File size: 16,798 Bytes
19e8f71 |
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 0x7f05f17a0700>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f05f17a0790>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f05f17a0820>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f05f17a08b0>", "_build": "<function ActorCriticPolicy._build at 0x7f05f17a0940>", "forward": "<function ActorCriticPolicy.forward at 0x7f05f17a09d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f05f17a0a60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f05f17a0af0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f05f17a0b80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f05f17a0c10>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f05f17a0ca0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f05f17a0d30>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f05f17a2a40>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [24], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False False False]", "bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVdwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLBIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAIC/AACAvwAAgL8AAIC/lGgKSwSFlIwBQ5R0lFKUjARoaWdolGgSKJYQAAAAAAAAAAAAgD8AAIA/AACAPwAAgD+UaApLBIWUaBV0lFKUjA1ib3VuZGVkX2JlbG93lGgSKJYEAAAAAAAAAAEBAQGUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLBIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYEAAAAAAAAAAEBAQGUaCFLBIWUaBV0lFKUjApfbnBfcmFuZG9tlE51Yi4=", "dtype": "float32", "_shape": [4], "low": "[-1. -1. -1. -1.]", "high": "[1. 1. 1. 1.]", "bounded_below": "[ True True True True]", "bounded_above": "[ True True True True]", "_np_random": null}, "n_envs": 16, "num_timesteps": 1507328, "_total_timesteps": 1500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1677472715940249147, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVfRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBvTCnQtWVUCUhpRSlIwBbJRNQAaMAXSUR0CLdvRNyo4udX2UKGgGaAloD0MIak3zjlMLU0CUhpRSlGgVTUAGaBZHQIuFXFm4Ajp1fZQoaAZoCWgPQwieKXReY6hRQJSGlFKUaBVNQAZoFkdAi4h8+RoysXV9lChoBmgJaA9DCLtjsU0qDlJAlIaUUpRoFU1ABmgWR0CLkgDfWMCLdX2UKGgGaAloD0MIyHvVyoRXRECUhpRSlGgVTUAGaBZHQIujc85jpcJ1fZQoaAZoCWgPQwh0t+ulKUdTQJSGlFKUaBVNQAZoFkdAi6TkPDpC8nV9lChoBmgJaA9DCJOKxtrf5lXAlIaUUpRoFU0uAWgWR0CLqIMBIWgwdX2UKGgGaAloD0MIovDZOji0UUCUhpRSlGgVTUAGaBZHQIuq9psXSBt1fZQoaAZoCWgPQwjZBu5AnfRJwJSGlFKUaBVNlANoFkdAi6zfe1rqMXV9lChoBmgJaA9DCPhtiPGacFNAlIaUUpRoFU1ABmgWR0CLriPH1e0HdX2UKGgGaAloD0MI41C/C1tWVECUhpRSlGgVTUAGaBZHQIvCnMY/FBJ1fZQoaAZoCWgPQwglWYejqxlXQJSGlFKUaBVNQAZoFkdAi9PceCCjDnV9lChoBmgJaA9DCHPWpxyTn0tAlIaUUpRoFU1ABmgWR0CL2WFW4mTldX2UKGgGaAloD0MIt5kK8UheTkCUhpRSlGgVTUAGaBZHQIvmddJJ5FB1fZQoaAZoCWgPQwjayeAoeTNQQJSGlFKUaBVNQAZoFkdAi+o6vA44qHV9lChoBmgJaA9DCFBUNqypq1BAlIaUUpRoFU1ABmgWR0CL79xsEaESdX2UKGgGaAloD0MIDCB8KNG+T8CUhpRSlGgVTYQDaBZHQIvwABNmDlJ1fZQoaAZoCWgPQwiZKELqdvNTQJSGlFKUaBVNQAZoFkdAi/GLP+n623V9lChoBmgJaA9DCGQFvw0xJlNAlIaUUpRoFU1ABmgWR0CL9quanaWYdX2UKGgGaAloD0MIvrwA++hhWsCUhpRSlGgVS4hoFkdAi/mp+DvmYHV9lChoBmgJaA9DCNukorH2TUpAlIaUUpRoFU1ABmgWR0CMBSjopx3ndX2UKGgGaAloD0MIZoLhXMNuRcCUhpRSlGgVTXkEaBZHQIwF0hzNliB1fZQoaAZoCWgPQwhVE0TdBxZUQJSGlFKUaBVNQAZoFkdAjAfmR/3Fk3V9lChoBmgJaA9DCCB9k6ZBV13AlIaUUpRoFUs7aBZHQIwJ+VgQYk51fZQoaAZoCWgPQwhYrOEi91tUwJSGlFKUaBVNzQJoFkdAjBTZdGAkLXV9lChoBmgJaA9DCPWc9L7xIFTAlIaUUpRoFU0WAmgWR0CMH7iTdLxqdX2UKGgGaAloD0MIXW4w1GE3RUCUhpRSlGgVTUAGaBZHQIwo8EzO5ax1fZQoaAZoCWgPQwi9VkJ3SXNRQJSGlFKUaBVNQAZoFkdAjDGgFX7tRnV9lChoBmgJaA9DCAd96e3P/U5AlIaUUpRoFU1ABmgWR0CMM86tknTidX2UKGgGaAloD0MIbjKqDOMgUUCUhpRSlGgVTUAGaBZHQIw1LnA6+391fZQoaAZoCWgPQwj0bFZ9rk1WQJSGlFKUaBVNQAZoFkdAjEBCI+GGmHV9lChoBmgJaA9DCIS9iSE55lVAlIaUUpRoFU1ABmgWR0CMT2/Vy3kQdX2UKGgGaAloD0MIN6eSAaBwVkCUhpRSlGgVTUAGaBZHQIxpYr6LwWp1fZQoaAZoCWgPQwiSJXMs7z5OQJSGlFKUaBVNQAZoFkdAjGyzJp35e3V9lChoBmgJaA9DCMx6MZQT5VDAlIaUUpRoFU1XA2gWR0CMbe6Gxlg/dX2UKGgGaAloD0MIEw69xcM/VECUhpRSlGgVTUAGaBZHQIxyMwnH/951fZQoaAZoCWgPQwj+DG/W4PtPQJSGlFKUaBVNQAZoFkdAjHhiaRZED3V9lChoBmgJaA9DCLvRx3xAZExAlIaUUpRoFU1ABmgWR0CMe1pZfUnYdX2UKGgGaAloD0MIE0n0MoomUkCUhpRSlGgVTUAGaBZHQIyGRp1zQu51fZQoaAZoCWgPQwgteNFXkHRPQJSGlFKUaBVNQAZoFkdAjIjoWgvlEXV9lChoBmgJaA9DCK9bBMb6+VFAlIaUUpRoFU1ABmgWR0CMiu08eS0TdX2UKGgGaAloD0MIgXozar5qUUCUhpRSlGgVTUAGaBZHQIyOMX3xnWd1fZQoaAZoCWgPQwjTFtf4TFhKQJSGlFKUaBVNQAZoFkdAjJj3974SH3V9lChoBmgJaA9DCCC3Xz5ZIVHAlIaUUpRoFU01A2gWR0CMo4FDfFaTdX2UKGgGaAloD0MIVrYPecuiVECUhpRSlGgVTUAGaBZHQIyrDLQokRl1fZQoaAZoCWgPQwizlZf8T3BOQJSGlFKUaBVNQAZoFkdAjK1xeLNwBHV9lChoBmgJaA9DCDV+4ZUkOU5AlIaUUpRoFU1ABmgWR0CMuLzFuNxVdX2UKGgGaAloD0MIuTR+4ZWETkCUhpRSlGgVTUAGaBZHQIzDVqN6w+t1fZQoaAZoCWgPQwiLxAQ1fGZQQJSGlFKUaBVNQAZoFkdAjNJuNgjQiXV9lChoBmgJaA9DCNrJ4Ch5LVBAlIaUUpRoFU1ABmgWR0CM6J6Q/5ckdX2UKGgGaAloD0MI38K68e7QTkCUhpRSlGgVTUAGaBZHQIzpo9mpVCJ1fZQoaAZoCWgPQwh0JQLVP3xVQJSGlFKUaBVNQAZoFkdAjO2vddmg8XV9lChoBmgJaA9DCNx++WTFHExAlIaUUpRoFU1ABmgWR0CM86YWtU4rdX2UKGgGaAloD0MIuRyvQPSeUECUhpRSlGgVTUAGaBZHQIz2l3MY/FB1fZQoaAZoCWgPQwitad5xir1bwJSGlFKUaBVLL2gWR0CM+Y6BAfMfdX2UKGgGaAloD0MI+itkrgwFUkCUhpRSlGgVTUAGaBZHQI0IaR+z+m51fZQoaAZoCWgPQwi858ByhP5IQJSGlFKUaBVNQAZoFkdAjQso/Z/Tb3V9lChoBmgJaA9DCD19BP7wCFFAlIaUUpRoFU1ABmgWR0CNDXgsK9f1dX2UKGgGaAloD0MIRKhSsweQUUCUhpRSlGgVTUAGaBZHQI0Qanzg/C91fZQoaAZoCWgPQwieRIR/EWpCQJSGlFKUaBVNQAZoFkdAjRr0PYnOSnV9lChoBmgJaA9DCGe1wB4THUlAlIaUUpRoFU1ABmgWR0CNJmZIg/1QdX2UKGgGaAloD0MIzmxX6IOpTkCUhpRSlGgVTUAGaBZHQI0uRvkzXSV1fZQoaAZoCWgPQwj4w89/D2dQQJSGlFKUaBVNQAZoFkdAjTDDxLCemXV9lChoBmgJaA9DCAYwZeCAdlNAlIaUUpRoFU1ABmgWR0CNMkRjjJdTdX2UKGgGaAloD0MIgLdAguJnT0CUhpRSlGgVTUAGaBZHQI09Ee0Xxe91fZQoaAZoCWgPQwhuwOeHETI5QJSGlFKUaBVNQAZoFkdAjUwvYnOSn3V9lChoBmgJaA9DCP5kjA+zUVBAlIaUUpRoFU1ABmgWR0CNa+6STyJ9dX2UKGgGaAloD0MI9nmM8syFSECUhpRSlGgVTUAGaBZHQI1tBUvPC2t1fZQoaAZoCWgPQwiJJlDEIiRWQJSGlFKUaBVNQAZoFkdAjXEK7iADrHV9lChoBmgJaA9DCDlf7L348EtAlIaUUpRoFU1ABmgWR0CNd5KpT/ACdX2UKGgGaAloD0MIEjC6vDksSUCUhpRSlGgVTUAGaBZHQI1/ACp3os91fZQoaAZoCWgPQwioHJPF/eZQQJSGlFKUaBVNQAZoFkdAjYgVschkiHV9lChoBmgJaA9DCOC593DJGlFAlIaUUpRoFU1ABmgWR0CNiz3BYV7AdX2UKGgGaAloD0MI6BN5knR3UUCUhpRSlGgVTUAGaBZHQI2N6Jyhi9Z1fZQoaAZoCWgPQwjOpiOAmy5QQJSGlFKUaBVNQAZoFkdAjZFnuRcNY3V9lChoBmgJaA9DCGy0HOihlk1AlIaUUpRoFU1ABmgWR0CNnbQ9A5aNdX2UKGgGaAloD0MI+8xZn3K+U0CUhpRSlGgVTUAGaBZHQI2u47V8Ti91fZQoaAZoCWgPQwhjsyPVdzFTQJSGlFKUaBVNQAZoFkdAjbW2PtD2J3V9lChoBmgJaA9DCALWql0TLk1AlIaUUpRoFU1ABmgWR0CNt+kj5bhWdX2UKGgGaAloD0MIumsJ+aD9TkCUhpRSlGgVTUAGaBZHQI25PAfuCwt1fZQoaAZoCWgPQwgFTyFX6t1PQJSGlFKUaBVNQAZoFkdAjcWnXVbzLHV9lChoBmgJaA9DCCo5J/bQWVFAlIaUUpRoFU1ABmgWR0CN1likO7QLdX2UKGgGaAloD0MI0clS6/3kTsCUhpRSlGgVTYYDaBZHQI3ZybWmP5p1fZQoaAZoCWgPQwioHJPF/dZYwJSGlFKUaBVLcGgWR0CN4ZaufVZtdX2UKGgGaAloD0MIXFSLiGKOTUCUhpRSlGgVTUAGaBZHQI3rAhStNi91fZQoaAZoCWgPQwhIpkOn53dXQJSGlFKUaBVNQAZoFkdAjev6kAPuonV9lChoBmgJaA9DCJVjsrj/mk5AlIaUUpRoFU1ABmgWR0CN76qoZQ54dX2UKGgGaAloD0MIOL72zJL0U0CUhpRSlGgVTUAGaBZHQI310QPI4l11fZQoaAZoCWgPQwgDzefc7atTQJSGlFKUaBVNQAZoFkdAjgcyde6ZpnV9lChoBmgJaA9DCFzHuOLiWFLAlIaUUpRoFU1NA2gWR0COCxk1/DtPdX2UKGgGaAloD0MIs/D1tS4CUkCUhpRSlGgVTUAGaBZHQI4QKtHQQcx1fZQoaAZoCWgPQwg98gcDz6NOQJSGlFKUaBVNQAZoFkdAjhLvkBCD3HV9lChoBmgJaA9DCB9N9WT+QlJAlIaUUpRoFU1ABmgWR0COF+fV7Qb/dX2UKGgGaAloD0MI09heC3p4VcCUhpRSlGgVTcsBaBZHQI4h821lXil1fZQoaAZoCWgPQwiH3XcMj6xSQJSGlFKUaBVNQAZoFkdAjiIqpDNQj3V9lChoBmgJaA9DCObpXFFKjFBAlIaUUpRoFU1ABmgWR0COK8xUNrj6dX2UKGgGaAloD0MImGvRArTQU0CUhpRSlGgVTUAGaBZHQI4yOcBltj11fZQoaAZoCWgPQwhEMXkDzEJSQJSGlFKUaBVNQAZoFkdAjjRFu3trsXV9lChoBmgJaA9DCIMT0a+thlZAlIaUUpRoFU1ABmgWR0CONbdweeWfdX2UKGgGaAloD0MIMZqV7UO6VcCUhpRSlGgVTUABaBZHQI5LNVea8Yh1ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 368, "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": 512, "n_epochs": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.4.0-122-generic-x86_64-with-glibc2.31 # 138~18.04.1-Ubuntu SMP Fri Jun 24 14:14:03 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.12.1+cu116", "GPU Enabled": "True", "Numpy": "1.23.4", "Gym": "0.21.0"}} |