{"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 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__": "<function ActorCriticPolicy.__init__ at 0x7f3622a4d5e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3622a4d670>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f3622a4d700>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f3622a4d790>", "_build": "<function ActorCriticPolicy._build at 0x7f3622a4d820>", "forward": "<function ActorCriticPolicy.forward at 0x7f3622a4d8b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f3622a4d940>", "_predict": "<function ActorCriticPolicy._predict at 0x7f3622a4d9d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f3622a4da60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f3622a4daf0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f3622a4db80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f3622a4e580>"}, "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": 1660582118.0504842, "learning_rate": 0.00096, "tensorboard_log": "./tensorboard", "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-5.4.0-122-generic-x86_64-with-glibc2.31 #138-Ubuntu SMP Wed Jun 22 15:00:31 UTC 2022", "Python": "3.9.12", "Stable-Baselines3": "1.5.1a8", "PyTorch": "1.12.1+cu102", "GPU Enabled": "False", "Numpy": "1.21.2", "Gym": "0.21.0"}}