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Tensorboard, refactoring and bug fixes
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@araffin araffin released this 18 Sep 09:19
· 270 commits to master since this release
v2.0.0
221f012

WARNING: This version contains breaking changes, please read the full details

  • Renamed DeepQ to DQN breaking changes
  • Renamed DeepQPolicy to DQNPolicy breaking changes
  • fixed DDPG behavior breaking changes
  • changed default policies for DDPG, so that DDPG now works correctly breaking changes
  • added more documentation (some modules from common).
  • added doc about using custom env
  • added Tensorboard support for A2C, ACER, ACKTR, DDPG, DeepQ, PPO1, PPO2 and TRPO
  • added episode reward to Tensorboard
  • added documentation for Tensorboard usage
  • added Identity for Box action space
  • fixed render function ignoring parameters when using wrapped environments
  • fixed PPO1 and TRPO done values for recurrent policies
  • fixed image normalization not occurring when using images
  • updated VecEnv objects for the new Gym version
  • added test for DDPG
  • refactored DQN policies
  • added registry for policies, can be passed as string to the agent
  • added documentation for custom policies + policy registration
  • fixed numpy warning when using DDPG Memory
  • fixed DummyVecEnv not copying the observation array when stepping and resetting
  • added pre-built docker images + installation instructions
  • added deterministic argument in the predict function
  • added assert in PPO2 for recurrent policies
  • fixed predict function to handle both vectorized and unwrapped environment
  • added input check to the predict function
  • refactored ActorCritic models to reduce code duplication
  • refactored Off Policy models (to begin HER and replay_buffer refactoring)
  • added tests for auto vectorization detection
  • fixed render function, to handle positional arguments
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