- Refactor step 1

- Compilation fix

- Yet another compilation fix

- Even more compilation fix

- Lint fixes

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- Removed deprectaed PADDLE_ENFORCE occurance

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- Candidate fix to BN forward

- Lint fixes

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- 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

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- Compilation fix

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- Lint

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- Mul fix

- Fix to MKLDNN MUL op and Elementwise MUL UT

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

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- Candidate fix for 5D convolution with groups

- Refactor of fix for conv3d and conv2d in fetch op

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- 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

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- minor fix in UT

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- Lint fixes

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- Extracted key generation from FWD and GRAD into separate function

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- Compilation fix

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- another compilation

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- optimization of TID to string

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* 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
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- compileation fix

- Yet another compilation fix

- Even yet another compilation fix

- Surprise! Again compilation fix

- lint fixes

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- Fix to workspace acquire of LRN

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- Fix to hash of BWD LRN

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- fix to lrn BWD PD acquire

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- Fixing LRN PD creation

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- cosmetic fix in comment

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- Fixes after review

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* - Added partial draft of pooling acquire

- Workspace support

- compilation fix

- Added draft of pooling backward reimplementation

- Segfault fix

- reverted 'any' for diff_dst crewation in pooling

- Lint fixes

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- lint fixes

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- Further lint fixes

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* - Fixes after review

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* - Lint fixes

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* - Even more lint fixes

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* test=develop, fix docker with paddle nccl problem

* test=develop, fix/gcc_4.8_ubt_link_error

* test=develop, fix code format

* rename mkldnn set/get_cur_thread_id() to set/get_cur_mkldnn_session_id()

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* update session id definition and adjust logic for default behavior

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* reset logic in mkldnn reuse as most of cases work in default.

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* Fix bug in quantize kernel which cause crash in vgg16/19 model

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* refine the code to reduce verbose code; test=develop

* remove useless code; test=develop

1. some key generation method is not aligned with PR#17965
2. enlarge ptr lifetime to avoid memory release if SetBlob fails
   otherwise it will get core dump.

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* - Reusing of reuder used in elementwise_add_mkldnn

- Added MKL-DNN sum prim reusing

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- Compilation fixes

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- Yet another compilation fix

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- Yet another compilation fix

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- Yet another linking fix

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- Final compilation fix

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- lint fixes

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- Lint fixes

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* - Fixes after review

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* - removed is_reusing_

* - Added TID to keys for reusing apart from softmax PD

* - compilation fix

* - Yet another compilation fix

* - Batch Norm and Conv adapted

* - Fix to softmax MT

* - Fixes to MT code of MKL-DNN

* - Lint fixes

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

* fix travis ci error, test=develop

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* Relu6 is the bottleneck op for Mobilenet-v2. As the mkldnn supports the conv/relu6 fusion, we implement it fusion via cpass way. Due to the int8 enabling for this fusion will be supported in MKLDNN v0.20, so this PR is focused on the fp32 optimization.

Below table shows the benchmark(FPS) which measured on skx-8180(28 cores)
Batch size | with fusion | without fusion
-- | -- | --
1 | 214.7 | 53.4
50 | 1219.727 | 137.280

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* Fix the format issue

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* Add the missing nolint comments.

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* Fix the typos.

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* Register the conv_brelu_mkldnn_fuse_pass for the MKLDNN engine.

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* Adjust the indentation.

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* Add the test_conv_brelu_mkldnn_fuse_pass case.

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* Slightly update the code per Baidu comments.
Let the parameter definition embedded into the code.
That's will make the code easy to understand.

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* - Reuse of conv PD

- conv transpose pd reused

- Added PD reusing of softmax and Batch Norm

- Refactoring and removal of not needed routines of mkl-dnn ops

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- Fix to reusing conv

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- Lint fixes

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- Further lint fixes

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- Lint  fixes

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- lint fixes

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- Lint workaround

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* - Fix after review on including boost as third party header

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* - Fix after review. Name change to something more descriptive

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* 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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* Optimize key creation of INT8 pool kernel to improve the peformance of ResNet-50 and MobileNet, especially for latency.
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* Optimize key creation of pool fp32 grad.
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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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reason: dereferencing smart pointer is the same as the underlying pointer
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checkpoint for distributed training.

* Enable basic MKL-DNN INT8 Conv OP
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* Modify test case
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* Clean unittest code
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* Fix test
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* Modify test
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* Enable MKL-DNN INT8 Conv with Relu Fusion OP
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* Enable INT8 Conv with residual fusion OP
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* Modify code.
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* Modify basic INT8 Conv
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* Modify Conv.
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* fix style
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* Fix style
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* Fix test
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* Modify code.
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* Fix test
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* Enable basic MKL-DNN INT8 Conv OP
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* Modify test case
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* Clean unittest code
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* Fix test
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* Modify test
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* Enable MKL-DNN INT8 Conv with Relu Fusion OP
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* Modify basic INT8 Conv
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* fix type
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* Modify test
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* Enable basic MKL-DNN INT8 Conv OP
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* Modify test case
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* Clean unittest code
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* Fix test
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* Modify test
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* Modify basic INT8 Conv
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- 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