| {"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 0x7c183a3205e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c183a320670>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c183a320700>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c183a320790>", "_build": "<function ActorCriticPolicy._build at 0x7c183a320820>", "forward": "<function ActorCriticPolicy.forward at 0x7c183a3208b0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c183a320940>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c183a3209d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7c183a320a60>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c183a320af0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c183a320b80>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c183a320c10>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c183a4c7440>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1710396085663711355, "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:": "gAWVGAwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQG/1oJZ4fOmMAWyUS/SMAXSUR0CRy0vllsgudX2UKGgGR0Bxqgu01IiDaAdNAgFoCEdAkc3Sa3I+4nV9lChoBkdAceXNiH6/I2gHTS4BaAhHQJHOIRoRIz51fZQoaAZHQHEsGweNkvtoB0v8aAhHQJHOVdiUgSx1fZQoaAZHQHLFhP9DQZ5oB0vkaAhHQJHPJlf7aZh1fZQoaAZHQHEDi2phnapoB00YAWgIR0CR0Wsr/bTMdX2UKGgGR0Bx6f/vOQhfaAdL4WgIR0CR0ZzCUHIIdX2UKGgGR0ByKWAd4mkWaAdNOAFoCEdAkdH3vhIe5nV9lChoBkdAcrIRJ2+wkmgHS+xoCEdAkdIkBbOeKHV9lChoBkdAaRbiPQv6CWgHTVQCaAhHQJHSoc94eLh1fZQoaAZHQHFjusPrfLtoB00tAWgIR0CR1S69kBjndX2UKGgGR0Bx89HmRvFWaAdNGQFoCEdAkdXfKZDzAnV9lChoBkdAciddUKiPAGgHTXMBaAhHQJHXBfVqesh1fZQoaAZHQHDeV2A5JbtoB00oAWgIR0CR12Hn2ZiNdX2UKGgGR0Buf96w+t8vaAdL92gIR0CR16L+glF+dX2UKGgGR0BxBlj6N2kjaAdL42gIR0CR1/CO3lS1dX2UKGgGR0BzF0Fpwjt5aAdNXQFoCEdAkdjJEhJRO3V9lChoBkdAcq6HO8kD6mgHTQ8BaAhHQJHY5J6IFeR1fZQoaAZHQG1emhdt2s9oB00EAWgIR0CR2tPxQSBcdX2UKGgGR0Bu9kL8aXKKaAdL/GgIR0CR2w56MR6GdX2UKGgGR0BwAj6eoUBXaAdNFAFoCEdAkdw8kMTewnV9lChoBkdAcPFvMr3CbmgHTS8BaAhHQJHcslsxfv51fZQoaAZHQHD1elXRw61oB00dAWgIR0CR3S8NhE0BdX2UKGgGR0BPQx/d69kCaAdLq2gIR0CR3iFNtZV5dX2UKGgGR0BwruhEjPfLaAdNCQFoCEdAkeAALmZE2HV9lChoBkdAcAwl9BrvcGgHTSYBaAhHQJHgca72+PB1fZQoaAZHQGW1kwnH/95oB007AmgIR0CR4NHMEA5rdX2UKGgGR0Bwmoy+HrQgaAdNAAFoCEdAkeDQo9cKPXV9lChoBkdAcScDPnjhk2gHS/RoCEdAkeIaPXCj13V9lChoBkdAcJN1/2Cd0GgHTQYBaAhHQJHioWykbgl1fZQoaAZHQG6L4WLxZuBoB009AWgIR0CR48XFLnLadX2UKGgGR0BvcEXDWK/EaAdL9mgIR0CR4//1QIlddX2UKGgGR0BwygwmE5AAaAdL4GgIR0CR5HrsByS3dX2UKGgGR0BxIz20zCUHaAdL9WgIR0CR5ZouwosqdX2UKGgGR0BxByXMQmNSaAdL9WgIR0CR5hNJvo/zdX2UKGgGR0BxnrWuoxYaaAdNLwFoCEdAkeYwsoUi6nV9lChoBkdAcaOiW3Sa3WgHTR0BaAhHQJHoakyk9EF1fZQoaAZHQHHdWR3eN1hoB0vhaAhHQJHo0JF9a2Z1fZQoaAZHQHA1YQrc0tRoB0v2aAhHQJH7+YBvJil1fZQoaAZHQGu6KoQ4CIVoB03yAWgIR0CR/Lin5zo2dX2UKGgGR0BwCQl5WzWxaAdL4mgIR0CR/U9B8hLXdX2UKGgGR0BygNoqTbFkaAdNHwFoCEdAkf5U8Rtgr3V9lChoBkdAXrHGS6lLvmgHTegDaAhHQJH+WUt7KJV1fZQoaAZHQHATYqslsxhoB01NAWgIR0CR/3MCcPOIdX2UKGgGR0BwozGMn7YTaAdL9WgIR0CSADAHmig1dX2UKGgGR0Bxca0UoKD1aAdNFAFoCEdAkgAs3hn8K3V9lChoBkdAcndrJKaodmgHTQ4BaAhHQJIBj2saKk51fZQoaAZHQHG847A+IM1oB0v2aAhHQJIC+ylenht1fZQoaAZHQHGfzuOS4e9oB00QAWgIR0CSA2Aaef7KdX2UKGgGR0ByibsdDIBBaAdNRAFoCEdAkgPy5mRNh3V9lChoBkdAcuWDnNgSe2gHTRQBaAhHQJIEAXpGFzx1fZQoaAZHQHI6dfoicG1oB0vSaAhHQJIEMYyfthN1fZQoaAZHQHAD+a8YhuBoB0viaAhHQJIEXGHYYix1fZQoaAZHQHGbe09hZyNoB0vqaAhHQJIFKu7pV0d1fZQoaAZHQHEV35N47ihoB0vmaAhHQJIF2ya/h2p1fZQoaAZHQFwmy0KJEYxoB03oA2gIR0CSBqUFjd56dX2UKGgGR0BwpdzS1E3LaAdL8GgIR0CSBt46wMYudX2UKGgGR0BxclAjY7JXaAdNJQFoCEdAkgdmcOLBK3V9lChoBkdAc2P9jwx33mgHTRoBaAhHQJIIIKVpsXV1fZQoaAZHQHKuFUQ04zdoB00EAWgIR0CSCDP3BYV7dX2UKGgGR0Bw3rnuAqd6aAdNFgFoCEdAkgk4D5j6N3V9lChoBkdAbsYEOAiFCmgHS/1oCEdAkgqeuA7Pp3V9lChoBkdAch2H5rP+oGgHS/ZoCEdAkgrQ2/BWP3V9lChoBkdAb+kSVW0Z32gHS+FoCEdAkgrPHDJlrnV9lChoBkdAcqnHYpUgjmgHTVoBaAhHQJILdTzd1uB1fZQoaAZHQHKjoXGff41oB0v6aAhHQJILhQpF1CB1fZQoaAZHQHJbhQemvW9oB009AWgIR0CSC4OeJ53UdX2UKGgGR0BwnZgb6xgRaAdL72gIR0CSC52qDK5kdX2UKGgGR0BvrT7hvR7aaAdL72gIR0CSDEbBXS0CdX2UKGgGR0ByU7Bk7OmjaAdNNAFoCEdAkg0iW7e2u3V9lChoBkdAb9zx2B8QZmgHS/doCEdAkg4COinHenV9lChoBkdAcY8/2Cdz4mgHTRwBaAhHQJIOG/7BO591fZQoaAZHQHIyFLSNOudoB00HAWgIR0CSDj3Zwn6VdX2UKGgGR0BtB/Nqxkd4aAdL+WgIR0CSDzdHUc4pdX2UKGgGR0Bwrx61LJ0XaAdNMwFoCEdAkhA59uxbCHV9lChoBkdARpDzyz5XVGgHS9JoCEdAkhCXE/B3zXV9lChoBkdAR0HqxC6YmmgHS6hoCEdAkhD2nwXqJXV9lChoBkdAcLwCLdepoGgHTREBaAhHQJIRB+KCQLh1fZQoaAZHQG+HH5zo2XNoB0v1aAhHQJISanVG0/p1fZQoaAZHQHF2j2i+L3toB00UAWgIR0CSEoELH+6zdX2UKGgGR0BvovBN21UmaAdNFAFoCEdAkhKsxTKkmHV9lChoBkdAcGgguh9LH2gHTQQBaAhHQJIS/XNC7bt1fZQoaAZHQHEAP47A+INoB00OAWgIR0CSEx3mFJxvdX2UKGgGR0ByEfFvQ4S6aAdNiwFoCEdAkhOx/EwWWXV9lChoBkdAcBpp5u63AmgHS/VoCEdAkhRIgzP8h3V9lChoBkdAcjzxA0Kqn2gHTWYBaAhHQJIVtMSK3ux1fZQoaAZHQHNArkXDWLBoB00ZAWgIR0CSFmjnmq5tdX2UKGgGR0BxPa4ZuQ6qaAdNHwFoCEdAkhZ9Dtw71nV9lChoBkdAcUdoRqXWv2gHTSoBaAhHQJIXFc/t6X11fZQoaAZHQG8CcBuGbkRoB00JAWgIR0CSFy/4ZdfLdX2UKGgGR0BunZjlPrOaaAdL7WgIR0CSF1TpPhybdX2UKGgGR0BVPPWpZOi4aAdLs2gIR0CSF/EBsANodX2UKGgGR0BLD0ILPUrkaAdLvmgIR0CSGAbQkX1rdX2UKGgGR0Btm+TibUgCaAdL+2gIR0CSGICe2/i6dX2UKGgGR0BxYb3K0UoKaAdNDwFoCEdAkhizmwJPZnV9lChoBkdAcQhJI1+AmWgHTSYBaAhHQJIZ1ITXarZ1fZQoaAZHQG/Jlz+3pfRoB0vvaAhHQJIaIu+RHPN1fZQoaAZHQHBgCLhrFfloB0vzaAhHQJIaH7zkIX11fZQoaAZHQFVJdd3Sro5oB0u3aAhHQJIbESwnpjd1fZQoaAZHQHEsRe5WilBoB0vtaAhHQJIbRo6CDmN1ZS4="}, "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-6.1.58+-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"}} |