| {"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 0x7ed458bf6050>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ed458bf60e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ed458bf6170>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ed458bf6200>", "_build": "<function ActorCriticPolicy._build at 0x7ed458bf6290>", "forward": "<function ActorCriticPolicy.forward at 0x7ed458bf6320>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ed458bf63b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ed458bf6440>", "_predict": "<function ActorCriticPolicy._predict at 0x7ed458bf64d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ed458bf6560>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ed458bf65f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ed458bf6680>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ed458b9e940>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 2015232, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1728415087694214247, "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": -0.007616000000000067, "_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": 764, "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": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.4.1+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |