| {"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 0x7a478024ea70>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a478024eb00>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a478024eb90>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a478024ec20>", "_build": "<function ActorCriticPolicy._build at 0x7a478024ecb0>", "forward": "<function ActorCriticPolicy.forward at 0x7a478024ed40>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a478024edd0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a478024ee60>", "_predict": "<function ActorCriticPolicy._predict at 0x7a478024eef0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a478024ef80>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a478024f010>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a478024f0a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7a47801f51c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1714963390958817150, "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": 248, "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-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |