jslowik's picture
initial commit
b8bab1a
{
"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 0x7fa843340d30>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fa843340dc0>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fa843340e50>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fa843340ee0>",
"_build": "<function ActorCriticPolicy._build at 0x7fa843340f70>",
"forward": "<function ActorCriticPolicy.forward at 0x7fa843344040>",
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7fa8433440d0>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fa843344160>",
"_predict": "<function ActorCriticPolicy._predict at 0x7fa8433441f0>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fa843344280>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fa843344310>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7fa8433443a0>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x7fa84333c900>"
},
"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": 1015808,
"_total_timesteps": 1000000,
"_num_timesteps_at_start": 0,
"seed": null,
"action_noise": null,
"start_time": 1676667852709372705,
"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": 248,
"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
}