File size: 19,832 Bytes
afb677d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
{
    "policy_class": {
        ":type:": "<class 'abc.ABCMeta'>",
        ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLnRkMy5wb2xpY2llc5SMCVREM1BvbGljeZSTlC4=",
        "__module__": "stable_baselines3.td3.policies",
        "__doc__": "\n    Policy class (with both actor and critic) for TD3.\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 features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\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    :param n_critics: Number of critic networks to create.\n    :param share_features_extractor: Whether to share or not the features extractor\n        between the actor and the critic (this saves computation time)\n    ",
        "__init__": "<function TD3Policy.__init__ at 0x7fd2f4a70af0>",
        "_build": "<function TD3Policy._build at 0x7fd2f4a70b80>",
        "_get_constructor_parameters": "<function TD3Policy._get_constructor_parameters at 0x7fd2f4a70c10>",
        "make_actor": "<function TD3Policy.make_actor at 0x7fd2f4a70ca0>",
        "make_critic": "<function TD3Policy.make_critic at 0x7fd2f4a70d30>",
        "forward": "<function TD3Policy.forward at 0x7fd2f4a70dc0>",
        "_predict": "<function TD3Policy._predict at 0x7fd2f4a70e50>",
        "set_training_mode": "<function TD3Policy.set_training_mode at 0x7fd2f4a70ee0>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc._abc_data object at 0x7fd2f4a76440>"
    },
    "verbose": 1,
    "policy_kwargs": {},
    "observation_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
        ":serialized:": "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",
        "dtype": "float64",
        "_shape": [
            11
        ],
        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]",
        "high": "[inf inf inf inf inf inf inf inf inf inf inf]",
        "bounded_below": "[False False False False False False False False False False False]",
        "bounded_above": "[False False False False False False False False False False False]",
        "_np_random": null
    },
    "action_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
        ":serialized:": "gAWVGAwAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLA4WUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWDAAAAAAAAAAAAIC/AACAvwAAgL+UaApLA4WUjAFDlHSUUpSMBGhpZ2iUaBIolgwAAAAAAAAAAACAPwAAgD8AAIA/lGgKSwOFlGgVdJRSlIwNYm91bmRlZF9iZWxvd5RoEiiWAwAAAAAAAAABAQGUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLA4WUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYDAAAAAAAAAAEBAZRoIUsDhZRoFXSUUpSMCl9ucF9yYW5kb22UjBRudW1weS5yYW5kb20uX3BpY2tsZZSMEl9fcmFuZG9tc3RhdGVfY3RvcpSTlIwHTVQxOTkzN5RoLYwUX19iaXRfZ2VuZXJhdG9yX2N0b3KUk5SGlFKUfZQojA1iaXRfZ2VuZXJhdG9ylIwHTVQxOTkzN5SMBXN0YXRllH2UKIwDa2V5lGgSKJbACQAAAAAAAAAAAIBTwrOchwO1k3Lsq1vo5rLyz7aB2tUG72GhMU2ga7XM2RPmGJ90nHkvyKUbgMR5AUmeD0PkXeAYk5ITVczUSilk0giVvjTQnkRyegPwrb8Kc5t7PulgsQbadQNFC2591hZq6wQ0ZoO38/WlL2nvQmNDtVz3wndSzEZENy0IiW7Qjq53+xi2gE97nvlPMuwS2LmOXoWpGcquPXYtZytCgJ7F7scf9SIBXUvPJA/MGVJkRFeYcJ0K9RIXtela3jvE/0HPOrFftofdM9hYiaqizX97P8mUt2wPQx8xmX0bYJCrtwcdGUzeyPuOugD1z6ka3iX+IAalFvzQduPBTvXKQ9MBWnnfUFetzaqYhTrP0WHhMA/Ht9nWRUX4vUiuWi77gKSTLtizn2cHsqRyJMj43mOVvrbJtm3T5laAgDosou93H+ZNC0HiTVqmVP8Lsv3/JsoIWfaq43/tiUiTGgfVTTF1psbquA6tH5Icya9TC+0oH7X0htvTuZKBVDKM0C+fIAM8l/emTHKVm2ft/85WlYRpZ+XoFwvDLSCusSBQr4f7w/xdYy4GCKdeDDOfezLj5k6WvjminpO26pfQqfP9LJIYOUEgrwmoo5vMHp8a36i8kcQzwqUvi94rCQuS64xYFp7HcUF1aySvLmqGyXEyCeTa2GHwNpeYB9u4jyPRKocxbWSV4hOL16R9fH95KLmFfUaMD8zrZmLG5rLUfzMf1WOxNFwZpzInS+HWE1F4MWg2xcVst8upoi9ssNCNjtPbz1ley6m8DG7YZVNupay35yQ8/PAfu8uKRQsL7B4ArDFquqb66ABeDLPvviZ4c6y9Bi67Xye+uu6eNlYO/Boq5iiETBR9Kemi0T1eFf33JRNzywY9CJ1N9eTOb+3wxY/yK3iXhVISAMufwZby3YMCHwTAVr8o4ahkQaNipnYgwDvQT4XYuqBpmVAsUw41MjHfK43kXZ7UxPi/bB0FEr1H6UYynEiI2V3I7DDEsMFNEMyF3sA+J2YPBAGe9oh5woVr3lu3AeREERRPmD778jQMODrzkRfg4w7Zi1M+ozc9CW5Lim4SEBBFW6Q0ZKHiBgOBwE8pmXhOE1/4b4TsSX1+ZYlw/f1KJ/Doyf4YSKwzVGEdjTldkdS/lbivyQPaNIsxj4ggvb4u1CtbuK3vLbz6wSJwugR9g6TL1kkXqXR9H6xcRrB/5EQf0u+1EnjLN/GvsqKw2mvVrG/Vp7kINdL5dPO44b8Emce+3xqudjVdYf1J2QI56iTowjwYEK2NMLEnklukjknSLQDrqYlpFb0sx8/oKKXf9xVFD243YpO1XejusnBjhcKePsMmaqtTCh8MOXsSTQ+g3vDQeHxgc7LyqE/DtXwAt2Nmft5i2MJAiV1C8dszUjvdG0ItC9AYUxdQInTbakZGpO9lfldZKLOpuBfpMmYjosMX3Bylh5qUHtwPB6V+p2nMdGbKNFshf1v7Di6P/9oNGA/ZKCI4Cr8P/3/RJuAr8TQVDJyWE1UCRsrBeEDEoZzOm8mjDSYUVQC3/l9PkoCyZBMC3ynQWysYwNN+ThHNmCplKb6KFVFLfvVPHe3CkYDWCij8Ah8mHyyUkLeGRHU4YI3ssA8YLBsz2seUpJTi66EmJ9/X3qH2rWQ8yV3r3z0x8otWS8KXuh8JG6s9Rbjpx4koT3nWxAPW/xwrQcrUma4FMJcB6UJQIgU0saTe0xc1Wa64UXejfFvhXhPUgBgh8F3IRUeEghk4T8kRjv11pDDyeNgS1DpjBnqQ0IFh+uOrY6CUhNxF3AOYg0vjaujoedtaAtlDwJ78SI9UG1YfCG8ZQcrUU043NHNeBPXMoSD5YCKB64rhBUjF0hMzhi9TJi+lAm4l37EYPWejsFggpd1XhoOWxGdZIyZL7NPJO8LT5OAEwI2ky90KGNoH9dOsxWybS+A+YJizCfTrsxNhZ+bmgKqqY1yKqhF8UvY7abEVPVUxwoOvEcF0FSFIblSYB6vHzooATK1uwJufo46PxjTZXBXKfNd3RYl8uKh4YxkhIzV6d5Z9NzWZDoKl0PEmpSZTzr8qwEvcFvRLY0CoXKwUlkrEPAt6PzHP7EfwjEQfOWSKI0f7YgirTrrcUDCLrCDp2ByvIOpD6U0PCfz3yfKWtxhKGKAOu2sUE17MrHdmOmQ8Kc9R5AHiElStgJQnLkLLK0L/HVSwHIp7P9pI0RaeVafNh0l/Y+govRh+ZpHcqlfOL1rHcEc+CTVx2aB1WSp68UnQNR1MEVCP+aFoqpxpPSsokuDL/XUCFZbidfv6QB2BHRvWICx4jRNswO2iEG6qpRl+ox9Qqx0jy/Zp5R3T4io6M8EV7tNlELs5RiZ/vz1JFOnD2Cy3i3PHu0tqnwmcW3aR4qGp3e8GCqm+WzG/HQNw8L5uj+oiV0qICfkPtM+N5YvMnWCamTWZUo7JY6/9nOVFN97zISwyxFyB0/Fs67EuOU7CjW4WH02Meg7P/FucjrYjj1nNPn0ZQI20AvvhSqOVGjJdnkQsSOFOf4Xl9h8SRjZOdKyAo7hbBv/EPjVLiYEvstxTIXvrJtXtjHQvpXZAahJ/KEcWoxAmz+Fos89bXyZYlv9QOX3Rk31MTNx1e9myYJ6rMJqALpgMend+in7mcBBKdP8HK3aPvP7pyeX9pmHqgqznGsQya7OksVtc1Wh/2E2ZfkTQNDYzy4Gqp5b3mnrPzJKc7FREA7byhhaxtXJ5ho2VYtms60gxkNGONt5xJLAwuWsGHDiZlWG3gOA5DEjX4/uw8dksx/z1T7ly1/WsPSvUBeDJePM7Eq8LFYyGvPoCHX37NqX9sAinD7RXs+rzk9FA7hR5JyYzA4NHyNw58gu4yajvFeF6Zj8mq06dySURoZqkx4aWSJ5+9CTH0vkRa8ufqy0jjNE/illfH2I7PXsgomYo5UeAIgA6KF5vRvCSM2Qi2V9g7cvN4ss+4EM0sWDu1C7k09bLbxricGwT+CzIS15G8XYQJgUg4mDTp3NzvshbDuj7PVDkA/EuD26/IWeJhY24nKTut+UsKZhyDWA3rnsJZ9/xh8+vS6Qo5qZyj3hfWcV3KujEeJCVFdo/3UM6oy54jWkJqzJFC3SO1tbDF0RXLM/cbNRlcFaprTFcLPB7b1zGDZqLAq64ABV9oIT8+3VwlerzC+WIXzWwwM8xujB3367Ja4TGr977ZbfBZ5XeFWh+iITJKMGsk9ZUlb375ShwlsLSmk3Dma0eS2RmpSTqRW1SBVDgKPi52P9uW5nNypaMi84Ik7nYz7FxBjzTwSLxP+XDBL1OC67NDd7QpHuGm2A1xfX9eEK8C5RoB4wCdTSUiYiHlFKUKEsDaAtOTk5K/////0r/////SwB0lGJNcAKFlGgVdJRSlIwDcG9zlE1wAnWMCWhhc19nYXVzc5RLAIwFZ2F1c3OURwAAAAAAAAAAdWJ1Yi4=",
        "dtype": "float32",
        "_shape": [
            3
        ],
        "low": "[-1. -1. -1.]",
        "high": "[1. 1. 1.]",
        "bounded_below": "[ True  True  True]",
        "bounded_above": "[ True  True  True]",
        "_np_random": "RandomState(MT19937)"
    },
    "n_envs": 1,
    "num_timesteps": 1000000,
    "_total_timesteps": 1000000,
    "_num_timesteps_at_start": 0,
    "seed": 0,
    "action_noise": {
        ":type:": "<class 'stable_baselines3.common.noise.NormalActionNoise'>",
        ":serialized:": "gAWVCgEAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5ub2lzZZSMEU5vcm1hbEFjdGlvbk5vaXNllJOUKYGUfZQojANfbXWUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWGAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJmOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwOFlIwBQ5R0lFKUjAZfc2lnbWGUaAgolhgAAAAAAAAAmpmZmZmZuT+amZmZmZm5P5qZmZmZmbk/lGgPSwOFlGgTdJRSlHViLg==",
        "_mu": "[0. 0. 0.]",
        "_sigma": "[0.1 0.1 0.1]"
    },
    "start_time": 1676735865824449818,
    "learning_rate": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
    },
    "tensorboard_log": "runs/Hopper-v3__td3__2320487108__1676735863/Hopper-v3",
    "lr_schedule": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
    },
    "_last_obs": null,
    "_last_episode_starts": {
        ":type:": "<class 'numpy.ndarray'>",
        ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
    },
    "_last_original_obs": {
        ":type:": "<class 'numpy.ndarray'>",
        ":serialized:": "gAWVzQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJZYAAAAAAAAAFFqHUF+VPk/bxTqdyH3sr+uxgh+esvfv7qD8T1epmc/CMCswXo35j9AgxOyISsCQKpHODIo/ua/R3AFL4wd8r/U5ZVcemXrv/rbbNMpxaO/AAAAAAAAJECUjAVudW1weZSMBWR0eXBllJOUjAJmOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwFLC4aUjAFDlHSUUpQu"
    },
    "_episode_num": 2464,
    "use_sde": false,
    "sde_sample_freq": -1,
    "_current_progress_remaining": 0.0,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "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"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 990000,
    "buffer_size": 1,
    "batch_size": 256,
    "learning_starts": 10000,
    "tau": 0.005,
    "gamma": 0.99,
    "gradient_steps": 1,
    "optimize_memory_usage": false,
    "replay_buffer_class": {
        ":type:": "<class 'abc.ABCMeta'>",
        ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
        "__module__": "stable_baselines3.common.buffers",
        "__doc__": "\n    Replay buffer used in off-policy algorithms like SAC/TD3.\n\n    :param buffer_size: Max number of element in the buffer\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param device: PyTorch device\n    :param n_envs: Number of parallel environments\n    :param optimize_memory_usage: Enable a memory efficient variant\n        of the replay buffer which reduces by almost a factor two the memory used,\n        at a cost of more complexity.\n        See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n        and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n        Cannot be used in combination with handle_timeout_termination.\n    :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n        separately and treat the task as infinite horizon task.\n        https://github.com/DLR-RM/stable-baselines3/issues/284\n    ",
        "__init__": "<function ReplayBuffer.__init__ at 0x7fd2f4a6e5e0>",
        "add": "<function ReplayBuffer.add at 0x7fd2f4a6e670>",
        "sample": "<function ReplayBuffer.sample at 0x7fd2f4a6e700>",
        "_get_samples": "<function ReplayBuffer._get_samples at 0x7fd2f4a6e790>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc._abc_data object at 0x7fd2f4a69280>"
    },
    "replay_buffer_kwargs": {},
    "train_freq": {
        ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
        ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"
    },
    "use_sde_at_warmup": false,
    "policy_delay": 2,
    "target_noise_clip": 0.5,
    "target_policy_noise": 0.2,
    "actor_batch_norm_stats": [],
    "critic_batch_norm_stats": [],
    "actor_batch_norm_stats_target": [],
    "critic_batch_norm_stats_target": []
}