Pretty sure at this point that I was reading the docs correctly.

* WIP input * weights rnn optimization

* concat + slcing + replacing new node works

* WIP unit test case of fusing rnn inputs

* - Added unit test case for fusing rnn input weights
- registered CPURnnMatFusion_v1/v2 in codegen and DEX

* fixed redeclaration of a variable

* Refactored rnn input traformation passes into a single pass

* Refactored CPURnnMatFusion call back functions

* change random generator range to include -ve values in unit test

* address PR comments

* dont fuse if the shape of the data slices dont match

* rename GPU_TensorView to GPUTensor and GPUTensorViewWrapper to GPUTensorWrapper

* undo bad search/replace

* revert change

* cleanup

* cleanup header includes

* cleanup

* cleanup TensorMemoryReservation pass

* include cleanup

* more cleanup

* more header cleanup

* style

* Remove obsolete comments

* Sigmoid and tanh  doc, edit for abs

* Add equation for sigmoid.

* Add CODEOWNERS file (will have no effect until enabled in GitHub settings)

* Review comments, and fix a username

* Tabs -> spaces

* Review comments

* /maint/ to @cconvey

* /maint/ back to @diyessi by default

* rename files

* rename runtime TensorView to Tensor

* rename HostTensorView to HostTensor

* Address deferred comments from PR 1676

* use dynamic pointer cast for added error checking

* set_output_size fix

* add assert

* dont run get_loop_kernels twice

* CI speedup and simplification

* Rebuild cached master when branch build fails

* Fixed sed command

* Fixed cahced nGraph path

* Exit function if cmake or make fails

* Fixed build path

* Fail building in case cached ngraph is not built

* Ensure cached nGraph is on master before pulling

* 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

* remove get_tensor method

* remove get_element_count as it is redundant to get_size

* fix a few issues with examples and python wrapper

* rename get_size to get_element_count and add get_size_in_bytes method

* add quantize op into intelgpu

* IntelGPU backend: ArgMax, ArgMin, LRN operations

* PR1697. Comments addressed

* PR1697. Empty lines added

* add DropOut op and stub to Documentation ToC

* cleanup stub for dropout and add template for op additions

* add checklist as helper for op_stub

* 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

* Move CallFrame functionality into GPUBackend

* IntelGPU backend: Switch Select operation to use implementation from clDNN

* PR1688: Style fix.

Fix DEX_ONLY compile error in cpu_external_function.cpp

Move definition of StaticInitializers out of `#ifndef NGRAPH_DEX_ONLY`

* IntelGPU backend: Types workaround removal

* PR1681. Fix style

* Don't reuse memory for non-destructive ops.

* Update comment.

* CPU Builder: Replace uint8_t with double in partial element type set

* Keep support for uint8_t kernels

* update nbench output to be more consistent for single vs. directory benchmark.

* wip

* add types used in model

* fix test

* style

* catch all exceptions when running any option

* fix CPU dependency

* zero dim elem fix

* switch to find

* fix runtime errors