* fc-dequantize squash
test=develop

* change according to reviews
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* change PADDLE_ENFORCE
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* add second test when fc-dequant do not fuse
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* change all related PADDLE_ENFORCE
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* Add reshape int8 op

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* Change test to CPUPlace

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* Correct tests

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* Implement Int8 FC

* Integrate FC into INT8v2

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* int8 FC: transpose weights before computing scales

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* Add support for activation_type string in FC

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* Disable MKL-DNN's FC in VGG16 and 19

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* Disable FC quantization when mkldnn FC is disabled

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* Solve PADDLE_ENFORCES in FC int8

* Fix Paddle enforces and remove const cast

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* Fix style changes

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* Fix quantizer_tester test and add fc quantization

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* Fix FC test fail on CUDA

* Remove unnecessary log from quantize placement pass

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* Add Thread ID to FC hash key

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* Add comments to MKL-DNN FC Kernel

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* Refactor quantizer

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* Fix linter issues

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* Fix crash in slim googlenet

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* Fix PADDLE_ENFORCE messages

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* Add transpose2 INT8 for mkl-dnn

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* Fix test_transpose_int8_mkldnn

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* Revert "Merge branch 'develop' into transpose_int8_mkldnn_2"

This reverts commit 34011bdb, reversing
changes made to 2ce6473f.

* Revert "Revert "Merge branch 'develop' into transpose_int8_mkldnn_2""

This reverts commit 23754dd7.

* Add template to TransposeMKLDNNHandler

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* Resolve conflict

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* Restore get_size and refactor

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* refactor dygraph,test=develop

* fix failed unittest,test=develop

* polish code,test=develop

* check windows ci error,test=develop
try to fix windows ci error by np.allclose,test=develop

* polish vlog and profiler, test=develop

* try to fix preceding ops order,test=develop

* test transformer in windows ci, test=develop

* use python c-api to speed up tracer.trace,test=develop

* test=develop, fix docker with paddle nccl problem

* test=develop, add ut for debug string and gradient_accumulator

* test=develop, add tests for layer/gradient_accumulator/prepared_op

* test=develop, fix complie error for test_prepared_op

* test=develop, add more ut for dygraph

* test=develop, create API.spec for dygraph api change

* optimize grad maker; test=develop

* optimize grad maker

* test

* grad make optim; test=develop

* fix unittest bugs; test=develop

* add dygraph grad op maker and split_op

* grad op maker refactor; test=develop

* add dygraph grad maker; test=develop

* fix op deformable_conv_v1_op bug; test=develop

* fix deformable_conv prroi pool bugs;

* fix new op grad op maker bug; test=develop

* fix split by ref bug; test=develop

* fix dygraph auto prune bug; test=develop

* fix test_trace bug; test=develop

* fix fused emb seq pool bug; test=develop

* remove useless code in op_desc file; test=develop

* remove useless code, StrVarBaseNode; test=develop

* fix review issues; test=develop

* fix rank_loss grad maker; test=develop

* remove flag in VarBase; test=develop

* fix distributed_notify_op compile bug ; test=develop

* fix reshape op double grad; test=develop

* fix expand as op; test=develop

* add impertive type_defs.h for demo_train; test=develop

* fix inference lib cmake; test=develop

* fix inference lib; test=develop

* fix infernce_lib; test=develop

* fix inference cmake; test=develop

* fix inference lib; test=develop

* fix inference lib; test=develop

* remove condition dygraph grad maker, modify local name; test=develop

* fix split grad maker bug; test=develop

* fix pyramid_op bug; test=develop

* change travis time out limit; test=develop

* restore travis; test=develop

* change timeout limit; test=develop

* Follow Wangzhen's comment in PR 18970, test=develop

* Review comments, test=develop

* Leave fake quantization around mul

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* Replace Fake with Real Quantized Mul

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* Fix bug in quantize placement pass

Nodes in the graph now have checked type instead of node name when they are to be marked for quantization test=develop

* Fix conv2d+dequantize squash for residual fusion

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* Disable conv-requant squash

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* Fix conv2d+dequantize squash for residual fusion

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* Change condition

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* Add a interface to enable cudnn for inference.

* Add cudnn_placement_pass.
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* Set the default value of cudnn_enabled_op_types to null.
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* Write the common basic class, placement_pass_base, to refine the codes.
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* Call EnableCUDNN in unittest.
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* Refine cudnn_placement_pass tester.

* Enable the testing of cudnn_placement_pass in inference's unittest.
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* Add the check of op kernels.
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* Add generalized Conv+Activation MKLDNN fuse pass creation Part2
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* Undefined behaviour of GetAttrIfExists<> FIX
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* Add requantize squash

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* Add more precise tests
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* REname and REfactor tester

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test=develop

* Int8: Fix Pooling output scale

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* Update scales quantization for certain operators

These include: concat, transpose, pool and reshape. test=develop

* Move concat minimum scale finding to quantizer

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add prior_box quantization code

add scale algo rules for prior box

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

* fix travis ci error, test=develop

* - changes to graph detector

- Changes to pass

- Added ut for new pass

- use_pass

- Added pass to mkldnn passes

- fix to registration

- improved verbose messaging for conv bias passes

- Lint fixes

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* - Lint fixes

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* add Concat quantization
add unit test for quantizing concat
fix for wrong value when the input is not in map of calculated scales
add use_quantizer to concat_op.cc
add scale_algo rules for concat

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* missing fix for multiple inputs quantize-squash

* wojtuss review fix: adding comment

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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

test=develop

* 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

test=develop

* add conv_concat_relu fuse

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* add test code

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* added missing include with unordered_map

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* review fixes for wojtuss

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* remove 'should (not) be fused' comment statements

one of them was invalid anyway

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

test=develop

* 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

test=develop

* 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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* add set_not_owned function for graph

* add scope set. test=develop

* add scope_ptr enforce not null before setting.test=develop

* modify the interface of Pass::Allay
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* Polish code
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* Fix Travis CI
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* fix Pass::Apply interface
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* Fix Travis CI
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* Add enabling quantization

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* remove unused (here) function

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* MKL-DNN: Add test for conv bias fuse pass

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* Remove const cast from Conv Bias Pass Test

* Add conv with bias test case for conv+bias fuse ut

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and #pragma once in edited headers

add #include<string> in edited headers

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test=develop