{"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 0x7f28d61b7040>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f28d61b70d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f28d61b7160>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f28d61b71f0>", "_build": "<function ActorCriticPolicy._build at 0x7f28d61b7280>", "forward": "<function ActorCriticPolicy.forward at 0x7f28d61b7310>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f28d61b73a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f28d61b7430>", "_predict": "<function ActorCriticPolicy._predict at 0x7f28d61b74c0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f28d61b7550>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f28d61b75e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f28d61b7670>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f28d61aeb40>"}, "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": 1676834158394097657, "learning_rate": 0.0001, "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": 0.0, "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"}}