test=develop

* mem opt

* test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* refine code  test=develop

* refine code  test=develop

* refine code  test=develop

* refine code  test=develop

* refine with cub test=develop

* fix mkldnn test && remove comments && test=develop

* polish code && test=develop

* add only_forward test && test=develop

* Enable basic MKL-DNN INT8 Conv OP
test=develop

* Modify test case
test=develop

* Clean unittest code
test=develop

* Fix test
test=develop

* Modify test
test=develop

* Enable MKL-DNN INT8 Conv with Relu Fusion OP
test=develop

* Enable INT8 Conv with residual fusion OP
test=develop

* Modify code.
test=develop

* Modify basic INT8 Conv
test=develop

* Modify Conv.
test=develop

* fix style
test=develop

* Fix style
test=develop

* Fix test
test=develop

* Modify code.
test=develop

* Fix test
test=develop

* Enable basic MKL-DNN INT8 Conv OP
test=develop

* Modify test case
test=develop

* Clean unittest code
test=develop

* Fix test
test=develop

* Modify test
test=develop

* Enable MKL-DNN INT8 Conv with Relu Fusion OP
test=develop

* Modify basic INT8 Conv
test=develop

* fix type
test=develop

* Modify test
test=develop

* Enable basic MKL-DNN INT8 Conv OP
test=develop

* Modify test case
test=develop

* Clean unittest code
test=develop

* Fix test
test=develop

* Modify test
test=develop

* Modify basic INT8 Conv
test=develop

* Add test items for mkldnn conv2d

* Fix the regression issue and pass the unit test for conv2d and conv3d

test=develop

test=develop

test=develop

test=develop

- Added new header for MKLDNN reuse functionality

- Extended conv2d_transpose GetExpectedKernelType for MKL-DNN supporrt

- Buildable conv transpose mkldnn and conv mkldnn using conv template

- Conv2d transpose roughlt implemented and buildable

- Added modifications conv2d transpose MKLDNN unit tests

- Fix to UT of conv2d transpose mkldnn op

- Wrong type of MKLDNN primitive was chosen for conv2d transpose

- HAcks for conv2d transpose

- UT enalbed

- Replaced copying loop with memcpy

- Draft of passing lambda into AcquireMemory

- Made reorder (IOHW->OIHW) to be called only once

* 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 output_data to point to the right tensor, also fix transpiler integration

MKLDNN conv + elementwise_add fusion: output and elemwise param share data in conv primitive. Output is properly allocated

* 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)

Also replace memory types from int64_t to size_t

* - Rebase of conv reuse

- clag formatter fixes

- Fix to conv reuse

- Yet another fix

- Fix

- Fix

- clagn format

* - comment update

* Fix conv_op.h

* Fix conv_mkldnn_op

* Fix cpplint issues in detection_map_op

* MKLDNN pool2d OP kernel added

* conv2d and pool2d MKLDNN kernels renamed

* MKLDNN conv2d kernel refactoring