File size: 14,752 Bytes
5322a8b |
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 0x7f0e42d06040>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0e42d060d0>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0e42d06160>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0e42d061f0>",
"_build": "<function ActorCriticPolicy._build at 0x7f0e42d06280>",
"forward": "<function ActorCriticPolicy.forward at 0x7f0e42d06310>",
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f0e42d063a0>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0e42d06430>",
"_predict": "<function ActorCriticPolicy._predict at 0x7f0e42d064c0>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0e42d06550>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0e42d065e0>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0e42d06670>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc._abc_data object at 0x7f0e42d082c0>"
},
"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": 1680501905870205188,
"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
} |