{"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 0x7e4a7e1fc0d0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e4a7e1fc160>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e4a7e1fc1f0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e4a7e1fc280>", "_build": "<function ActorCriticPolicy._build at 0x7e4a7e1fc310>", "forward": "<function ActorCriticPolicy.forward at 0x7e4a7e1fc3a0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e4a7e1fc430>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e4a7e1fc4c0>", "_predict": "<function ActorCriticPolicy._predict at 0x7e4a7e1fc550>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e4a7e1fc5e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e4a7e1fc670>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e4a7e1fc700>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e4a7e186d00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1719584838436006379, "learning_rate": 0.001, "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 Tue Jun 18 14:18:04 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"}}