| {"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 0x7e81dcacb7f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e81dcacb880>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e81dcacb910>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e81dcacb9a0>", "_build": "<function ActorCriticPolicy._build at 0x7e81dcacba30>", "forward": "<function ActorCriticPolicy.forward at 0x7e81dcacbac0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e81dcacbb50>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e81dcacbbe0>", "_predict": "<function ActorCriticPolicy._predict at 0x7e81dcacbc70>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e81dcacbd00>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e81dcacbd90>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e81dcacbe20>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e81dca72b00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1705120308169559176, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAALM0Pr2Pvma6QB/1s+B+iK/XJFS7MLGZMwAAgD8AAIA/M0z8vBT8v7pLyFi6oPhFtXgtA7nWenY5AACAPwAAgD8z4Q28uz71PSYFSLxefhG+GxxePLE5A74AAAAAAAAAAGZBBb6rh1w/CkZGPQFMhr4SNPi8/Qd6vQAAAAAAAAAAM7l0vPZ4J7pznG034g1NMm51KjuIUoq2AACAPwAAgD+AgRO9jzZGukbjgz0QPn88tBlduxjpXr0AAIA/AACAP5rJyrv27Ea6ArB3OgCCSTTjupm6giyNuQAAgD8AAIA/GtwjvcMFPLrHrxQ4HhYlMwmSGDvg0Su3AACAPwAAgD+a/8S8w1Fiup42NTlrbaUzLDY4uQ7fULgAAIA/AACAPwB20Dx7BoW6PlHDuwLYkLVjcru6xFoDNQAAgD8AAIA/mjC9vFzjQ7qN3FO5QzaetA0NwjpDJHg4AACAPwAAgD+AS2u9UniYuT7WbjoVOtw0YDnAu+lgj7kAAIA/AACAPxrojb2Fo+y55YTUunxdZ7WeJcO6zpz6OQAAgD8AAIA/ANBOvEgBkro3DYQ60xV+NeDc+zqmFJm5AACAPwAAgD/N+nw8UoCHuVjG7jj3RVwzZ210uoOjAjIAAIA/AACAP5qg1DzsEcy5JLSAOd49w7J5WSo7YFmXuAAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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:": "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-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": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |