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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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* 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

test=develop

* Fix the format issue

test=develop

* Add the missing nolint comments.

test=develop

* 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.

test=develop

* - 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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* 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

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* removed gmock

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* fix after merge

- 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

test=develop

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* - 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

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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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* mem opt

* test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* refine code  test=develop

* refine code  test=develop

* refine code  test=develop

* refine code  test=develop

* refine with cub test=develop

* fix mkldnn test && remove comments && test=develop

* polish code && test=develop

* add only_forward test && test=develop

* Enable basic MKL-DNN INT8 Conv OP
test=develop

* 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
test=develop

* Modify code.
test=develop

* 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.
test=develop

* Fix test
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* Enable basic MKL-DNN INT8 Conv OP
test=develop

* Modify test case
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* Clean unittest code
test=develop

* Fix test
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* Modify test
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* Enable MKL-DNN INT8 Conv with Relu Fusion OP
test=develop

* 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
test=develop

* Modify test case
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* Clean unittest code
test=develop

* Fix test
test=develop

* Modify test
test=develop

* Modify basic INT8 Conv
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* Add test items for mkldnn conv2d

* Fix the regression issue and pass the unit test for conv2d and conv3d

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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

* add is_test to pooling and activations

add prop_kind support for layers activation. conv and pooling

add a pass that sets is_test to true

add transpiler version of is_test pass

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* patch test and pass

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* add pass to analyzer.h

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* add is_test attr description & pass only on mkldnn

in:
activation_op.cc
batch_norm_op.cc
conv_op.cc
dropout_op.cc
lrn_op.cc
pool_op.cc
sequence_pool_op.cc
softmax_op.cc

* fix is_test handling for activation pool and conv

* change description of is_test for all layers again

* remove GetAttr(use_mkldnn) from pass

* rename correct_mkldnn_test_phase to is_test

and remove dependency on MKLDNN
test=develop

* review fix magic number

* two if(..)s into one

* Check is_test once and pass mkldnn forward prop kind

* dereference shared_ptr with * (without get())

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* add is_test_pass back

test=develop

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MKLDNN conv + elementwise_add fusion: skip connection attribute renamed. Comments about patterns added.

test=develop

MKLDNN conv + elementwise_add fusion: Fix output_data to point to the right tensor, also fix transpiler integration

MKLDNN conv + elementwise_add fusion: output and elemwise param share data in conv primitive. Output is properly allocated

* Fuse Convolution and Eltwise Add into Conv+Bias

* Reduce bias branching at conv_mkldnn_op

* Add MKLDNN build checks for Conv Bias

* Conv-bias: check if bias input exist befor assignment

* Conv-bias: Remove Bias dim check from infershape

It was causing conv3d test to crash upon\ncalling HasInput(Bias)

Also replace memory types from int64_t to size_t