* IntelGPU backend: BatchNorm operation optimization

* PR1579. Function moved by request

* ReduceSum and ReduceSumSquare ONNX operations.

* Add new reduction ops.

- ReduceLogSum,
- ReduceLogSumExp,
- ReduceMax,
- ReduceMin,
- ReduceMean,
- ReduceProd.

* Add ReduceL1 and ReduceL2

* Utility generic functions generating monotonic sequences of values.

* Review comments: return AxisSet not std::vector

* Use common functions for generating monotonic sequence.

* Review comments.

* Add support for Dequantize op via mkldnn for IA backend (codegen + DEX)

* Remove unused variable

* Static cast target range

* constant + pad

* adding broadcast test back

* Implement TopK.

* Update python wrappers for TopK, ArgMin and ArgMax.

* Address some reviewer comments.

* Add type property check tests for TopK.
Set correct TopK behavior for K==0.

* TopK: Add 1d and 3d unit tests.

* Address more reviewer comments.

* Apply code style.

* Update doc build v and fix doc on captioning

* Clarify to build the library

* update link on README

Double curly-brace initialization (required by clang for non-templated functions) causes a compiler error in centos. (#1561)

Since the warning is not enforced in clang for templated functions, we can get around the centos compiler error with only a single set of curly braces here.

* onnx: add missing header files
Signed-off-by: Artur Wojcik <artur.wojcik@intel.com>

* onnxifi: implementation of onnxGetBackendIDs
Signed-off-by: Artur Wojcik <artur.wojcik@intel.com>

* onnxifi: add unit tests for onnxGetBackendIDs
Signed-off-by: Artur Wojcik <artur.wojcik@intel.com>

* onnxifi: change std::out_of_range to std::length_error
Signed-off-by: Artur Wojcik <artur.wojcik@intel.com>

* onnxifi: after review changes
Signed-off-by: Artur Wojcik <artur.wojcik@intel.com>

* simplify result copy elimination

* gpu fix

* remove include header

* circumvent gpu issue

* add a whitepace

* add cuda reduce

* clang format

* fix bugs

* fix bug

* add 1d reduce

* clang format

* fix bugs

* unroll loop

* remove debug info

* revert tests

* unroll 1D reduce op

* add comments

* using cudnn for nd to scalar reduction

* remove cuda 1d reduction since cudnn version is faster

* remove 1D kernel

* fix bugs

* 1d multi block size

* remove debug

* change kernel name

* add reduce to scalar optimization, add test

* fix bugs and tune parameters

* clang format

* update comments

* update comments

* update comments

* clang format

* update comments

* remove wrong comments, apply clang format

* resolve Bob's comment

* clang format

* pass shared mem size from cuLaunchKernel, set unroll loop size through host code

* remove unused code.clang format

* change reduce to thread with shfl for each warp first

* add seed

* unroll size

* Merge descriptor::TensorView into descriptor::Tensot

* fix GPU build

* Added cmake flags to specify D_GLIBCXX_USE_CXX11_ABI and disable building of doc

* Renamed the NGRAPH_DOC_BUILD_ENABLE flag based on PR feedback

* IntelGPU backend: Sum operation optimization

* PR1545. Comments addressed. Test added. Helper function refactored.

* Move reshape utils down to reshape namespace.

* Reshape operation.

* Reshape operator binding.

* Error fixes.

* Reshape unit tests.

* Move flatten utility function to reshape namespace.

* Fix unused catched exception object

* Add Constant support for int64

* Review fix.

* clang-format

* Review fix part 2.

* Enable output shape as a second node input (only Constant).

* Unit test for "dynamic" output shape (from Constant node).

* Review fixes.

* Make sure second Reshape op input is Constant node.

* IntelGPU backend: helper function improvement

* PR1541. Change string to stringsteam

* Validate/infer types as a virtual function
BroadcastLike, ScalarConstantLike
Set output shape separately from output types
Remove some obsolete tests
Replace *Like ops with fixed type versions

* Review comments

* Remove TensorViewType

* Remove PrimaryTensorView

* Reviewer comments

* Style fix.

* Another try at GPU

* GPU

* Simplify class hierarchy

* More of previous.

* Better errors

* Remove unneeded classes

* Merge

* Update Python bindings

* clang-format

* Remove redundant files

* Remove commented out lines

* clang-format

* Group includes

* Missing tests

* Merge error

* Expose onnx_import C++ interface in Python API.

* Pretty printing.

* Add Computation interface using Ngraph Function objects plus UT.

* Apply code format.

* Remove unnecessary stream open mode.

- Code formatting.

* Fix onnx_import submodule visibility.

- Folder restructurization.

* Fix some small errors.

- Wrong function type annotations.
- Class doc.
- Code formatting.
- Class inheritance from object.

* Use modified Runtime class interface.

* Add model for test_onnx_import.

* Revert back to old API.

- Use of Function object in Computation class.

* Use of previous verions API.

* Small refactoring

* Code cleanup

* onnxifi: upgrade libonnx
Signed-off-by: Artur Wojcik <artur.wojcik@intel.com>

* onnx: upgrade libonnx to version 1.3
Signed-off-by: Artur Wojcik <artur.wojcik@intel.com>

* [ONNX] Concat operator

* Style fix

* only print details if details enabled

* refactor print routines to main file

* refactor for multi dir support

* dir support prints nice results