{"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 0x7f394c142570>"}, "verbose": true, "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": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652546156.3737378, "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": 248, "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"}}