{"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 0x7fbe312bd160>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fbe312bd1f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fbe312bd280>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fbe312bd310>", "_build": "<function ActorCriticPolicy._build at 0x7fbe312bd3a0>", "forward": "<function ActorCriticPolicy.forward at 0x7fbe312bd430>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fbe312bd4c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fbe312bd550>", "_predict": "<function ActorCriticPolicy._predict at 0x7fbe312bd5e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fbe312bd670>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fbe312bd700>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fbe312bd790>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fbe312b5ea0>"}, "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:": "gAWVZwIAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLHIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWcAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/lGgKSxyFlIwBQ5R0lFKUjARoaWdolGgSKJZwAAAAAAAAAAAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH+UaApLHIWUaBV0lFKUjA1ib3VuZGVkX2JlbG93lGgSKJYcAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLHIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYcAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUaCFLHIWUaBV0lFKUjApfbnBfcmFuZG9tlE51Yi4=", "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": 506524, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1675856648512625240, "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:": "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"}, "_episode_num": 0, "use_sde": true, "sde_sample_freq": -1, "_current_progress_remaining": 0.7467520000000001, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 15828, "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"}}