{"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 0x7f36cff1beb0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f36cff1bf40>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f36cff24040>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f36cff240d0>", "_build": "<function ActorCriticPolicy._build at 0x7f36cff24160>", "forward": "<function ActorCriticPolicy.forward at 0x7f36cff241f0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f36cff24280>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f36cff24310>", "_predict": "<function ActorCriticPolicy._predict at 0x7f36cff243a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f36cff24430>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f36cff244c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f36cff24550>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f36cff17d00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 500736, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1684923403432139422, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAALP+rz1cjxC663Ost6vJG7Jw4DG7tk7HNgAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0014719999999999178, "_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": 43960, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVcAIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoB4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoECiWCAAAAAAAAAABAQEBAQEBAZRoFEsIhZRoGHSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBAoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaApLCIWUaBh0lFKUjARoaWdolGgQKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgKSwiFlGgYdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "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": 1, "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": 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-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "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"}}