* update comp cost

* add dist default op cost

* add dist fill constant batch size like op cost

* add elewise op cost

* add fill_constant_batch_size_like op cost unittest

* add unittest and remove fill_constant_batch_size_like grad op cost

* add to cmakelist

* fix unittest bug

* avoid sync with cpp in partition op

* delay eval & predict mode

* bugfix for gradient merge pass

* fix op_role

* fix engine

* update op_role

* fixed bug for pass & engine

* fixed bug for benchmark GPT-3

* 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

* adapt for 10 loss

* partitioner support optimizer

* [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>

* auto parallel support primitive op with data parallel

* add primitive change

* 5 loss 3D cylinder acc aligned

* add unitest

* 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

* add dist reshape impl_idx=2

* fix cmakelist

* add dist_pnorm op

* update cmakelist

* fix cmakelist

* fix cmakelist

* add dist slice

* fix debug

* fix cmakelist

* adapot dist op

* [Auto Parallel] Support the auto completion of while_op

* add dist_fill_constant_batch_size_like

* align infer  accuracy

* [Auto Parallel] Support the auto completion of while_op
* align infer  accuracy

* 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

* [Auto Parallel] Add distributed mul for the old version

* [Auto Parallel] Support the auto completion of while_op

* [Auto Parallel] Improve the completion algorithms

* [Auto Parallel] Fix bugs for ernie inference

* [Auto Parallel] Remove attrs which cannot be pickled

* [Auto Parallel] make the dims_mappings of LodTensorArray vars empty

* [Auto Parallel] Fix bugs for the ernie inference in the pipeline parallel

* [Auto Parallel] Remove unncessary comments

* [Auto Parallel] Fix a bug of the CMakeLists

* [Auto Parallel] Use the newest APIs to write the unit test

* [Auto Parallel] Remove unnecessary statements

* adapot dist op

* add dist_fill_constant_batch_size_like

* remvoe print

* update compitable

* add unitest

* add subblock logic for context and partitioner

* partitioner support sub blocks

* revise typos

* fixed param init bug for while

* chmod 644

* add unitest

* mv forward parser

* update unitest

* update dist op ctx

* update dist op ctx

* fixed bug in dist op ctx

* fixed bug for recompute subblock

* support qkv fuse

* support qkv fuse

* update completion

* update completion

* update dist_split

* rerun ci

* is_auto_compatible added

* is_auto_compatible added

* update planner

* update unitest

* update dist matmul

* update auto converter

* Add the backward support for QR

* Remove unnecessary comments

* [Auto Parallel] Improve the dist op interface and compatible computation

* Remove unnecessary modification

* Recover some modifications

* Add lost files

* Fix a minor bug

* Fix the bug of the planner

* Fix the format problem

* [AutoParallel] Recompute Pass

* update unittest

* reshard for amp

* add comment

* auto parallel sharding base

* chmod

* add unitest

* set unitest cmake dist label

* revise code according to rewiew

* chmod

* bugfix for grad_clip and param broadcast

* chmod

* update unitest

* chmod

* add clip

* chmod

* add amp pass

* chmod

* add unitest

* remove grad update

* fixed bug

* fixed bug

* fixed typose

* fixed typoes

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

* [Auto Parallel] Rename back dist_context to distop_context

* auto parallel sharding base

* chmod

* add unitest

* set unitest cmake dist label

* revise code according to rewiew

* chmod

* add planner

* add planner

* add cost model update

* add relaunch updation

* update process_group

* fix error

* add unitest

* update unitest

* update cost model

* avoid api problem

* dist matmul op compatible

* dist op unittest

* modify dist matmul

* modify dist reshape

* modify dist reshape

* add a space

* add a space

* delete dist matmul op

* modify reshape

* add dist op unittest

* modify dist op unittest

* dist matmul op compatible

* modify common dist op

* modify common

* add a space

* adapt auto search

* adapt auto search

* fix matmulv2 compatible

* del debug

* AutoParallel Save&Load

* tiny modi

* update func name

* tiny fix

* add NotImplementedError

* fix doc

* update func name

* update func param

* update interface

* add unitest & modi make_data_unshard

* update unittest

* update unittest

* fix unittest

* fix cmakelist

* update unittest

* 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

* Improve the interface and the underlying mechanisms of auto parallel

* revise completion for backward

* revise completion for update

* revise completion for update

* update unitest

* chmod

* bugfix for grad_op output var's mesh

* Modify codes for pr 36744

* Remove unnecessary comments in framework.py

* Remove unnecessary comments in completion.py
Co-authored-by: NJZ-LIANG <jianzhongliang10@gmail.com>
Co-authored-by: Nzhaoyingli <zhaoyingli@baidu.com>
Co-authored-by: NJZ-LIANG <38102074+JZ-LIANG@users.noreply.github.com>

* 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>