code: def _load_with_retry(  # pylint: disable=unused-private-name
      path: str,
      element_spec: Any = None,
      compression: Optional[str] = None,
      reader_func: Optional[
          Callable[[dataset_ops.Dataset], dataset_ops.Dataset]
      ] = None,
  ) -> dataset_ops.Dataset:
      """Tries loading the snapshot. Retries if not found with a timeout."""
  
      deadline = time.time() + _LOAD_TIMEOUT_SECONDS
      error = None
      while time.time() < deadline:
          try:
              dataset = dataset_ops.Dataset.load(
                  path, element_spec, compression, reader_func
              )
              logging.info("Load tf.data snapshot at %s.", path)
              return dataset
          except errors.NotFoundError as e:
              logging.info(
                  "Could not find tf.data snapshot at %s. Will wait and retry.",
                  path,
              )
              error = e
              time.sleep(10)
      raise error
  
imports: import multiprocessing
  import os
  import time
  from typing import Any, Callable, Optional, Union
  from absl import logging
  from google.protobuf import message
  from google.protobuf import text_format
  from tensorflow.core.protobuf import snapshot_pb2
  from tensorflow.python.data.experimental.service import _pywrap_snapshot_utils
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import structured_function
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.ops import gen_experimental_dataset_ops
  from tensorflow.python.platform import gfile
  from tensorflow.python.saved_model import nested_structure_coder
label_desc: Use image node_id 2 for calling a global function with example usage: _load_with_retry(path, element_spec, compression, reader_func) and returns: dataset