test=develop

test=develop

test=develop

* MKLDNN handler cleanup

* MKLDNN handler cleanup
test=develop

* using MKLDNNMemoryFormat = mkldnn::memory::format changes
test=develop

* PADDLE_ENFORCE update
test=develop

- Refactor step 1

- Compilation fix

- Yet another compilation fix

- Even more compilation fix

- Lint fixes

test=develop

- Removed deprectaed PADDLE_ENFORCE occurance

test=develop

- Candidate fix to BN forward

- Lint fixes

test=develop

- Refactoring in data_layout_transform

- compilation fix

- Another comppilation fix

- Step further into darkness

- Yet another compilation fix

- Yet another compilation fix

- missing header

- compilation fix

- Added MKLDNN -> Paddle conversion in fetch op

test=develop

- Compilation fix

test=develop

- Lint

test=develop

- Mul fix

- Fix to MKLDNN MUL op and Elementwise MUL UT

test=develop

- Workaround for diffrent weights with groups representation Paddle vs
  MKL-DNN.

test=develop

- Candidate fix for 5D convolution with groups

- Refactor of fix for conv3d and conv2d in fetch op

test=develop

- Compilation fix

- Still same compilation fix

- Compilation fix

- Compilation fix

- Reverted refactoring of fixes

- Adapted test_conv2d_int8_mkldnn so it exects data in NCHW format
  not NHWC

test=develop

- minor fix in UT

test=develop

- Lint fixes

test=develop

* change INT8 to template so that checking dst_dt with if-else could be removed. CI will be enabled after fixing reviews

* reverse user_residual_memory_p and user_bias_memory_p declaration scope
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

test=develop

* 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)

* - Rebase of conv reuse

- clag formatter fixes

- Fix to conv reuse

- Yet another fix

- Fix

- Fix

- clagn format

* - comment update

- Added hash function inside of MKLDNN softmax op to be used as handle for primitives stroing in a
context

- Style fixes to softmax mkldnn op

- Fixes after review

- Coding style

- Fix to style

- style fixes

- style fix

- style fixes

- Fix to cody style check

- Rephrasing a comment

fix t obroken merge

Fixes to rebase

Conflicts:
	benchmark/fluid/models/machine_translation.py
	cmake/external/mkldnn.cmake
	paddle/fluid/operators/softmax_mkldnn_op.cc

- Bumped revision of MKL-DNN up to have softmax backward primitive

- Added choosing MKLDNN softmax grad operator

- First reuse of softmax backward

- Reinvented reusing for softmax

- Fix to crash in reinvented reuse

- Clang format fixes

- Clang format fixes

- Improved softmax mkldnn reuse mechanism

- clang format fixes

- Fix to broken merge

- Fix

This reverts commit 4d8e8ee2, reversing
changes made to d6a9f005.

* Add MKLDNN layout support in Paddle

Add MKLDNN layout in Paddle so that MKLDNN friendly memory layout
can be used in MKLDNN enabled OP kernel. Before this commit, NCHW
is hardcode to be used in all MKLDNN op kernels. As a result,
non-optimized execution path is selected in MKLDNN primitive which
bring worse performance.
Besides framework change, three MKLDNN OP kernels were updated
for using new MKLDNN layout. They are conv/pool2d/batch_norm.
Other MKLDNN OP kernels need be also updated in similar way to
achieve best performance.

* Add MKLDNN layout support in activation OP

* Don't populate layout from input to output when kMKLDNN in

* Refine pool mkldnn op kernel

* MKLDNN layout

* Remove the inferitance from tensor file

* MKLDNN layout: refactoring

* Remove additional #define to register new operator

* Prepare mkldnn tests to work with layout

- Finished draft of pooling reusing of operators

- Using gethash in PoolGrad added

- Removed diagnostic

- Added pool mkldnn grad reusing of primitives

- Added diagnostic

- Removed diagnostic

- added dependency to mkldnn data type for pooling mkldnn

- Added mkldnn memory data type determining based on template type of op

- Compilation warning fix

- codying style fixes

* MKLDNN conv2 OP kernel added

* TODOs added

* mkldnn conv2d OP refactor

* CanCUDNNBeUsed and CanMKLDNNBeUsed moved