| {"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 0x7f072284da20>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f072284dab0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f072284db40>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f072284dbd0>", "_build": "<function ActorCriticPolicy._build at 0x7f072284dc60>", "forward": "<function ActorCriticPolicy.forward at 0x7f072284dcf0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f072284dd80>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f072284de10>", "_predict": "<function ActorCriticPolicy._predict at 0x7f072284dea0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f072284df30>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f072284dfc0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f072284e050>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f0722854980>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 2113536, "_total_timesteps": 2100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1686793201850251364, "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": -0.006445714285714388, "_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": 776, "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "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-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |