| {"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 0x7c2be9816320>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c2be98163b0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c2be9816440>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c2be98164d0>", "_build": "<function ActorCriticPolicy._build at 0x7c2be9816560>", "forward": "<function ActorCriticPolicy.forward at 0x7c2be98165f0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c2be9816680>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c2be9816710>", "_predict": "<function ActorCriticPolicy._predict at 0x7c2be98167a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c2be9816830>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c2be98168c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c2be9816950>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c2c4b074ec0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1001472, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1698049881900108783, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAADPZTD1cY2m6MSoLO3sMMDcpK5w6e5HeNQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": -0.0014719999999999178, "_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": 1956, "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": 1, "n_steps": 2048, "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-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |