* Add mention of blob ref of original file from caffe2

* Mention location of source listing originally from LLVM project

* Average pool type checking and kernel; type checking tests

* Fix and enable average-pool tests

* Docstring fix

* Extend AvgPool op type checking to support padding

* Untested code for padded avg-pool

* Unit tests for padded avg-pool

* Add CPU implementation

* Temp delete

* Docstring fix

* Docstring fix

* Add tests mixing padding and stride

* Temporary cut to ease merge

* Restore temporary cut for merge

* Empty commit to try to force CI to wake up

* remove refs on types in tensor,tensor_view_type,convert

* fix build breaks

* change default is_functionally_identical to return false so if an op forgets to override it gets a behavior that might be slower to compile but it will at least work

* add test for empty tuple

* fix null function breaking

* remove a node from users

* style

* add mxnet seq2seq forward and backward

* add benchmarks for seq2seq forward and backward

* Numerically stable sum so we can pass mxnet unit tests

* Add a small initial residual

* Initial GPU_ExternalFunction implementation

Other changes:

Add GPU runtime to same cmake block as GPU, include CUDA headers if GPU enabled

Initial passing (a+b)*c test

Properly link cuda libraries

Simple GPUTensorView implementation

Initial GPU emitter

GPU codegen initial function gen, no kernels yet

Rename GPU emitter and tensor_view_wrapper to match naming convention

* GPU external function based on BASE

* Fix stray base -> gpu

* TensorViewWrapper -> GPU_TensorViewWrapper

* Copy over emitter from base transformer

* Fix for naming dense layout

* Copy kernel emitters from base -> gpu and strip out kernel_utils

* Add aliases to GPU_TensorViewWrappers

* More fixes for naming descriptor::TensorViews

* Move in call_frame implementation from base -> gpu

* apply code format

* GPU codegen running A+B*C

gpu emitters
gpu ctx setup cuda_module kernels
Remove GPU_CF perf counters
Use gpu kernels in external function
Add GPU 1d dot test

Review Changes:
* Remove CPU specific kernel emitting method bodies

* Use copy_data from test/util.cpp, uncomment compileTest

* Use test_utils copy_data function

* Grab function name from pass manager for def, clean up indentation

* Add a few more openmp ops

* fix a warning

* fix merge error

* bump argon version

* ask argon to install itself

* bump version again

* argon lib dir

* installs argon to ngraph_dist

* fix path

* upgrade argon version

Add support for reinitializing the compiler if a compile fails, allowing subsequent compiles to succeed

Sub-PR: image dilation tests (#362) via @adstraw 

* add interpreter nan check option

* add unit test

* the first stab at pattern for sum

test refactoring, debug msg clean up, formatting fixes

removing v1 and cleaning up v2 + formatting

rollback the changes in reduce_ops

rename v2 -> sum_pred

remove unused funcs

switch to new c-tors

remove TensorViewType

removing an assert

fix a docstring to match a c-tor

* fixes after rebase

* speed up reduceslice with kernel emitter

* const-ify and fix a clang warning

* add elementwise ops, slice to for loops

* add broadcast codegen

* add Exp

* fix bugs introduced in eigen kernels

* fix another introduced bug in Eigen

* Fix an Atomic Bug with Sum, do some cleanup

* unit tests pass

* Add Reshape Op, passes Tests

* rewrite sum to correctly handle muti-threading

* Code Cleanup

* add some extra unary ops

* Address review comments

* fix an error in the review comment refactor

* Add Power op

* Add (most) of the Logic Ops

* Make Concat default to OpenMP kernel

* fix n-D reshape issue

* remove caching of ordered_ops

* graph_util logging msgs

* small cleanup

* remove files for the TopologicalSort pass

* remove NGRAPH_DEBUG from graph_util.hpp

* much faster compile time
* Remove all variables and just directly access inputs, output, and temps.
* compare layouts when checking if two ops are equal
* make performance counters available to all backends

* general cleanup

* remove runtime::Value

* more cleanup

* more cleanup

* cleanup

* remove arg_index

* remove argno from Input

* uncleanup

* Simple boilerplate for GPU runtime files

  - GPUBackend
  - GPU ExternalFunction
  - GPUManager
  - GPUCallFrame

* Test for construction all GPU runtime classes

* Comment out calls, constructors haven't been defined

* Clang CUDA source example to later test compiling

Clang cuda example from:
https://gist.github.com/anonymous/855e277884eb6b388cd2f00d956c2fd4

* Initial nvptx compiler copied from CPU compiler sources

* Define FunctionMap and Instruction for gpu external function

* Rename Compiler -> NVPTXCompiler for gpu compile. Add call to compile for test

* Rename StaticCompiler -> NVPTXStaticCompiler for GPU code gen

* CAdd nvptx_compiler and nvptx_execution_engine to gpu sources

* Compiling source unit test using hardcoded PTX

* (a+b)*c test for GPU

* WIP Fix compile

* rmed accidentally included file

* Fix compile, and LLVM link errosr from nvptx_compiler.cpp

* Stub out parts needed for GPU manager

* Test GPU runtime method stubs

* Cleanup

* Add GPU runtime to same cmake block as GPU, include CUDA headers if GPU enabled

* Kill reflexive assertion

* change GPU naming convention to match CPU

* Snake case functions and identifiers in test case

* Change element type to match changes in master

* Make CUDA headers accessible for codegen with GPU transformer

* clang-format

* apply-code-format

* updated the sphinx version using pip install in Dockerfile.ngraph_cpp

added a make target to build the docs to the contrib/docker/Makefile

* avoid upgrade pip message during build

* Definition and type checking for max pool

* Implement kernel, integrate into INTERPRETER, add a few unit tests, make function result type mismatch error message more informative (still need to update tests to reflect that)

* Temporarily delete unit tests to ease merge

* Temporarily delete unit tests to ease merge

* Restore deleted unit tests

* Fix a broken error message check in the unit tests

* Update to handle various TensorViewType-related things going away; add NGVM support

* Add codegen case

* Change various get_blah_shape methods to return const refs, and while we're here, make a similar change where it should have been done in convolution

* Use NDArray for max-pool tests