File size: 14,710 Bytes
f879a52 |
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 0x7f2262ae2050>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2262ae20e0>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2262ae2170>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2262ae2200>",
"_build": "<function ActorCriticPolicy._build at 0x7f2262ae2290>",
"forward": "<function ActorCriticPolicy.forward at 0x7f2262ae2320>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2262ae23b0>",
"_predict": "<function ActorCriticPolicy._predict at 0x7f2262ae2440>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2262ae24d0>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2262ae2560>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2262ae25f0>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x7f2262b381b0>"
},
"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": 507904,
"_total_timesteps": 500000,
"_num_timesteps_at_start": 0,
"seed": null,
"action_noise": null,
"start_time": 1652625000.310725,
"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": 128,
"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
} |