DI Engine Versions Save

OpenDILab Decision AI Engine

v0.5.1

3 months ago

Env

  1. add MADDPG pettingzoo example (#774)
  2. polish NGU Atari configs (#767)
  3. fix bug in cliffwalking env (#759)
  4. add PettingZoo replay video demo
  5. change default max retry in env manager from 5 to 1

Algorithm

  1. add QGPO diffusion-model related algorithm (#757)
  2. add HAPPO multi-agent algorithm (#717)
  3. add DreamerV3 + MiniGrid adaption (#725)
  4. fix hppo entropy_weight to avoid nan error in log_prob (#761)
  5. fix structured action bug (#760)
  6. polish Decision Transformer entry (#754)
  7. fix EDAC policy/model bug

Fix

  1. fix env typos
  2. fix pynng requirements bug
  3. fix communication module unittest bug

Style

  1. polish policy API doc (#762) (#764) (#768)
  2. add agent API doc (#758)
  3. polish torch_utils/utils API doc (#745) (#747) (#752) (#755) (#763)

News

  1. AAAI 2024: SO2: A Perspective of Q-value Estimation on Offline-to-Online Reinforcement Learning
  2. LMDrive: Closed-Loop End-to-End Driving with Large Language Models

Full Changelog: https://github.com/opendilab/DI-engine/compare/v0.5.0...v0.5.1

Contributors: @PaParaZz1 @zjowowen @nighood @kxzxvbk @puyuan1996 @Cloud-Pku @AltmanD @HarryXuancy

v0.5.0

5 months ago

Env

  1. add tabmwp env (#667)
  2. polish anytrading env issues (#731)

Algorithm

  1. add PromptPG algorithm (#667)
  2. add Plan Diffuser algorithm (#700) (#749)
  3. add new pipeline implementation of IMPALA algorithm (#713)
  4. add dropout layers to DQN-style algorithms (#712)

Enhancement

  1. add new pipeline agent for sac/ddpg/a2c/ppo and Hugging Face support (#637) (#730) (#737)
  2. add more unittest cases for model (#728)
  3. add collector logging in new pipeline (#735)

Fix

  1. fix logger middleware problems (#715)
  2. fix ppo parallel bug (#709)
  3. fix typo in optimizer_helper.py (#726)
  4. fix mlp dropout if condition bug
  5. fix drex collecting data unittest bugs

Style

  1. polish env manager/wrapper comments and API doc (#742)
  2. polish model comments and API doc (#722) (#729) (#734) (#736) (#741)
  3. polish policy comments and API doc (#732)
  4. polish rl_utils comments and API doc (#724)
  5. polish torch_utils comments and API doc (#738)
  6. update README.md and Colab demo (#733)
  7. update metaworld docker image

News

  1. NeurIPS 2023 Spotlight: LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios
  2. OpenDILab + Hugging Face DRL Model Zoo link

Full Changelog: https://github.com/opendilab/DI-engine/compare/v0.4.9...v0.5.0

Contributors: @PaParaZz1 @zjowowen @AltmanD @puyuan1996 @kxzxvbk @Super1ce @nighood @Cloud-Pku @zhangpaipai @ruoyuGao @eltociear

v0.4.9

8 months ago

API Change

  1. refactor the implementation of Decision Transformer, DI-engine supports both discrete and continuous DT outputs with the multi-modal observation now (example: ding/example/dt.py)
  2. Update the multi-GPU Distributed Data Parallel (DDP) example (link)
  3. Change the return value of InteractionSerialEvaluator, simplifying redundant results

Env

  1. add cliffwalking env (#677)
  2. add lunarlander ppo config and example

Algorithm

  1. add BCQ offline RL algorithm (#640)
  2. add Dreamerv3 model-based RL algorithm (#652)
  3. add tensor stream merge network tools (#673)
  4. add scatter connection model (#680)
  5. refactor Decision Transformer in new pipeline and support img input and discrete output (#693)
  6. add three variants of Bilinear classes and a FiLM class (#703)

Enhancement

  1. polish offpolicy RL multi-gpu DDP training (#679)
  2. add middleware for Ape-X distributed pipeline (#696)
  3. add example for evaluating trained DQN (#706)

Fix

  1. fix to_ndarray fails to assign dtype for scalars (#708)
  2. fix evaluator return episode_info compatibility bug
  3. fix cql example entry wrong config bug
  4. fix enable_save_figure env interface
  5. fix redundant env info bug in evaluator
  6. fix to_item unittest bug

Style

  1. polish and simplify requirements (#672)
  2. add Hugging Face Model Zoo badge (#674)
  3. add openxlab Model Zoo badge (#675)
  4. fix py37 macos ci bug and update default pytorch from 1.7.1 to 1.12.1 (#678)
  5. fix mujoco-py compatibility issue for cython<3 (#711)
  6. fix type spell error (#704)
  7. fix pypi release actions ubuntu 18.04 bug
  8. update contact information (e.g. wechat)
  9. polish algorithm doc tables

New Repo

  1. DOS: [CVPR 2023] ReasonNet: End-to-End Driving with Temporal and Global Reasoning

Full Changelog: https://github.com/opendilab/DI-engine/compare/v0.4.8...v0.4.9

Contributors: @PaParaZz1 @zjowowen @zhangpaipai @AltmanD @puyuan1996 @Cloud-Pku @Super1ce @kxzxvbk @jayyoung0802 @Mossforest @lxl2gf @Privilger

v0.4.8

11 months ago

API Change

  1. stop value is not the necessary field in config, defaults to math.inf, users can indicate max_env_step or max_train_iter in training entry to run the program with a fixed termination condition.

Env

  1. fix gym hybrid reward dtype bug (#664)
  2. fix atari env id noframeskip bug (#655)
  3. fix typo in gym any_trading env (#654)
  4. update td3bc d4rl config (#659)
  5. polish bipedalwalker config

Algorithm

  1. add EDAC offline RL algorithm (#639)
  2. add LN and GN norm_type support in ResBlock (#660)
  3. add normal value norm baseline for PPOF (#658)
  4. polish last layer init/norm in MLP (#650)
  5. polish TD3 monitor variable

Enhancement

  1. add MAPPO/MASAC task example (#661)
  2. add PPO example for complex env observation (#644)
  3. add barrier middleware (#570)

Fix

  1. fix abnormal collector log and add record_random_collect option (#662)
  2. fix to_item compatibility bug (#646)
  3. fix trainer dtype transform compatibility bug
  4. fix pettingzoo 1.23.0 compatibility bug
  5. fix ensemble head unittest bug

Style

  1. fix incompatible gym version bug in Dockerfile.env (#653)
  2. add more algorithm docs

New Repo

  1. LightZero: A lightweight and efficient MCTS/AlphaZero/MuZero algorithm toolkit.

Full Changelog: https://github.com/opendilab/DI-engine/compare/v0.4.6...v0.4.7

Contributors: @PaParaZz1 @zjowowen @puyuan1996 @SolenoidWGT @Super1ce @karroyan @zhangpaipai @eltociear

v0.4.7

1 year ago

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: https://github.com/opendilab/DI-engine/compare/v0.4.6...v0.4.7

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

v0.4.6

1 year ago

API Change

  1. middleware: CkptSaver(cfg, policy, train_freq=100) -> CkptSaver(policy, cfg.exp_name, train_freq=100)

Env

  1. add metadrive env and related ppo config (#574)
  2. add acrobot env and related dqn config (#577)
  3. add carracing in box2d (#575)
  4. add new gym hybrid viz (#563)
  5. update cartpole IL config (#578）

Algorithm

  1. add BDQ algorithm (#558)
  2. add procedure cloning model (#573)

Enhancement

  1. add simplified PPOF (PPO × Family) interface (#567) (#568) (#581) (#582)

Fix

  1. fix to_device and prev_state bug when using ttorch (#571)
  2. fix py38 and numpy unittest bugs (#565)
  3. fix typo in contrastive_loss.py (#572)
  4. fix dizoo envs pkg installation bugs
  5. fix multi_trainer middleware unittest bug

Style

  1. add evogym docker (#580)
  2. fix metaworld docker bug
  3. fix setuptools high version incompatibility bug
  4. extend treetensor lowest version

New Paper

  1. GoBigger: [ICLR 2023] A Scalable Platform for Cooperative-Competitive Multi-Agent Interactive Simulation

Contributors: @PaParaZz1 @puyuan1996 @timothijoe @Cloud-Pku @ruoyuGao @Super1ce @karroyan @kxzxvbk @eltociear

v0.4.5

1 year ago

API Change

  1. Move default examples about adding new env from extending BaseEnv to utilize DingEnvWrapper
  2. rename final_eval_reward to eval_episode_return in all related codes (including envs and evaluators)

Env

  1. add beergame supply chain optimization env (#512)
  2. add env gym_pybullet_drones (#526)
  3. rename eval reward to episode return (#536)

Algorithm

  1. add policy gradient algo implementation (#544)
  2. add MADDPG algo implementation (#550)
  3. add IMPALA continuous algo implementation (#551)
  4. add MADQN algo implementation (#540)

Enhancement

  1. add new task IMPALA-type distributed training scheme (#321)
  2. add load and save method for replaybuffer (#542)
  3. add more DingEnvWrapper example (#525)
  4. add evaluator more info viz support (#538)
  5. add trackback log for subprocess env manager (#534)

Fix

  1. fix halfcheetah td3 config file (#537）
  2. fix mujoco action_clip args compatibility bug (#535)
  3. fix atari a2c config entry bug
  4. fix drex unittest compatibility bug

Style

  1. add Roadmap issue of DI-engine (#548)
  2. update related project link and new env doc

New Project

  1. PPOxFamily: PPO x Family DRL Tutorial Course
  2. ACE: [AAAI 2023] Official PyTorch implementation of paper "ACE: Cooperative Multi-agent Q-learning with Bidirectional Action-Dependency".

Contributors: @PaParaZz1 @sailxjx @zjowowen @hiha3456 @Weiyuhong-1998 @kxzxvbk @song2181 @zerlinwang

v0.4.4

1 year ago

API Change

  1. context in new task pipeline is implemented by dataclass now, rather than dict
  2. recommend visulization is wandb now, rather than tensorboard

Env

  1. add modified gym-hybrid including moving, sliding and hardmove (#505) (#519)
  2. add evogym support (#495) (#527)
  3. add save_replay_gif option (#506)
  4. adapt minigrid_env and related config to latest MiniGrid v2.0.0 (#500)

Algorithm

  1. add pcgrad optimizer (#489)
  2. add some features in MLP and ResBlock (#511)
  3. delete mcts related modules (#518) (we will release a MCTS repo in future)

Enhancement

  1. add wandb middleware and demo (#488) (#523) (#528)
  2. add new properties in Context (#499)
  3. add single env policy wrapper for policy deployment (demo)
  4. add custom model demo and doc (文档)

Fix

  1. fix build logger args and unittests (#522)
  2. fix total_loss calculation in PDQN (#504)
  3. fix save gif function bug
  4. fix level sample unittest bug

Style

  1. update contact email address (#503)
  2. polish env log and resblock name
  3. add details button in readme

New Repo

  • DI-1024: Deep Reinforcement Learning + 1024 Game

Contributors: @PaParaZz1 @puyuan1996 @karroyan @hiha3456 @davide97l @Weiyuhong-1998 @zjowowen @norman26625

v0.4.3

1 year ago

Env

  1. add rule-based gomoku expert (#465)

Algorithm

  1. fix a2c policy batch size bug (#481)
  2. enable activation option in collaq attention and mixer
  3. minor fix about IBC (#477)

Enhancement

  1. add IGM support (#486)
  2. add tb logger middleware and demo

Fix

  1. the type conversion in ding_env_wrapper (#483)
  2. di-orchestrator version bug in unittest (#479)
  3. data collection errors caused by shallow copies (#475)
  4. gym==0.26.0 seed args bug

Style

  1. add readme tutorial link(environment & algorithm) (#490) (#493)
  2. adjust location of the default_model method in policy (#453)

New Repo

  • DI-sheep: Deep Reinforcement Learning + 3 Tiles Game

Contributors: @PaParaZz1 @nighood @norman26625 @ZHZisZZ @cpwan @mahuangxu

v0.4.2

1 year ago

API Change

  1. config will be deepcopyed by default in compile_config function
  2. After calling compile_config function, current code repo git log and git diff information will be saved in exp_name directory

Env

  1. add rocket env (#449)
  2. updated pettingzoo env and improved related performance (#457)
  3. add mario env demo (#443)
  4. add MAPPO multi-agent config (#464)
  5. add mountain car (discrete action) environment (#452)
  6. fix multi-agent mujoco gym comaptibility bug
  7. fix gfootball env save_replay variable init bug

Algorithm

  1. add IBC (Implicit Behaviour Cloning) algorithm (#401)
  2. add BCO (Behaviour Cloning from Observation) algorithm (#270)
  3. add continuous PPOPG algorithm (#414)
  4. add PER in CollaQ (#472)
  5. add activation option in QMIX and CollaQ

Enhancement

  1. update ctx to dataclass (#467)

Fix

  1. base_env FinalMeta bug about gym 0.25.0-0.25.1
  2. config inplace modification bug
  3. ding cli no argument problem
  4. import errors after running setup.py (jinja2, markupsafe)
  5. conda py3.6 and cross platform build bug

Style

  1. add project state and datetime in log dir (#455)
  2. polish notes for q-learning model (#427)
  3. revision to mujoco dockerfile and validation (#474)
  4. add dockerfile for cityflow env
  5. polish default output log format

Contributors: @PaParaZz1 @ZHZisZZ @zjowowen @song2181 @zerlinwang @i-am-tc @hiha3456 @nighood @kxzxvbk @Weiyuhong-1998 @RobinC94