| {"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 0x78b8c9139750>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78b8c91397e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78b8c9139870>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78b8c9139900>", "_build": "<function ActorCriticPolicy._build at 0x78b8c9139990>", "forward": "<function ActorCriticPolicy.forward at 0x78b8c9139a20>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x78b8c9139ab0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78b8c9139b40>", "_predict": "<function ActorCriticPolicy._predict at 0x78b8c9139bd0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78b8c9139c60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78b8c9139cf0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x78b8c9139d80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x78b8c90dc880>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1724161945210610862, "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:": "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": "2.3.1+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |