|
{ |
|
"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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7fdb40fbf820>", |
|
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fdb40fbf8b0>", |
|
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fdb40fbf940>", |
|
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fdb40fbf9d0>", |
|
"_build": "<function ActorCriticPolicy._build at 0x7fdb40fbfa60>", |
|
"forward": "<function ActorCriticPolicy.forward at 0x7fdb40fbfaf0>", |
|
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7fdb40fbfb80>", |
|
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fdb40fbfc10>", |
|
"_predict": "<function ActorCriticPolicy._predict at 0x7fdb40fbfca0>", |
|
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fdb40fbfd30>", |
|
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fdb40fbfdc0>", |
|
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7fdb40fbfe50>", |
|
"__abstractmethods__": "frozenset()", |
|
"_abc_impl": "<_abc_data object at 0x7fdb40fba9c0>" |
|
}, |
|
"verbose": 1, |
|
"policy_kwargs": {}, |
|
"observation_space": { |
|
":type:": "<class 'gym.spaces.box.Box'>", |
|
":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", |
|
"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": 1674142615195133831, |
|
"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 |
|
} |