code: def load_configs(run_uuid: str, *, is_only_hyperparam: bool = True):
      r"""
      Load configs of a previous run
  
      Arguments:
          run_uuid (str): if provided the experiment will start from
              a saved state in the run with UUID ``run_uuid``
  
      Keyword Arguments:
          is_only_hyperparam (bool, optional): if True all only the hyper parameters
              are returned
      """
  
      conf = _get_configs(run_uuid)
      if not conf:
          return {}
      values = {}
      for k, c in conf.items():
          is_hyperparam = c.get("is_hyperparam", None)
          is_explicit = c.get("is_explicitly_specified", False)
  
          if not is_only_hyperparam:
              values[k] = c["value"]
          elif is_hyperparam is None and is_explicit:
              values[k] = c["value"]
          elif is_hyperparam:
              values[k] = c["value"]
  
      return values
  
imports: from pathlib import Path
  from typing import Optional, Set, Dict, overload
  import numpy
  from labml.configs import BaseConfigs
  from labml.internal.experiment import create_experiment, experiment_singleton, has_experiment
  from labml.internal.experiment.experiment_run import get_configs
  from labml.internal.monitor import monitor_singleton
label_desc: Use image node_id 12 for calling a global function with example usage: load_configs(run_uuid) and returns: values, dict