File size: 13,755 Bytes
f69a28a |
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 0x7edc2c5acca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7edc2c5acd30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7edc2c5acdc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7edc2c5ace50>", "_build": "<function ActorCriticPolicy._build at 0x7edc2c5acee0>", "forward": "<function ActorCriticPolicy.forward at 0x7edc2c5acf70>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7edc2c5ad000>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7edc2c5ad090>", "_predict": "<function ActorCriticPolicy._predict at 0x7edc2c5ad120>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7edc2c5ad1b0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7edc2c5ad240>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7edc2c5ad2d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7edc2c542840>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1702176491576197702, "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:": "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-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"}} |