* add double yaml

* add inline func

* 增加PixelUnshuffle的形状推断

* 增加PixelUnshuffle的算子注册

* 增加PixelUnshuffle及其梯度的核函数

* 增加PixelUnshuffle算子的描述

* 增加PixelUnshuffle算子的签名

* 在Python层面增加PixelUnshuffle

* 增加PixelUnshuffle的单测

* Update test_pixel_unshuffle.py

* test=document_fix

* Update test_pixel_unshuffle.py

增加对extra_repr的测试

* 修正代码格式

* Update test_pixel_unshuffle.py

修正对extra_repr的测试

* 修改pixel_unshuffle核函数的实现位置

* 修正代码格式

* 完善对输入的检查

* Update test_pixel_unshuffle.py

* 完善pixel_unshuffle的输入检查

* Update pixel_unshuffle_op.cc

* Update unary.cc

* add pixel_unshuffle

* Update test_pixel_unshuffle.py

* Update vision.py

* 调整代码格式

* Update vision.py

* Delete extra spaces

* Update pixel_unshuffle_sig.cc

* Update vision.py

* Update vision.py

* add PixelUnshuffleGradInferMeta

* remove PixelUnshuffleOpArgumentMapping

* Update pixel_unshuffle_op.cc

* 调整pixel_unshuffle及其梯度的核函数的实现位置

* Update pixel_unshuffle_op.cc

* Add infermeta for ChannelShuffle

* Create channel_shuffle_grad_kernel.h

* Create channel_shuffle_kernel.h

* Create channel_shuffle_sig.cc

* Create channel_shuffle_op.cc

ChannelShuffle算子的描述

* Create channel_shuffle_kernel_impl.h

ChannelShuffle核函数的实现

* Create channel_shuffle_grad_kernel_impl.h

ChannelShuffle反向核函数的实现

* Add kernel register of channel shuffle and grad

注册ChannelShuffle及其反向的核函数

* add nn.functional.channel_shuffle

* add nn.ChannelShuffle

* Create test_channel_shuffle.py

* Update example of ChannelShuffle in vision.py

* Update test_channel_shuffle.py

* 修改channel_shuffle核函数的实现位置

* 修正代码格式

* 删除多余空格

* 完善channel_shuffle的错误检查

* Update unary.cc

* Update channel_shuffle_op.cc

* Update test_channel_shuffle.py

* Update unary.cc

* add channel_shuffle

* Update test_channel_shuffle.py

* Update vision.py

* 调整代码格式

* Update channel_shuffle_sig.cc

* 更新ChannelShuffle的文档

* 更新channel_shuffle的文档

* remove ChannelShuffleOpArgumentMapping

* add ChannelShuffleGradInferMeta

* Update channel_shuffle_op.cc

* 调整channel_shuffle及其梯度的核函数的位置

* Add gpudnn yaml config for some OPs

* Add grad gpudnn config

* Fix CI errors

* Fix CI errors

* Fix CI errors

* Fix conflicts

* make fast through to linear

* make fast through to linear

* add to do for later upgrades

* support build once for now

* update

* add conv yaml

* add backward

* remove useless code

* fix bug

* fix bug

* revert fluid dygraph conv2d

* remove useless infermeta function

* fix meta fn deluplicat error

* conv using custom impl

* remove amp include

* fix bug

* use final op in maskrcnn and hrnet

* refine
Co-authored-by: Nphlrain <phliuhongyu@126.com>

* [DoubleGrad] Enabled double grad test cases in eager_mode for test_imperative_double_grad

* Fixed elementwise issue

* Addressed CI failures

* [DoubleGrad] Enabled test_imperative_triple_grad test cases under eager_mode

* [DoubleGrad] Enabled test_autograd_functional_dynamic.py under eager mode

* Enabled more test cases

* [DoubleGrad] Enabled test_imperative_star_gan_with_gradient_penalty.py under eager mode

* Adjusted test_imperative_star_gan_with_gradient_penalty.py

* add layer norm infermeta

* add layer norm yaml

* polish layer norm infer meta

* add layer norm to black list

* add multi_dot,maxout,multiplex yaml

* add code converage

* fix_ci_problem3

* support windows no default error

* remove elementwise add in conv

* use reshape

* add swish yaml and final state api

* skip mkldnn test

* fix grad mkldnn test

* add dist erfinv gumbel softmax

* fix test gumbel softmax op bug

* try to fix gumbel softmax error

* add label smooth backlist

* add yaml

* perfect converage

* add gelu pythonapi and unittest

* fix prelu

* [Eager] Support test_layers's test cases switch to eager mode

* Update batch_norm _C_ops action to fix CI

* Use None instead of new EmptyTensor

* Updated var name

* Make sure to switch eager mode, Fix Coverage_CI

* Remove _non_static_mode statement

* Remove batch_norm dispensable input statement

* Polish batch_norm code

* Fix CI issue

* Remove _non_static_mode()

* [Eager] Support test_layers's test cases switch to eager mode

* Update batch_norm _C_ops action to fix CI

* Use None instead of new EmptyTensor

* Updated var name

* Make sure to switch eager mode, Fix Coverage_CI

* Remove _non_static_mode statement

* Remove batch_norm dispensable input statement

* Polish batch_norm code

* Fix CI issue

* update

* add conv yaml

* add backward

* remove useless code

* fix bug

* fix bug

* revert fluid dygraph conv2d

* remove useless infermeta function

* fix meta fn deluplicat error

* conv using custom impl

* remove amp include

* fix bug

* use cudnn = true

* fix test mkldnn caching bug

* update

* fix bug

* update epxand and sigmoid with cross entropy

* skip expand as infrt check

* fix sigmoid cross entropy bug

* remove no grad set white list

* remove no grad set

* fix bug

* fix sigmoid error

* fix bug

* add infershape and forward yaml

* add final_state call

* add base unittests

* add backward yaml and test

* fix without softmax test error

* add cross_entropy test

* add dropout slice yaml

* remove useless code

* fix infer shape error

* skip infrt compile for dropout

* Add yaml config

* Add yaml for flatten_contiguous_range_op

* Remove h_sigmoid yaml

* Fix CI errors

* Fix code format

* Fix flatten OP errors

* Fix conflicts

* Fix CI errors

* Remove flatten_contiguous_range OP

* Remove redundant code

* Fix typos

* add yaml for ele_max ele_min

* add yaml for: mish / logexpsum / expm1 / elemenwise_pow / elementwise_floordiv

* 1. add the python api grad 2. add final and intermediate state vlog 3. change the python_api error logic

* add python api or close the check_eager=True

* fix the compatibility

* add nll_loss yaml

* fix nll loss

* fix nll loss bug

* fix bug

* fix bug

* fix infrt problem
Co-authored-by: Nxiongkun <xiongkun03@baidu.com>

* [Refactor] refactored eager_gen.py PR #2

* [DoubleGrad PR #1] Decoupled code generation logics for Dygraph ForwardFunctions and GradNodes

* Fixed minor issue

* Adjusted logics of GenerateNodeCreationCodes and GenerateForwardDefinition

* Fixed issues

* Supported higher-order grad node generation

* [DoubleGrad PR #4] Supported higher-order GradNode generation

* [DoubleGrad #4] Bug Fixes to Double Grad Node Generation

* Fixed yaml typo

* Fixed yaml typo

* fixed minor issues

* Fixed minor issue

* fix error; test=develop

* update

* close some yaml

* fix backward attrite error; test=develop

* add div test

* polish code; test=develop

* update

* update

* fix bug

* update bitwise code; test=develop

* update

* update

* fix some bug

* update

* revert cmakelist

* fix optional bug;

* fix bug

* fix bug;

* add backward test

* open bn

* update

* update

* revert eager_gen

* polish code

* fix topk error

* update

* update

* fix bug;

* move label smooth, nll loss

* revert topk

* fix topk label smooth bug;

* remove batch_norm

* remove topk

* change flip infer meta

* fix flip bug

* update yaml

* close abs

* fix histogram bug

* fix histogram bug

* add abs

* fix histogram kernel

* remove expand

* refactor eager flags

* fix flags error when we switch from eager to dygraph

* fix ci problem

* fix ci

* fix ci

* merge develop and fix code style

* merge develop and fix code style

* fix op test error

* fix op test error

* fix op test error

* fix op test error

* fix op test error

* merge develop

* support inplace in eager_final state

* little change

* little bug

* add add yaml

* add elementwise add yaml; test=develop

* add norm

* update

* add some yaml config; test=develop

* fix bug; test=develop

* fix compare error; test=develop

* revert erger_gen.py

* update; test=deveop

* remove usless code; test=deveop

* fix bug; test=develop

* fix test error; test=develop

* remove int_type; test=develop

* fix type error; test=develop

* format; test=develop

* remove type register; test=develop

* polish code; test=develop

* fix ci error; test=develop