File size: 13,697 Bytes
c7d1365 |
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 0x7a184398bb50>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a184398bbe0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a184398bc70>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a184398bd00>", "_build": "<function ActorCriticPolicy._build at 0x7a184398bd90>", "forward": "<function ActorCriticPolicy.forward at 0x7a184398be20>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a184398beb0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a184398bf40>", "_predict": "<function ActorCriticPolicy._predict at 0x7a184398c040>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a184398c0d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a184398c160>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a184398c1f0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7a184392e140>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1507328, "_total_timesteps": 1500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1727377270578873546, "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": -0.004885333333333408, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWV/gsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQG07JtSAH3WMAWyUS8yMAXSUR0CbCTGcWj46dX2UKGgGR0BRH6fe1rqMaAdLmmgIR0CbCTWHDaXbdX2UKGgGR0BwTfkzXSSeaAdL3mgIR0CbCUsGxD9gdX2UKGgGR0Byr/B7/n4gaAdL/WgIR0CbCVFpwjt5dX2UKGgGR0Byxz4i5d4WaAdLvGgIR0CbCq7ZnL7odX2UKGgGR0BcNDtPYWcjaAdN6ANoCEdAmwq7SiM5wXV9lChoBkdAczkpXIU8FWgHS/VoCEdAmwsvTgEU03V9lChoBkdAcIHzGxUvPGgHS+9oCEdAmws/8IiTuHV9lChoBkdAc9QdaMaS92gHS+5oCEdAmwtKmXPZ7HV9lChoBkdAcg/w4bS7XmgHTQUBaAhHQJsLWwmmce91fZQoaAZHQHH84BNmDlJoB01HAWgIR0CbC5CNCJGfdX2UKGgGR0BuUg1zhgmaaAdL+2gIR0CbDIWIGhVVdX2UKGgGR0ByS5Bsyi22aAdL4mgIR0CbDIMr3CbddX2UKGgGR0Bwq1kXk5p8aAdL9GgIR0CbDNlA/s3RdX2UKGgGR0Bu2HCIk7fYaAdL/mgIR0CbDYpLmITHdX2UKGgGR0Bx1IG0NSZSaAdLz2gIR0CbDiQ4jrzHdX2UKGgGR0BwjKyE+PilaAdL2WgIR0CbDnQD3dsSdX2UKGgGR0Byi6aJAMUiaAdL72gIR0CbDrnMt9QXdX2UKGgGR0BxCsG1QZXNaAdL92gIR0CbDwz/ZM+NdX2UKGgGR0Bxvl4mkWRBaAdNAAFoCEdAmw9avmoze3V9lChoBkdAcWt/Z/Tb4GgHS/toCEdAmxB0t/WlM3V9lChoBkdAc44sS00FbGgHS+toCEdAmxC1UADJVHV9lChoBkdAcSuvt+kP+WgHS/xoCEdAmxER/y5I6XV9lChoBkdAcuyqgyuZC2gHTQIBaAhHQJsRKLbYbsF1fZQoaAZHQHAiNwNsnAtoB00VAWgIR0CbETKmKqGUdX2UKGgGR0Bx+qbe/Ho6aAdNDAFoCEdAmxF4VuaWonV9lChoBkdAcb02mpEQXmgHTQoBaAhHQJsRtpRGc4J1fZQoaAZHQHHXBhlUZNxoB0vZaAhHQJsR8OJ+Dvp1fZQoaAZHQHF1azJIUahoB0vpaAhHQJsR+yKNyYJ1fZQoaAZHQHC+1RgqmTFoB00BAWgIR0CbEnPlMh5gdX2UKGgGR0Bwl+Bz3h4uaAdL7mgIR0CbEvlXiiqRdX2UKGgGR0Bx04PtlZoxaAdL1WgIR0CbE0n8sMAndX2UKGgGR0By4AO09hZyaAdL2mgIR0CbFEmT1TR6dX2UKGgGR0BxvS0fHPu5aAdNCAFoCEdAmxS6HKwIMXV9lChoBkdAcJn45cTrV2gHTQcBaAhHQJsVELPUrkN1fZQoaAZHQHKEigoPTXtoB0vbaAhHQJss2iVSn+B1fZQoaAZHQHJbzpX6qKhoB01PAWgIR0CbLXCih37ldX2UKGgGR0BwfkfDDTBqaAdLzWgIR0CbLiR0lqrSdX2UKGgGR0Bvt47A+IM0aAdL6mgIR0CbLlkoF3Y+dX2UKGgGR0BvR41ejVQRaAdL72gIR0CbLlpMpPRBdX2UKGgGR0BwqDqKP4mDaAdL9GgIR0CbLpzTWoWIdX2UKGgGR0BzMDeTFERbaAdL+mgIR0CbLzftx+8XdX2UKGgGR0Bw9zCP6sQvaAdL1GgIR0CbL2m+j/ModX2UKGgGR0Bx+0Qe3hGZaAdNBwFoCEdAmzADQqqfe3V9lChoBkdAcwvRtgrpaGgHTT8BaAhHQJswEBFNL151fZQoaAZHQHEHX1BdD6ZoB0vqaAhHQJswxqh11W91fZQoaAZHQHFkAc94eLhoB00DAWgIR0CbMP5imVJMdX2UKGgGR0BzAuHM2WIHaAdNWAFoCEdAmzHJ40Mw13V9lChoBkdAb/fNC7btZ2gHS/ZoCEdAmzIjSThYNnV9lChoBkdATrzG1hLGrGgHS7doCEdAmzIphOP/73V9lChoBkdAcNmKbKA8S2gHS+JoCEdAmzLFopQUH3V9lChoBkdAcimv+OwPiGgHS81oCEdAmzNL2YfGMnV9lChoBkdAcspigkC3gGgHTRgBaAhHQJszZNBWxQl1fZQoaAZHQHCFM8TzundoB00TAWgIR0CbM5fdyksSdX2UKGgGR0BvGVOfukULaAdL5WgIR0CbNAv0AcT8dX2UKGgGR0ByI3ZmI0qIaAdL1GgIR0CbNB1k1/DtdX2UKGgGR0BwkvA0sOG1aAdLzGgIR0CbNCO938oAdX2UKGgGR0By0TkHUtqYaAdNBgFoCEdAmzRvN7jT8nV9lChoBkdAbyv+pfhMrWgHTQgBaAhHQJs0l5s0pEx1fZQoaAZHQG/Lur6tT1loB0veaAhHQJs1D6xgRbt1fZQoaAZHQHD7GD6Fds1oB0vlaAhHQJs2RT/ACXB1fZQoaAZHQHIvIczZYgdoB00FAWgIR0CbNs3IdU83dX2UKGgGR0BwWg6Kcd5qaAdL4GgIR0CbNvu/1xsEdX2UKGgGR0BzCEqAjIJaaAdL4mgIR0CbN1pz90ihdX2UKGgGR0BDcQw9JSR9aAdLj2gIR0CbN1oX9BKMdX2UKGgGR0BNNMOG0u14aAdLtGgIR0CbN2Mj/uLKdX2UKGgGR0BwJfLOiWVvaAdL9mgIR0CbN8pGFzuGdX2UKGgGR0Bw/pxm03OwaAdL5WgIR0CbOAQxesxPdX2UKGgGR0BwFI8vEjxDaAdL+GgIR0CbORKJVKf4dX2UKGgGR0BydZ7F85S4aAdL22gIR0CbOYsXzlLfdX2UKGgGR0Bwfe3UhFEzaAdL9GgIR0CbOdMw1zhhdX2UKGgGR0BujN/tpmEoaAdL42gIR0CbOfbaRISUdX2UKGgGR0BxTvZyuIRAaAdL4WgIR0CbOoRZlnRLdX2UKGgGR0ByAS/pMYdiaAdNNQFoCEdAmzrboOhCdHV9lChoBkdAcVWDO1OTJWgHS91oCEdAmzxsrupjt3V9lChoBkdAcsCXDWK/EmgHTQIBaAhHQJs8oHgP3BZ1fZQoaAZHQHF3Yna37UJoB0vgaAhHQJs871/Ue+51fZQoaAZHQHIH1LOAy2xoB0vnaAhHQJs9KMS9M9N1fZQoaAZHQG3QBt1p0wJoB00UAWgIR0CbPbe0ojOcdX2UKGgGR0ByzwPUaybAaAdNDQFoCEdAmz4m1c+qznV9lChoBkdAbgvV81Gb1GgHTQQBaAhHQJs+dkvsZ511fZQoaAZHQHGyjeTFERdoB0vQaAhHQJs+g1KoQ4F1fZQoaAZHQHJX3OKO1fFoB0v9aAhHQJs+iax5cC51fZQoaAZHQHEi7RnezldoB0vnaAhHQJs/fNbC79R1fZQoaAZHQHCHfxUedTZoB0vuaAhHQJs/7fVI7Nl1fZQoaAZHQHHTRBqsU7FoB0vnaAhHQJtAZe7cwg11fZQoaAZHQHKSs3yZrpJoB00CAWgIR0CbQIotcv/SdX2UKGgGR0BwjyMVDa4+aAdL4WgIR0CbQJoQWepXdX2UKGgGR0ByLJIbwSamaAdLw2gIR0CbQglTFVDKdX2UKGgGR0BwiO0E5hjOaAdL32gIR0CbQpj/dZaFdX2UKGgGR0Byqc1FYuCgaAdL8mgIR0CbQs8uSOindX2UKGgGR0BuvkZBLPD6aAdL42gIR0CbQ3sSkCV9dX2UKGgGR0BxR910T101aAdL42gIR0CbRD7NjbztdX2UKGgGR0ByFEQHzH0caAdL82gIR0CbRLu0TlDGdX2UKGgGR0BzJaOlwcYJaAdNRQFoCEdAm0TlnEl3QnV9lChoBkdAc4CvZyuIRGgHTRIBaAhHQJtFQTJyQxN1fZQoaAZHQHJbscMmWt5oB00SAWgIR0CbRYk0rK/3dX2UKGgGR0Buj3qNZNfxaAdL6WgIR0CbRhH+qBEsdX2UKGgGR0BwUZivxH5KaAdL22gIR0CbRjgOBlMAdX2UKGgGR0BxiTc2zfJnaAdL4GgIR0CbRpZZ0SyudWUu"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 460, "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": 5, "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": "2.4.1+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |