v0.4.7

API Change

1. remove the requirements of sub fields (learn/collect/eval) in the policy config (users can define their own config formats)
2. use wandb as the default logger in task pipeline
3. remove value_network config field and implementations in SAC and related algorithms

Env

1. add dmc2gym env support and baseline (#451)
2. update pettingzoo to the latest version (#597)
3. polish icm/rnd+onppo config bugs and add app_door_to_key env (#564)
4. add lunarlander continuous TD3/SAC config
5. polish lunarlander discrete C51 config

Algorithm

1. add Procedure Cloning (PC) imitation learning algorithm (#514)
2. add Munchausen Reinforcement Learning (MDQN) algorithm (#590)
3. add reward/value norm methods: popart & value rescale & symlog (#605)
4. polish reward model config and training pipeline (#624)
5. add PPOF reward space demo support (#608)
6. add PPOF Atari demo support (#589)
7. polish dqn default config and env examples (#611)
8. polish comment and clean code about SAC

Enhancement

1. add language model (e.g. GPT) training utils (#625)
2. remove policy cfg sub fields requirements (#620)
3. add full wandb support (#579)

Fix

1. fix confusing shallow copy operation about next_obs (#641)
2. fix unsqueeze action_args in PDQN when shape is 1 (#599)
3. fix evaluator return_info tensor type bug (#592)
4. fix deque buffer wrapper PER bug (#586)
5. fix reward model save method compatibility bug
6. fix logger assertion and unittest bug
7. fix bfs test py3.9 compatibility bug
8. fix zergling collector unittest bug

Style

1. add DI-engine torch-rpc p2p communication docker (#628)
2. add D4RL docker (#591)
3. correct typo in task (#617)
4. correct typo in time_helper (#602)
5. polish readme and add treetensor example
6. update contributing doc

New Plan

• Call for contributors about DI-engine (#621)

Full Changelog: v0.4.6...v0.4.7

Contributors: @PaParaZz1 @karroyan @zjowowen @ruoyuGao @kxzxvbk @nighood @song2181 @SolenoidWGT @PSHarold @jimmydengpeng @eltociear