{"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 0x7f785cdb14c0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f785cdb1550>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f785cdb15e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f785cdb1670>", "_build": "<function ActorCriticPolicy._build at 0x7f785cdb1700>", "forward": "<function ActorCriticPolicy.forward at 0x7f785cdb1790>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f785cdb1820>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f785cdb18b0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f785cdb1940>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f785cdb19d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f785cdb1a60>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f785cdb1af0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f785cdad7e0>"}, "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": 1674221418944716884, "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": 0.0, "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"}}