code: def __init__(self, uuid: str):
      runs = RunsSet()
      self.run_info, self.name = runs.get(uuid)
  
      with open(str(self.run_info.indicators_path), "r") as f:
          indicators = util.yaml_load(f.read())
  
      if "indicators" not in indicators:
          raise RuntimeError(
              "This run is corrupted or from an old version of LabML. "
              "Please update labml_dashboard and run it on this project. "
              "It will automatically migrate all the experiments."
          )
  
      indicators = indicators["indicators"]
  
      inds = []
      for k, v in indicators.items():
          cn = v["class_name"]
          class_ = None
          if cn == "Histogram":
              class_ = IndicatorClass.histogram
          elif cn == "Queue":
              class_ = IndicatorClass.queue
          elif cn == "IndexedScalar":
              class_ = IndicatorClass.scalar
          elif cn == "Scalar":
              class_ = IndicatorClass.scalar
          elif cn == "Tensor":
              class_ = IndicatorClass.tensor
  
          if class_ is None:
              continue
          inds.append(Indicator(k, class_, self.run_info.uuid, v))
  
      self.indicators = IndicatorCollection(inds)
  
imports: from enum import Enum
  from pathlib import Path
  from typing import List, Optional, Tuple, NamedTuple, Dict, Union
  from labml import lab
  from labml.internal import util
  from labml.internal.experiment.experiment_run import RunInfo
  from labml.internal.util.strings import is_pattern_match
label_desc: Use image node_id 1 to create a new Run object  with example: obj = Run(uuid)