* support trt serialize when load model from memory

* delete conv_bn_fuse_pass before tensorrt, with which trt serialize engine id is not stable

* Revert "delete conv_bn_fuse_pass before tensorrt, with which trt serialize engine id is not stable"

performance degradation, fix in the future

This reverts commit fa6cd17e60b15df351efda379ddd00e9e9c1fea9.

* add delete conv_bn

* delete path when delete_cache_files

* refine ernie trt dynamic shape support
1. add slice op converter
2. add emb eltwise layernorm fp16 support
test=develop

* fix dynamic shape test ut
test=develop

* fix comments.
test=develop

* fix comments
test=develop

* add elementwise pool2d, prelu, shuffle channel
test=develop

* add scale and refine concat eltwise conveter
test=develop

* refine elementwise converter
test=develop

* refine ut test and enforce error.
test=develop

* modify const cast
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

* refine trt int8 for dynamic range set
test=develop

* refine trt int8
test=develop

Bug Fix: Paddle-TRT cannot handle adaptive pooling in pool2d op converter and "num" attribute in split op converter (#20733)

* fix pool2d trt converter, test=develop

* add fix for split op converter, test=develop

* fix trt bugs when sharing params, test=develop

* add unittest for cascade_rcnn

zerocopytensor support uint8, analysis config support profile, analysis predictor support GetInputTensorShape, test=develop (#19822)

* 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

test=develop