* Add move operations to AlignedBuffer

* unit test

* Remove parent from PlaidML tensor initializer

* Remove plaidml tensor parent plumbing

* style

* remove throw from dtor (#2854)

* add special handle for the 'NNP_xx' op name

* style

* add special handle for the 'NNP_xx' op name

* style

* use description as suggest by bob

* Add builders for QLinearMatmul for onnxruntime

* Generic Dot

* Change the onnx bridge and address PR feedback

* Fix date

* Fix CI failure

* Change varibale filter to input1

* const & reference

* update branch

* Comment

* Introduce QuantizedMatmul

* change pattern

* QDot tests passing

* style

* PR feedback

* Fix pattern

* style

* Don't use
pragma GCC diagnostic error "-Wswitch"
pragma GCC diagnostic error "-Wswitch-enum"
for GCC 4.8.X

* Fix typo.

* Style.

* SquaredDifference implementation

* Broadcast input before using it

* Simple test of SquaredDifference

* SquaredDifference validation tests

* Formatting adjustments

* Docs correction

* Exclude the unit test on iGPU

* Keep the includes in a single group

* Update intelgpu_backend.cpp

* Update unit_test.manifest

* UT for the broadcasting path

* Add test for i32 gather

* Add support for ints to Gather op

* Move helper function to anonymous namespace

* Add more types

* Use static_cast instead of the old one

* Style fix

* Skip tests on GPU

* Add more tests

* Skip tests on gpu

* Change bool to char

* Supports more cases for Convolution Bias fusion and also removes redundant namespace qualifiers in core_fusion.cpp

* added unit test

* select all fusions

* constexpr ctor for EnumMask

* added pass properties to core passes.

* added unit tests.

* minor fixes.

* Extend lp-norm functions to take bias.

* Move lp-norm utilities to nGraph core op/util.

* Move norm files to builder directory.

* Apply clang-format.

* Sceleton for GRN operation.

* Add GRN implementation.

* Fix reshape utility function.

* Address review comments.

* Add using namespace std.

* Review comments.

* Few fixes in grn implementation.

* Clang format.

* Basic UT.

* Fix expected data.

* Add more UT and skip them on IGPU.

* Review comments: const correctness and remove using namespace std statement.

* Unblock GRN on IGPU.

* Get back GRN op case to switch.

* merge error

IntelGPU backend: Make ScaleShift op as not supported in callback of FusedOpDecomposition pass (#2940)

* IntelGPU backend: Make ScaleShift op as not supported in callback of FusedOpDecomposition pass

* style

* merge error

* Style was correct.  Return back 0965fb5 changes

* merge error

This PR removes compiler warnings like this one:

```
src/ngraph/frontend/onnx_import/utils/reduction.hpp:73:28: warning: prior to the resolution
  of a defect report against ISO C++11, local variable 'op_node' would have been copied
  despite being returned by name, due to its not matching the function return type
  ('shared_ptr<ngraph::Node>' vs 'shared_ptr<ngraph::op::ArgMin>') [-Wreturn-std-move-in-c++11]
                  return op_node;
                         ^~~~~~~
```

IntelGPU backend: Change clDNN mode of Relu op to allow ConvolutionBiasAdd fusing inside clDNN (#2939)

* Add placeholder for doc versioning

* Finalize module to include tags of verified releases only

* Add fused Squeeze op

* Use fused Squeeze op in ONNX importer

* Update serializer

* Add unit tests

* Add type prop tests

* Change Squeeze signature to accept a dynamic input for axes

* Update src/ngraph/op/fused/squeeze.cpp
Co-Authored-By: Adam Rogowiec <adam.rogowiec@intel.com>

* Code review comments

* Fix failing unit test

* Code review comments

* Code review comments

* style

* Add op to iGPU backend

* Add op to iGPU backend

* Fix clang compiler warnings

* Remove unintended file.

* style

* Not part of PR

* Another extra closure ref

* More warnings from merges

* Lambda arg was used

* Remove remaining osx compiler warnings

* style

* Try to avoid compiler warning

* Same for the other test

* IntelGPU backend: Enable FusedOpDecomposition pass

* PR2912. Adress comments.

I had renamed the directory at one point during development but forgot to update this

* Temp save.

* Temp save.

* Temp save.

* Temp save.

* Temp save.

* Temp save.

* Temp save.

* Fix compile errors.

* Fix incorrect index.

* Fix UT typo.

* Interpreter passes UT.

* Fix more bugs.

* Apply style.

* Add shape check for updates tensor.

* Merge typo

* Fix clang compiler warnings

* Remove unintended file.

* style

* Not part of PR

* Another extra closure ref

* More warnings from merges

* Lambda arg was used

* Add ScaleShift operator

* Add ScaleShift to serializer

* Add UT for ScaleShift

* Add type_prop tests for ScaleShift

* Style-fix

* Skip tests on Intel GPU

* Review fix 1

* Style fix

* add gemm operation

* style apply

* erase if statement

* fix the test

* enable tests

Change CPUTensorRole -> TensorRole in ngraph core and utilize it in GPU backend instead of a local enum. This is also now use in NNP backend. (#2900)

* Dump the expected and actual values for NgraphTestCase

* Adapt to changes in master

* Some docs and API unification

* Extend lp-norm functions to take bias.

* Move lp-norm utilities to nGraph core op/util.

* Move norm files to builder directory.

* Normalize fused operator implementation.

* Fused op boilerplate.

* Fix node validation and normalization across spatial axes.

* Add UT normalize across CHW with scalar scale.

* Fix expanding input tensor to 4D.

* Add more UT for 3D and 2D.

* Add more UT, with scale and across HW.

* Update to new localization of l2_norm function.

* Add type_prop UT and update gpu/igpu manifests.

* Apply clang-format.

* Add positive UT for type_prop.

* Update unit test manifests.

* Address review comments.

* Add using namespace std.

* Remove unnecessary std prefixes.

* Remove blacklisted unittests for GPU.

* Apply clang-format.

* Review comments.

* Fix clang errors.

* Basic mean normalization

* Add NVM to serializer

* Add test for mean normalization

* Add support for across_channel atribute

* Add test for mvn_mean_normalization splited by channels

* Assume that data have n and c channels

* Add support for normalize_variance attribute

* Add test for full mean variance normalization

* Add type prop test

* Skip tests on GPU

* Use ngraph builder functions instead of my own

* Update mvn.cpp

* Change order in initializer list

* Review fix