File size: 13,131 Bytes
ee26451 |
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 0x7c417b641ea0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c417b641f30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c417b641fc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c417b642050>", "_build": "<function ActorCriticPolicy._build at 0x7c417b6420e0>", "forward": "<function ActorCriticPolicy.forward at 0x7c417b642170>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c417b642200>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c417b642290>", "_predict": "<function ActorCriticPolicy._predict at 0x7c417b642320>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c417b6423b0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c417b642440>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c417b6424d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c419a482d40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1718896454771370220, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAA1yT2pvIM/KocLPkvOjb7xSVk9j62uuwAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00044800000000000395, "_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": 3908, "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": 1, "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |