code: def _latest_checkpoints_changed(configs, run_path_pairs):
      """Returns true if the latest checkpoint has changed in any of the runs."""
      for run_name, assets_dir in run_path_pairs:
          if run_name not in configs:
              config = ProjectorConfig()
              config_fpath = os.path.join(
                  assets_dir, metadata.PROJECTOR_FILENAME
              )
              if tf.io.gfile.exists(config_fpath):
                  with tf.io.gfile.GFile(config_fpath, "r") as f:
                      file_content = f.read()
                  text_format.Parse(file_content, config)
          else:
              config = configs[run_name]
  
          # See if you can find a checkpoint file in the logdir.
          logdir = _assets_dir_to_logdir(assets_dir)
          ckpt_path = _find_latest_checkpoint(logdir)
          if not ckpt_path:
              continue
          if config.model_checkpoint_path != ckpt_path:
              return True
      return False
  
imports: import collections
  import functools
  import imghdr
  import mimetypes
  import os
  import threading
  import numpy
  from werkzeug import wrappers
  from google.protobuf import json_format
  from google.protobuf import text_format
  from tensorboard import context
  from tensorboard.backend.event_processing import plugin_asset_util
  from tensorboard.backend.http_util import Respond
  from tensorboard.compat import tf
  from tensorboard.plugins import base_plugin
  from tensorboard.plugins.projector import metadata
  from tensorboard.plugins.projector.projector_config_pb2 import ProjectorConfig
  from tensorboard.util import tb_logging
label_desc: Use image node_id 4 for calling a global function with example usage: _latest_checkpoints_changed(configs, run_path_pairs) and returns: False, True