* 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

1. infernce multi card occupy
2. facebox model inference occupy too much
test=develop

* Refine default MKL-DNN Pass order

test=develop

* Add comment to default MKL-DNN Pass list

test=develop

* C-API quantization core

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

* Decouple Quantizer from AnalysisPredictor

test=develop

* fixes after review

test=develop

* renamed mkldnn quantize stuff

test=develop

* remove ifdef from header file

test=develop

* Add enabling quantization

test=develop

* remove unused (here) function

support change input size

test=develop

test=develop

test=develop

fix conv+elemenwise fuse bug.

test=develop

(test=develop)

* 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

test=develop

* patch test and pass

test=develop

* add pass to analyzer.h

test=develop

* 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())

test=develop

* add is_test_pass back

test=develop

* Refine the tester for MixedRTPredictor.
test=develop

* Enable the profiler in TensorRT engine.

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