* add split concat

* fix bug

* fix bug

* fix bug

* add test

* fix test bug

* add comments

* format

* return intead of check processed

* remove .back() since it's not vector anymore.

* format

* change to paramter tests based on Geoff's comments

* types-> type

* change split size to 256

* Add builder for {de}quantize

* Add declaration in header

* Add mkldnn support for {de}quantize

* Add support for {de}quantize with mkldnn

* Add Dex support

* Generalizing some api's and adding a test case for DQ in backend_test.in.cpp

* Unify scale between ngraph and mkldnn

* Check for nullptrs

* PR feedback

* fix unit test failure

* Adding tests for builder and deleting the backend tests

* curly braces

* test rename

* Update ArgReduce to handle i64 indices.

* Formatting.

* Add throw for output types other than int32/64.

* Add output type to hash.

* Add type to throw.

* Interpreter doesn't currently support 64bit output indices for argmin/max and so disabling this test [JIRA:NGRAPH-3183].

* Temp bn update commit.

* Add CUDNNBatchNorm which adds two additional outputs to batchnorm, the batch mean and batch inv variance.
The batch mean is the same as the output mean if the cummulative average factor is 1.0. Add BatchNormCache pass which replaces all BatchNorm ops that are inputs to BatchNormBackprop
with CUDNNBatchNorm which outputs the saved batch statistics directly to the backprop step.

* Updated bn cache pass, removed extra tests, added test checking that provided stats are used in bprop instead of batch stats.
This test was disabled for interpreter as the reference kernel needs to be updated to use provided statistics.

* Formatting.

* Update to new batch norm API.

* CUDNNBatchNorm -> BatchNormTrainingWithStats

* new line

* Preprocess input variance into BN denominator for cudnn (#1885)

* Add explicit cuda kernel to calculate what cuDNN describes as the inverse
variance. In reality, the backward cudnn kernel for BN requires 1.0f / sqrt(variance + eps),
which is the batchnorm denominator for each channel (a numerically stable inverse stddev).

This introduces op annotations for batch norm backprop and updates the cudnn_emitter to support the insertion of this cuda kernel when required.

* Disable second test on INTERPRETER.

* added half_toward_zero; all previous tests passing

* all rounding modes added with unit tests

* fix cpu emitter

* round mode doc

* round out round modes

* doc typo

* using  names for round modes

* use ceil/floor for rounding functions instead of round/nearbyint

* clean up doc

* equidistant

* split bn into bn_inference bn_training

* fix warnings

* Add GPU support for the new BN ops (#1569)

* Add GPU support and change batchnorm_globalstats test to use BNInference.

* Changed test back to using BNTraining for global stats and updated cudnn backend to account for it.

* Fix issues in merge with master.

* Formatting.

* CPU fixes

* remove 5-arg training BN for now

* more fixes

* python batchnorm changes

* fix onnx_import

* fix a call BatchNormInference c-tor

* yet another fix to BatchNormInference c-tor

* AND yet another fix to batchnorm_inference c-tor

* ops.py

* address adam's feedback

* Remove unnecessary parameter/argument.

* remove batch_norm_training_relu_with_global_stats

* remove bn_relu (training)

* comparisons

* move more unit test out of backend_test.in.cpp

* move more tests

* move more tests

* 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.

* 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

* Add pad with fill operator using the outward-in index pattern.

* Remove static pad and rename build_pad_dynamic -> build_pad. Update maxpool 1d padding.

* Formatting.

* Split build_pad_dynamic into build_pad and build_pad_fill.

* Add test coverage for fixed bug in op::Pad for gpu.

* add a test failed on gpu, pass on cpu

* fixed bug

* get datatype size

* add descript for test

* update comment

* update comments and name

* rename files

* rename runtime TensorView to Tensor

* rename HostTensorView to HostTensor

* add ngraph dequantize op

* use a floating point offset

* code format

* reminder to fix serializer

* add serializer support

* add dequantize test cases

* cleanup and code format

* fix build warning for implicit conversion

* adding nGraph Quantize op

* unit test failing for floating point exception

* unit test working in float

* unit test working in uint8

* improved type checking and polished unit test - passing

* quantized axes working

* inclusive project method

* add round mode

* TODO cleanup

* code format

* adding serializer support - fails build

* add serializer support

* make CPU quantize op work; new tests for int8, clamp)

* fix build failure

* fix GPU build issue

* fix GPU unit test manifest

* use quantized offset

* add is_quantized field to element::Type

* add reduce function to coordinate.hpp

* pass args instead of pointer to array

* add 3d tiled reshpae

* working version

* add shared mem version of 2d, 3d reshape

* remove unused code

* style

* resolve commits

* add test for 3D reshape, some 3D reshape will be treat as 2D

* add unsupported_op exception

* unsupported_op test

* add printout of unsupported op in model

* fix GPU dispatcher check

* fix test designation

* catch exceptions on single file runs too

* add unsupported_op exception where needed

* remove unsupported_op class

* add unassigned op exception

* add unit test

* catch unsupported op in nbench

* add cpu test back

* update all latest merges

* mode change

* Add in_place suport for ReplaceSlice

* Add emit_replace_slice_inplace kernel

* changed file permissions to original

* Formatted code using maint/apply-code-format.sh

* Removed data type check and removed dead code

* Removed setting mkldnn_op(true). ReplaceSlice is not mkldnn op

* 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.

* 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

* IntelGPU backend: Sum operation optimization

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

* use line comments instead of multiline comments for license header

* update more

* update new files

* more header updates

* style

* normalize comments

* address review comments

* argmax

* manifests and serailizer

* argmin

* address feedbacka argmin

* add new lines

*  addnew lines

* address adam's nitpicks

* scott's feedback

* fix unit tests

* enable parameter validation for all unit tests

* Remove validation checks from performance critical code paths and skip layout propagation to inputs

* Add templated call method to backend for cases where users need input validation

* Added missing return

* fix python api compile error due to ngraph api change.

* disable parameter validation in python api

* make validating call a separate call rather than templated

* lrn init

* fix comment

* mkldnn lrn (#1295)

* add serializer + fix compiler warnings

* IntelGPUBackend: Broadcast operation

* IntelGPUBackend: more tests for Broadcast operation

* Move macro to static C function in Broadcast tests

* make pool test check backends other than CPU

* more unit test cleanup