{"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 0x7fa97cb03d00>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fa97cb03d90>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fa97cb03e20>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fa97cb03eb0>", "_build": "<function ActorCriticPolicy._build at 0x7fa97cb03f40>", "forward": "<function ActorCriticPolicy.forward at 0x7fa97cb0c040>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fa97cb0c0d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fa97cb0c160>", "_predict": "<function ActorCriticPolicy._predict at 0x7fa97cb0c1f0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fa97cb0c280>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fa97cb0c310>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fa97cb0c3a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fa97cb08580>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 131072, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1706442440016683710, "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": -0.3107200000000001, "_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": 40, "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": 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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}