File size: 13,789 Bytes
2065fc8 |
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 0x7b545ed885e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b545ed88670>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b545ed88700>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b545ed88790>", "_build": "<function ActorCriticPolicy._build at 0x7b545ed88820>", "forward": "<function ActorCriticPolicy.forward at 0x7b545ed888b0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b545ed88940>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b545ed889d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7b545ed88a60>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b545ed88af0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b545ed88b80>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b545ed88c10>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b545ed22d80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1713193628768594911, "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:": "gAWVQQwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHFGpQ+EAYKMAWyUTToBjAF0lEdAl2XZtelbeXV9lChoBkdAWcPmEGqxT2gHTegDaAhHQJdokbVBlc11fZQoaAZHQF038YQ8OkNoB03oA2gIR0CXaYpDeCTVdX2UKGgGR0Bxoeg+QlruaAdN3gJoCEdAl2rRxkupTHV9lChoBkdAb5B0Yj0L+mgHTS8BaAhHQJdrqSzPa+N1fZQoaAZHQEQ+M+eOGTNoB0vXaAhHQJdu0qqfe1t1fZQoaAZHQHEVjohY/3ZoB01eAmgIR0CXb0aIvalDdX2UKGgGR0BvyIj+rELqaAdNkgFoCEdAl2+tCNS62HV9lChoBkdAcFm67dznzWgHTWYBaAhHQJdzvxc3VCp1fZQoaAZHQGDxOryUcGVoB03oA2gIR0CXdITfBN21dX2UKGgGR0Byjy7ulXRxaAdNPQJoCEdAl3UDxwyZa3V9lChoBkdAcOWbjtG/e2gHTQsBaAhHQJd2y39aUzN1fZQoaAZHQHCt/su3+ddoB01LAWgIR0CXd1GYrrgPdX2UKGgGR0BaNO63AmAtaAdN6ANoCEdAl3fmMbWEsnV9lChoBkdAcHPtP557gWgHTWcBaAhHQJd5+l1r6+F1fZQoaAZHQHAOH/DLr5ZoB02xAWgIR0CXevDOC5EudX2UKGgGR0Bws8VLzwtraAdNVANoCEdAl3ugkPczqXV9lChoBkdAcFcFId2gWmgHTcMDaAhHQJd9uh6By0d1fZQoaAZHQG6fqAjIJZ5oB01dAWgIR0CXfh33Hq/udX2UKGgGR0BwGl1PnB+GaAdNrwFoCEdAl5kGIGhVVHV9lChoBkdAZ8/tb9qDb2gHTegDaAhHQJeaM51eSjh1fZQoaAZHQHCv2YrrgO1oB03YAmgIR0CXmshjvuw5dX2UKGgGR0ByfWwB5ooNaAdNVQFoCEdAl53d9QXQ+nV9lChoBkdAb63wMpgCwWgHTT0BaAhHQJefm5UcXFd1fZQoaAZHQG/dPEjxCppoB027AWgIR0CXoDymhufmdX2UKGgGR0Bv5lXA/LTyaAdNPwJoCEdAl6BJlnRLK3V9lChoBkdAcbwNzKcNIGgHTUUBaAhHQJehpL127nR1fZQoaAZHQHGP5m7J4jdoB021A2gIR0CXohlV94NadX2UKGgGR0BwOkO5J9RaaAdNLwJoCEdAl6PnTuv2XnV9lChoBkdAcgWNzbN8mmgHTfYBaAhHQJelsTRIBil1fZQoaAZHQHCEtVrAP/doB03LAWgIR0CXprm5UcXFdX2UKGgGR0BylKJbdJrdaAdNSwFoCEdAl6eMIiTt9nV9lChoBkdAb8glqrR0EGgHTTABaAhHQJenm5avA451fZQoaAZHQHF9i9M9KVZoB008AWgIR0CXqJ1UEPlNdX2UKGgGR0BxHnOgQHzIaAdNnAJoCEdAl6lQ88s+V3V9lChoBkdAcZBNkvsZ52gHTUkBaAhHQJer7dj5Kvp1fZQoaAZHQG6XNcOby6NoB00dAWgIR0CXrDPva11GdX2UKGgGR0BsvvWz4UN8aAdNQwFoCEdAl63GOAAhjnV9lChoBkdAcQC4TbnHN2gHTSoBaAhHQJeugRNATqV1fZQoaAZHQG1OLwF1SwZoB01HAmgIR0CXrs8NQTEjdX2UKGgGR0BsPGRV6u4gaAdNmQFoCEdAl7C7Gza9K3V9lChoBkdAbv6gdwNsnGgHTTEBaAhHQJeyN47ihnJ1fZQoaAZHQHBQTZxrBTJoB027AmgIR0CXs01IAfdRdX2UKGgGR0BxUsjVx0dSaAdNZQFoCEdAl7fbKFIuoXV9lChoBkdAcO2lmvnr6mgHTVQBaAhHQJe4krtmcvx1fZQoaAZHQGzxo+nqFAVoB00OAmgIR0CXuiXl8w6AdX2UKGgGR0BzFQeXAuZkaAdNKgFoCEdAl7t54jbBXXV9lChoBkdAYQlrtVrAQGgHTegDaAhHQJe8uNcW0qp1fZQoaAZHQG/4Opjtoi9oB00fAWgIR0CXvUkTHsC1dX2UKGgGR0BqhX+XJHRUaAdN1wFoCEdAl8CrSiM5wXV9lChoBkdAcYj98JD3NGgHTZABaAhHQJfAws3AEdN1fZQoaAZHQHCBW4qgAZNoB00VAWgIR0CXway/sVtXdX2UKGgGR0BxdOdH2AXmaAdNdwFoCEdAl8JbUoa1kXV9lChoBkdAcCarXUYsNGgHTa0CaAhHQJfEQmfGuLd1fZQoaAZHQHL8o9cKPXFoB00AAWgIR0CXxhdgOSW7dX2UKGgGR0ByGsWi1y/9aAdNrQFoCEdAl8aEX+ERJ3V9lChoBkdAca5a8Yht+GgHTXoBaAhHQJfG3QVsUIt1fZQoaAZHQG5HQwCbMHNoB00IAWgIR0CX3qfuTibVdX2UKGgGR0BvlBwZOzppaAdNZwFoCEdAl9+LpaA4GXV9lChoBkdAbMmtVaOghGgHTTUCaAhHQJfgDXqZ+hJ1fZQoaAZHQHB89vGZNPBoB02xAWgIR0CX4lD9wWFfdX2UKGgGR0BuXeZLIxQBaAdNHwFoCEdAl+L69TP0I3V9lChoBkdAcXPADaGpM2gHTZYBaAhHQJfjboouwot1fZQoaAZHQHGi2j4593NoB00vAWgIR0CX5JvCuU2UdX2UKGgGR0BNmvxpcophaAdLz2gIR0CX5kn7HhjwdX2UKGgGR0BxBuGpMpPRaAdNRAFoCEdAl+l7l7tzCHV9lChoBkdAcKAKHwgDBGgHTT0BaAhHQJfshJsfq5d1fZQoaAZHQGH/i9h7VrhoB03oA2gIR0CX7QmMwUQDdX2UKGgGR0BklF2vB7/oaAdN6ANoCEdAl+3vJiiItXV9lChoBkdAbkm8274BWGgHTR8BaAhHQJfu9krf+CN1fZQoaAZHQHBB1SjxkNFoB01BAWgIR0CX7+4nWrfcdX2UKGgGR0BuXuKyfL9uaAdNGwFoCEdAl/EYqwyIpHV9lChoBkdAcO+ALy+YdGgHTQ4BaAhHQJfxwDFId2h1fZQoaAZHQG+jWRq46OpoB000AWgIR0CX8u6dlNDddX2UKGgGR0BwX76BRQ7+aAdNKQFoCEdAl/P8tK7I1nV9lChoBkdAbjnplBhQWWgHTRwBaAhHQJf0rHp8neB1fZQoaAZHQHID0it7rs1oB02lAmgIR0CX9jZmZmZmdX2UKGgGR0BubEYj0L+haAdNFwJoCEdAl/geWrwOOXV9lChoBkdAcbcgr6LwWmgHTWYBaAhHQJf5+LP2PDJ1fZQoaAZHQHNUdmcvugJoB008AWgIR0CX+iTVDrqudX2UKGgGR0Btj9NahYeUaAdNCQFoCEdAl/osoQWepXV9lChoBkdAclgHpKSPl2gHTWUBaAhHQJf8OZAprk91fZQoaAZHQGzLaUiY9gZoB00YAWgIR0CX/W3Q2MsIdX2UKGgGR0BxhcWvbGm2aAdNFwFoCEdAl/6pd4Vym3V9lChoBkdAcDHEaVD8cmgHTUcBaAhHQJf+/o6jnFJ1fZQoaAZHQHBKyNsFdLRoB00MAWgIR0CX//+HJtBOdX2UKGgGR0BkitZvDP4VaAdN6ANoCEdAmAA+Cf6Gg3V9lChoBkdAa2yN5MURF2gHTe8BaAhHQJgC7StvGZN1fZQoaAZHQHJBIOYplSVoB03SAWgIR0CYA5bRF7UodX2UKGgGR0BxPhNXYDkmaAdNHQFoCEdAmAQRo24usnV9lChoBkdAY6rgfEGZ/mgHTegDaAhHQJgFLMqz7dl1fZQoaAZHQHEh8YyfthNoB02eAWgIR0CYB0HU+cH4dX2UKGgGR0A/yVEuxrzoaAdLu2gIR0CYB2T9bX6JdX2UKGgGR0BwgS9oN/e+aAdNEgFoCEdAmAdyzgMtsnV9lChoBkdAcQJ1qWTouGgHTUsBaAhHQJgHxEQXhwV1fZQoaAZHQHKJjF6zE75oB01WAWgIR0CYCCWFev6kdX2UKGgGR0BgIhjBl+VkaAdN6ANoCEdAmAiveUILPXV9lChoBkdAcVvhAGB4EGgHTZEBaAhHQJgKD1yvLYB1fZQoaAZHQHE5RxHXmNloB01VAWgIR0CYCsvpQk5ZdX2UKGgGR0BvdmsaKk2xaAdNOAFoCEdAmAr3/xUedXVlLg=="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 310, "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-6.1.58+-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"}} |