{"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 0x7f859ca33090>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "", ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "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": 1652134496.5962725, "learning_rate": 0.0005, "tensorboard_log": "logs", "lr_schedule": {":type:": "", ":serialized:": "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"}, "_last_obs": {":type:": "", ":serialized:": "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"}, "_last_episode_starts": {":type:": "", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAABAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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"}}