This reverts commit 02083bda.

* Add mkldnn bfloat16 option to C-API

* Add test for bfloat16 gpu

* Change coverage test

* add SetCommandLineOption

* add the print_FLAGS function

* remove the test demo

* modify the location of macro

* add the 'WITH_STATIC_LIB' option on windows

* modify the macro of PD_INFER_DECL

* modify the the fuction name

* modify the unittest

* modify the code style

* Add three passes and api reference of paddle_pass_builder.h

* Remove the NGraph engine from PDPD repository
1. Each operator was removed from the operator's directory
2. Each test was removed from the unittest directory
3. The parallel executor support was removed from the PDPD
4. The CMake file was removed from the PDPD
5. The NG flags were removed from the repository
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* Remove ngraph from:
1. Cmake file
2. Python file
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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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* 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)
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* fix ci aboud PADDLE_ENFOCE
fix merge lod infer op ut
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* Fix Mask rcnn predictor
    1. refine memory optim algorithm to support the model with the block op.
    2. output diff : modify the affine channel fuse
    3. add condition_block_infer op
add interface for setting trt calib table dir
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* add the missing files.
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* 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

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* 4. add the missing file
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* 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
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1. infernce multi card occupy
2. facebox model inference occupy too much
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* Refine default MKL-DNN Pass order

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* Add comment to default MKL-DNN Pass list

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* C-API quantization core

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Co-authored-by: NSylwester Fraczek <sylwester.fraczek@intel.com>

* Decouple Quantizer from AnalysisPredictor

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* fixes after review

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* renamed mkldnn quantize stuff

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* remove ifdef from header file

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* Add enabling quantization

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* remove unused (here) function

support change input size

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fix conv+elemenwise fuse bug.

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* 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
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* 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

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* Refine the tester for MixedRTPredictor.
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* Enable the profiler in TensorRT engine.

* Support the use of combined inference model in TensorRT unittest, and print the shape of feed targets.