| { | |
| "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 0x7f44748d8820>", | |
| "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f44748d88b0>", | |
| "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f44748d8940>", | |
| "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f44748d89d0>", | |
| "_build": "<function ActorCriticPolicy._build at 0x7f44748d8a60>", | |
| "forward": "<function ActorCriticPolicy.forward at 0x7f44748d8af0>", | |
| "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f44748d8b80>", | |
| "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f44748d8c10>", | |
| "_predict": "<function ActorCriticPolicy._predict at 0x7f44748d8ca0>", | |
| "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f44748d8d30>", | |
| "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f44748d8dc0>", | |
| "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f44748d8e50>", | |
| "__abstractmethods__": "frozenset()", | |
| "_abc_impl": "<_abc_data object at 0x7f44749529f0>" | |
| }, | |
| "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": 1673781558445070797, | |
| "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": 310, | |
| "n_steps": 2048, | |
| "gamma": 0.99, | |
| "gae_lambda": 0.95, | |
| "ent_coef": 0.0, | |
| "vf_coef": 0.5, | |
| "max_grad_norm": 0.5, | |
| "batch_size": 64, | |
| "n_epochs": 10, | |
| "clip_range": { | |
| ":type:": "<class 'function'>", | |
| ":serialized:": "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" | |
| }, | |
| "clip_range_vf": null, | |
| "normalize_advantage": true, | |
| "target_kl": null | |
| } |