{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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__": "<function ActorCriticPolicy.__init__ at 0x7b6b39ba1750>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b6b39ba17e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b6b39ba1870>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b6b39ba1900>", "_build": "<function ActorCriticPolicy._build at 0x7b6b39ba1990>", "forward": "<function ActorCriticPolicy.forward at 0x7b6b39ba1a20>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b6b39ba1ab0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b6b39ba1b40>", "_predict": "<function ActorCriticPolicy._predict at 0x7b6b39ba1bd0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b6b39ba1c60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b6b39ba1cf0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b6b39ba1d80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b6b39ba8480>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1693634971177827489, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 268, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVcAIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoB4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoECiWCAAAAAAAAAABAQEBAQEBAZRoFEsIhZRoGHSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBAoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaApLCIWUaBh0lFKUjARoaWdolGgQKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgKSwiFlGgYdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "dtype": "float32", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_shape": [8], "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |