* fix unittest_group_norm_op_v2, test=develop

* fix unittest_group_norm_op_v2, test=develop

fix cuda atomic for ARCH<350 for the automic_max

* Add pass compatibility check for four mkldnn pass, test=develop

* modify ci api white list, add annotation

* modify ci api white list, add annotation

* move gpu_not_white list to wlist.json

* add null line

* update gcc8 in python3 ci docker

* change cuda 10.2

* update cudnn8

* nvidia error cuda10.2-cudnn8-centos6 images

* fix third cache

* add unittest count of windows

* Reduce the number of retries

* make places of DataLoader optional. test=develop

* test=develop, bug fix

As the title, decrease random failure probability for test_parallel_executor_mnist

The old code set larger delta when comparing reduce and all reduce, but didn't set all. I added it.

On my linux machine, I run 100 times, no failure occurs. In addition, we only saw this random failure on CI two times since I worked. I thought it was rare and I just increased the delta.

* fix error message in conv/conv_transpose. test=develop

* refine err msg in shuffle channel op

* fix approveals message;test=document_fix

* fix approveals message;test=document_fix

* fix tensorrt 6 build error. test=develop

* fix. test=develop

* bug fix

* test=develop

* Remove dependency on nltk for paddle __init__.
test=develop

* Remove nltk.movie_reivew sentiment dataset to remove dependency on nltk.
test=develop

* 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

* reproduce summary api

* rename StaticLayer

* rename

* refine the error message for bath size like

* fix dtype of gradientclipbyglobalnorm

* fix dtype bug of GradientClipbyGlobalnorm

Add GPU Kernels of Segment Ops,  support, sum, max, min, mean

* init commit of new save/load

* fix failed unittests

* fix save_load_v2 unittest failed

* fix failed unittest & polish doc

* add tests for coverage

* add more tests & move static apis

* fix example code error

* polish emample code

* fix detail example code problem

* [bug fix]:Memory increases after adapting the cudnn version to 8

* [bug fix]cudnnGetConvolutionForwardAlgorithm not defined

* Makes the Bind Method more intelligent

* Makes the Bind Method more intelligent

* fix unittest

* fix unittest

* fix conflict

The calculation result of Diag_v2 Op under large size input is wrong