File size: 14,711 Bytes
28aa0a7 |
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 0x7f511db7a290>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f511db7a320>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f511db7a3b0>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f511db7a440>",
"_build": "<function ActorCriticPolicy._build at 0x7f511db7a4d0>",
"forward": "<function ActorCriticPolicy.forward at 0x7f511db7a560>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f511db7a5f0>",
"_predict": "<function ActorCriticPolicy._predict at 0x7f511db7a680>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f511db7a710>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f511db7a7a0>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f511db7a830>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x7f511dbb5ea0>"
},
"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": 1658685968.1620543,
"learning_rate": 0.0003,
"tensorboard_log": null,
"lr_schedule": {
":type:": "<class 'function'>",
":serialized:": "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"
},
"_last_obs": {
":type:": "<class 'numpy.ndarray'>",
":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAALuYjL6ueh4/M1lTvOmFUb5zyWe7jPuyvAAAAAAAAAAAANiyO3GwtD+ihA0/5QECPdkCz7tBOQC+AAAAAAAAAAAay9W9uKbeueNMZLwBbHg2T2BFuhYV5LUAAIA/AACAPxsXzL7CJI8+cX4hPXyRX74jGjc8IPHUvAAAAAAAAAAA+MXpvljUZD+n4xS+HGiDvg1RuL0gZW68AAAAAAAAAAANMr+9uA7vufMhZTrOEA82/rIzO77ShLkAAIA/AACAPxp9aL09wac/ZizsvvGNt76dcyM9Cv6/PAAAAAAAAAAA+nAtvpsclT3+pqg8S5vyvbLJH7zl2eq5AAAAAAAAAAAzg6m8XPtGutmwrbvbb904Kdk1uhOuNjoAAIA/AACAP5ozpj0pBAq6tq7Su6B1TjagfvK6diK6tQAAgD8AAIA/QB/VvQrnBbmnFMu6iRQRtV5Izro4j+45AACAPwAAgD8qq4S+n/HsPi6qKLwgjHO+PqgTvSSGCT0AAAAAAAAAADMA/jyPej668oL+usnfHzixE3e71uewOAAAgD8AAIA/E+IavqNHhD7Cyls9TmdNvi0XGr0/HYE9AAAAAAAAAAAzeuO9XFcPuugnILuQhLO2R+kmO22EIzYAAIA/AACAP23ya762+DE9pYByOJMPO7fupMy+A46HtQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
},
"_last_episode_starts": {
":type:": "<class 'numpy.ndarray'>",
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAABAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": 124,
"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
} |