File size: 13,767 Bytes
a1a5bb6 |
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 0x78bad9604430>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78bad96044c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78bad9604550>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78bad96045e0>", "_build": "<function ActorCriticPolicy._build at 0x78bad9604670>", "forward": "<function ActorCriticPolicy.forward at 0x78bad9604700>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x78bad9604790>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78bad9604820>", "_predict": "<function ActorCriticPolicy._predict at 0x78bad96048b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78bad9604940>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78bad96049d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x78bad9604a60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x78bad9f1a580>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1715021365647988999, "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": 424, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "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": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |