* isort all files

* revert conflicting files

* revert conflicting files

* revert conflicting files

* [CodeStyle][py2][U004] unecessary explicit `object` inheritance in class definition

* fix an increment

* [CodeStyle][py2][U008] remove unnecessary args in `super()`

* remove remained args

* revert changes in test_pylayer_op

* Revert "revert changes in test_pylayer_op"

This reverts commit ff185a9ae738afac3b0264f61bde6c6b7f72e7c4.

* revert some changes in example code

* update config

* re-blacken python code

* temporarily disable date and diff_py_file

* skip a format

[CodeStyle][F401] remove unused imports in python_paddle/proto_onnx_optimizer_hapi_autograd_framework. (#46754)

* 1. Delete some expression like 'This Op'
2. remove import numpy as np

* test=document_fix

* fix eg; test=document_fix

* fix 'import numpy' cases; test=document_fix

* fix 'import numpy' cases; test=document_fix

* fix some docs; test=document_fix

* delete raise; test=document_fix

* add some introduction; test=document_fix

* add some introduction; test=document_fix

* test=document_fix

* Fix ’note‘ format; test=document_fix

* Fix Returns of cholesky; test=document_fix

* Fix Example format; test=document_fix

* Fix det; test=document_fix

* Fix eig; test=document_fix

* Fix eigh; test=document_fix

* Fix eigh; test=document_fix

* Apply suggestions from code review;test = document_fix
Co-authored-by: NNyakku Shigure <sigure.qaq@gmail.com>

* Apply suggestions from code review;test = document_fix
Co-authored-by: NNyakku Shigure <sigure.qaq@gmail.com>

* Apply suggestions from code review;test = document_fix
Co-authored-by: NNyakku Shigure <sigure.qaq@gmail.com>

* test=document_fix

* test=document_fix

* KLDiv;test=document_fix

* norm example code; test=document_fix

* revert python/paddle/fluid/**/*

* revert python/paddle/distributed/spawn.py

* revert python/paddle/fluid/*

* fix a `Note` format

* Fix inv; test=document_fix

* Fix lu; test=document_fix

* Fix lu_unpack; test=document_fix

* Fix matrix_power; test=document_fix

* Fix multi_dot; test=document_fix

* Fix solve; test=document_fix
Co-authored-by: NNyakku Shigure <sigure.qaq@gmail.com>

* [CodeStyle] trim trailing whitespace in yaml and hook

* python incremental whitespace and yml files

* saved_tensors_hooks

* trim trailing whitespace

* fix `.cmake-format.py`

* revert npu ut changes, avoid npu ci error

* pylayer detach output tensor if it is equal with input

* pylayer detach output tensor if it is equal with input

* move _gradients to primapi and rename to grad

* modify jvp to call forward_grad in primitive mode

* add primapi unittest and remove some unused test cases.

* fix  circular import problem

* move paddle/autograd/functional into paddle/incubate.autograd/functional

* remove unused JacobianBatchLast class

* enable Jacobian,Hessian supporting new autograd

* fix prim mode failed in PR-CI-Windows

* add forward_gradients api

* add forward_gradients api

* skip test_autograd_functional_prim in windows ci

* fix test_autograd_funciton_prim timeouot

* remove the block parameter in prim2orig method

* remove duplicate to_tensors code snippet # test=allcases

* rename eagerpylayer

* 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

* Updated triple_grad_check func

* add todo for gradient checker and refine some comments

* remove additional code

* add test for warnging in backward.py

* format python code

* support multi input in triple gradient checker

* Add matmul triple grad kernel

* Updated comments of TODO

* Supported some special tests

* Change code-format to follow CI std

* Updated gradient_checker.py

* Fix conflicts

* Removed unnecessary printing log

* Change code style to follow CI std

* merge upstream

* add priops.py

* add_p

* rm useless files

* add sub_p mul_p div_p

* add sqrt_p and tanh_p

* add reshape_p

* add broadcast_p

* Add python primitive wrappers.

* Jvp rules updated.

* JVP rules done for all the 17 primops.

* quick check and fixes.

* add jvp(op, *args)

* add broadcast_p fill_constant_p matmul_p reduce_p reshape_p transpose_p

* add split_p and concat_p

* add gather_p and scatter_add_p

* add slice_select_p and slice_assign_p

* Add transpose rules.

* add multi input check for add_p, sub_p, mul_p, div_p

* update concat_p

* Linearize and transpose in progress..

* refine gather_p and scatter_add_p

* updated.

* update transpose.

* refine slice_assign_p and slice_select_p

* init commit for lower

* Merged with primitive ops.

* small update

* add rules for orig2prim and prim2orig

* add 9 test for prim ops

* add more test and fix some bug

* add more test

* register proto

* Adding primops test.

* add shape valid check for broadcast_p op, and add keepdim attr into reduce_p op proto

* support multi input and multi output for split_p and concat_p

* Test updated.

* update

* fix slice bug for slice_select_p and slice_assign_p

* updated.

* Ops updated.

* Refactor and bug fixes.

* updated.

* finish orig2prim and prim2orig rules

* dtype for axis attr should be long int

* update dtype for axis attr int64_t

* update for iscan CI

* Update primx.

* Refactor vars in primx.

* update for lower transform

* add more shape and dtype check

* update primx.py

* change IndexTensor into int32 dtype

* update

* Fix linearize and transpose.

* Update is_dot

* Update is_dot

* Update is_dot

* add gradient aggregation, fix add_transpose.

* pass first linearize+transpose test.

* update test

* refactor op registration and primx.

* update rule for slice_assign

* try test lower

* update orig2prim and prim2orig

* pass simple lower pass

* update

* Update input types in the unit test.

* orig2prim segfault.

* 50% for adam.minimize

* test updated.

* temp fix erros in removing vars.

* primx updated.

* update for matmul_v2 and reshape2 orig2prim

* update for minimize

* Refine primrules

* Remove some code

* supporting unused and unreachable vars.

* update for use prim2orig in minimize

* fix gather and scatter_add transpose.

* Add rules UT

* update scatter_add

* Refine UT code

* fix nonetype check in topo

* Update gather_p pywrapper.

* remove useless print

* Merge tongxin PR and refine code

* readd some test

* rm useless print

* polish code.

* fix bug in minimize

* add get_input_var_list and get_output_var_list and use it in lower

* Fix scatter_add_p prim2orig

* Update code and fix orig2prim/prim2orig UT

* delete vars after block.desc._remove

* Improve ops and vars clean up logics.

* fix some bug in linearize and lower

* update tanh transpose.

* use set instead of list for var2remove

* test updated.

* polish code.

* fix dot2bar delete.

* merge tx/ad

* add indextensor_dot for gather and scatter_add

* add sorted for set

* Fix scale_orig2prim params

* fix some syntax bug

* add golbal_lower_update list

* Better handling of unused vars.

* update tests.

* Fix elementwise_sub orig2prim

* support none for transpose rule

* Merge and add transform UT

* fix a bug in transpose

* Fix transpose and UT

* a hacky fix for cancat op

* Fix exector place

* Refine variable name

* Add elementwise_mul orig2prim and support p_norm when p=1

* Add sqrt orig2prim rule and UT

* merge wz test

* rename files, add enable_prim, disable_prim, prim_enabled, delete global_lower_update

* fix a bug in test_ad_transform_trans

* revert modify in framework.py

* add paddle.fluid.incubate.ad_transform to  python/setup.py.in

* Fix remove vars error

* Fix p_norm_orig2prim

* merge wz

* Modify the code directory

* Add utils.py and remove get_input/output_vars functions

* Update maolin code

* Rename UT and refine test_ad_transform_primops

* Fix div_p jvp rule

* Add higher derivatives UT

* Remove UT to autograd dir

* Fix comments

* import paddle in primops.py

* Add some error message for assert

* Refine UT class name and refine some comments in primreg.py

* update minimize of paddle/optimizer for supporting new autograd

* resolve cicular importing between backward.py and optimizer.py

* fill gradients and minimize unittest

* Replace `assert isinstance` with `raise TypeError`

* Add some assert message for primx.py

* Polish variable name

* Add some assert message

* add some docstring

* refine some name

* update the format of english documents

* Split test_transform.py to two files to avoid ci error

* fix the document format of enable_prim/disable_prim/prim2orig/prim_enabled

* polish test_gradients_and_minimize

* add default value for prim_enabled api doc

* Remove some UT to avoid windows ci error

* Enlarge test_gradients_and_minimize limit time

* Fix ut limit time
Co-authored-by: Nveyron95 <veyron_wu@163.com>
Co-authored-by: NJiabin Yang <360788950@qq.com>
Co-authored-by: Nlevi131 <limaolin01@baidu.com>
Co-authored-by: NTongxin Bai <waffle.bai@gmail.com>
Co-authored-by: NXiaoxu Chen <chenxx_id@163.com>
Co-authored-by: Nlevi131 <83750468+levi131@users.noreply.github.com>

* native commit for triple grad of sigmod

* Updated unittests files

* init functional jacobian api

* Updated trible_test func

* Updated gradient_checker & test_script

* finish test with dtype float32

* add float64 test case

* polish code

* use atol=1e-5 with dtype float64

* fix for ci

* set timeout for test_jacobian

* fix dygraph grad to support high differential

* polish API docstring

* Updated gradient checker and some related files

* fix double grad strip error for high differential

* fix double grad strip error for high differential

* Add Sigmoid triple grad tests

* fix dygraph double grad dtype error when calling for high differential senario

* Updated triple grad teses func

* Use np.random to initialize ddx

* Updated triple_grad_check func

* add todo for gradient checker and refine some comments

* remove additional code

* add test for warnging in backward.py

* format python code

* support multi input in triple gradient checker

* Add matmul triple grad kernel

* Updated comments of TODO

* Supported some special tests

* Change code-format to follow CI std

* Updated gradient_checker.py

* Fix conflicts

* Removed unnecessary printing log

* Change code style to follow CI std

* merge upstream

* add priops.py

* add_p

* rm useless files

* add sub_p mul_p div_p

* add sqrt_p and tanh_p

* add reshape_p

* add broadcast_p

* Add python primitive wrappers.

* Jvp rules updated.

* JVP rules done for all the 17 primops.

* quick check and fixes.

* add jvp(op, *args)

* add broadcast_p fill_constant_p matmul_p reduce_p reshape_p transpose_p

* add split_p and concat_p

* add gather_p and scatter_add_p

* add slice_select_p and slice_assign_p

* Add transpose rules.

* add multi input check for add_p, sub_p, mul_p, div_p

* update concat_p

* Linearize and transpose in progress..

* refine gather_p and scatter_add_p

* updated.

* update transpose.

* refine slice_assign_p and slice_select_p

* init commit for lower

* Merged with primitive ops.

* small update

* add rules for orig2prim and prim2orig

* add 9 test for prim ops

* add more test and fix some bug

* add more test

* register proto

* Adding primops test.

* add shape valid check for broadcast_p op, and add keepdim attr into reduce_p op proto

* support multi input and multi output for split_p and concat_p

* Test updated.

* update

* fix slice bug for slice_select_p and slice_assign_p

* updated.

* Ops updated.

* Refactor and bug fixes.

* updated.

* finish orig2prim and prim2orig rules

* dtype for axis attr should be long int

* update dtype for axis attr int64_t

* update for iscan CI

* Update primx.

* Refactor vars in primx.

* update for lower transform

* update primx.py

* update

* Fix linearize and transpose.

* Update is_dot

* Update is_dot

* Update is_dot

* add gradient aggregation, fix add_transpose.

* pass first linearize+transpose test.

* update test

* add_prim_op_pywrapper

* Add primops UT

* Fix set_value and update

* Fix code format and PR-CI-Coverage
Co-authored-by: Nveyron95 <veyron_wu@163.com>
Co-authored-by: NJiabin Yang <360788950@qq.com>
Co-authored-by: NTongxin Bai <waffle.bai@gmail.com>
Co-authored-by: N0x45f <wangzhen45@baidu.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

* Fixed performance issues

* Fixed minor issue

Enhance vjp/jvp/Jacobian/Hessian API for supporting dynamic, static graph and batched, unbatched mode (#40692)

* modify vjp/jvp for both dynamic and static graph

* enforce jacobian class for supporting first/last batch

* add unittest for jvp, jacobian withlast batch, jacobian with first batch

* fix the incorrect shape when multi-index Jacobian

* enforce Hessian class for supporting dynamic graph

* add Hessian class unittest

* bugfix, jvp double_backward_trick zeros_like return stop_gradient=True in static graph

* add API beta warnnings

* add white_list for cuda11.x ci windows.

* optimize some code snippets and documments

* set unittest timeout to 100 seconds

* move vjp,jvp,Jacobian,Hessian to incubate

* fix vjp,vjp import path of sample code

* fix code style error of augtograd/__init__ file

* Supported Complex2Real Conversion for Eager Dygraph

* Supported Complex2Real Conversion for Eager Dygraph

* Enabled complex type promotion test for matmul_v2

* pylayer, test=develop

* Fix CI issues

* Support initializing specific grad tensors to zero for selected operators

* finish forward, test=develop

* create grad node finish, test=develop

* Merged adj_edges_ with GradSlotMeta

* Fixed monir issue

* backward finish, start dbg, test=develop

* Adjusted num runs

* Recovered Eager performance tests configurations

* Recovered Eager performance tests configurations

* finish, test=develop

* polish, test=develop

* polish, test=develop

* refine, test=develop

* eager, test=develop

* Adjusted performance tests configurations

* Fixed Minor Issues with performance tests

* [Phi] Fix macro name typo

* support set_materialize_grads, test=develop

* suppotr mark_non_differentiable, test=develop

* support once_differentiable, test=develop

* refine, test=develop

* refine, test=develop

* Moved out Edge from GradSlotMeta

* Fixed issues from merge

* Fixed typo

* Addressed review comments

* Fixed merge issues

* Fixed minor issues

* Fixed minor issue

* refine, test=develop

* refine, test=develop

* refine, test=develop

* Fixed major issues and enabled auto_prune test cases

* Fixed issues from merge

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop
Co-authored-by: Njim19930609 <jim19930609@gmail.com>
Co-authored-by: NAurelius84 <zhangliujie@baidu.com>

* 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

* eager, test=develop

* fix bug, test=develop

* eager, test=develop

* merge legacy to fluid

* eager, test=develop

* eager, test=develop

* Refactor TensorAdd func by template and remove gradient_accumulation in eager

* Remove needless target name

* eager, test=develop

* eager, test=develop

* Use overload instead of template

* Remove legacy code

* Remove legacy code

* selectedrows, test=develop

* Remove DataType test

* eager, test=develop

* eager, test=develop

* support gan, test=develop

* Using Tensor directly instead of using EagerTensor

* support gradient_accumulation

* make test_imperative_lod_tensor_to_selected_rows longer

* make test_imperative_lod_tensor_to_selected_rows longer

* refine code

* ptb, test=develop

* Rename all EagerTensor to Tensor

* Rename some EagerTensor to Tensor

* rename EagerTensor to EagerVariable

* eager, test=develop

* eager, test=develop

* eager, test=develop

* eager, test=develop

* add more test

* eager, test=develop

* Support copiable selected rows and merge develop

* save load, eager, test=develop

* save load, eager, test=develop

* refine, test=develop

* remove useless _set_value method

* refine, test=develop

* refine, test=develop

* revert static_runner, test=develop

* EagerTensor to Tensor, test=develop

* refine, test=develop

* refine, test=develop

* clear grad, test=develop

* merge, develop

* merge, develop

* merge, test=develop

* merge, test=develop

* Support quant and part of slice

* support legacy static save

* extend slim tests time

* remove imperative on inference

* remove imperative on inference

* merge develop

* fix typo

* fix typo

* split slice related code into 2 part for imperative and eager

* split slice from inference

* split slice from inference

* fix test_tensor_register_hook

* support custom op in eager mode

* fix inference deps error

* split eager utils from custom operator

* fix type match

* fix typo
Co-authored-by: NWang Huan <wanghuan29@baidu.com>
Co-authored-by: NWeilong Wu <veyron_wu@163.com>
Co-authored-by: Nwanghuancoder <wanghuancoder@163.com>

* fix pylayer problem with amp

* add ut

* refine code

* [autograd] static Jacobian pass tests.

* [autograd] apply CR suggested changes.

* [autograd] more tests.

* [autograd] add CPUPlace in tests.

* [autograd] bug fixes.

* [autograd] reformatted.

* [autograd] adding Hessian, in progress.

* [autograd] Hessian passes. A double grad bug fixed.

* [autograd] fix renaming conflict in double backward pass.

* [autograd] polish test.s

* fix a bug when using brackets

* debug for ci

* [autograd] fixing Hessian test.

* polish format.
Co-authored-by: Nlevi131 <83750468+levi131@users.noreply.github.com>
Co-authored-by: Nlevi131 <limaolin01@baidu.com>

* [autograd] static Jacobian pass tests.

* [autograd] apply CR suggested changes.

* [autograd] more tests.

* [autograd] add CPUPlace in tests.

* [autograd] bug fixes.

* [autograd] reformatted.

* add control/status API, test=develop

* fix import error, test=develop

* add is_grad_enabled unittest, test=develop

* add code comment for example code and API, test=develop

* add checking for type, test=develop

* add api description, test=develop

* fix docs index_en, test=document_fix

* fix doc of is_floating_point, test=document_fix

* native commit for triple grad of sigmod

* Updated unittests files

* init functional jacobian api

* Updated trible_test func

* Updated gradient_checker & test_script

* finish test with dtype float32

* add float64 test case

* polish code

* use atol=1e-5 with dtype float64

* fix for ci

* set timeout for test_jacobian

* fix dygraph grad to support high differential

* polish API docstring

* Updated gradient checker and some related files

* fix double grad strip error for high differential

* fix double grad strip error for high differential

* Add Sigmoid triple grad tests

* fix dygraph double grad dtype error when calling for high differential senario

* Updated triple grad teses func

* Use np.random to initialize ddx

* Updated triple_grad_check func

* add todo for gradient checker and refine some comments

* remove additional code

* add test for warnging in backward.py

* format python code

* support multi input in triple gradient checker

* Add matmul triple grad kernel

* Updated comments of TODO

* Supported some special tests

* Change code-format to follow CI std

* Updated gradient_checker.py

* Fix conflicts

* Removed unnecessary printing log

* Change code style to follow CI std

* support batch in jacobian and hessian

* add batch jacobian and batch hessian

* Add batch_jacobian test, draft version

* [New features] Add elementwise_mul triple grad kernel (#37152)

* Add elementwise_mul triple grad kernel

* Removed InplaceInferer and polished code

* Add numerical_batch_jacobian,numerical_batch_hessian and tests

* Support batch_jacobian and batch_numerical

* Use pre-commit to check code format

* Update doc, polish code, add unit test

* Reset the TIMEOUT properties of test_jacobian to pass CI
Co-authored-by: Nlevi131 <limaolin01@baidu.com>
Co-authored-by: NJiabin Yang <360788950@qq.com>

* init functional jacobian api

* finish test with dtype float32

* add float64 test case

* polish code

* use atol=1e-5 with dtype float64

* fix for ci

* set timeout for test_jacobian

* init hessian API

* save status

* polish API docstring

* modify docstring

* add utils.py

* save status

* fix dygraph double grad dtype error when calling for high differential senario

* reinvoke ci

* test_hessian.py is ok

* polish hessian API

* init vhp

* Revert "init vhp"

This reverts commit cbd4d3b66abe82b0ac10721b9eddeb7d82e0a1c8.

* init vhp

* finish vhp API logically

* add test for partial_engine.cc

* modify numerical_delta with dtype float32

* merge fix for dtype float64

* spell fix

* save status

* polish code

* rm _stop_gradient_pre_process

* save status

* add example for vhp interface

* add _compute_numerical_vjp and _compute_numerical_vhp

* test is ok

* vhp is ok

* add testVHPFloat64

* modify for comments

* modify format

* modify format

* save status

* test_vhp is ok

* finish code polish

* small modify for v is None
Co-authored-by: NJiabinYang <360788950@qq.com>

* autograd.functional passed pylint checker.

* autograd.functional: fix import errors.

* autograd.functional: fixed unit tests.

* autograd.functional minor format change

* [autograd.functional] Fixed vjp and jvp's v=None bug.

* modify format

* modify format

* autograd.functional passed pylint checker.

* autograd.functional: fix import errors.

* autograd.functional: fixed unit tests.

* autograd.functional minor format change

* init functional jacobian api

* finish test with dtype float32

* add float64 test case

* polish code

* use atol=1e-5 with dtype float64

* fix for ci

* set timeout for test_jacobian

* init hessian API

* save status

* polish API docstring

* modify docstring

* add utils.py

* save status

* fix dygraph double grad dtype error when calling for high differential senario

* reinvoke ci

* test_hessian.py is ok

* polish hessian API

* init vhp

* Revert "init vhp"

This reverts commit cbd4d3b66abe82b0ac10721b9eddeb7d82e0a1c8.

* add test for partial_engine.cc

* modify numerical_delta with dtype float32

* merge fix for dtype float64

* spell fix

* polish code

* rm _stop_gradient_pre_process
Co-authored-by: NJiabinYang <360788950@qq.com>

* init functional jacobian api

* finish test with dtype float32

* add float64 test case

* polish code

* use atol=1e-5 with dtype float64

* fix for ci

* set timeout for test_jacobian

* polish API docstring

* modify docstring

* remove autograd/grad api

* import grad, no_grad set_grad_enable from autograd module

* modify import no_grad_ as no_grad

* add gradients_with_optimizer api

* modify gradients_with_optimizer

* add gradients_with_optimizer api into paddle.auto.backward_mode

* add gradients_with_optimizer test case

* add doc for gradients_with_optimizer

* add doc for gradients_with_optimizer

* update 2.0 public api in all left files

* reverse device.py all list;
fix some flake8 errors

* custom python backward

* polish up the code

* polish up the code

* polish up the code.

* Fix code format and comments.

* Delete redundant files.

* add unnittest.

* edit unnittest.

* edit unnittest.

* Remove redundant header files.

* Improve coverage and remove redundant code.

* support saving for backward.

* polish code according to comments.

* Add support type for PyLayer.

* Modify the DOC.

* polish Doc.

* polish Doc.

* polish Doc.

* polish Doc.

* polish Doc.

* polish Doc.

* polish code and make the code robust.

* Modify the code format.

* add custom init grad for backward function

* add custom init grad for backward function

* handle when the grad_tensor is none

* handle when the grad_tensor is none

* fix the args type error on windows platform

* modify the args order and doc

* format code

* add grad_tensor to xpu

* modify the grad_tensor type check

* add paddle.backward api to support multi tensors gradient compute

* add paddle.backward api to support multi tensors gradient compute

* add paddle.atuograd module and backward api

* change tensor.backward func args

* modify tensor backward api

* remove create_graph intputs args

* add doc and examplex code for backward api

* when have the same tensor, throw error

* modify test Init func args

* modify the execute.Init func args in test files

* add paddle.autograd package in setup.py.in

* modify error msg, remove _run_backward method in class Tensor

* add test cases for backward api