| {"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 0x7f0662f0fac0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0662f0fb50>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0662f0fbe0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0662f0fc70>", "_build": "<function ActorCriticPolicy._build at 0x7f0662f0fd00>", "forward": "<function ActorCriticPolicy.forward at 0x7f0662f0fd90>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f0662f0fe20>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0662f0feb0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f0662f0ff40>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0662f1c040>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0662f1c0d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0662f1c160>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f0662eae0c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000.0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1707170844454174337, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAM2ihLxIIYG6rhFqs8TYV6sWTTc7EkPJMwAAgD8AAIA/TUlmPSmMXbr+mdk22eVbMgTMeDuFnfy1AACAPwAAgD+zz8+912I6uxJQcD5wtdG9vOIYuu6Bcr8AAAAAAACAP82UNL1obLw9g6PvPA5zz76iv5I8Cq4/PQAAAAAAAAAA2vSwvXtesbrUA6A3xKm/tKJSQbpQArC2AACAPwAAgD9mDPE9OsgsPkLMzr5pYgS/jsyVvdKAI74AAAAAAAAAADMqvD0h+iU+Fwe1vWwVC7/P/hU9yD3JvAAAAAAAAAAAzbMuvUghn7hO6Au4u3p3s8ZyJzsz9Cc3AACAPwAAgD9Nwl297oPCP4yEqb5kfdI9rF5KvO7eKb0AAAAAAAAAAE12Rr0pJCm6vUjUthyP7rGPgDi7MFr4NQAAgD8AAIA/WkKRPdfaZLsNrlK9TjiXPBow0TwWN4G9AACAPwAAgD/aeqG9j+oouuUVbj33elw8nzE2OzJpQD0AAAAAAACAP0PpbL6D+Fc/J7KhvW0TSL+Rdru+PWzzPAAAAAAAAAAAZkjUPHsukLrLy5M1GsSbMKAexLoWEqy0AACAPwAAgD8aUZ49zJ2VP+hCOT7rAEO/YIKtPaZ2Sz4AAAAAAAAAAE2mIb4FNmE/UPKcvqvKPL/WosO+/qSRvgAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": 1491, "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-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"}} |