{"policy_class": {":type:": "", ":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__": "", "_get_constructor_parameters": "", "reset_noise": "", "_build_mlp_extractor": "", "_build": "", "forward": "", "_get_action_dist_from_latent": "", "_predict": "", "evaluate_actions": "", "get_distribution": "", "predict_values": "", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fca0eeba2a0>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "", ":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:": "", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 9011200, "_total_timesteps": 9000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652208115.7804134, "learning_rate": 0.003, "tensorboard_log": null, "lr_schedule": {":type:": "", ":serialized:": "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"}, "_last_obs": {":type:": "", ":serialized:": "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"}, "_last_episode_starts": {":type:": "", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0012444444444443814, "ep_info_buffer": {":type:": "", ":serialized:": "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"}, "ep_success_buffer": {":type:": "", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 2200, "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": 32, "n_epochs": 4, "clip_range": {":type:": "", ":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": "False", "Numpy": "1.21.6", "Gym": "0.21.0"}}