| {"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 0x7b8f6afd2a70>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b8f6afd2b00>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b8f6afd2b90>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b8f6afd2c20>", "_build": "<function ActorCriticPolicy._build at 0x7b8f6afd2cb0>", "forward": "<function ActorCriticPolicy.forward at 0x7b8f6afd2d40>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b8f6afd2dd0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b8f6afd2e60>", "_predict": "<function ActorCriticPolicy._predict at 0x7b8f6afd2ef0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b8f6afd2f80>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b8f6afd3010>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b8f6afd30a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b8f6af77640>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1702094446153350283, "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": 248, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "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-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |