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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* refractor the function ConvFwdPrimitiveDesc
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* change according to review
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* use pointer way without boost::optional
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* pass vector to function by reference instead of raw vector
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* change pointer to shared_ptr
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* added unit test for QAT FP32 & INT8 comparison

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* enabled other models and updated filenames

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* added accuracy check and multiple batch handling

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* removed quantization_mkldnn_pass.py

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* cleanup

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* updated model paths

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* renamed tests without MKL-DNN

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* fix reusing mkldnn pool2d primitive

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* add performance measuring

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* fix accuracy statistics

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* removed non-mkldnn tests

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* added conv2d_depthwise->conv2d mkldnn transformation

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* format update

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* fixed creating key for pool2d grad

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* added pass

* Fix the accuracy issue while using float precision to get the scale.

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* Fix the format issue when 'X' is not nchw.

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* removed output comparing and changed number of images

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* cmake and comment fix

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* updated acc threshold for QAT comparison tests

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* added OMP_NUM_THREADS setting

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* enable all QAT INT8 tests

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* restored upstream version of a file

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* modified directory names

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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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* fix the bug of mobilenet-ssd INT8 inference without overloading GetHash
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* remove the out_grad->format() in TransposeMKLDNNGradOpKernel
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* add INT8 conv+relu6 fuse and enbale mobilentv2 INT8 test
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* change fasle and 0.0 to fuse_brelu and brelu_threshold
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change the "fuse_relu||fuse_brelu" to "unsigned_output"
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* Use relu instead of brelu as INT8 post-op because INT8 brelu is not enabled in mkldnn v0.18
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* continuous-integration fix
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* fuse mul and elementwise add to fc

* Reimplement the FC forward operator

* Fix FC MKLDNN integration by transposing weights

* Add FC MKLDNN Pass

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* FC MKLDNN Pass: change memcpy to std::copy

* Fix MKLDNN FC handling of mismatch input and weights dims

* Lower tolerance for MKL-DNN in resnet50 test

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* Adjust FC to support MKLDNN Op placement

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* Adjust Placement Op to set use_mkldnn attribute for graph

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* MKLDNN FC: fix weights format so that gemm version is called

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* FC MKLDNN: Remove tolerance decrease from tester_helper

* FC MKL-DNN: Refactor the code, change input reorder to weight reorder

* MKL-DNN FC: Introduce operator caching

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* FC MKL-DNN: Fix the tensor type in ExpectedKernelType

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* FC MKL-DNN: fix style changes

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* FC MKL-DNN: fallback to native on non-supported dim sizes

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* FC MKLDNN: fix CMake paths

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* FC MKLDNN: Refine placement pass graph mkldnn attribute

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* Fix Transpiler error for fuse_conv_eltwise

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* Fix missing STL includes in files

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* FC MKL-DNN: Enable new output size computation

Also, refine pass to comply with newest interface.
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* FC MKL-DNN: enable only when fc_mkldnn_pass is enabled

* FC MKL-DNN: Allow Weights to use oi or io format

* FC MKL-DNN: Adjust UT to work with correct dims

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* Enable MKL DEBUG for resnet50 analyzer

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* FC MKL-DNN: Improve Hashing function

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* FC MKL-DNN: Fix shape for fc weights in transpiler

* FC MKL-DNN: Update input pointer in re-used fc primitive

* Add log for not handling fc fuse for unsupported dims

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* FC MKL-DNN: Move transpose from pass to Op Kernel

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* FC MKL-DNN: Disable transpose in unit test

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* FC MKL-DNN: Remove fc_mkldnn_pass from default list

* Correct Flag for fake data analyzer tests

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* FC MKL-DNN: Add comment about fc mkldnn pass disablement

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* FC MKL-DNN: Disable fc in int8 tests

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* fix quantize_squash_pass segfault when there is no tensor linked do Bias input

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* add googlenet test

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* fix concat CreateKey not using input format

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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)"

test=develop

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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* Enable INT8 Concat Kernel to improve the performance of MobileNet-SSD.
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* Optimize UT format.
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* Fix UT file address issue.
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* Refine the license year.
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* Optimize code for new API.
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* Restructure INT8 Concat kernel.
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* Enable INT8 transpose kernel for MobileNet-SSD improvement.
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* Refine the license year.
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* Delete redundant code.
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* Add axis check.
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* Add cpu_quantize_pass for C-API quantization

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* add cpu_quantize_pass test

* fix lint: add include memory unorderd_map and unordered_set

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* fuse_relu 1

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* tuned 2 without squash

* fixes

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* remove unused vars

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* refactored

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* fix lint c-style cast -> C++ style cast

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* remove QuantMax and c style casts

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* last usage of QuantMax removed

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* Fix Analysis Predictor UT

Check if memory_optimize_pass has already been added
to the analysis config before adding a new one, so
that it is not added multiple times.
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* change map to unordered_map

fix the forgotten part of cpu_quantize_pass_tester.cc

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* removed quantized attribute

* fixed cpu_quantize_pass_tester and op attr comments

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* removed redundant line

test=debug

* removed gmock

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* fix after merge

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* Enable INT8 ReQuantize OP
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* Clean code
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* Add comments
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* Revert "Clean code"
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This reverts commit a7a49b8aa214f9730cb84e11ea96da564fe4b4d9.

* Modify requantize op test
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* fix requantize UT by moving public function to public test file.
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* Fix test fail due to file address change.
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* Change file address for requantize 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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- MKLDNN ops revisited

- disabled softmax modifications

- disabled elementwise_add

- reverted LRN modifications

- reverted SUM primitive

- Partial reviing of softmax

- Enable softmax

- Softmax changes

- LRN is back

- LRN partially disabled

- LRN is back

- LRN fix

- compilation fixes

- Sum fixed(hopefully)

- Enabling (partially) elementwise_add

- Fixes to elemenwise_add

- Lint fixes

quantize fix

- compilation fix

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Disabling pooling

- Disabled quantize 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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reason: dereferencing smart pointer is the same as the underlying pointer
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