{"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 0x7a5584aad900>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a5584aad990>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a5584aada20>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a5584aadab0>", "_build": "<function ActorCriticPolicy._build at 0x7a5584aadb40>", "forward": "<function ActorCriticPolicy.forward at 0x7a5584aadbd0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a5584aadc60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a5584aadcf0>", "_predict": "<function ActorCriticPolicy._predict at 0x7a5584aadd80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a5584aade10>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a5584aadea0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a5584aadf30>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7a55853b22c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1720962044728030150, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}