| {"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 0x7c32f69a87c0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c32f69a8860>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c32f69a8900>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c32f69a89a0>", "_build": "<function ActorCriticPolicy._build at 0x7c32f69a8a40>", "forward": "<function ActorCriticPolicy.forward at 0x7c32f69a8ae0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c32f69a8b80>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c32f69a8c20>", "_predict": "<function ActorCriticPolicy._predict at 0x7c32f69a8cc0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c32f69a8d60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c32f69a8e00>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c32f69a8ea0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c32f6900500>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1507328, "_total_timesteps": 1500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1741777760246610082, "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": -0.004885333333333408, "_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": 368, "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"}} |