{"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 0x7ded5dce37f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ded5dce3880>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ded5dce3910>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ded5dce39a0>", "_build": "<function ActorCriticPolicy._build at 0x7ded5dce3a30>", "forward": "<function ActorCriticPolicy.forward at 0x7ded5dce3ac0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ded5dce3b50>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ded5dce3be0>", "_predict": "<function ActorCriticPolicy._predict at 0x7ded5dce3c70>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ded5dce3d00>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ded5dce3d90>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ded5dce3e20>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ded5dc8f1c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1706163453269434481, "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:": "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": 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-6.1.58+-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"}}