{"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 0x7bd067796710>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bd0677967a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bd067796830>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bd0677968c0>", "_build": "<function ActorCriticPolicy._build at 0x7bd067796950>", "forward": "<function ActorCriticPolicy.forward at 0x7bd0677969e0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bd067796a70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bd067796b00>", "_predict": "<function ActorCriticPolicy._predict at 0x7bd067796b90>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bd067796c20>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bd067796cb0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bd067796d40>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7bd0677a0140>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1703432178217720281, "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:": "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"}}