{"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 0x7e305d507490>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e305d507520>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e305d5075b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e305d507640>", "_build": "<function ActorCriticPolicy._build at 0x7e305d5076d0>", "forward": "<function ActorCriticPolicy.forward at 0x7e305d507760>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e305d5077f0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e305d507880>", "_predict": "<function ActorCriticPolicy._predict at 0x7e305d507910>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e305d5079a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e305d507a30>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e305d507ac0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e305d4fc700>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1706982570421687638, "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": 310, "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": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "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-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"}}