{"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 0x7f00f9425360>"}, "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": 1507328, "_total_timesteps": 1500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652044401.5599012, "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": -0.004885333333333408, "ep_info_buffer": {":type:": "", ":serialized:": "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"}, "ep_success_buffer": {":type:": "", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 368, "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"}}