File size: 13,760 Bytes
43635c0 |
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 0x7d033a5deb90>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d033a5dec20>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d033a5decb0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d033a5ded40>", "_build": "<function ActorCriticPolicy._build at 0x7d033a5dedd0>", "forward": "<function ActorCriticPolicy.forward at 0x7d033a5dee60>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d033a5deef0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d033a5def80>", "_predict": "<function ActorCriticPolicy._predict at 0x7d033a5df010>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d033a5df0a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d033a5df130>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d033a5df1c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d033a5e4180>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1713107963535132552, "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": 310, "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, "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:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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"}} |