File size: 14,632 Bytes
d3f6efb |
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 0x7f00419b6160>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f00419b61f0>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f00419b6280>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f00419b6310>",
"_build": "<function ActorCriticPolicy._build at 0x7f00419b63a0>",
"forward": "<function ActorCriticPolicy.forward at 0x7f00419b6430>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f00419b64c0>",
"_predict": "<function ActorCriticPolicy._predict at 0x7f00419b6550>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f00419b65e0>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f00419b6670>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f00419b6700>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x7f00419b15d0>"
},
"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": 1007616,
"_total_timesteps": 1000000,
"_num_timesteps_at_start": 0,
"seed": null,
"action_noise": null,
"start_time": 1670372470685307427,
"learning_rate": 0.0005,
"tensorboard_log": "logs",
"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": -0.007616000000000067,
"ep_info_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "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"
},
"ep_success_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
},
"_n_updates": 492,
"n_steps": 512,
"gamma": 0.995,
"gae_lambda": 0.985,
"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
} |