* MKLDNN v1.0 rebase to Paddle 1.6
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* Add hacky paddle::string::to_string() implementation

* vectorize<int64-t>() -> vectorize() cleanup
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* PADDLE_ENFORCE and void_cast fixes
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* Rebase changes
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* Cosmetics
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* Delete MKL from mkldnn.cmake
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* CMake debug commands
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* Delete MKLDNN_VERBOSE and rebase fixes
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* Rebase fixes
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* Temporarily disable int8 resnet101 vgg16 and vgg19 tests
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* Add libmkldnn.so.1 to python setup
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* Add libmkldnn.so.1 to inference_lib cmake after rebase
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* Post rebase fixes + FC int8 changes
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* Fix LRN NHWC
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* Fix NHWC conv3d
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* Windows build fix + next conv3d fix
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* Fix conv2d on AVX2 machines
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* add numpy bridge

* fix template compile

* add unittest, add default
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* fix unittest
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* fix unittest
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* zero_copy=True for to_variable,
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* bug fix
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* disable deprecated NumPy API
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* use better design of NumpyAllocator
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* fix Py_None check
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* reset c++ tracer when jump out dygraph guard
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* refine PADDLE_ENFORCE_xx format
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* bug fix of tracer switch
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* update decref
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* feature/buffer_shared_inplace, test=develop

* refine code, test=develop

* fix elementwise_add op cpu inplace and sum inplace bug, test=develop

* add unittest and debug log, test=develop

* fix parallel_executor scope bug, polish code, test=develop

* fix sum op, activation op, single_in_place_inference bug, test=develop

* remove kLocalExecScopeName, test=develop

* fix unittest,test=develop

* fix out_var first version bug, test=develop

* follow comments,test=develop

* remove attribute in Allocator::Allocate, test=develop

* fix travis ci error, test=develop

* fuse optimizer

* Revert "[MKL-DNN] Fix to crash of Transformer when mkldnn is to be used (#16233)"

This reverts commit 13816dd4.
Apart from enabling transformer for MKL-DNN

* Revert "- MKL-DNN pooling updated to set_prim_desc"

This reverts commit c63f6b20.

Conflicts:
	paddle/fluid/operators/mkldnn/concat_mkldnn_op.cc

* Revert "[MKL-DNN] MKL-DNN specific Tensor modification (#15429)"

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This reverts commit dec9cf53.

* - concat compilation fix

- lint

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- Lint fixes

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- Lint fixes

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- Fix Transpose MKLDNN op

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* - Implemented draft of primitive desc keeping in Tensor

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- TransposeMKLDNNHandler::AcquireSrcMemory was reimplemented

- Added nchw and nc formats setting for sake of compatiblity

Fixed unit tests

- Worakaround to problem with 5D data in conv

- Added 3D and 1D MKL-DNN formats for name handles for tensor

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- Fix to UTs

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- Conv fp32 op was updated

Cosmetic fixes

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- tensor mkldnn cosmetics

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- Moved most of mkl-dnn specific code from Tensor to mkl-dnn utils

* - Lint fixes

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* - setting prim dec in Tensor , sets also layout to kMKLDNN

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* - Moved creation of prim desc totally out of Tensor

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* - Cosmetic fixes adter review

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* refine tensor
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* refine tensor
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* fix device_context log
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* Add Temporal Allocator

* add Temporay Allocator to DeviceContext
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* code refine
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* fix mean_iou
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* Add DeviceTemporaryAllocator
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* fix conv_op bug
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* small fix
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* code refine
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* log refine
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* fix unit test
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* move double check

* refine concat_and_split
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* add limit_of_temporary_allocation
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* fix name
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add unittest model containing while_op
remove unnecessary codes
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Use OO style to rewrite memory allocation.

Also replace memory types from int64_t to size_t

* 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