File size: 14,566 Bytes
a5505a7 |
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 |
{
"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 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 0x7f8d69cc7ef0>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8d69cc7f80>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8d69c50050>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8d69c500e0>",
"_build": "<function ActorCriticPolicy._build at 0x7f8d69c50170>",
"forward": "<function ActorCriticPolicy.forward at 0x7f8d69c50200>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8d69c50290>",
"_predict": "<function ActorCriticPolicy._predict at 0x7f8d69c50320>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8d69c503b0>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8d69c50440>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8d69c504d0>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x7f8d69ca70f0>"
},
"verbose": 1,
"policy_kwargs": {},
"observation_space": {
":type:": "<class 'gym.spaces.box.Box'>",
":serialized:": "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",
"dtype": "float32",
"_shape": [
8
],
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
"high": "[inf inf inf inf inf inf inf inf]",
"bounded_below": "[False False False False False False False False]",
"bounded_above": "[False False False False False False False False]",
"_np_random": null
},
"action_space": {
":type:": "<class 'gym.spaces.discrete.Discrete'>",
":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
"n": 4,
"_shape": [],
"dtype": "int64",
"_np_random": null
},
"n_envs": 16,
"num_timesteps": 32768,
"_total_timesteps": 10,
"_num_timesteps_at_start": 0,
"seed": null,
"action_noise": null,
"start_time": 1652028072.0409198,
"learning_rate": 0.0003,
"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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
},
"_last_original_obs": null,
"_episode_num": 0,
"use_sde": false,
"sde_sample_freq": -1,
"_current_progress_remaining": -3275.8,
"ep_info_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "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"
},
"ep_success_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
},
"_n_updates": 10,
"n_steps": 2048,
"gamma": 0.99,
"gae_lambda": 0.95,
"ent_coef": 0.0,
"vf_coef": 0.5,
"max_grad_norm": 0.5,
"batch_size": 64,
"n_epochs": 10,
"clip_range": {
":type:": "<class 'function'>",
":serialized:": "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"
},
"clip_range_vf": null,
"normalize_advantage": true,
"target_kl": null
} |