* [Auto Parallel] Suppport different dataloaders

* [Auto Parallel] Add num_shards config for dataset

* [Auto Parallel] Unify the logger and outputs of Engine API

* [Auto Parallel] Fix the bugs of to_static

* [Auto Parallel] Adjust the test_to_static.py

* [Auto Parallel] Add the prepare API and replace __call__ with run

* [Auto Parallel] Improve the private implementations of Engine

* [Auto Parallel] Set capacity of dataloader for opt tuning

* [Auto Parallel] [WIP] Change the fine-grained API

* [Auto Parallel] Improve APIs to support different user cases

* [Auto Parallel] Add removed config

* [Auto Parallel] Add imports

* [Auto Parallel] Fix bugs for to_static

* [Auto Parallel] Remove unnecessary imports

* [CodeStyle][F401] remove unused import in python/paddle/distributed

* remove pass

* empty commit

* Fix ValueError: list.remove(x): x not in list for meta_optimizer_names.

Fix ValueError: list.remove(x): x not in list for meta_optimizer_names.

* Fix split import.

Fix split import.

* add noqa after meta_optimizers in factory

* restort collective ops

* expand `import *`

* add noqa after required imports

* try to fix APIs without core.ops

* Revert "try to fix APIs without core.ops"

This reverts commit 6172beaf601e84bf61f2490c12c4739f0edaa5eb.

* fix an increment

* empty commit

* add noqa after required imports

* expand `import *`, fix ci error
Co-authored-by: NShuangchi He <34329208+Yulv-git@users.noreply.github.com>

* [Auto Parallel] Unify the logger and outputs of Engine API

* [Auto Parallel] Fix the bugs of to_static

* [Auto Parallel] Adjust the test_to_static.py

* [Auto Parallel] Imporve the user-defined fetches and logging

* [Auto Parallel] Make Engine class callable

* [Auto Parallel] Update the data loading of tuner

* bugfix

* bugfix

* typos fixed

* [Auto Parallel] Use c++ dist attr in the completion process

* [Auto Parallel] Add minor changes

* [Auto Parallel] Use c++ dist attr in the completion process

* [Auto Parallel] Add minor changes

* [Auto Parallel] Add the serialization process for dist attrs

* [Auto Parallel] Remove unnecessary comments

* [Auto Parallel] Fix some bugs

* [Auto Parallel] Fix the code style

* [Auto Parallel] Remove unnecessary impls

* [Auto Parallel] Fix the importing error

* [Auto Parallel] Fix the copy from bugs of op dist attr

* [Auto Parallel] Replace the use of constexpr if

* [Auto Parallel] Redesign the shard_tensor, shard_op and ProcessMesh

* [Auto Parallel] Change API of the completion unittest

* [Auto Parallel] Fix the bug when set_attr an int

* [Auto Parallel] Add the unittest for the serialization

* [Auto Parallel] Add some unit tests

* [Auto Paralle] Unify the strategy

* [Auto Parallel] Improve the engine api

* [Auto Parallel] Reset the changes made to the framework

* [Auto Parallel] Change the engine unittest

* [Auto Parallel] Update API of the completion and partitioner

* [Auto Parallel] Update unit tests using engine api

* update shard annotation

* [Auto Parallel] Remove the modifications of other modules

* [Auto Parallel] Add docs for APIs

* add new strategy

* [Auto Parallel] Replace the logger

* [Auto Parallel] Restore the test_program.py

* [Auto Parallel] Change the import rules

* [Auto Parallel] Add the examples for Engine

* [Auto Parallel] Do some minor changes

* [Auto Parallel] Remove yaml dependency

* [Auto Parallel] Fix the unittests

* add valid after train

* bug fix
Co-authored-by: Nzhaoyingli <zhaoyingli@baidu.com>
Co-authored-by: Ncaozhou <caozhou@radi.ac.cn>
Co-authored-by: Ncaozhou <48191911+Caozhou1995@users.noreply.github.com>

* bugfix (#45332)

* dist embedding support lookup table v1

* add unitest

* customize wait_comm

* group gradients

* bugfix

* update program

* adapt gradient merge

* fix op_role

* fix strategy

* adapt lazy init and fix pass

* add unittest

* update comment

* fix amp and sharding

* remove clip_by_norm

* support iterable dataset for auto parallel

* add split_data proto

* fix unittest bug

* fix recompute bug

* update cmake

* bugfix

* remove scaling

* support rescale_grad opt

* add unitest

* add clip_grad

* fix comments

* add unittest

* update logger

* add collate_fn

* fix number of inputs

* fixed bug for pass & engine

* fixed bug for benchmark GPT-3

* add tuner & profiler

* add algorithms & config

* [dy2st]Add ProgramHelper to polish build program logic in autoparallel.Engine

* refine code

* avoid sync with cpp in partition op

* delay eval & predict mode

* bugfix for gradient merge pass

* add comm init control by socket

* avoid single card instance failure

* add 'to_static' in engine api

* fix cmakelist

* fix op_role

* fix engine

* update op_role

* fixed bug for pass & engine

* fixed bug for benchmark GPT-3

* [Auto Parallel] Use a fast completion for data parallelism

* remove unuse cuSparse function

* [Auto Parallel] Fix some bugs of the fast dp completion

* [Auto Parallel] Add the cmake statements

* [Auto Parallel] Make the unittest adapt to the new interface

* [Auto Parallel] Modify the timeout of the unittest

* [Auto Parallel] Remove unnecessary comments
Co-authored-by: Nzhouwei25 <zhouwei25@baidu.com>

* fix fetch list

* fix unittest

* add fetch_list

* fix evaluate log

* tiny fix

* 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

* prepare only once

* [Auto Parallel] Add the parallel tuner

* [Auto Parallel] Improve the parallel tuner and fix some bugs

* upodate cost model

* update import Resharder by dist op

* update cost model

* fix comp cost bug

* update cost model

* [Auto Parallel] Amend the dist attr for #processses=1

* update cost model and tuner

* update cost model and tuner

* update cost model and tuner

* update cluster

* update reshard

* [Auto Parallel] Add the estimation from the cost model

* [Auto Parallel] Reimplement the backup and restore functions

* [Auto Parallel] Fix the bugs of the parallel tuner

* [Auto Parallel] Update the engine api and dist context

* [Auto Parallel] Work around the high order grad problem

* [Auto Parallel] Add some miscellaneous improvements

* [Auto Parallel] Add a unittest for DistributedContext
Co-authored-by: Ncaozhou <caozhou@radi.ac.cn>

* slice data in dist_loader & flag to scale grad

* bug fix

* update unittest

* enable static

* [Auto Parallel] Refactor the engine api and parallelizer

* [Auto Parallel] Fix the default dist op for the slice op

* [Auto Parallel] Fix the format of planer.py

* [Auto Parallel] Fix a bug

* [Auto Parallel] Replace the old planner by the new partition tuner

* [Auto Parallel] Improve the completion and distributed context

* [Auto Parallel] Fix some bugs of the compatible check of some dist ops

* [Auto Parallel] Fix some bugs

* 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

* adapot dist op

* [Auto Parallel] Support the auto completion of while_op

* add dist_fill_constant_batch_size_like

* align infer  accuracy

* fix code stype

* update unitest

* add dist_saver and update engine

* add dist_saver and update engine