File size: 14,730 Bytes
e66dbe9 a7e850b e66dbe9 a7e850b e66dbe9 a7e850b e66dbe9 a7e850b e66dbe9 a7e850b e66dbe9 a7e850b e66dbe9 |
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 0x7f69ebb96310>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f69ebb963a0>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f69ebb96430>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f69ebb964c0>",
"_build": "<function ActorCriticPolicy._build at 0x7f69ebb96550>",
"forward": "<function ActorCriticPolicy.forward at 0x7f69ebb965e0>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f69ebb96670>",
"_predict": "<function ActorCriticPolicy._predict at 0x7f69ebb96700>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f69ebb96790>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f69ebb96820>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f69ebb968b0>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x7f69ebb8dbd0>"
},
"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": 1015808,
"_total_timesteps": 1000000,
"_num_timesteps_at_start": 0,
"seed": null,
"action_noise": null,
"start_time": 1672550000414184436,
"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": -0.015808000000000044,
"ep_info_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "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"
},
"ep_success_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
},
"_n_updates": 252,
"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
} |