| {"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 0x7efe35b59870>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7efe35b59900>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7efe35b59990>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7efe35b59a20>", "_build": "<function ActorCriticPolicy._build at 0x7efe35b59ab0>", "forward": "<function ActorCriticPolicy.forward at 0x7efe35b59b40>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7efe35b59bd0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7efe35b59c60>", "_predict": "<function ActorCriticPolicy._predict at 0x7efe35b59cf0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7efe35b59d80>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7efe35b59e10>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7efe35b59ea0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7efe35b52d00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1687505045629123661, "learning_rate": 0.0003, "tensorboard_log": null, "_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, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_shape": [8], "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |