File size: 15,934 Bytes
c7ac5c9
 
 
 
 
 
acc6d19
c7ac5c9
acc6d19
c7ac5c9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
acc6d19
c7ac5c9
 
 
 
 
 
 
 
acc6d19
 
 
 
c7ac5c9
 
 
 
 
 
 
acc6d19
c7ac5c9
acc6d19
c7ac5c9
 
 
 
 
 
 
 
 
acc6d19
c7ac5c9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
{
    "policy_class": {
        ":type:": "<class 'abc.ABCMeta'>",
        ":serialized:": "gAWVRQAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMG011bHRpSW5wdXRBY3RvckNyaXRpY1BvbGljeZSTlC4=",
        "__module__": "stable_baselines3.common.policies",
        "__doc__": "\n    MultiInputActorClass 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 (Tuple)\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: Uses the CombinedExtractor\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 MultiInputActorCriticPolicy.__init__ at 0x7f7bf5b18e50>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc._abc_data object at 0x7f7bf5b24c40>"
    },
    "verbose": 1,
    "policy_kwargs": {
        ":type:": "<class 'dict'>",
        ":serialized:": "gAWVgQAAAAAAAAB9lCiMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=",
        "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
        "optimizer_kwargs": {
            "alpha": 0.99,
            "eps": 1e-05,
            "weight_decay": 0
        }
    },
    "num_timesteps": 1000000,
    "_total_timesteps": 1000000,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1681887789297969351,
    "learning_rate": 0.0007,
    "tensorboard_log": null,
    "lr_schedule": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
    },
    "_last_obs": {
        ":type:": "<class 'collections.OrderedDict'>",
        ":serialized:": "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",
        "achieved_goal": "[[0.4118754  0.00955259 0.5572276 ]\n [0.4118754  0.00955259 0.5572276 ]\n [0.4118754  0.00955259 0.5572276 ]\n [0.4118754  0.00955259 0.5572276 ]]",
        "desired_goal": "[[-0.41984633 -0.44675288  0.94236934]\n [ 0.8960074  -0.10326681 -1.7142965 ]\n [ 0.21994889  1.0956788   0.03827107]\n [-0.3725872   1.2614866   0.800038  ]]",
        "observation": "[[ 0.4118754   0.00955259  0.5572276   0.00205687 -0.00073977  0.00507724]\n [ 0.4118754   0.00955259  0.5572276   0.00205687 -0.00073977  0.00507724]\n [ 0.4118754   0.00955259  0.5572276   0.00205687 -0.00073977  0.00507724]\n [ 0.4118754   0.00955259  0.5572276   0.00205687 -0.00073977  0.00507724]]"
    },
    "_last_episode_starts": {
        ":type:": "<class 'numpy.ndarray'>",
        ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
    },
    "_last_original_obs": {
        ":type:": "<class 'collections.OrderedDict'>",
        ":serialized:": "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",
        "achieved_goal": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]]",
        "desired_goal": "[[ 0.12140356  0.03555538  0.21820298]\n [-0.14125098  0.06938329  0.08574309]\n [ 0.09371155 -0.13538256  0.04399193]\n [ 0.14634654 -0.09951859  0.15047337]]",
        "observation": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]]"
    },
    "_episode_num": 0,
    "use_sde": false,
    "sde_sample_freq": -1,
    "_current_progress_remaining": 0.0,
    "_stats_window_size": 100,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "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"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 50000,
    "n_steps": 5,
    "gamma": 0.99,
    "gae_lambda": 1.0,
    "ent_coef": 0.0,
    "vf_coef": 0.5,
    "max_grad_norm": 0.5,
    "normalize_advantage": false,
    "observation_space": {
        ":type:": "<class 'gym.spaces.dict.Dict'>",
        ":serialized:": "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",
        "spaces": "OrderedDict([('achieved_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('desired_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('observation', Box([-10. -10. -10. -10. -10. -10.], [10. 10. 10. 10. 10. 10.], (6,), float32))])",
        "_shape": null,
        "dtype": null,
        "_np_random": null
    },
    "action_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
        ":serialized:": "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",
        "dtype": "float32",
        "_shape": [
            3
        ],
        "low": "[-1. -1. -1.]",
        "high": "[1. 1. 1.]",
        "bounded_below": "[ True  True  True]",
        "bounded_above": "[ True  True  True]",
        "_np_random": null
    },
    "n_envs": 4
}