File size: 14,938 Bytes
3fe18f4
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
{
    "policy_class": {
        ":type:": "<class 'abc.ABCMeta'>",
        ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
        "__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 sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\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 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 0x7f249d5565f0>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f249d556680>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f249d556710>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f249d5567a0>",
        "_build": "<function ActorCriticPolicy._build at 0x7f249d556830>",
        "forward": "<function ActorCriticPolicy.forward at 0x7f249d5568c0>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f249d556950>",
        "_predict": "<function ActorCriticPolicy._predict at 0x7f249d5569e0>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f249d556a70>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f249d556b00>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f249d556b90>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc_data object at 0x7f249d59fb70>"
    },
    "verbose": 1,
    "policy_kwargs": {
        ":type:": "<class 'dict'>",
        ":serialized:": "gASVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu",
        "log_std_init": -2,
        "ortho_init": false,
        "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
        "optimizer_kwargs": {
            "alpha": 0.99,
            "eps": 1e-05,
            "weight_decay": 0
        }
    },
    "observation_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
        ":serialized:": "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",
        "dtype": "float32",
        "_shape": [
            28
        ],
        "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 -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 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\n 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\n False False False False]",
        "_np_random": null
    },
    "action_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
        ":serialized:": "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",
        "dtype": "float32",
        "_shape": [
            8
        ],
        "low": "[-1. -1. -1. -1. -1. -1. -1. -1.]",
        "high": "[1. 1. 1. 1. 1. 1. 1. 1.]",
        "bounded_below": "[ True  True  True  True  True  True  True  True]",
        "bounded_above": "[ True  True  True  True  True  True  True  True]",
        "_np_random": null
    },
    "n_envs": 4,
    "num_timesteps": 2000000,
    "_total_timesteps": 2000000,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1658587530.9055486,
    "learning_rate": 0.00096,
    "tensorboard_log": "./tensorboard",
    "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:": "gASVjAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwSFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDBAAAAACUdJRiLg=="
    },
    "_last_original_obs": {
        ":type:": "<class 'numpy.ndarray'>",
        ":serialized:": "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"
    },
    "_episode_num": 0,
    "use_sde": true,
    "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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 62500,
    "n_steps": 8,
    "gamma": 0.99,
    "gae_lambda": 0.9,
    "ent_coef": 0.0,
    "vf_coef": 0.4,
    "max_grad_norm": 0.5,
    "normalize_advantage": false
}