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!!python/object/apply:collections.OrderedDict
- - - batch_size
    - 256
  - - buffer_size
    - 200000
  - - callback
    - - utils.callbacks.ParallelTrainCallback:
          gradient_steps: 200
      - utils.callbacks.LapTimeCallback
  - - ent_coef
    - auto
  - - env_wrapper
    - - gym.wrappers.time_limit.TimeLimit:
          max_episode_steps: 10000
      - ae.wrapper.AutoencoderWrapper
      - utils.wrappers.HistoryWrapper:
          horizon: 2
  - - gamma
    - 0.99
  - - gradient_steps
    - 256
  - - learning_rate
    - 0.00073
  - - learning_starts
    - 500
  - - n_timesteps
    - 2000000.0
  - - normalize
    - '{''norm_obs'': True, ''norm_reward'': False}'
  - - policy
    - MlpPolicy
  - - policy_kwargs
    - dict(log_std_init=-3, net_arch=[256, 256], n_critics=2, use_expln=True)
  - - sde_sample_freq
    - 16
  - - tau
    - 0.02
  - - train_freq
    - 200
  - - use_sde
    - true
  - - use_sde_at_warmup
    - true