX Shape with dynamic input and static rank

* Handle the dynamic target shape in ONNX Reshape

* Fix for the ONNX Shape input validation

* Handle ONNX Softmax with dynamic input and static rank

* Fix the failing Broadcast type prop test

* Code formatting

* Dont broadcast bias before adding it to the conv node

* Drop the conv node validation and rely on the core op implementation checks

* Code review feedback

* Revert the Broadcast op changes

* More code review feedback

* Dynamic conv test using ng test case

* Obsolete headers removal

* Code formatting

* Variable names refactor

* Disable model_conv_with_dynamic_batch test on GPU

* Code formatting
Co-authored-by: Sang Ik Lee <sang.ik.lee@intel.com>

* Asinh dynamic shape support prototype

* Asinh static shape test

* Asinh dynamic shapes test

* Unified asinh implementation for static and dynamic shapes

* Atanh dynamic shapes support

* Style apply

* Acosh dynamic shape support

* Tests update

* Style apply

* Update PlaidML manifest

* Use default tolerance bits

* Style apply

* Def tolerance bits for dynamic tests

* Rename dim_param

* Update acosh.prototxt

* Update acosh_dyn_shape.prototxt
Co-authored-by: Robert Kimball <robert.kimball@intel.com>

* Use ConvolutionBackpropData in ONNX ConvTranspose operator.

* Replace deprecated functions and update documentation.

* Remove GroupConvolutionTranspose fused op.

* Add more UT for GroupConvolutionBackpropData.

- They're transformed from GroupConvolutionTranspose

* Fix validate_and_infed types for ConvolutionBackpropData v1.

* Add new constructor for GroupConvolutionBackpropData

- Additionally do some code formatting.

* Improve validation in GroupConvBackprop v0.

* Update/fix upgrade & downgrade passes for
(Group)ConvolutionBackpropData.

* Add decomposition and validation for GroupConvolutionBackpropData:v1

* Type properties UT for GroupConvolutionBackprop v1

* Remove include of deleted header.

* Add squeeze to opset1::builder.

* Use opset1 squeeze.

* Helper functions for padding and output spatial shape inference.

These helper functions are specialized only for *ConvolutionBackpropData operators.

* Update documentation.

* Add more checks and remove deprecated assert.

* Refactor GroupConvolutionBackpropData validation.

- Use helper functions to infer padding and output shape.
- Change get_output_shape to return only spatial features dimensions

* Remove unnecessary code from donwgrade pass.

The GroupConvolutionBackpropData node has already computed all those required
information.

* Call Node API. Small review suggestions.

* Work only on spatial dimensions inside helper functions.

* Enhance documentation for ConvolutionBackpropData

* Refactoring.

* Reuse values computed in downgraded operator.

* Check for correct filters input shape.

* Add additional check on auto pad value.

* Remove unused variables.

* Rename helper function.

* Add more checks.

* Override is dynamic and add more restrictive check.

* Fix merge artifact and force unsigned type for argument.

* Review comments: renaming.

* Change Convolution + bias pattern.

Change from bias broadcasting to appropriate convolution output shape
into reshape into (1, C, 1, 1) shape, which sould work better.

* Add few more test cases for ONNX ConvTranspose op.

* Skip one UT failing on PlaidML backend due to accuracy.

* Add provenance tag in opset0 downgrade pass

* Add provenance tag in opset1 upgrade pass

* Type name as string

* Change op_cast to return replacement_node instead of bool

* Add provenance tags to all nodes created while downgrade

* Add provenance tags to all nodes created while upgrade

* Comments

* Style apply

* Update ONNX import provenance test function

* Add const statement

* Add upgrade/downgrade provenance tag tests

* Update tests

* Style apply

* Provenance enabled check

* Removed redundant add_tag

* Test for add_provenance_tags above

* Add graph test for provenance tags in transformation pass

* Use EXPECT_TRUE and EXPECT_FALSE instead of EXPECT_EQ

* Return replacement node directly

* Style apply

* Test downgrade provenance tag with ONNX importer

* Update test/onnx/onnx_import_provenance.in.cpp
Co-Authored-By: Michał Karzyński <postrational@users.noreply.github.com>

* Test update

* Update provenance test to check node type occurence

* Style apply
Co-authored-by: Michał Karzyński <postrational@users.noreply.github.com>
Co-authored-by: Sang Ik Lee <sang.ik.lee@intel.com>
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>

* Switch to PartialShape in onnx_importer ValueInfo

* Construct dynamic dimensions out of ONNX dimensions defined as dim_param

* Validate the PartialShape of inputs created from an ONNX model with dynamic shapes

* Validate the output shape inference for a dynamic ONNX model

* Test the execution of an ONNX model with dynamic dimensions

* Test the Ax+B with more than one batch size

* Provenance tagging adjustments - PartialShape instead of Shape

* Correct translation of ONNX shapes to nG shapes

* Test the shape of Constant produced by scalar initializers

* Review comments & more strict assertions in UT

* UT checking a dynamic rank input

* Fully dynamic input inference test

* ONNX provenance tags adjustments and back to get_shape

* Remove an obsolete space in provenance tags
Co-Authored-By: Michał Karzyński <postrational@users.noreply.github.com>

* Remove an obsolete space in provenance tests
Co-authored-by: Michał Karzyński <postrational@users.noreply.github.com>
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>

* Changes version from v0 to default for Min and Max ops.

* Added broadcast option in variadic function.

* Added tests.

* Added test for opset8.

* Undo changes for Mean op.
Co-authored-by: Tomasz Dołbniak <tomasz.dolbniak@intel.com>
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>

* Checking if provenance_tags key exists

* Add provenance tag prototype

* Format provenance tag

* Display provenance tag

* Clean debug printing

* Add const to variables

* Separate method for add provenance tags

* Return NodeVector reference

* Return const NodeVector

* Moved add_provenance_tags function to commons

* Style apply

* Simple model for tests

* Provenance tag test

* Expect substring instead of  equal

* Add provenance tags to intermediate nodes recursively

* One tag per node

* Add traverse node args instead of recursion

* Return NodeVector instead of set of pointers

* Use treverse_nodes and lambda function

* Remove unused helper functions

* Remove is_constant() condition

* Update test model prototxt

* Update test substring

* Use node name and output names to build provenance tags in onnx importer

* Unit tests for onnx_importer provenance tags

* Missing <numeric> include

* Add provenance tags to constants buit from ONNX initializers

* Add provenance tags to Constants and Parameters created out of ONNX inputs and initializers

* More strict assertions in onnx provenance tests

* Unit test for onnx importer Parameter nodes tagging

* Helper function for the onnx provenance tests

* Some docs

* Obsolete comment removal

* Separate file for onnx provenance tags unit tests

* Code formatting

* Move the inputs tagging to the Graph class

* Tagging moved to the Graph class entirely

* Missing include and extra helper variable

* Unit tests helper documentation

* Change the UT helper to lowercase
Co-authored-by: Katarzyna Mitrus <katarzyna.mitrus@intel.com>

* Added GatherElements op to ONNX importer.

* Changed attributes to inputs.

* Undo unnecessary changes.

* Added Pad version 11.

* Added 11 version for Pad op.

* Changed axis element type.

* Added optional input.

* Code formatting.

* Added test.

* Update onnx_import.in.cpp

* Removed debug code.

* Added function for setting mode.

* Added support for pads argument provided as Constant.

* Code refactoring.

* Code refactoring.
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>
Co-authored-by: Sang Ik Lee <sang.ik.lee@intel.com>

* Removed Recoprocal FusedOp and moved definition to ONNX importer.

* Removed unnecessary changes.

* Added test.

* Undo unnecessary changes.
Co-authored-by: Sang Ik Lee <sang.ik.lee@intel.com>

* Checking if provenance_tags key exists

* Add provenance tag prototype

* Format provenance tag

* Display provenance tag

* Clean debug printing

* Add const to variables

* Separate method for add provenance tags

* Return NodeVector reference

* Return const NodeVector

* Moved add_provenance_tags function to commons

* Style apply

* Simple model for tests

* Provenance tag test

* Expect substring instead of  equal

* Add provenance tags to intermediate nodes recursively

* One tag per node

* Add traverse node args instead of recursion

* Return NodeVector instead of set of pointers

* Use treverse_nodes and lambda function

* Remove unused helper functions

* Remove is_constant() condition

* Update test model prototxt

* Update test substring

* Make code slightly more readable
Co-authored-by: Tomasz Dołbniak <tomasz.dolbniak@intel.com>
Co-authored-by: Michał Karzyński <postrational@users.noreply.github.com>
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>
Co-authored-by: Sang Ik Lee <sang.ik.lee@intel.com>

* Update license to new year

* Pick up some strays

* Added scatterND op to ONNX importer.

* Added ScatterND FusedOp.

* Removed unnecessary files.

* Added op to config files.

* Changed input order.

* Fixed validation checking.

* Added suport for int64 in ScatterNDAdd op.

* Changed test.

* Disabled test for plaidML.

* Code refactoring

* Added tests.

* [ONNX] Added gatherND op to ONNX importer.

* Added tests.

* Removed new line.

* Update onnx_import.in.cpp

* Changed tests.

* Register CumSum operator in onnx importer

* Missing whitespace

* Update CMakeLists.txt

* ONNX importer - CumSum op init

* Simple CumSum onnx model

* ONNX CumSum model simple test

* Default axis

* Axis input test

* Inputs variable

* Style apply

* Test 3d exclusive reverse

* Apply style

* Add memory header and std namespace

* Add model_cum_sum tests to plsidml unit_test.manifest

* Add model_cum_sum tests to plaidml unit_test.manifest

* Changed default axis type

* Test model update

* Style apply

* Add test for dynamic axis input

* Mod operator introduced

* Introduced onnx importer, fixed implementation

* styles applied

* Refactored assert comment for mod

* Add failure mod test to plaidml manifest

* Code review remarks introduced

* Changed ops used in decompose to v1

* Moved Mod to op_v1_tbl

* Matmul float type test case for UEP
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>

* Removed microsoft ops domains and ran clang-format
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>

* Minor cleanup

* Add support for ONNX 1.5 version of TopK

* Add unit tests

* Style apply

* Exclude failing tests

* Exclude failing tests

* Add support for ONNX 1.6 TopK attribures: larges and sorted

* Support for ONNX 1.6 TopK

* If k_node is a Constant, recreate as constant with Shape{}

* Extend `interpret_as_scalar` function

* Extend `interpret_as_scalar` function

* Remove merge artifact

* Add doc string

* Exclude failing tests

* Exclude failing tests

* Refactor function

* Remove unnecessary template param

* Use get_k function in OpSet 10 TopK

* Style apply

* Remove merge artifact

* Add tests for `interpret_as_scalar`

* Revert "Add tests for `interpret_as_scalar`"

This reverts commit 8b85965acb39c75ff9e66b06ad8f64df16e1a9da.

* [ONNX] Added Expand op to ONNX importer.

* Added support only for static broadcating.

* Changed version of set from 8 to 1.

* Added test for expand op.

* Do not throw for unknown domains in ONNX models

* UT that makes sure onnx_importer does not throw for unknown domains

* Check if nGraph throws for unknown ONNX domain and op

* ReverseSequence operator introduced

* Code review remarks introduced

* Added missing EOF

* Removed unused whitespaces in onnx_import.in.cpp

* Added convert to i32 for sequence_lenghts

* Coode review remarks introduced

* Disable reverse sequence for plaidml backend

* Code style fixed

* Helper function converting ONNX auto_pad into nGraph PadType.

Separate auto_pad support from explicitly provided paddings.

* Add support for more PadType values for GroupConvolutionTranspose.

* Pass auto_pad attribute value to nGraph operator.

* Helper class for generating ONNX pooling operators.

* Pass auto pad type to nGraph Convolution operator.

* Use pooling factory.

* Helper function calculating pads taking into account auto_pad attribute.

* Fix attribute type in UT ONNX models.

* Take auto_pad attribute value into account.

* Rename helper function and update doc.

* Retain old API for GroupConvoloutionTranspose

* Remove PadType::INVALID and use other approach to validate auto_pad
value.

* Style apply.

* Fix clang err on documentation style.

* Refactor get_auto_pad method.

* Fix segfaults on CentOS 7.

When using const reference the node member m_attributes had invalid
data.

* Fix used operator for reversing input sequences in LSTM.

* Fix backward pass for bidirectional LSTM.

* UT for LSTM with sequence_lens shorter than input sequence size.

* Skip LSTM UT using ReverseSequence since it is not supported yet on
PlaidML.

* Add LpNormalization operator along with unit tests.

* Add validation macro based on NGRAPH_CHECK.

* Add InstanceNormalization operation along with unit tests.

* Update supported ops table.

* Fix merge error.

* [ONNX] Add eyelike operator

* Use shifted square identity in square identity

* Make new helper function to map onnx_types<->ngraph_types

* Add fp16 support to ngraph Python API

* Move helper common.hpp => common.cpp

* Add checker for attribute presence

* Style check

* Add definition of shifted word

* Change return value of attribute presence !(==) -> !=

* Rename is_attribute_present => has_attribute

* Clean-up headers in eyelike.cpp

* Organize headers in common.*pp

* Minor review fixes

* Style check

* Add test for EyeLike with negative k

* Initial implementation of the Shrink op

* Multiply the values by the correct masks

* Basic test case for Shrink with floats

* Shrink test on integers

* Code formatting

* Shrink documentation and typo fix

* Rephrase the Shrink docs

* Out of <memory> ;)

* Unit tests for ConvInteger

* Add ONNX ConvInteger op

* Add QuantizedConvInteger builder

* Add unit tests

* Exclude tests on nVidia GPU backend

* Fix merge artifact

* Add const-correctness and allow RVO

* Unit tests for MatMulInteger

* Add ONNX MatMulInteger op

* Add QuantizedLinearMatmulInteger builder

* Additional unit test

* Exclude tests on nVidia GPU backend

* Add 4D test case

* Enable >2D MatMulInteger

* Refactoring to MatMulFactory - step 1

* Refactoring to MatMulFactory - step 2

* Remove `using namespace ngraph` to make `Node` unambiguous.

* Disable quantized ops tests on GPU backend

* Remove unused `includes`

* Remove redundant dynamic_pointer_cast

* Remove redundant `move`

* Add const correctness

* Code review comments

* Style apply

* Add documentation

* Use more complex shapes in tests

* [ONNX] Unit test models for QLinearMatMul

* [ONNX] Extended types support for NgraphTestCase

* [ONNX] Move the value comparators to the NgraphTestCase class

* Add test cases

* Add shape checking

* disable GPU tests