File size: 13,630 Bytes
de657b1 |
1 |
{"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 0x78150d02b130>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78150d02b1c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78150d02b250>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78150d02b2e0>", "_build": "<function ActorCriticPolicy._build at 0x78150d02b370>", "forward": "<function ActorCriticPolicy.forward at 0x78150d02b400>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x78150d02b490>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78150d02b520>", "_predict": "<function ActorCriticPolicy._predict at 0x78150d02b5b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78150d02b640>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78150d02b6d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x78150d02b760>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x78150d7a14c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1699002981537132442, "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": 620, "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-5.15.120+-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"}} |