{"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 0x7f185d8cbe50>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f185d8cbee0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f185d8cbf70>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f185d8d1040>", "_build": "<function ActorCriticPolicy._build at 0x7f185d8d10d0>", "forward": "<function ActorCriticPolicy.forward at 0x7f185d8d1160>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f185d8d11f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f185d8d1280>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f185d8d1310>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f185d8d13a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f185d8d1430>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f185d8ca3c0>"}, "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": 32, "num_timesteps": 5046272, "_total_timesteps": 5000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1671132696106443888, "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:": "gAWVkwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksghZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.009254400000000107, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 308, "n_steps": 2048, "gamma": 0.999, "gae_lambda": 0.99, "ent_coef": 0.009, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 128, "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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}