* Add a class TensorInplaceVersion to count the inplace version and put it in framework::Tensor instead of Allocation or Variable.

* Add a new attribute `_inplace_version` for VarBase.

* Raise exception if an inplace operation can result in incorrect gradient computation.

* Add a new interface _bump_inplace_version() for VarBase to bump the version whenever the Tensor is modified through an inplace operation.

* For api assign, call _bump_inplace_version() when it's an inplace operation inn dynamic mode.

* Use original var_wrapper if the inplace_version is not changed.

* Replace SnapshotVarWrapperList with SnapshotVarWrapper to optimize performane.

* use iwyu clean include, test=develop, test=win

* compilation error, test=develop

* fix compilation error2, test=develop

* fix compilation error3, test=develop

* fix compilation error4, test=develop

* fix compilation error5, test=develop

* fix compilation error6, test=develop

* fix compilation error7, test=develop

* fix compilation error8, test=develop

* fix compilation error8, test=develop

* fix compilation error10, test=develop

* fix compilation error11, test=develop

* polish one line error message in tensor.cc

* polish error messages in tensor.cc,tensor.h tensor_impl.h

* polish error messages in tensor.cc tensor.h tensor_impl.h

* polish error messages in tensor.cc,tensor.h tensor_impl.h

* polish error messages in tensor.cc tensor.h tensor_impl.h tensor_test.cc

* polish error messages in tensor.cc tensor.h tensor_impl.h

* MKLDNN v1.0 rebase to Paddle 1.6
test=develop

* Add hacky paddle::string::to_string() implementation

* vectorize<int64-t>() -> vectorize() cleanup
test=develop

* PADDLE_ENFORCE and void_cast fixes
test=develop

* Rebase changes
test=develop

* Cosmetics
test=develop

* Delete MKL from mkldnn.cmake
test=develop

* CMake debug commands
test=develop

* Delete MKLDNN_VERBOSE and rebase fixes
test=develop

* Rebase fixes
test=develop

* Temporarily disable int8 resnet101 vgg16 and vgg19 tests
test=develop

* Add libmkldnn.so.1 to python setup
test=develop

* Add libmkldnn.so.1 to inference_lib cmake after rebase
test=develop

* Post rebase fixes + FC int8 changes
test=develop

* Fix LRN NHWC
test=develop

* Fix NHWC conv3d
test=develop

* Windows build fix + next conv3d fix
test=develop

* Fix conv2d on AVX2 machines
test=develop

* add numpy bridge

* fix template compile

* add unittest, add default
test=develop

* fix unittest
test=develop

* fix unittest
test=develop

* zero_copy=True for to_variable,
test=develop

* bug fix
test=develop

* disable deprecated NumPy API
test=develop

* use better design of NumpyAllocator
test=develop

* fix Py_None check
test=develop

* reset c++ tracer when jump out dygraph guard
test=develop

* refine PADDLE_ENFORCE_xx format
test=develop

* bug fix of tracer switch
test=develop

* update decref
test=develop

* 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)"

test=develop

This reverts commit dec9cf53.

* - concat compilation fix

- lint

test=develop

- Lint fixes

test=develop

- Lint fixes

test=develop

- Fix Transpose MKLDNN op

test=develop

* - Implemented draft of primitive desc keeping in Tensor

test=develop

- 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

test=develop

- Fix to UTs

test=develop

- Conv fp32 op was updated

Cosmetic fixes

test=develop

- tensor mkldnn cosmetics

test=develop

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

* - Lint fixes

test=develop

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

test=develop

* - Moved creation of prim desc totally out of Tensor

test=develop

* - Cosmetic fixes adter review

test=develop

* refine tensor
test=develop

* refine tensor
test=develop

* fix device_context log
test=develop

* Add Temporal Allocator

* add Temporay Allocator to DeviceContext
test=develop

* code refine
test=develop

* fix mean_iou
test=develop

* Add DeviceTemporaryAllocator
test=develop

* fix conv_op bug
test=develop

* small fix
test=develop

* code refine
test=develop

* log refine
test=develop

* fix unit test
test=develop

* move double check

* refine concat_and_split
test=develop

* add limit_of_temporary_allocation
test=develop

* fix name
test=develop

test=develop

test=develop

test=develop

add unittest model containing while_op
remove unnecessary codes
test=develop

test=develop

test=develop

test=develop

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