File size: 14,759 Bytes
aa842c2 1d1c16c aa842c2 99ffa29 aa842c2 99ffa29 aa842c2 1d1c16c aa842c2 99ffa29 aa842c2 99ffa29 aa842c2 |
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:": "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 0x7f250eaa8b00>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f250eaa8b90>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f250eaa8c20>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f250eaa8cb0>",
"_build": "<function ActorCriticPolicy._build at 0x7f250eaa8d40>",
"forward": "<function ActorCriticPolicy.forward at 0x7f250eaa8dd0>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f250eaa8e60>",
"_predict": "<function ActorCriticPolicy._predict at 0x7f250eaa8ef0>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f250eaa8f80>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f250eaad050>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f250eaad0e0>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x7f250ea80480>"
},
"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:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
"n": 4,
"_shape": [],
"dtype": "int64",
"_np_random": null
},
"n_envs": 16,
"num_timesteps": 507904,
"_total_timesteps": 500000,
"_num_timesteps_at_start": 0,
"seed": null,
"action_noise": null,
"start_time": 1653669191.9946926,
"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:": "gASVmAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDEAAAAAAAAAAAAAAAAAAAAACUdJRiLg=="
},
"_last_original_obs": null,
"_episode_num": 0,
"use_sde": false,
"sde_sample_freq": -1,
"_current_progress_remaining": -0.015808000000000044,
"ep_info_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "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"
},
"ep_success_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
},
"_n_updates": 376,
"n_steps": 1024,
"gamma": 0.999,
"gae_lambda": 0.98,
"ent_coef": 0.01,
"vf_coef": 0.5,
"max_grad_norm": 0.5,
"batch_size": 64,
"n_epochs": 4,
"clip_range": {
":type:": "<class 'function'>",
":serialized:": "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"
},
"clip_range_vf": null,
"normalize_advantage": true,
"target_kl": null
} |