{"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 0x7ba9f101d480>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ba9f101d510>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ba9f101d5a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ba9f101d630>", "_build": "<function ActorCriticPolicy._build at 0x7ba9f101d6c0>", "forward": "<function ActorCriticPolicy.forward at 0x7ba9f101d750>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ba9f101d7e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ba9f101d870>", "_predict": "<function ActorCriticPolicy._predict at 0x7ba9f101d900>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ba9f101d990>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ba9f101da20>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ba9f101dab0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ba9f10163c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 5017600, "_total_timesteps": 5000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1691160382419627950, "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:": "gAWVfQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYKAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwqFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0035199999999999676, "_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": 980, "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": 10, "n_steps": 2048, "gamma": 0.999, "gae_lambda": 0.99, "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-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 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"}}