{"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 0x7f1582a38810>"}, "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": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651731173.9040565, "learning_rate": 0.0003, "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": -0.015808000000000044, "ep_info_buffer": {":type:": "", ":serialized:": "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"}, "ep_success_buffer": {":type:": "", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 124, "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:": "", ":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"}}