* [CodeStyle][py2] remove `paddle.compat`

* remove compat from `paddle.__init__`

* enable_static in sample code

* Revert "enable_static in sample code"

This reverts commit ffccaa633900154ea5f3d056e746aae9a1927399.

* enable_static in sample code

* update config

* re-blacken python code

* temporarily disable date and diff_py_file

* skip a format

* [CodeStyle][py2] remove `compat` module (to_text)

* remove some unnecessary decode

* remove to_text definition and unittest

* Revert "remove to_text definition and unittest"

This reverts commit a6b69cb8dca8b9b031ce10ea32d1040e7e0dd267.

* remove an assertion

* empty commit

* [CodeStyle][py2] remove `compat` module (to_bytes)

* remove some unused imports

* clean up to_bytes definition and unittests

* Revert "clean up to_bytes definition and unittests"

This reverts commit e726539e1768172a411ff60e63fab82f164343cf.

* use `b` prefix instead of `encode()`

* [CodeStyle] remove all future import

* revert test_error.py

* restore future import in example code

* trim trailing whitespace

* fix `.cmake-format.py`

* revert npu ut changes, avoid npu ci error

* relace fill_zeros_like op with fill_any_like op in backward.py and tensor.py

* Remove unnecessary comments

* modify create op_desc param

* 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

* 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

* use original id in dist_op_context.grad_op_id_to_op_id

* del assert

* remove redundant map

* 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>

* add default_ctx in backward.py

* record grad_var_to_var with grad_times

* fix backward

* update annotation

* add complete_high_order_grad in complete_forward

* add dist slice op

* update grad_var_to_var type

* update partition_block init mapping before loss op

* update compatible for 'XShape' & update 'allreduce_vars'

* add dist reshape op when input dim equal to output dim

* update 'set_grad_var_shape' with grad_var_to_var

* fix dist slice

* fix set_grad_var_shape

* add dist pnorm op

* fix dist pnorm dist_attr

* fix engine startprogram & adapt highorder grad

* fix set_grad_var_shape when mp

* update unittest

* update cmakelist

* default strategy in engine: dp

* bug fix

* tiny fix

* flatten outputs

* fix default strategy

* init default ctx

* tiny fix

* test=allcase

* fix collections.Sequence in python3.10

* fix format

fix en docs of some Apis (gradients, scope_guard, cuda_places, name_scope, device_guard, load_program_state, scale, ParamAttr and WeightNormParamAttr) (#41604)

* Update scope_guard; test=document_fix

* gradients; test=document_fix

* gradients; test=document_fix

* name_scope; test=document_fix

* cpu_places; test=document_fix

* WeightNormParamAttr; test=document_fix

* cuda_places; test=document_fix

* load_program_state; test=document_fix

* device_guard; test=document_fix

* device_guard; test=document_fix

* ParamAttr; test=document_fix

* scale; test=document_fix

* scale; test=document_fix

* update code example；test=document_fix
Co-authored-by: NChen Long <1300851984@qq.com>

* gradients; test=document_fix

* fix VarType; test=document_fix

* fix vartype; test=document_fix

* cumsum; test=document_fix

* t; test=document_fix

* add dropout slice yaml

* remove useless code

* fix infer shape error

* skip infrt compile for dropout

* Fix bug while specifying target grad in high order gradient

* add more unittest

* add more unittest

* [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>

* [Auto parallel] Make the id of var and op unique

* [Auto Parallel] Rename back dist_context to distop_context

* default dist op

* add dist_attr for dist op

* add unitest

* update inputname

* update function name

* add unitest

* update CMakeLists.txt for CI

* fix dis_matmul

* fix compile error

* update matmul to matmul_v2

* unify api

* unify api

* todo

* update distop forward func

* update distop forward func

* auto parallel backward

* update dist op

* autoparallel backward

* add backward for embedding

* temp1

* temp2

* temp3

* temp4

* backward done1

* backward done2

* backward done3

* dist embedding remove mp mode

* dist matmul remove mp mode

* update dist embedding
『

* dist op init1

* dist op init 2

* update unitest

* context remove parallel mode

* partitioner remove parallel mode

* update unitest

* a more general method to support varying mesh in pipeline parallel

* support varying mesh in pipeline parallel

* embedding support varying mesh in pipeline parallel

* matmul support varying mesh in pipeline parallel

* default dist op support varying mesh in pipeline parallel

* dist attribute for startup program

* default dist op support varying mesh in pipeline parallel 2

* partitoner support varying mesh in pipeline parallel

* revise logic for auto compeletion

* revise framework.py

* revise reshard unitest

* revise unitest for parallelize

* chmod

* fixed bug for dist embedding name mapping
Co-authored-by: Nzhaoyingli <zhaoyingli@baidu.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
Co-authored-by: Nveyron95 <veyron_wu@163.com>
Co-authored-by: Nlevi131 <limaolin01@baidu.com>

* [HIP] fix op not support AMD GPU bug, the flag PADDLE_WITH_ROCM is invalid

* [HIP] fix op not support AMD GPU bug, the flag PADDLE_WITH_ROCM is invalid

* [HIP] fix op not support AMD GPU bug

* [hybrid] seed and dropout op support force-cpu

* [hybrid] seed and dropout op support force-cpu

* [hybrid] seed and dropout op support force-cpu

* [hybrid] seed and dropout op support force-cpu

* [hybrid] seed and dropout op support force-cpu

* [hybrid] fix seed ci failed issue

* add AsExtra for force_cpu of seed op

* 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

* modify API nn.Bilinear's doc, test=develop

* Modified params of some APIs to support tuple and list.

* fixed bug.

* oneps (3/4)
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* add static_only for static api

* addd static_only for class init

* remove static_only for default_main_program

* remove creater_parameter & startup_program

* remove failed apis

* revert py_func import

* remove global scope

* remove some api

* remove cuda pinned place

* modify sample code

* variable -> tensor

* migrate program_guard sample code

* refine error message

* migrate program_guard

* refine comment style

* fix indent