* 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

* generate default cluster

* add unittest

* fix sharding in eager

* support eager sharding

* update base cost

* update unittest of cost model

* add unittest

* fix conflict

* new pg apis

* add docs of new apis

* update

* fix coverage

* update

* fix bug

* fix reduce scatter

* fix api

* update
Co-authored-by: NForFishes <2282912238@qq.com>

* 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

* rename eagerpylayer

* tmp fix

* init

* compile ok

* compile ok

* add vlogs

* add test

* fix termination error

* add testfile

* add

* fix window compile

* fix window compile

* fix windows compile

* fix windows compile

* fix windows compile

* fix windows compile

* fix windows compile

* fix windows compile

* fix kunlun compile

* fix compilation

* fix compilation

* fix compilation

* tmp fix

* add windows

* add windows

* add more logs

* change timeout to protected

* SB

* add

* add

* fix timeout

* add

* fix test

* fix test

* fix test

* fix ut

* fix ut

* fix ut

* [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>

* gpups default config and dataset

* codestyle

* add unittest

* code style

* add dymf to gpups

* codestyle

* add static.nn.cvm import

* PSERVER_DEBUG

* add fs config to worker desc

* update unittest

* unittest

* remove gpups unittest

* remove gpups unittest

* static check

* back fl

* delete ssl cert

* .

* make warning

* .

* unittest paral degree

* solve unittest

* heter & multi cloud commm ready

* .

* .

* fl-ps v1.0

* .

* support N + N mode

* .

* .

* .

* .

* delete print

* .

* .

* .

* .

* fix bug

* .

* .

* update paddle.distributed.launch

* add sample code

* update shell

* fix typo

* fix typo

* update docs

* rm code

* fix doc 2

* fix doc 3

* fix doc 4
Co-authored-by: Nroot <root@sgjur-pod004-1.ipu.graphcore.cn>

* Replace np.bool/np.bool8 with np.bool_

* Replace np.object with np.object_

* Replace np.complex with np.complex128

* Replace np.float with np.float64

* Replace np.int with np.int_

* Rerun pre-commit for newer pre-commit configuration

* Use builtin bool instead of np.bool_ based on the context

* fix fetch list

* fix unittest

* gpups default config and dataset

* codestyle

* add unittest

* code style

* add nproc_per_node for DistributedFusedLamb

* fix nproc_per_node communicator bug

* fix ring_id = 1 init bug

* fix ci

* fix test_parallel_executor_mnist.py

* add fetch_list

* fix evaluate log

* tiny fix

* fix bugs of reducer

* update

* update

* fix gradient merge

* bug fix

* update annotation

* 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

* back fl

* delete ssl cert

* .

* make warning

* .

* unittest paral degree

* solve unittest

* heter & multi cloud commm ready

* .

* .

* fl-ps v1.0

* .

* support N + N mode

* .

* .

* .

* .

* delete print

* .

* .

* .

* .

* 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