class_docstr: Builds ensembles out of runs that exist in the Backend
  
  This is used by EnsembleBuilderManager and created in a dask-client
  every time a run finishes and there is currently no EnsembleBuilder active.
docstr: Delete runs
  
  Will not delete dummy runs
  
  Parameters
  ----------
  runs : Sequence[Run]
      The runs to delete
docstr_tok: ["Delete","runs","Will","not","delete","dummy","runs","Parameters","--","--","--","--","--","runs",":","Sequence","[","Run","]","The","runs","to","delete"]
code: def delete_runs(self, runs: Iterable[Run]) -> None:
      """Delete runs
  
      Will not delete dummy runs
  
      Parameters
      ----------
      runs : Sequence[Run]
          The runs to delete
      """
      items = iter(
          run for run in runs if not run.is_dummy() and run.dir.exists()
      )
      for run in items:
          try:
              rmtree(run.dir, atomic=True)
              self.logger.info(f"Deleted files for {run}")
          except Exception as e:
              self.logger.error(
                  f"Failed to delete files for {run}: \n{e}"
              )
  
imports: from __future__ import annotations
  from typing import Any, Iterable, Mapping, Sequence, Type, cast
  import logging.handlers
  import multiprocessing
  import numbers
  import os
  import pickle
  import time
  import traceback
  from itertools import accumulate
  from pathlib import Path
  import numpy
  import pandas
  import pynisher
  from sklearn.utils.validation import check_random_state
  from autosklearn.automl_common.common.utils.backend import Backend
  from autosklearn.data.validation import SUPPORTED_FEAT_TYPES
  from autosklearn.data.xy_data_manager import XYDataManager
  from autosklearn.ensemble_building.run import Run, RunID
  from autosklearn.ensembles.abstract_ensemble import AbstractEnsemble
  from autosklearn.ensembles.ensemble_selection import EnsembleSelection
  from autosklearn.metrics import Scorer, calculate_loss, calculate_scores
  from autosklearn.util.disk import rmtree
  from autosklearn.util.functional import cut, findwhere, roundrobin, split
  from autosklearn.util.logging_ import get_named_client_logger
  from autosklearn.util.parallel import preload_modules
label_desc: Use image node_id 14 for calling the EnsembleBuilder obj's underlying member method code with example usage: obj.delete_runs(runs) without return types