* [Auto Parallel] Make Engine class callable (#46416)

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

* [Auto Parallel] Make Engine class callable

* [Auto Parallel] Update the data loading of tuner

* Print IPS in auto parallel Engine (#46554)

* [AutoParallel] fix dist_split (#46505)

* [AutoParallel] fix dist_split

* add unittest

* update cmakelist

* [AutoParallel] fix sharding (#46572)

* [AutoParallel] fix process_mesh (#46583)

* [AutoParallel] fix reshard when train with eval (#46605)

* [AutoParallel] fix reshard when train with eval

* fix mppp

* [AutoParallel] fix amp when predict (#46637)

* [Auto Parallel]Update comp cost and completion for gpt auto search (#46387)

* update comp cost and completion for gpt auto search

* add unittest

* [Auto Parallel] Fix bugs caused by the inconsistent outputs of Engine API (#46633)

* [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] Improve the fine-grained APIs (#46552)

* [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

* bugfix (#46921)

* [Auto Parallel] Fix the bug for None labels (#46987)

* [AutoParallel] adapt for gpt-gen (#46771)

* for gpt-gen

* fix reshard

* adapt assign and shape op

* add dist_assign & unittest

* add conditional block unittest

* rename unittest

* [Auto Parallel] Fix the bug of completion (#47056)

* [Auto Parallel] Fix the bug for None labels

* [Auto Parallel] Fix the completion bug

* [AutoParallel] add callbacks (#47014)

* [AutoParallel] add callbacks

* fix unittest

* fix dist_context

* fix engine

* fix cmakelist

* fix unittest's returns

* fix cmakelist

* [Auto Parallel] Add cost interface (#47043)

* add cost interface

* update inferface and add unittest

* update unittest

* update inferface

* [Auto Parallel]Add parallel tuner (#46189)

* add parallel tuner

* add unittest

* fix unittest

* set timeout of unittest

* set unittest timeout

* fix auto_mode setting

* update unittest

* sync from develop and update unittest

* remove unused import

* update unittest

* update cmakelist

* add unittests
Co-authored-by: NYulong Ao <aoyulong@baidu.com>
Co-authored-by: NRuibiao Chen <chenruibiao@baidu.com>
Co-authored-by: Ncaozhou <48191911+Caozhou1995@users.noreply.github.com>
Co-authored-by: NJZ-LIANG <jianzhongliang10@gmail.com>

* 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

* fix warning error , test=document_fix

* fix warning error , test=document_fix

* fix warning error , test=document_fix

* fix warning error , test=document_fix

* fix warning error , test=document_fix

* fix warning error , test=document_fix

* fix warning error , test=document_fix

* update 2.0 public api in vision

* fix some flake8 errors

* [OPs] Bug fix, fix the segment mean for illegal syncthreads usage. (#32596) (#32610)

* [OPs] Bug fix, fix the segment mean for illegal syncthreads usage.

* remove packages in __all__

* create new public api level paddle.callbacks;paddle.hub;paddle.utils.unique_name
Co-authored-by: NZhong Hui <zhonghui.net@gmail.com>

* make hapi support amp, and add unittest

* make unittest only support GPU

* update parameters for amp in hapi.Model

* update hapi.Model.prepare interface, and update unittest

* fix test_model.py unittest bug

* add grad clear in dygraph

* use_fp16_guard defaults to True, which could avoid nan

* add input check, and add internal doc link to low level api

* update doc, and decrease the sample num of dataset to avoid timeout

* make hapi amp param  support str 'O1' or 'O2'

* resume calling , modify the code of the check part

* upgrade the usage of Fleet API, and disable 'pure_fp16' param

test=document_fix

* update condition of logger print

* update EarlyStopping doc

* update EarlyStopping doc, test=document_fix

* add ReduceLROnPlateau

* enhance logger callback for benchmark

* Fix doc format for callbacks, metrics and Model
* Fix code sample and doc

* add early stopping

* add doc for early stopping

* fix sample code bugs

* update infer of mode, update doc, add unittests to increase coverage rate

* fix sample code for early stopping

* update sample code and unittests

* reduce time cost of test_callbacks unittest

* fix model.py code style error

* add lr scheduler

* return pil image as default according backend

* add visualdl callback

* refine vision models

* Move hapi form paddle/incubate to paddle

* Remove vision/datasets/utils.py and clean code

* Add sample code for conll05

* Print pull path when saving model

* Fix sample code after paramter_list of SGD is changed to parameters

* Fix bug in wmt16 datase

* Move paddle/incubate/hapi/metrics to paddle/metric
* Add Precision, Recall and Auc metric

* Rename `Input` into `InputSpec`

* fix argument place of Input api

* Remove paddle.incubate.hapi.loss and reuse the paddle.nn.layer.loss in high level API

* Refine Model

1. Take the network (instance of Layer) as the input of Model.
2. Refine set_dict/load_dict of Layer.
3. Refine Input interface, so update code sample about Input

* Merge hapi into Paddle

Hapi is a high level API for training and inference.
The main modules include Model, Loss, Metrics, Dataset.
Also includes common modules and models in NLP and computer vision, such as BERT, ResNet.

These modules are developed by:
0YuanZhang0, guoshengCS heavengate, LielinJiang, qingqing01, xyzhou-puck huangjun12, wangxiao1021, zhangyang.