{"policy_class": {":type:": "", ":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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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__": "", "_get_constructor_parameters": "", "reset_noise": "", "_build_mlp_extractor": "", "_build": "", "forward": "", "_get_action_dist_from_latent": "", "_predict": "", "evaluate_actions": "", "get_distribution": "", "predict_values": "", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fccde32f660>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652207807.1498046, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "", ":serialized:": "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"}, "_last_obs": {":type:": "", ":serialized:": "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"}, "_last_episode_starts": {":type:": "", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "ep_info_buffer": {":type:": "", ":serialized:": "gAWVOBAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIj20ZcJZMcUCUhpRSlIwBbJRL3IwBdJRHQJ6ISTnq3Vl1fZQoaAZoCWgPQwhgH526sk5zQJSGlFKUaBVLv2gWR0CeiFw++ueSdX2UKGgGaAloD0MINzgR/Vqac0CUhpRSlGgVS/xoFkdAnoqaSTyJ9HV9lChoBmgJaA9DCPqXpDLFrFJAlIaUUpRoFUu8aBZHQJ6KyYiPhhp1fZQoaAZoCWgPQwig3SHFwMlyQJSGlFKUaBVNcAJoFkdAnoshw2l2vHV9lChoBmgJaA9DCPOtD+sN+nBAlIaUUpRoFUvOaBZHQJ6L4fkmx+t1fZQoaAZoCWgPQwhA3qtWJhZ0QJSGlFKUaBVL4WgWR0CejBZ6D5CXdX2UKGgGaAloD0MIEY3uIPaEZ0CUhpRSlGgVTegDaBZHQJ6M8ppeu3d1fZQoaAZoCWgPQwjyfAbU2xVwQJSGlFKUaBVL5WgWR0Cejc0kGA09dX2UKGgGaAloD0MIz4b8M4OuUUCUhpRSlGgVS6loFkdAno4nzlLeynV9lChoBmgJaA9DCGr11VWBCHJAlIaUUpRoFUv3aBZHQJ6OW6bvw3J1fZQoaAZoCWgPQwgsmzkktfBwQJSGlFKUaBVL4WgWR0CejlLx7RfGdX2UKGgGaAloD0MIm+Ydp2gdckCUhpRSlGgVS+poFkdAno/s7QswtnV9lChoBmgJaA9DCIaqmEq/jG9AlIaUUpRoFU0aAWgWR0CekYGZuyeJdX2UKGgGaAloD0MIh97i4f1VckCUhpRSlGgVTTIBaBZHQJ6R3hDPWx11fZQoaAZoCWgPQwgrhqsDIHZGQJSGlFKUaBVLtGgWR0Cekn4X40uUdX2UKGgGaAloD0MIA9L+B5gpcUCUhpRSlGgVTSwBaBZHQJ6S70RODap1fZQoaAZoCWgPQwhuT5DYbv1yQJSGlFKUaBVL82gWR0Cek3OZ9d/sdX2UKGgGaAloD0MICYfe4mEAcUCUhpRSlGgVS/ZoFkdAnpPn8Kohp3V9lChoBmgJaA9DCCfeAZ40l3FAlIaUUpRoFU0XAWgWR0CelI8PWhAXdX2UKGgGaAloD0MIdv7tsh/JckCUhpRSlGgVTQcDaBZHQJ6UvLOiWVx1fZQoaAZoCWgPQwgAdQMFnmFzQJSGlFKUaBVL/2gWR0CelPWIoE0SdX2UKGgGaAloD0MI6V+SytQlcECUhpRSlGgVS9FoFkdAnpU1glWwNnV9lChoBmgJaA9DCDUmxFxSFHFAlIaUUpRoFU0IAWgWR0CeljEnLJS0dX2UKGgGaAloD0MINWPRdDYgckCUhpRSlGgVS99oFkdAnpYhU70WdnV9lChoBmgJaA9DCOwUqwZhw25AlIaUUpRoFUv2aBZHQJ6WtZDArQR1fZQoaAZoCWgPQwh/h6JAXwRyQJSGlFKUaBVL82gWR0Cels7NSqEOdX2UKGgGaAloD0MIhqxu9ZwmcUCUhpRSlGgVS9poFkdAnpjVvVEux3V9lChoBmgJaA9DCFjhlo9k6XJAlIaUUpRoFU0FAWgWR0CemOg00m+kdX2UKGgGaAloD0MInS/2XvykcECUhpRSlGgVS8VoFkdAnpnxGlQ/HHV9lChoBmgJaA9DCBl2GJO+LXBAlIaUUpRoFUv5aBZHQJ6aQK7ZnL91fZQoaAZoCWgPQwhXQndJXEhzQJSGlFKUaBVL5WgWR0CempEc81XOdX2UKGgGaAloD0MIW9O841TCcUCUhpRSlGgVTQYBaBZHQJ6bTLpzLfV1fZQoaAZoCWgPQwgZOnZQCQBzQJSGlFKUaBVNpQNoFkdAnptpemelK3V9lChoBmgJaA9DCI2ACkeQNXBAlIaUUpRoFUv0aBZHQJ7hzbcoH9p1fZQoaAZoCWgPQwj99+C1i1dxQJSGlFKUaBVNBQFoFkdAnuHENFz+33V9lChoBmgJaA9DCLLXuz8eTnFAlIaUUpRoFUvgaBZHQJ7h1XhfjS51fZQoaAZoCWgPQwhyTuyh/epwQJSGlFKUaBVNAAFoFkdAnuJoixFAmnV9lChoBmgJaA9DCOilYmMeFXJAlIaUUpRoFUvdaBZHQJ7jTZJ04ip1fZQoaAZoCWgPQwhGX0GasVtzQJSGlFKUaBVL8WgWR0Ce43RWLgn/dX2UKGgGaAloD0MI8iiV8ARLcECUhpRSlGgVTRsBaBZHQJ7jjb7CSA91fZQoaAZoCWgPQwg5tMh2/iNwQJSGlFKUaBVL52gWR0Ce474tHxz8dX2UKGgGaAloD0MIkx6GVucAc0CUhpRSlGgVS/1oFkdAnuPCsCDEnHV9lChoBmgJaA9DCOJYF7eRsHBAlIaUUpRoFUvfaBZHQJ7lUolUp/h1fZQoaAZoCWgPQwgteNFXkNJxQJSGlFKUaBVNEAFoFkdAnubviHZbp3V9lChoBmgJaA9DCL6HS467jm9AlIaUUpRoFUvPaBZHQJ7nRVDKHO91fZQoaAZoCWgPQwjezOhHA5VyQJSGlFKUaBVL8GgWR0Ce50GFi8WcdX2UKGgGaAloD0MIPsvz4G5ncUCUhpRSlGgVS/9oFkdAnud4RmK64HV9lChoBmgJaA9DCOaV621zXHJAlIaUUpRoFUveaBZHQJ7o9rzoUzt1fZQoaAZoCWgPQwiJ6xhX3AxxQJSGlFKUaBVL62gWR0Ce6YZVGTcJdX2UKGgGaAloD0MIW1653ralbkCUhpRSlGgVS+5oFkdAnumc6BAfMnV9lChoBmgJaA9DCJJbk25LanJAlIaUUpRoFU0rAWgWR0Ce6aWyTpxFdX2UKGgGaAloD0MIorQ3+ALHcUCUhpRSlGgVS9doFkdAnuqAIUrTY3V9lChoBmgJaA9DCDm1M0ztcXNAlIaUUpRoFUvbaBZHQJ7qgIdELIB1fZQoaAZoCWgPQwhubHak+iRxQJSGlFKUaBVNCQFoFkdAnuskpNKywHV9lChoBmgJaA9DCNkFg2tu3G9AlIaUUpRoFUvmaBZHQJ7rICKaXrt1fZQoaAZoCWgPQwhgzQGCuaRwQJSGlFKUaBVL8GgWR0Ce66U5uIhydX2UKGgGaAloD0MIv9U6cTkFb0CUhpRSlGgVS/hoFkdAnuvtBKL88HV9lChoBmgJaA9DCKisputJK3JAlIaUUpRoFUu5aBZHQJ7tMdJaq0d1fZQoaAZoCWgPQwjyzwziA89xQJSGlFKUaBVL92gWR0Ce7aoA4n4PdX2UKGgGaAloD0MIblD7rR1Sc0CUhpRSlGgVS85oFkdAnu5wTmGM43V9lChoBmgJaA9DCNgo6zeTAG5AlIaUUpRoFUvUaBZHQJ7ubCAMDwJ1fZQoaAZoCWgPQwgao3VUNV5yQJSGlFKUaBVLxWgWR0Ce8EI0IkZ8dX2UKGgGaAloD0MIzCVV280Rc0CUhpRSlGgVS9FoFkdAnvCSuuA7P3V9lChoBmgJaA9DCMYUrHF2EnFAlIaUUpRoFUvBaBZHQJ7xAkNWluZ1fZQoaAZoCWgPQwhOe0rOyUNwQJSGlFKUaBVNIgFoFkdAnvEtE1EVnHV9lChoBmgJaA9DCGFu93KfCXJAlIaUUpRoFU0LAWgWR0Ce8i8XvYvndX2UKGgGaAloD0MIdAtdiQDmcUCUhpRSlGgVS9RoFkdAnvJu9alk6XV9lChoBmgJaA9DCLXGoBPCdnBAlIaUUpRoFU0EAWgWR0Ce8pURnOB2dX2UKGgGaAloD0MI3NlXHiQ1bkCUhpRSlGgVS+JoFkdAnvN2nGbTdHV9lChoBmgJaA9DCJzFi4XhCHBAlIaUUpRoFUv6aBZHQJ7zxAhStNl1fZQoaAZoCWgPQwhM/bypiKdzQJSGlFKUaBVL0GgWR0Ce9IgX/HYIdX2UKGgGaAloD0MITgrzHuf6b0CUhpRSlGgVS+FoFkdAnvWib+cYqHV9lChoBmgJaA9DCKiN6nTgWnJAlIaUUpRoFU0dAWgWR0Ce9dbT+ee4dX2UKGgGaAloD0MIDp90IsHpb0CUhpRSlGgVS+JoFkdAnvZ4j0L+gnV9lChoBmgJaA9DCOjZrPpcdUlAlIaUUpRoFUuyaBZHQJ72o371qWV1fZQoaAZoCWgPQwhwRPesq89yQJSGlFKUaBVNqgJoFkdAnveqZtvXLHV9lChoBmgJaA9DCM1bdR1qQXFAlIaUUpRoFU0jAWgWR0Ce+L24NI9UdX2UKGgGaAloD0MIxyx7EpguckCUhpRSlGgVS+RoFkdAnvlHEyckMXV9lChoBmgJaA9DCB/ZXDXPYHFAlIaUUpRoFUvyaBZHQJ75okGA09B1fZQoaAZoCWgPQwgKEtvdgyBzQJSGlFKUaBVL/mgWR0Ce+aICEHt4dX2UKGgGaAloD0MIfXVVoJZtbUCUhpRSlGgVS95oFkdAnvpLngYP5HV9lChoBmgJaA9DCIVf6ueNXnJAlIaUUpRoFU0AAWgWR0Ce+1QoCuEFdX2UKGgGaAloD0MIgSTs2wkPdECUhpRSlGgVS+ZoFkdAnvt3O0LMLXV9lChoBmgJaA9DCIf9nlhnFnJAlIaUUpRoFUvvaBZHQJ78Efp2U0N1fZQoaAZoCWgPQwijPV5IB/xwQJSGlFKUaBVNNAFoFkdAnvzqhHskZHV9lChoBmgJaA9DCN0MN+AzjHFAlIaUUpRoFUvNaBZHQJ789PUKArh1fZQoaAZoCWgPQwhUkJ+NnEJyQJSGlFKUaBVL/GgWR0Ce/UtT1kDqdX2UKGgGaAloD0MIYAMixBV5c0CUhpRSlGgVS8NoFkdAnv1S4e9zwXV9lChoBmgJaA9DCNkj1AypJnBAlIaUUpRoFUvvaBZHQJ79yucMEzR1fZQoaAZoCWgPQwiCxeHM76ZxQJSGlFKUaBVLxmgWR0Ce/j5n13+udX2UKGgGaAloD0MIc2cmGE7IbkCUhpRSlGgVTQsBaBZHQJ7/cIJJGvx1fZQoaAZoCWgPQwhZw0XuqUBxQJSGlFKUaBVL2mgWR0CfAGoSteUqdX2UKGgGaAloD0MIMGR1q+f4cUCUhpRSlGgVS/FoFkdAnwCpyyUs4HV9lChoBmgJaA9DCKD/Hry2V3NAlIaUUpRoFUvMaBZHQJ8A+nFYMfB1fZQoaAZoCWgPQwjYn8TnjrFxQJSGlFKUaBVL6GgWR0CfATDAaef7dX2UKGgGaAloD0MIXjC45k7EcUCUhpRSlGgVTQcBaBZHQJ8CLyz5XU91fZQoaAZoCWgPQwhb64uEtsdxQJSGlFKUaBVL3GgWR0CfApZgogFHdX2UKGgGaAloD0MIJ9nqcsoYb0CUhpRSlGgVS/hoFkdAnwNu3Ytg8nV9lChoBmgJaA9DCJavy/DfLXNAlIaUUpRoFUvlaBZHQJ8DhOh0yQB1ZS4="}, "ep_success_buffer": {":type:": "", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 620, "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:": "", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}