File size: 13,698 Bytes
080b39c |
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 0x7a8db0b20dc0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a8db0b20e50>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a8db0b20ee0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a8db0b20f70>", "_build": "<function ActorCriticPolicy._build at 0x7a8db0b21000>", "forward": "<function ActorCriticPolicy.forward at 0x7a8db0b21090>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a8db0b21120>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a8db0b211b0>", "_predict": "<function ActorCriticPolicy._predict at 0x7a8db0b21240>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a8db0b212d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a8db0b21360>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a8db0b213f0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7a8db9ad0c00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1689561347436035841, "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": 256, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVcAIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoB4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoECiWCAAAAAAAAAABAQEBAQEBAZRoFEsIhZRoGHSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBAoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaApLCIWUaBh0lFKUjARoaWdolGgQKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgKSwiFlGgYdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "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-5.15.109+-x86_64-with-glibc2.31 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |