{"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 0x7fcf4a2557a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcf4a255830>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fcf4a2558c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fcf4a255950>", "_build": "<function ActorCriticPolicy._build at 0x7fcf4a2559e0>", "forward": "<function ActorCriticPolicy.forward at 0x7fcf4a255a70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fcf4a255b00>", "_predict": "<function ActorCriticPolicy._predict at 0x7fcf4a255b90>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fcf4a255c20>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fcf4a255cb0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fcf4a255d40>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fcf4a2b0090>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":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:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 3014656, "_total_timesteps": 3000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651849346.802499, "learning_rate": 0.0003, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.004885333333333408, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 1156, "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": 4, "clip_range": {":type:": "<class 'function'>", ":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"}}