Also fix MKL-DNN pooling integration for ceil mode

* 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

* Fix CPPLint errors in operators

* Fix prior box op

* Fix Prior Box op

* Fix top_k_op.cu

* Fix pool mkmldnn

* Fix pool mkmldnn

* MKLDNN pool2d OP kernel added

* conv2d and pool2d MKLDNN kernels renamed

* MKLDNN conv2d kernel refactoring