* fix compatibility issue with the newest paddle

* remove logging lines

* resolve the compatibility issue with the newest paddle

* yapf
Co-authored-by: Nrobot <zenghongsheng@baidu.com>

* add SGD and Adam Optimizer for DeepES

* update deepes readme

* add warning when input different size in the same param update()

* add error return in update(), add optimizer.cc

* separate SGD and Adam, optimizer type in config is not case sensitive

* delete optimizer.cc

* config optimizer in deepes.proto

* more readable

* update maddpg readme, fixed gym version

* add tutorial of deepes, written with numpy, less than 100lines

* modify learning_rate as an arugment of Agent

* fix compatibility issue with the newest paddle

* remove logging lines
Co-authored-by: Nrobot <zenghongsheng@baidu.com>

* mac compatibility

* refine import trick

* liftsim a2c baseline

* update readme

* compatible with different os

* empty

* refine comments

* remove unnecessary assertion; add tensorboard guide

* remove unnecessary assertion

* update parl dependence of A2C

* add deepES & a demo that is compatible with torch

* add copyright & update protoc file path

* add copyright

* rm useless files

* update dependency on libtorch

* add the demonstration gif

* update gif

* Create README.md

* Update README.md

* Update README.md

* Update README.md

* update scripts

* update scripts#2

* update torch_predictor

* update comments for ES

* check dependence on paddle or torch

* update readme

* update readme#2

* users can still use parl.remote when no DL framework was found

* yapf

* add maddpg example

* format with yapf

* fix coding style

* fix coding style

* unittest without import multiagent env

* update maddpg code

* update maddpg readme

* add copyright comments

* update parl.maddpg without import gym

* update NeurlIPS2018.gif to NeurlIPS2019.gif

* update readme and comments

* fix paddle version bug

* add gym dependence (introduced by MADDPG)

* recall

* torch benchmark policy gradient

* refine comments and use native api

* add maddpg example

* format with yapf

* fix coding style

* fix coding style

* unittest without import multiagent env

* update maddpg code

* update maddpg readme

* add copyright comments

* add offline q learning

* Update README.md

* update

* yapf

* add sac

* Training pipeline of NeurIPS2019-Learn-to-Move-Challenge

* fix grammar mistakes

* release 1.2.1

* copyright

* fix bug

* refine README

* refine README

* fix typo

* Update README.md

* Update README.md

* Update reward calculation in QuickStart

* update

* yapf

* Update train.py

remove create_actors thread in train.py

* Update GA3C train.py

* add TD3

* update

* yapf.....

* Update train.py

* update dqn readme

* update merge.png

* make job run task in a separate process

* fix typo

* add more debug info in xparl client

* refine control flow of different processes in xparl job

* refine control flow of different processes in xparl job

* remove tsinghua source

* remove tsinghua source

* remove unnecessary logic

* fix typo

* refine comments and some logic

* fix bug, `decay=0` means totally synchronize weights of source model to target model

* add save_param in docs and quickstart

* Update train.py

* add pytorch a2c

* add set/get_weights test & copyright

* yapf....

* Update model_base_test_torch.py

* update

* Delete banma.py

* Update model_base_test_torch.py

* update

* Update model.py

* update torch tests

* Update model_base_test_torch.py

* final submit models of NeurIPS2019 challenge

* update readme

* fix yapf

* refine comment

* add Double & Dueling DQN

* yapf......................

* update

* Update train.py

* torch test env

* Update build.sh

* update torch unit test

* git commit -m torchdqn

* yapf

* fix bugs

* fix bugs

* fix bugs

* yapf

* remove fstring format

* torch_test yapf

* yapf

* Add torch in unittest.requirements

* update torch_unittest

* Torch and FLUID conflict problem in __init__.py

* Unittest fail for torch when both torch and fluid exists.

* cluster_test fail in the unittest, add timeout seconds.

* Torch backend for PARL

* add sleep time for unit test send_job_test.py

* Unit test for send_job_test.py

* use multiple try for unit test

* Fix compatibility for python2.7.

* fix send_job_test.py bugs

* check file exist before send_job_test.py

* Modify send_job_test.py

* add dygraph pg

* update acc. comments

* update comments

* Limit impala to single GPU training

* refine comment of scheduler

* refine comment