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Role of managers

The manager is responsible for the non-learning aspects. The roles of each manager are as follows.

config_manager

  • It processes the config file and the optional parameter of run_command, and dumps the config to the storage path.

distributed_manager

  • It manages actors in distributed scripts. Let actors interact for update_period and sync actors network.

eval_manager

  • A simulation is performed for a certain number of episodes to obtain an evaluated score.
  • It saves the frames for recording.

log_manager

  • It records the learning progress in TensorBoard.
  • It receives the frames for recording and creates it as a gif.

metric_manager

  • It manages metrics and calculates and provides statistics.