code: def get_checkpoint_mtimes(checkpoint_prefixes):
      """Returns the mtimes (modification timestamps) of the checkpoints.
  
      Globs for the checkpoints pointed to by `checkpoint_prefixes`.  If the files
      exist, collect their mtime.  Both V2 and V1 checkpoints are considered, in
      that priority.
  
      This is the recommended way to get the mtimes, since it takes into account
      the naming difference between V1 and V2 formats.
  
      Note: If not all checkpoints exist, the length of the returned mtimes list
      will be smaller than the length of `checkpoint_prefixes` list, so mapping
      checkpoints to corresponding mtimes will not be possible.
  
      Args:
        checkpoint_prefixes: a list of checkpoint paths, typically the results of
          `Saver.save()` or those of `tf.train.latest_checkpoint()`, regardless of
          sharded/non-sharded or V1/V2.
      Returns:
        A list of mtimes (in microseconds) of the found checkpoints.
      """
      mtimes = []
  
      def match_maybe_append(pathname):
          fnames = file_io.get_matching_files(pathname)
          if fnames:
              mtimes.append(file_io.stat(fnames[0]).mtime_nsec / 1e9)
              return True
          return False
  
      for checkpoint_prefix in checkpoint_prefixes:
          # Tries V2's metadata file first.
          pathname = _prefix_to_checkpoint_path(
              checkpoint_prefix, saver_pb2.SaverDef.V2
          )
          if match_maybe_append(pathname):
              continue
          # Otherwise, tries V1, where the prefix is the complete pathname.
          match_maybe_append(checkpoint_prefix)
  
      return mtimes
  
imports: import collections
  import copy
  import os.path
  import re
  import time
  from google.protobuf import text_format
  from tensorflow.core.protobuf import saver_pb2
  from tensorflow.python.checkpoint import checkpoint_options
  from tensorflow.python.eager import context
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.lib.io import file_io
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.training import training_util
  from tensorflow.python.training.checkpoint_state_pb2 import CheckpointState
  from tensorflow.python.util import compat
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 11 for calling a global function with example usage: get_checkpoint_mtimes(checkpoint_prefixes) and returns: mtimes, False, True