File size: 13,769 Bytes
0f95821 |
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 0x7dfa4b1df760>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7dfa4b1df7f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7dfa4b1df880>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7dfa4b1df910>", "_build": "<function ActorCriticPolicy._build at 0x7dfa4b1df9a0>", "forward": "<function ActorCriticPolicy.forward at 0x7dfa4b1dfa30>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7dfa4b1dfac0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7dfa4b1dfb50>", "_predict": "<function ActorCriticPolicy._predict at 0x7dfa4b1dfbe0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7dfa4b1dfc70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7dfa4b1dfd00>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7dfa4b1dfd90>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7dfa4b177c40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1726307959812568073, "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:": "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.4.0+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |