test=develop

add module cleanup
test=develop

* add is_test to pooling and activations

add prop_kind support for layers activation. conv and pooling

add a pass that sets is_test to true

add transpiler version of is_test pass

test=develop

* patch test and pass

test=develop

* add pass to analyzer.h

test=develop

* add is_test attr description & pass only on mkldnn

in:
activation_op.cc
batch_norm_op.cc
conv_op.cc
dropout_op.cc
lrn_op.cc
pool_op.cc
sequence_pool_op.cc
softmax_op.cc

* fix is_test handling for activation pool and conv

* change description of is_test for all layers again

* remove GetAttr(use_mkldnn) from pass

* rename correct_mkldnn_test_phase to is_test

and remove dependency on MKLDNN
test=develop

* review fix magic number

* two if(..)s into one

* Check is_test once and pass mkldnn forward prop kind

* dereference shared_ptr with * (without get())

test=develop

* add is_test_pass back

test=develop

test=develop

test=develop

MKLDNN conv + elementwise_add fusion: skip connection attribute renamed. Comments about patterns added.

test=develop

MKLDNN conv + elementwise_add fusion: Fix transpiler integration to predict skip connection input of eltwise_add

MKLDNN conv + elementwise_add fusion: Fix output_data to point to the right tensor, also fix transpiler integration

test=develop

* hide operator API

* update

* update api.spec

* fix merge

* fix test

* Fuse Convolution and Eltwise Add into Conv+Bias

* Reduce bias branching at conv_mkldnn_op

* Add MKLDNN build checks for Conv Bias

* Conv-bias: check if bias input exist befor assignment

* Conv-bias: Remove Bias dim check from infershape

It was causing conv3d test to crash upon\ncalling HasInput(Bias)

* hide misc APIs

* update

* fix transformer test

* update API.spec

* remove block api

* remove clone_variable

* hide block inner apis

* update

* fix tests

* bnorm+relu fuse for mkldnn

* separate fuse_relu function

* bug fix

* proper while range in inference_transpiler

* description fix

* review fix

* review fix

* unit test for fwd batch norm+relu MKLDNN fuse

* add test float16 inference accuracy example

* complete the test

* clean code

* add argument parse and refine tests

* add shell script

* add float16 benchmark code

* refine code

* prepare for contrib/float16

* put things in contrib float16 folder

* update benchmark result

* further update benchmark report

* add float16 inference report

* update report

* add float16 transpiler

* fix feed fetch target names mismatch

* fix cast op input change issue

* fix program desc flush error

* fix inconsistent var names in block desc bug

* code clean up

* add float16 infernce C++ example and fix prune bug