* fix trt bugs when sharing params, test=develop

* add unittest for cascade_rcnn

* paddle::framework::vectorize() templatization

test=develop

* update pybind/imperative.cc

test=develop

* revert update on unsqueeze_op.cc and warpctc_cudnn_op.cu.cc

test=develop

* add tensorrt support for windows

* 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
test=develop

* add the missing files.
test=develop

* 1 add trt fp16 support
test=develop

* update paddle-trt for:
    1. fix bug: when batch > 2, core in split plugin.
    2. add leaky_relu trt5.0 support (yolov3 from 65ms to 42ms.)
    3. add new attr to dropout.
    4. shuffle channel, swish, relu6 support
    test=develop

* 1. fix ci
test=develop

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

ban all trt ut. will fix it later.

test=develop

test=develop

test=develop

1). add static trt load model
2). fix bug: when device_id is not 0, the trt will have a bug
test=develop

add simple static mode loading
test=develop

test=develop

1. bind trt input and output to fluid tensors

test=develop

1). add static trt load model
2). fix bug: when device_id is not 0, the trt will have a bug
test=develop

add simple static mode loading
test=develop

test=develop

1. bind trt input and output to fluid tensors

BUG: After continuing to input different data, the output cannot be aligned
test=develop

test=develop

test=develop

test=develop

test=develop

* Initialize the elementwise plugin.

* Implement the basic CUDA kernel of elementwise plugin.
test=develop

* wip simplify operator framework

* wip

* wip

* done test=develop

* clean test=develop

* fix test=develop

* fix deps test=develop

* fix cpu build test=develop

* fix tensorrt build test=develop

* fix tests test=develop

* fix test=develop

* fix cpu build test=develop

test=develop