{"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 0x7f0f39f52c10>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0f39f52ca0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0f39f52d30>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0f39f52dc0>", "_build": "<function ActorCriticPolicy._build at 0x7f0f39f52e50>", "forward": "<function ActorCriticPolicy.forward at 0x7f0f39f52ee0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f0f39f52f70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0f39ed8040>", "_predict": "<function ActorCriticPolicy._predict at 0x7f0f39ed80d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0f39ed8160>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0f39ed81f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0f39ed8280>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f0f39f53330>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu", "log_std_init": -2, "ortho_init": false, "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [28], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]", "bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-1. -1. -1. -1. -1. -1. -1. -1.]", "high": "[1. 1. 1. 1. 1. 1. 1. 1.]", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_np_random": null}, "n_envs": 4, "num_timesteps": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1675599163715662438, "learning_rate": 0.00096, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVNQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJbAAQAAAAAAAAAAAACQmRO3AACAPwAAAAAAAAAAAAAAAAAAAAAAAACAO0LOPQAAAABwC/e/AAAAAGv5tL0AAAAAPuv0PwAAAACDt6u9AAAAAAcH+z8AAAAANUnWPQAAAABmKuG/AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAUc2FtgAAgD8AAAAAAAAAAAAAAAAAAAAAAAAAgAJv9D0AAAAA/UPkvwAAAAAoVuG9AAAAAPCi8T8AAAAAXBs8vQAAAADJvPI/AAAAAOFCyb0AAAAA48ftvwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAM0DrjQAAIA/AAAAAAAAAAAAAAAAAAAAAAAAAIAh8gY+AAAAALva2r8AAAAAugJ5PQAAAACED/U/AAAAAK9ukbwAAAAAokoBQAAAAADCKMq9AAAAAKzq7r8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACrOoW1AACAPwAAAAAAAAAAAAAAAAAAAAAAAACAZuXbPQAAAACoU/W/AAAAANKZ3zwAAAAArl/lPwAAAADN+Pe8AAAAABGv2j8AAAAAn4aJvQAAAADzLPu/AAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwRLHIaUjAFDlHSUUpQu"}, "_episode_num": 0, "use_sde": true, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 62500, "n_steps": 8, "gamma": 0.99, "gae_lambda": 0.9, "ent_coef": 0.0, "vf_coef": 0.4, "max_grad_norm": 0.5, "normalize_advantage": false, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}