| {"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 0x7d83c62c5bd0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d83c62c5c60>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d83c62c5cf0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d83c62c5d80>", "_build": "<function ActorCriticPolicy._build at 0x7d83c62c5e10>", "forward": "<function ActorCriticPolicy.forward at 0x7d83c62c5ea0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d83c62c5f30>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d83c62c5fc0>", "_predict": "<function ActorCriticPolicy._predict at 0x7d83c62c6050>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d83c62c60e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d83c62c6170>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d83c62c6200>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d83c643b700>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1718987290373738194, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAJo1C72OZ8c91JZMPhnukL7QIz+8KFigPAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00044800000000000395, "_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": 7856, "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": "Generator(PCG64)"}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "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", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 1, "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 Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "False", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |