| {"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 0x7e1fcdefb560>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e1fcdefb600>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e1fcdefb6a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e1fcdefb740>", "_build": "<function ActorCriticPolicy._build at 0x7e1fcdefb7e0>", "forward": "<function ActorCriticPolicy.forward at 0x7e1fcdefb880>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e1fcdefb920>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e1fcdefb9c0>", "_predict": "<function ActorCriticPolicy._predict at 0x7e1fcdefba60>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e1fcdefbb00>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e1fcdefbba0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e1fcdefbc40>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e1fcde5b140>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000.0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1741986168700758569, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": null, "_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:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "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": "3.11.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |