* Add a interface to enable cudnn for inference.

* Add cudnn_placement_pass.
test=develop

* Set the default value of cudnn_enabled_op_types to null.
test=develop

* Write the common basic class, placement_pass_base, to refine the codes.
test=develop

* Call EnableCUDNN in unittest.
test=develop

* Refine cudnn_placement_pass tester.

* Enable the testing of cudnn_placement_pass in inference's unittest.
test=develop

* Add the check of op kernels.
test=develop

* Add simplify_with_basic_ops_pass to replace dropout_op with scale_op when is_test is true.
test=develop

* Delete dropout_op directly when upscale_in_train is true.
test=develop

* Improve the debug string, adding the print of op_desc information.

* Fix the case when dropout's input x is reused as the next op's output.

* Add the pass to inference.
test=develop

* Change the log level.
test=develop

* Add unittest for inplace case.

* Add comment to explain the pass.

* Apply the pass for CPU inference.
test=develop

* Fix the typo.
test=develop

* Add the check of AttrType.
test=develop

* fix mask rcnn bug:
1. affine channel fuse (diff)
2. condition block op (memory leak)
3. merge lod tensor op (diff)
4. memroy optim (diff)
test=develop

* fix ci aboud PADDLE_ENFOCE
fix merge lod infer op ut
test=develop

test=develop

* add fusion_seqpool_cvm_concat test=develop

* simplify pass, test=develop

* fix code style, test=develop

* support sparse gradients
test=develop

* update anakin-engine interfaces for content-dnn

test=develop

* support only-gpu mode of Anakin

modify eltwise parse

test=develop

* modification for thread-safe

test=develop

* Integrated template instance

test=develop

* increase template parameters

test=develop

* support MLU predictor

test=develop

* update anakin cmake files

test=develop

* update TargetWrapper::set_device

* update the initialization of anakin subgraph

test=develop

* use the default constructor of base class

test=develop

* fluid int8 train and trt int8 predict align.
trt int8 predict init
op converter

* 2. align fluid int8 train and trt int8 inference.
enhance quant dequant fuse pass
enhance op converter, trt engine, trt engine op, trt subgraph pass.

* 3. add delete_quant_dequant_pass for trt

test=develop

* 4. add the missing file
test=develop

* 5. i modify the c++ interface, but forget to modify the pybind code
fix the IS_TRT_VERSION_GE bug, and fix elementwise op converter
test=develop

* fuse mul and elementwise add to fc

* Reimplement the FC forward operator

* Fix FC MKLDNN integration by transposing weights

* Add FC MKLDNN Pass

test=develop

* 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

test=develop

* Adjust FC to support MKLDNN Op placement

test=develop

* Adjust Placement Op to set use_mkldnn attribute for graph

test=develop

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

test=develop

* 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

test=develop

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

test=develop

* FC MKL-DNN: fix style changes

test=develop

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

test=develop

* FC MKLDNN: fix CMake paths

test=develop

* FC MKLDNN: Refine placement pass graph mkldnn attribute

test=develop

* Fix Transpiler error for fuse_conv_eltwise

test=develop

* Fix missing STL includes in files

test=develop

* FC MKL-DNN: Enable new output size computation

Also, refine pass to comply with newest interface.
test=develop

* 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

test=develop

* Enable MKL DEBUG for resnet50 analyzer

test=develop

* FC MKL-DNN: Improve Hashing function

test=develop

* 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

test=develop

* FC MKL-DNN: Disable transpose in unit test

test=develop

* FC MKL-DNN: Remove fc_mkldnn_pass from default list

* Correct Flag for fake data analyzer tests

test=develop

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

test=develop

* FC MKL-DNN: Disable fc in int8 tests

test=develop

* add conv_concat_relu fuse

test=develop

* add test code

test=develop

* added missing include with unordered_map

test=develop

* review fixes for wojtuss

test=develop

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

one of them was invalid anyway

test=develop

* 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.

test=develop

* Register the conv_brelu_mkldnn_fuse_pass for the MKLDNN engine.

test=develop

* Adjust the indentation.

test=develop

* Add the test_conv_brelu_mkldnn_fuse_pass case.

test=develop

* 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

test=develop

* move pass to ir

* polish code
test=develop

* fix dependency
test=develop

* cherry-pick commit from 88770542

* cherry-pick commit from 3f0b97df

* cherry-pick from 16691:Anakin subgraph support yolo_v3 and faster-rcnn

(cherry picked from commit 8643dbc2)

* Cherry-Pick from 16662 : Anakin subgraph cpu support

(cherry picked from commit 7ad182e1)

* Cherry-pick from 1662, 16797.. : add anakin int8 support

(cherry picked from commit e14ab180)

* Cherry-pick from 16813 : change singleton to graph RegistBlock
test=release/1.4

(cherry picked from commit 4b9fa423)

* Cherry Pick : 16837 Support ShuffleNet and MobileNet-v2

Support ShuffleNet and MobileNet-v2, test=release/1.4

(cherry picked from commit a6fb066f)

* Cherry-pick : anakin subgraph add opt config layout argument #16846
test=release/1.4

(cherry picked from commit 8121b3ec)

* 1. add shuffle_channel_detect

(cherry picked from commit 6efdea89)

* update shuffle_channel op convert, test=release/1.4

(cherry picked from commit e4726a06)

* Modify symbol export rules

test=develop

refine trt first run
add quant dequant fuse pass
omit simplify_anakin_priorbox_detection template
omit transpose_flatten_concat_fuse template
test=develop

test=develop

test=develop

test=develop

test=develop

* Add cpu_quantize_placement_pass for C-API quantization

test=develop

* added a comment on required pass attributes

test=develop

* Add cpu_quantize_pass for C-API quantization

test=develop

* add cpu_quantize_pass test

* fix lint: add include memory unorderd_map and unordered_set

test=develop

* fuse_relu 1

test=develop

* tuned 2 without squash

* fixes

test=develop

* remove unused vars

test=develop

* refactored

test=develop

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

test=develop

* remove QuantMax and c style casts

test=develop

* last usage of QuantMax removed

test=develop

* 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.
test=develop

* change map to unordered_map

fix the forgotten part of cpu_quantize_pass_tester.cc

test=develop

* removed quantized attribute

* fixed cpu_quantize_pass_tester and op attr comments

test=develop

* removed redundant line

test=debug

* removed gmock

test=develop

* fix after merge

test=develop

* Support Sync Batch Norm.
* Note, do not enable it in one device.

Usage:

build_strategy = fluid.BuildStrategy()
build_strategy.sync_batch_norm = True
binary = fluid.compiler.CompiledProgram(tp).with_data_parallel(
        loss_name=loss_mean.name,
        build_strategy=build_strategy)

* Add cpu_quantize_squash_pass for C-API quantization

test=develop

* add cpu_quantize_squash_pass teste

* fix lint: add include memory unorderd_map and unordered_set

test=develop

* lint fix 2

* fixes

test=develop

* refactored

test=develop

* fix windows ci

test=develop

test=develop

test=develop

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

test=develop

* Remove const cast from Conv Bias Pass Test

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

test=develop

test=develop

* 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

test=develop

test=develop