{"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 0x7e352ed40a60>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e352ed40af0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e352ed40b80>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e352ed40c10>", "_build": "<function ActorCriticPolicy._build at 0x7e352ed40ca0>", "forward": "<function ActorCriticPolicy.forward at 0x7e352ed40d30>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e352ed40dc0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e352ed40e50>", "_predict": "<function ActorCriticPolicy._predict at 0x7e352ed40ee0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e352ed40f70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e352ed41000>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e352ed41090>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e352eceab00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1723584576137814340, "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": "2.3.1+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}