unnecessary prefixes can be avoided

* change Emit* function to templated

Remove additional target attributes since we already supply

the host CPU name in TargetOptions

* Doc for the rest of the Cs.

* Review comments.

* Move op implementation out of namespace

* Update includes for CPU ops

* Op not in default tests.

* Allow caching of external dependencies (everything but TBB, which I can't figure out yet)

* Tweaks to get CPU backend building and linking (but not actually working) on macOS

* Tweaks to codegen/CPU backend to enable macOS (no builtin headers yet)

* Re-enable header caching stuff on macOS

* Suppress unsupported compiler warning for Apple Clang

* Fix includes for macOS compatibility

fixed sphinx_doc target in the contrib/docker/Makefile to build the docker image as a dependency

removed doxygen_doc target from the contrib/docker/Makefile as it is included with make sphinx_doc as a dependency for make html

* fuse dot(a,b) + c

cblas_gemm working on mlp

rebase & small fixes

enable debug output

support replacing function's outputs

* WIP pattern matching for variance

* - Added pattern matcher graph to look up variance(sub graph) in bn
- Added test case to verify the variance graph pattern

* added batch norm mean pattern matcher.

* remove reshapes

(cherry picked from commit ecad321fb1b1bc3f7facda229beb940118ca0701)

* fixed mean test to use Matcher.

* resolve merge conflict in test/pattern.cpp

* WIP bn fprop pattern

* fprop bn fusion working

* - Added unit test case to read the bn serializeed *.json file and run bn fprop fusion pass
- Added batchnorm header file and defined the bn class to emit the mkldnn kernel
- Added pattern matcher for fprop bn in CPU graph_rewrite pass

* WIP MKLDNN fprop bn emitter code

* completed fprop batchnorm kernel in CPU emitter

* fixed bug in the emitter code for fprop bn

* - Fixed copilation issues
- unit tests are passing for bn emitter fprop code

* Added support to compute fprop bn with mean annd variance as input

* resolved compilation issues

* refactored bn fprop code

* - added batchnorm src file to the CMakeFilelist
- moved bn fusion under CPU runtime/pass/cpu_fusion
- fixed compilation issue

* Resolved compilation issues in bn emitted code

* Addded debug statements in fprop bn emitted code

* added batchnorm.cpp src file

* - Added test case to test fprop batchnorm with known tensor values
- fixed bug related to defining weights in fprop bn

* - Added test case for fprop batchnorm Op
- Added test case for mean and variance pattern matcher
- Added fprop bn *.json file with input having 4dmis mb2c3h2w2
- refactored fprop bn op class

* Style fix

* - Removed Debug symbols

* - Fixed header template with correct year
- appended mkldnn.hpp in the CPU generated code

*  Addressed PR review comments
 -  added support for batchnorm op in serializer and de-serializer
 - added more sanity in bn constructor
 - renamed "BatchnormFprop" -> BatchNorm

* - Addressed PR review comments
- replaced auto with speicfic mkldnn::type in emitted bn kernel
- modified function signature to take 'eps' as double instead of <Node> type

* added missing header files, resolved compilation issue

* style fix

* Addressed PR comments
1. initilized member variables for bn in the same order as they are defined
2. renamed bn member variables to start with m_* as per coding convention
3. moved bn fusion test to test/cpu_fusion.cpp
4. style fix
5. added more checks to evaluate type and shape of inputs to bn

* Added support for EMITDECL macro for batchnorm

* - made correction to batchnorm src file name batchnorm -> batch_norm as per coding guidelines
- corrected bn copy_with_new_args() method

* Removed redundant SqrtOp support in serializer

* Doc the A-ops.

* Better structure for ops and the docs around them, based on cyphers branch for doc-the-a-ops

* More edits for merge into preview branch

* Update link to framework integration guide page on testing libngraph

* New branch for editing public-facing docs

* Make sure updated graphic gets added, correct compiler version on install page

* Update README to match content on legacy Python repo

* Let's see if this fixes the bad merge

* Working down in doc directory, forgot to update top-level readme with feedback from review

* Correct typo

* Trying to fix the ops

* Try adding convolution manually from master

* Update pictorial image of nGraph IR

- enable distributed ngraph (MPI)
- add AllReduce op to ngraph core, interpreter and CPU backend
- add AllReduce unit test

in emitter function definitions

CPU Layout Part 1: Infrastructure

* Some more op doc

* Review comments

* Review comments.

* Review comments