| { | |
| "policy_class": { | |
| ":type:": "<class 'abc.ABCMeta'>", | |
| ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", | |
| "__module__": "stable_baselines3.common.policies", | |
| "__doc__": "\n Policy class for actor-critic algorithms (has both policy and value prediction).\n Used by A2C, PPO and the likes.\n\n :param observation_space: Observation space\n :param action_space: Action space\n :param lr_schedule: Learning rate schedule (could be constant)\n :param net_arch: The specification of the policy and value networks.\n :param activation_fn: Activation function\n :param ortho_init: Whether to use or not orthogonal initialization\n :param use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param full_std: Whether to use (n_features x n_actions) parameters\n for the std instead of only (n_features,) when using gSDE\n :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n a positive standard deviation (cf paper). It allows to keep variance\n above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n :param squash_output: Whether to squash the output using a tanh function,\n this allows to ensure boundaries when using gSDE.\n :param features_extractor_class: Features extractor to use.\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\n :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\n :param normalize_images: Whether to normalize images or not,\n dividing by 255.0 (True by default)\n :param optimizer_class: The optimizer to use,\n ``th.optim.Adam`` by default\n :param optimizer_kwargs: Additional keyword arguments,\n excluding the learning rate, to pass to the optimizer\n ", | |
| "__init__": "<function ActorCriticPolicy.__init__ at 0x7ff0e3284550>", | |
| "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff0e32845e0>", | |
| "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff0e3284670>", | |
| "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff0e3284700>", | |
| "_build": "<function ActorCriticPolicy._build at 0x7ff0e3284790>", | |
| "forward": "<function ActorCriticPolicy.forward at 0x7ff0e3284820>", | |
| "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ff0e32848b0>", | |
| "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff0e3284940>", | |
| "_predict": "<function ActorCriticPolicy._predict at 0x7ff0e32849d0>", | |
| "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff0e3284a60>", | |
| "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff0e3284af0>", | |
| "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff0e3284b80>", | |
| "__abstractmethods__": "frozenset()", | |
| "_abc_impl": "<_abc_data object at 0x7ff0e3288030>" | |
| }, | |
| "verbose": 1, | |
| "policy_kwargs": {}, | |
| "observation_space": { | |
| ":type:": "<class 'gym.spaces.box.Box'>", | |
| ":serialized:": "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", | |
| "dtype": "float32", | |
| "_shape": [ | |
| 8 | |
| ], | |
| "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", | |
| "high": "[inf inf inf inf inf inf inf inf]", | |
| "bounded_below": "[False False False False False False False False]", | |
| "bounded_above": "[False False False False False False False False]", | |
| "_np_random": null | |
| }, | |
| "action_space": { | |
| ":type:": "<class 'gym.spaces.discrete.Discrete'>", | |
| ":serialized:": "gAWViAAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", | |
| "n": 4, | |
| "_shape": [], | |
| "dtype": "int64", | |
| "_np_random": null | |
| }, | |
| "n_envs": 16, | |
| "num_timesteps": 1015808, | |
| "_total_timesteps": 1000000, | |
| "_num_timesteps_at_start": 0, | |
| "seed": null, | |
| "action_noise": null, | |
| "start_time": 1678070014638407270, | |
| "learning_rate": 0.0, | |
| "tensorboard_log": null, | |
| "lr_schedule": { | |
| ":type:": "<class 'function'>", | |
| ":serialized:": "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" | |
| }, | |
| "_last_obs": { | |
| ":type:": "<class 'numpy.ndarray'>", | |
| ":serialized:": "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" | |
| }, | |
| "_last_episode_starts": { | |
| ":type:": "<class 'numpy.ndarray'>", | |
| ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg==" | |
| }, | |
| "_last_original_obs": null, | |
| "_episode_num": 0, | |
| "use_sde": false, | |
| "sde_sample_freq": -1, | |
| "_current_progress_remaining": -0.015808000000000044, | |
| "ep_info_buffer": { | |
| ":type:": "<class 'collections.deque'>", | |
| ":serialized:": "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" | |
| }, | |
| "ep_success_buffer": { | |
| ":type:": "<class 'collections.deque'>", | |
| ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg==" | |
| }, | |
| "_n_updates": 248, | |
| "n_steps": 1024, | |
| "gamma": 0.999, | |
| "gae_lambda": 0.98, | |
| "ent_coef": 0.01, | |
| "vf_coef": 0.5, | |
| "max_grad_norm": 0.5, | |
| "batch_size": 64, | |
| "n_epochs": 4, | |
| "clip_range": { | |
| ":type:": "<class 'function'>", | |
| ":serialized:": "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" | |
| }, | |
| "clip_range_vf": null, | |
| "normalize_advantage": true, | |
| "target_kl": null | |
| } |