This reverts commit c5b082c6.

* onnx: return signle nGraph function with multiple outputs
Signed-off-by: Artur Wojcik <artur.wojcik@intel.com>

* onnx: remove excessive code
Signed-off-by: Artur Wojcik <artur.wojcik@intel.com>

* Update ngraph python unit tests

* Update setup.py

* Update setup.py

* fix errors in edit

* fix ascii error

* get the right readme

* rename a variable at Scott's request

* Add license files and cleanup compiler/linker options.

* Update comment on c++ standard option flag

* Fix batchnorm argument order, cleanup some comments, fix backprop

* Merge error

* Clean up training function, organize inference test

* BatchNormInference tests

* Training case

* Training test

* Fix autodiff BatchNorm test

* Cleanup

* Move file to doc checkout

* Update disabled test name in igpu manifest
Fix unnused variable

* Unit tests disables

* Review comments

* [Py] Add make python_wheel target

* Add make install step

* Use tagged pybind11 version 2.2.4

* remove forward op

* fix bbrks

* fix pybind c-tor for max_pool_bprop

* Add new c-tor to MaxPoolBackprop that takes MaxPool as an explicit argument. Add serializer support.

* Add nvgpu support for new backward pooling c-tor, and calculate fprop when it isn't available.

* Add extra layout for 3 arg maxpool backprop.

* Formatting.

* cpu_workspace_insertion to expect 3-arg maxpool bprop

* GPU: add bprop_needs_pooling flag to primitive hash

* Update INTELGPU arguments_check for MaxPoolBackprop and GPU invocation for avg pool.

* Move ParameterVector and ResultVector to the ngraph namespace where they belong

* update python wrapper

* more python fixes

* style

* Update setup.py

* fix some new code

* onnx: enable external weights to enable Caffe2 support
Signed-off-by: Artur Wojcik <artur.wojcik@intel.com>

* onnx: update ONNX importer interface documentation
Signed-off-by: Artur Wojcik <artur.wojcik@intel.com>

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

* create unique_ptr backend

* unit test cleanup

* address more code that was recently added

* change from reference to pointer when passing backend to reduce the number of lines changed.

* fix build error

* fix python wrapper

* style

* more specific treatment for unique_ptr

* Add PlaidML backend

* CR comments

Used m_ prefix for members; removed trailing underscores
Updated license headers
Moved associated header inclusions to project blocks
Wrapped comments to 100 chars
Added missing newlines between functions
Removed nested namespaces in operation implementations

* Add earhart to CODEOWNERS

* Rebase updates

* style

* 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)

* [Py] Apply PEP8 code style to setup.py

* Remove unused var

* Update version to 0.9.0

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.

* rename files

* rename runtime TensorView to Tensor

* rename HostTensorView to HostTensor

* 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

* Update fusion doc and add ONNX build flag to buildlb doc

* Fix PR comments

* Final PR review comments addreswsed

* Fix link on reformmatted doc README

* Delete index.rst.save

* 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.

* 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

* use line comments instead of multiline comments for license header

* update more

* update new files

* more header updates

* style

* normalize comments

* address review comments

* [Py] Wrapper for LRN

* Add missing header

* Add default param values, docs and some unit tests

* Fixes

* clang-format

* [Py] Add __repr__ to Strides and CoordDiff

* Apply clang-format

* Repr fix

* Apply clang-format

* [Py] Add convolution_backprop_data to API

* Conv fix

* Update input_validation.py

* Update runtime.py

* Update types.py

* Update broadcasting.py

* Enable retrieving data from Constant in python.

* Test on wide value range.

* complete the new backend construction/destruction API
* close each dlopen
* don't close libraries for now as it causes python to segfault

* updated to work with llvm 8.1 that tensorflow is built with

* sane extensions on the mac

* not doing rpath on apple

* apply style