code: def delete_checkpoints(
      manager: storage.StorageManager,
      to_delete: List[str],
      globs: List[str],
      dry_run: bool,
  ) -> Dict[str, Dict[str, int]]:
      """
      Delete some of the checkpoints associated with a single experiment.
      """
      logger.info(f"Deleting {len(to_delete)} checkpoints")
  
      storage_id_to_resources: Dict[str, Dict[str, int]] = {}
      for storage_id in to_delete:
          if not dry_run:
              logger.info(f"Deleting checkpoint {storage_id}")
              try:
                  storage_id_to_resources[storage_id] = manager.delete(
                      storage_id, globs
                  )
              except errors.CheckpointNotFound as e:
                  logger.warn(e)
          else:
              logger.info(f"Dry run: deleting checkpoint {storage_id}")
  
      return storage_id_to_resources
  
file_path: determined/harness/determined/exec/gc_checkpoints.py
imports: import argparse
  import json
  import logging
  import os
  import sys
  from typing import Any, Dict, List
  import urllib3
  import determined
  from determined import errors, tensorboard
  from determined.common import api, constants, storage, util
  from determined.common.api import bindings, certs
label_desc: Use image node_id 2 for calling a global function with example usage: delete_checkpoints(manager, to_delete, globs, dry_run) and returns: storage_id_to_resources