| {"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 0x7cbf10193130>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7cbf101931c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7cbf10193250>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7cbf101932e0>", "_build": "<function ActorCriticPolicy._build at 0x7cbf10193370>", "forward": "<function ActorCriticPolicy.forward at 0x7cbf10193400>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7cbf10193490>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7cbf10193520>", "_predict": "<function ActorCriticPolicy._predict at 0x7cbf101935b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7cbf10193640>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7cbf101936d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7cbf10193760>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7cbeb2754740>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 114688, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1736176362604388149, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAAAZq7y+4rE/YmeHveFkn77O95k9wgOPPQAAAAAAAAAAAKZSPTFGtj817yE/QwCivJZ0jb2GXsO9AAAAAAAAAAAFZw6/ET66PQa3Ob7QsIq/kBPpvo6zpD0AAAAAAAAAALNiVL3rILw/Rf65vvXqWz0clw28v0aevAAAAAAAAAAAmol4vbKXvj+3kAe/rg9iPgRhPj0Df+s6AAAAAAAAAAAe5hM/AV3uPtfmrD53RIe/tewCP41ra7sAAAAAAAAAAM3sQbySL7I/kvwav2be3L4aDoE8fSg3PgAAAAAAAAAAM/WQPF7PtT8RXZY+tF95PQ/44LxGJr+9AAAAAAAAAADmqpI9x2CkPgeRwz0Bs2q/6QvwvKDvED4AAAAAAAAAAPZbxD4h3P0+zIUcP8PXgL/39pM9EHhrPgAAAAAAAAAAzXZ6PN3+Bz/0LhA+HCJ8vxaStT3wffQ9AAAAAAAAAACalNc+tPhoP3z1KT+P+ju/gjIrPmI44T0AAAAAAAAAAM18yDxkb7k/sozbPbZJfL0+xq89NW5jPgAAAAAAAAAA5gTgPYgTwj/UYCg/saB7PbI2vL3mOBK+AAAAAAAAAACz6cg9mr2KP/kawT1MmAy/Y+86Phou8T0AAAAAAAAAAM2FQr3yYh8/th41PtweVb9S6pq+f90DPQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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": -0.1468799999999999, "_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": 28, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.5.1+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.0", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |