class_docstr: Class for storing information about a run used during ensemble building.
  
  Note
  ----
  This is for internal use by the EnsembleBuilder and not for general usage.
class_docstr_tok: ["Class","for","storing","information","about","a","run","used","during","ensemble","building",".","Note","--","--","This","is","for","internal","use","by","the","EnsembleBuilder","and","not","for","general","usage","."]
docstr: Records the last time each prediction file type was modified, if it exists
docstr_tok: ["Records","the","last","time","each","prediction","file","type","was","modified",",","if","it","exists"]
code: def record_modified_times(self) -> None:
      """Records the last time each prediction file type was modified, if it exists"""
      self.recorded_mtimes = {}
      for kind in ["ensemble", "test"]:
          path = self.pred_path(kind)  # type: ignore
          if path.exists():
              self.recorded_mtimes[kind] = path.stat().st_mtime
  
imports: from __future__ import annotations
  from typing import Tuple
  import re
  from pathlib import Path
  import numpy
  from autosklearn.util.disk import sizeof
label_desc: Use image node_id 6 for calling the Run obj's underlying member method code with example usage: obj.record_modified_times() without return types