IntelGPU backend: ArgMin/ArgMax functionality was fixed; Tests on unsupported functionality were disabled (#1834)

* IntelGPU backend: ArgMin/ArgMax functionality was fixed; Tests on unsupported functionality were disabled

* Additional improvement of ArgMin/ArgMax algorithm

* WIP

* More WIP

* More chiseling

* Move conv validation utils to a separate file; update unit tests

* Fix invalid attributes in pattern containing ConvolutionBackpropFilters

* Remove zero_const_conv test (it's no longer possible to construct the graph being tested)

* Rename infer_convolution_output_item_shape to infer_windowed_reduction_output_shape and add a boolean flag to control whether window-all-in-padding is allowed

* Add generalized function for inferring pooling fprop, use it in AvgPool/AvgPoolBackprop

* Update MaxPool to use new utility functions

* Fix comment

* Remove faulty and redundant check for window shape relative to pre-padding data shape

* Revert change to pattern construction in cpu_fusion

* Update unit test for maxpool

* Restore unjustly eliminated tests; move some computation to ptrdiff_t for safety; fix wording on some error messages

* Formatting

* reset buffer size, use original input size for memcpy

* resolve comment and add test

* update comment

* Update email notification method

- Link to pull request
- Jenkins build links to Blue Ocean

* Update prepare_environment.sh

- remove artifacts from previous build

* Add type_prop unit tests for Quantize

* Fix naming consistency; add test for unsupported RoundMode fail

* Add type-prop unit tests for Dequantize

* [ONNX] Tool to serialize ONNX models

* Review fix.

* Add back dependencies to onnx_import_interface target.

* Review fix pt. 2

* Check also for errors when opening file stream.

* Switch to scale and offset design from min and max for Quantization

* Remove offset and make the quantize ops a single o/p op

* move cpu QuantOps to core and create builders

* rebase to HEAD

* remove convbias and convbiasrelu ctors which take conv

* remove mistakenly added quantize.rst

* remove offset

* Compute scale, move quantization ops to experimental dir and some PR feedback

* Normalize license headers

* dex core quantize/de

* more types

* codegen

* remove comments

* remove more dead code

* [ONNX] Assert all op types supported

* Apply clang-format

* Address code review comments

* Fix #include statements

* Update ONNX Squeeze Op implementation to conform with doc. Add unit test.

* Apply code-format.

* Correct attribute value type.

* Change used loop structure.

* Modified version of loops.

- Without erase and with minimal computation time complexity.

* Run CI

* Reshape with no permutation optimized out

* PR1671. Apply optimization to the same shapes only

* PR1671. Reuse Reshape optimization from common passes

* PR1671. Remove eliminate_reshape from nop_elimination procedure

Add support for an environment variable `NGRAPH_ONNX_IMPORT_ENABLE` to setup.py
This variable controls whether the Python API is build with or without support for ONNX import functionality built into core nGraph.

* Improved AvgPool unit test coverage. Fixed small bug that was revealed.

* Renamed disabled unit tests to reflect new names.

* Ran clang-format on backend_test.in.cpp to fix format.

* Renamed cpu_results->backend_results in two unit tests.

* Added Jenkins Job No and URL

* Update prepare_environment.sh

- clone onnx models
- remove wheel build artifacts

* Link onnx models

* Update Jenkinsfile

- Only send email on fail,
- Change ONNX branch warning to info field
- Disable cloning after tox tests

* Update prepare_environment.sh

- Added comments
- link ONNX models directory

* Update cleanup

* dynamic to static casts

* ScalarConstantLikeBase needs a dynamic cast

* revert change

*  unary, binary folding

* fix divide wrong template args

* add tests

* fix merge breaks

* Why am I still needing to fix license headers?

* fix a few more in test

* Handle zero sized buffer requests

* Removed aligned buffer initialize() and moved allocation to constructor instead

* onnx: add register operator macro
Signed-off-by: Artur Wojcik <artur.wojcik@intel.com>

* onnx: add set information to 'op' namespace
Signed-off-by: Artur Wojcik <artur.wojcik@intel.com>

* initial rough draft

* import changes md to release notes for readability

* import changes md to release notes for readability

* remove draft

* update README with link to Release Notes

* release notes link

* fix graphic placement

* Wording change on ONNX supported frameworks

* return nullptr when workspace size is zero+modify insert method to accept const lvalue ref

* Unit test added

* move backend specific test files to test/backend directory

* remove unit_test_control

* move tests back to test root

* fix comment

* wip

* fix manifest

* update test to verify all header files are complete, meaning they include what they use.

* disable

* Project initialization commit

* Added unit tests for 3D tensors for argmax

* Refactored reduce to be used by argmax argmin. argmax argmin still has some issues. WIP

* [WIP]First working version of ArgMax ArgMin

* added reduce buffer for the cudnn api calls

* added reduce buffer for the cudnn api calls

* Further modifications. Using rvalues to pass enums to build reduce method

* more unit tests added

* Incorporate Fenglei's comments

* Incorporating Chris's first set of comments

* small change to test file

* Resolving clang issue that was causing argmin test to fail

* Incorporate Chris's  comments

* clang format issue

Signed-off-by: Artur Wojcik <artur.wojcik@intel.com>

* updated unit tests

* remove debug comments

* update onehot

* clang

* fix bugs

* format

* add output_datatype_size to hash

* typo

* hash