* use iwyu clean include, test=develop, test=win

* compilation error, test=develop

* fix compilation error2, test=develop

* fix compilation error3, test=develop

* fix compilation error4, test=develop

* fix compilation error5, test=develop

* fix compilation error6, test=develop

* fix compilation error7, test=develop

* fix compilation error8, test=develop

* fix compilation error8, test=develop

* fix compilation error10, test=develop

* fix compilation error11, test=develop

* support trt dynamic shape int8

* add unittest

* add support for sigmoid; adapt to trt6+ api

* Paddle-TensorRT support slim QAT. test=develop

* add comments. test=develop

* use RenameInput instead of ResetInputs. test=develop

This commit fixs the compiling bug regarding unique_ptr of IOptimizationProfile.

IOptimizationProfile has protected dtor and is controlled by TensorRT
internally. Application shouldn't delete the pointer of IOptimizationProfile.
See TensorRT document: https://docs.nvidia.com/deeplearning/sdk/tensorrt-api/c_api/classnvinfer1_1_1_i_builder.html#a9ac47e100454151d8206ac91d543299a
test=develop

test=develop

* add dynamic plugin support.
test=develop

* change emb eltwise layernorm to math function
test=develop

* add emb eltwise layernorm
test=develop

* can run dynamic shape ernie
test=develop

* fix ci
test=develop

* add ut for trt ernie dynamic

test=develop

* refine dynamic shape c++ interface.
test=develop

* fix comments
test=develop

* fix comments
test=develop

* change the ci trt from version 5. to 6.0

* paddle-trt dynamic shape support init

* conv+bias or conv+bn dynamic shape support
test=develop

* modity trt engine opconvert
test=develop

* fix ci error
test=develop

* add mutex for trt engine
test=develop

* add the test for copy_to_cpu
test=develop

added splitter "__" between weight name and suffix number to avoid conflicts.

* refine trt int8 for dynamic range set
test=develop

* refine trt int8
test=develop

* fix trt bugs when sharing params, test=develop

* add unittest for cascade_rcnn

* 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

* 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

* fix trt fp16 ce error
test=develop

* add an vlog if the user use trt4 and specify fp16.
test=develop

* 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

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

1. bind trt input and output to fluid tensors

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

fix comments

test=develop

test=develop

* Initialize the elementwise plugin.

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

test=develop