File size: 14,747 Bytes
6caa3a4 |
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 |
{
"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 0x7fd3db79ed30>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd3db79edc0>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd3db79ee50>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd3db79eee0>",
"_build": "<function ActorCriticPolicy._build at 0x7fd3db79ef70>",
"forward": "<function ActorCriticPolicy.forward at 0x7fd3db7a1040>",
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7fd3db7a10d0>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd3db7a1160>",
"_predict": "<function ActorCriticPolicy._predict at 0x7fd3db7a11f0>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd3db7a1280>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd3db7a1310>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd3db7a13a0>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x7fd3db799c30>"
},
"verbose": 1,
"policy_kwargs": {
":type:": "<class 'dict'>",
":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/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": 1677144020042267659,
"learning_rate": 0.00096,
"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:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
},
"_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:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
},
"_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
} |