File size: 14,533 Bytes
dd2f81d 9cb367c dd2f81d 9cb367c dd2f81d 9cb367c dd2f81d 9cb367c dd2f81d 9cb367c dd2f81d |
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 0x000002AD702E8040>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x000002AD702E80D0>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x000002AD702E8160>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x000002AD702E81F0>",
"_build": "<function ActorCriticPolicy._build at 0x000002AD702E8280>",
"forward": "<function ActorCriticPolicy.forward at 0x000002AD702E8310>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x000002AD702E83A0>",
"_predict": "<function ActorCriticPolicy._predict at 0x000002AD702E8430>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x000002AD702E84C0>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x000002AD702E8550>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x000002AD702E85E0>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x000002AD702E18A0>"
},
"verbose": 0,
"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": 1673158217400907500,
"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": 310,
"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
} |