* 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>

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

* Start of rework

* Faster multiply simplification

* Fix uniform constant check

* Support Add op

* Fix build error
Co-authored-by: Sang Ik Lee <sang.ik.lee@intel.com>

* Fixed memory blob

* Fixed code style
Co-authored-by: Sang Ik Lee <sang.ik.lee@intel.com>

* Use test case in quant tests

* Reshape test refactor

* Reshape tests refactor

* Test case refactor onnx_import

* onnx import_in test case refactor

* onnx reshape test case refactor

* onnx convpool test case refactor

* onnx import in test case refactor

* onnx reshape test case refactor

* Style apply

* Style apply

* Removed commented code

* Infinity check softplus test refactor
Co-authored-by: Robert Kimball <robert.kimball@intel.com>

* Fix warnings

Control reaches end of non-void function

* Format

* Revert changes + add throw at EOF

* Alternative fix
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>
Co-authored-by: Sang Ik Lee <sang.ik.lee@intel.com>
Co-authored-by: Robert Kimball <robert.kimball@intel.com>

* - add fused_op.td to CmakeLists
- define pattern to fuse Wx + b and to replace with MatMulBias

* - remove table-gen LLVM_TARGET_DEFINATION for fused_ops_pattern.td,
fused_ops.td
- fix build issues

* - change pattern to to match MatMul instead of Dot
- support in CMake to register MatMulBias fused Op pattern

* - made changes to fusion pattern to match Add( Dot (op1, op2), bias) for
MatmulBias
- use applyPatternsGreedily instead of applyFullConversion in the graph
pass
- add unit test inter v/s CPU for MatMulBias

* - Affine lowering, verifier logic to NgMatMulBiasOp

* add missing header file

* - WIP, use NGGemm instead of NGMatMulBias

* -undo unintended changes

* Addressed PR comments

* - refactor the ctor of the NgDialectFusion pass
- register NgDialectFusion pass with the PassRegistration

* Address PR comments

* -add lit test for matmul+bias fusion

* -style fix lit test
Co-authored-by: Sang Ik Lee <sang.ik.lee@intel.com>

Co-authored-by: Robert Kimball <robert.kimball@intel.com>
Co-authored-by: Sang Ik Lee <sang.ik.lee@intel.com>

* Update sitemap to not use a page title

* Update doc for DLDT layers and remove references to PlaidML

* Set output shape of Deconv with dynamic input

* Trigger CI

Co-authored-by: Robert Kimball <robert.kimball@intel.com>

* Add ngraph visibility exports for the NVIDIA GPU backend.

* Remove GroupConvTranspose emitter.

* Disable failing tests that have appeared since removal of GPU backend in v0.25

* Update src/ngraph/runtime/gpu/unit_test.manifest

* Add more disabled tests.

* Add more disabled tests.
Co-authored-by: Robert Kimball <robert.kimball@intel.com>

* Always use control deps in sorting

* Fix build

* Deprecate old topological sort
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>

* ConvBackPropData dynamic output shape input

* Adam comments
Co-authored-by: aslepko <44713115+aslepko@users.noreply.github.com>
Co-authored-by: Robert Kimball <robert.kimball@intel.com>
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>

* Remove Event tracing and replace with chrome trace

* style
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>

* Add some attribute visitors

* Need to keep size_t for opset1

* Fix condition

* Misso

* Missed int64_t

* Revert std changes

* Header reorg
Co-authored-by: aslepko <44713115+aslepko@users.noreply.github.com>

Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.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>

* Start

* Move Input

* Move Output

* Move ostream
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>

* Extend normalization. Part.1

* Normalize axis. Part.2

* Code review remarks introduced

* Fixed normalizes ranges type

* Trigger CI
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>
Co-authored-by: Robert Kimball <robert.kimball@intel.com>

* Update onnx_import_provenance.in.cpp

* Update onnx_import_dyn_shapes.in.cpp

* Update constant_folding_one_hot.cpp

* Update constant.hpp

* Update constant.hpp

* Update constant_folding_one_hot.cpp

* Update onnx_import_provenance.in.cpp

* Update onnx_import_dyn_shapes.in.cpp
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>

* Update table.

* More updates.
Co-authored-by: Michał Karzyński <postrational@users.noreply.github.com>
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>
Co-authored-by: Robert Kimball <robert.kimball@intel.com>

This PR disables treating warnings as errors by default so that
nGraph can be built with compiler versions that are not currently
tested in CI. We could enable Werror in CI for those compiler versions
we want to target for warning-free builds.
Co-authored-by: Robert Kimball <robert.kimball@intel.com>

* Squeeze/Unsqueeze dynamic input type/rank infer

* Unit-tests

* style

* Removed squeeze Rank propagation

* Fixed comment

* Revert comment back

* Comment resolved

* Style fixes

* Moved unsqueeze axis check

* Style

* Discussion resolved

* Style

* Assert in decompose_op, if output shape is not static

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

* Cleanup headers

* Fix more headers

* Fix compile error

* Fix plaid build error
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>

Co-authored-by: Robert Kimball <robert.kimball@intel.com>

Co-authored-by: Sang Ik Lee <sang.ik.lee@intel.com>
Co-authored-by: Robert Kimball <robert.kimball@intel.com>

* Fixed warning "control reaches end of non-void function"

* Fixed codestyle
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>

Co-authored-by: asemx <998264+asemx@users.noreply.github.com>
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>

This reverts commit 43172068.
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>

Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>

* [MLIR] MLIR repo update

* Revert test

* More MLIR repo forward

* Move MLIR repo forward

* Add Loop-to-Std lowering pass to nGraph pipeline
Co-authored-by: Robert Kimball <robert.kimball@intel.com>
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>

* Add replaceable topological sort to Function

* Cleanup

* Cleanup unit test

* Address review comment

* Fix missed item in merge
Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.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.

* Failed test if not v1 with error Unsupported ops detected

* Python test for execution unit-test

* Finilize printing csv file with opset1

* Finilize test development

* style-check

* Fixed ov_runtime tensor

* Fixed code style

* Apply suggestions from code review
Co-Authored-By: Geoffrey Wenger <geoffrey.wenger@intel.com>

* Fixed comments
Co-authored-by: Ilya Churaev <ilyachur@gmail.com>
Co-authored-by: Geoffrey Wenger <geoffrey.wenger@intel.com>

Co-authored-by: Scott Cyphers <diyessi@users.noreply.github.com>