* 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

* clear the directory for the function

* add the unit test

* unit test bug

* yapf

* Add `files` argument when creating a client.

* Add `distributed_files` to parl.connect

* yapf

* Add try exception for `cls=cloudpickle.loads()`

* yapf

* unittest cluster_status_test.py `address is used`.

* Solve port address duplicate problem.

* combine two try except

* check monitor for xparl status

* yapf

* fix bugs

* fix bugs

* More sleep in cluster_test.py.

* yapf

* add debug mode

* add debug model

* Fix reset_job_test.py timeout problem.

* remove time decorator

* Add timeout_decorator

* add implemented algorithms in doc

* update implemented algorithms

* fix the thread-safe problem of  parl.client

* yapf

* Add total CPU nums to monitor

* fix unittest keyerro

* yapf

* test_max_memory error, add more sleep time

* Add more sleep time in job._reply_client_heartbeat

* Try sleep 6 times to check actor number.

* update layer wrappers to align latest fluid

* update version

* fix minor probmels in the docs

* typo

* remove pip source

* fix monitor

* add performance of A2C

* Update README.md

* modify logger for GPU detection

* add favicon

* Sleep longer for unittest.

* fix unittest bugs

* increase sleep seconds after job_memory error

* fix css max-width bug

* check if monitor_port is used

* change master log dir to .parl_data/master/port

* Add docs/parallel_training/features.rst

* rename feature.rst to overview.rst

* Add xparl status & @remote_class(max_memory)

* fix yapf error

* use new remote/tests

* reply job_memory_info to client heartbeat

* add cluster_status_test.py

* update overview.rst

* Update docs

* upgrade unit test to reduce test time

* minor change

* fix the bug in unit tests

* fix the bug in build.sh

* Update build.sh

* Update test.sh

* fix a potential bug that will hung the test

* then

* solve the problem in documentation

* make remote client support multiprocessing

* refine unittest

* refine unittest

* refine comment