* [CodeStyle] remove all future import

* revert test_error.py

* restore future import in example code

* use yapf to format all python file

* yapf exclude two unittests file for they rely on writing and reading file, and format will break them

* disable diff_py_file because too many diff files cause command following failed

* [Eager] FLAGS_retain_grad set false

* Add FLAGS_retain_grad_ for some tests

* Add FLAGS_retain_grad_ to some tests

* modified set_flags

* modified set_flags

* fix windows-ci and windows-openblas-ci

* import paddle.fluid

* add double yaml

* add inline func

* support 3-rd order gradient

* change code format

* Add elementwise_mul triple grad kernel

* Removed InplaceInferer and polished code

* Support elementwise_add triple grad Kernel

* Change code-format to follow CI std

* double backward, elementwise_div

* fix dx empty. test=develop

* bug fix (#17392)

fix secure bug

* Eanble stack operator for a Ngraph, test=develop (#17406)

* fix sqrt_grad_grad unittest. test=develop (#17410)

* fix sqrt_grad_grad unittest. test=develop

* disable sqrt_grad_grad unittest. test=develop

* test=develop, fix unittest

* test=develop, fix unittest

* test=develop, fix unittest

* test=develop, fix bug

* fix unittest. test=develop

* fix unittest dx. test=develop

* tmp fix! for test... test=develop

* reduce tmp, test=develop

* test=develop, reduce tmp

* fix broadcast unittest. test=develop

* fix format. test=develop

* refine code. test=develop

* refine code. test=develop

* refine GetDoubleGradSafeTensor. test=develop

* fix format. test=develop

add elementwise_sub_grad_grad op for backward of backward calculation

* fix sqrt_grad_grad unittest. test=develop

* disable sqrt_grad_grad unittest. test=develop

* double backward sqrt

* refine unittest. test=develop

* refine test. test=develop

* remove alpha in unittest. test=develop

* test=develop, double backward reduce_mean

* add comment. test=develop

* fix format. test=develop

* rename GradGrad -> DoubleGrad. test=develop

* fix op_use_default_grad_op_maker.spec. test=develop

* add elementwise_add_grad_grad op. test=develop

* use defined GradMaker. test=develop

* add double grad for mul_op. test=develop

* fix format. test=develop

* fix format. test=develop

* fix format. test=develop

* refine code. test=develop

* remove setzero. test=develop

* fix dx/dy init bug. test=develop

* fix format. test=develop

* add double grad for elementwise_mul. test=develop

* remove comment. test=develop

* fix grad sum. test=develop

* fix for axis expand. test=develop

* add test for axis expand. test=develop

* add double grad for square. test=develop

* formax code. test=develop

* fix for grad sum. test=develop

* refine shape. test=develop

* refine extract. test=develop

* Add conv2d_grad_grad_op
* Extracte the cuDNN conv algo searching code in conv_cudnn_helper.h.
    - Now use it in conv2d_grad_grad.
    - Will simply the searching code in conv2d and conv2d_grad in next PR.
* Enhance and fix bug in unit testing of gradient_checker.
* Support to fetch empty variables，return None in Python.

backward of backward: leaky_relu

Support backward of backward for Relu and add a new gradient checker by comparing theoretical and numerical Jacobian. (#16862)

* Support backward of backward and a new gradient checker
* Rename decorators.py to decorator_helper.py, since Python on Windows CI has decorators package.

1. Add ReluDoubleGradMaker when register relu_grad.
2. Add a new gradient checker by comparing theoretical and numerical Jacobian.  Check double gradients by double_grad_check.