| {"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 0x789569efcc20>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x789569efccc0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x789569efcd60>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x789569efce00>", "_build": "<function ActorCriticPolicy._build at 0x789569efcea0>", "forward": "<function ActorCriticPolicy.forward at 0x789569efcf40>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x789569efcfe0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x789569efd080>", "_predict": "<function ActorCriticPolicy._predict at 0x789569efd120>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x789569efd1c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x789569efd260>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x789569efd300>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x789569e59100>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1740452030121127591, "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": "3.11.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.5.1+cu124", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |