| {"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 0x7f4a6566c8b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f4a6566c940>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4a6566c9d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4a6566ca60>", "_build": "<function ActorCriticPolicy._build at 0x7f4a6566caf0>", "forward": "<function ActorCriticPolicy.forward at 0x7f4a6566cb80>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f4a6566cc10>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4a6566cca0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f4a6566cd30>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4a6566cdc0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4a6566ce50>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4a6566cee0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f4a1de22e80>"}, "verbose": 0, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1687082657976280730, "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": 310, "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": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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"}} |