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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
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