* prepare only once

This reverts commit e680d581.

* 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>

* [IPU] support paddle.distributed.launch with IPUs

* add device_num to env_args_mapping

* use original id in dist_op_context.grad_op_id_to_op_id

* del assert

* remove redundant map

* fix_sharding3_offload

* fix_fp16dtype_bug

* 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

* fix recompute in mp

* fix recompute

* update

* add nvsmi

* collect gpu info to log

* fix unitest

* rm ret_type

* add cinn pass to program

* remove build_cinn_pass ut

* polish ut, add ut

* guard ut with is_compiled_with_cinn

* enable ut test_build_cinn_pass_resnet

* [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

* [cherry-pick2.3]fix compile bug of windows cuda11.5 (#41464)

cherry-pick

fix compile bug of windows cuda11.5 #41433

* fix bug of missing boost when compile cache.cc (#41449)

【chery-pick #41430】fix bug of random compile failure, due to incorrect compile order of dependencies

* Fix eager try catch (#41438) (#41477)

[Cherry-Pick]Fix eager try catch (#41438)

* Cherry-pick-PR41407, fix device_id bug for final_state op in multiprocess testcase (#41407) (#41475)

Cherry-pick PR #41407

* [BugFix] Add error hint for one_hot gpu version (#41335) (#41495)

* add one_hot gpu hint

* move allow_out_of_range judgement

* delete useless unittest

* fix bugs of reshape double grad infermeta (#41459) (#41493)

* [cherrypick-2.3] modify infer gpu memory strategy (#41427), remove cudnn_deterministic=True (#41341)  (#41491)
Co-authored-by: NJingZhuangzhuang <75348594+JZZ-NOTE@users.noreply.github.com>

* [Cherry-pick][ROCm] fix dcu error in device event base, test=develop (#41523)

Cherry-pick of #41521

* [Cherry-Pick]Cherry pick PR41200, PR41474, PR41382 (#41509)

* Use `self`as a parameter of _hash_with_id function to avoid error caused by hash_id reuse (#41200)

* Add fill_constant_batch_size YAML and UT (#41474)

* Switch some dy2st UT to eager mode (#41382)

* Sitch some dy2st UT to eager mode

* Fix test_lstm and remove test_transformer

* Run test_resnet_v2 in old dy mode

* Unittest recover (#41431)

* update name

* update name

* fix test

* fix fleet bind

* update name

* update name

* fix test

* fix gpups wrapper

* remove Push/Pull/Load/Save with context in client and wrapper base class

* fix

* fix

* remove some interface

* fix

* remove

* code style

* recover

* fix

* remove code unused

* remove some unused table & accessor & CommonDenseTable => MemoryDenseTable

* fix

* fix

* fix

* recover

* remove unused code

* recover unittest

* fix

* remove

* fix

* remove code unuseful

* remove

* fix

* recover

* remove
Co-authored-by: Nesythan <esythan@126.com>

* add ssd sparse table

* fix

* add cache shuffle

* fix

* fix

* fix

* fix

* fix

* fix

* add unit test

* fix
Co-authored-by: Zhou Wei <1183042833@qq.com>
Co-authored-by: NSing_chan <51314274+betterpig@users.noreply.github.com>
Co-authored-by: N0x45f <23097963+0x45f@users.noreply.github.com>
Co-authored-by: Npangyoki <pangyoki@126.com>
Co-authored-by: NSiming Dai <908660116@qq.com>
Co-authored-by: NYuanRisheng <yuanrisheng@baidu.com>
Co-authored-by: NZhang Jun <ewalker@live.cn>
Co-authored-by: NJingZhuangzhuang <75348594+JZZ-NOTE@users.noreply.github.com>
Co-authored-by: NQi Li <qili93@qq.com>
Co-authored-by: Nesythan <esythan@126.com>

* double accessor and show_scale

* double accessor and show_scale

* rename

* fix bug in pslib config

* add unittest

* add dist reshape impl_idx=2

* fix cmakelist