{"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 0x785000f556c0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x785000f55750>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x785000f557e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x785000f55870>", "_build": "<function ActorCriticPolicy._build at 0x785000f55900>", "forward": "<function ActorCriticPolicy.forward at 0x785000f55990>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x785000f55a20>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x785000f55ab0>", "_predict": "<function ActorCriticPolicy._predict at 0x785000f55b40>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x785000f55bd0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x785000f55c60>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x785000f55cf0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x784fa4e45d40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1732614801601482536, "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": 310, "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": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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"}} |