code: def _try_unwrap(maybe_collection):
      """If input is a collection of one item, return that, or return input."""
      if isinstance(maybe_collection, str) or isinstance(
          maybe_collection, bytes
      ):
          return maybe_collection
      try:
          if len(maybe_collection) == 1:
              return next(iter(maybe_collection))
      except TypeError:
          return maybe_collection
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import os
  import tempfile
  from typing import List, Mapping, Optional, Text, Tuple, Union
  import apache_beam
  from apache_beam.options.pipeline_options import PipelineOptions
  import pandas
  import pyarrow
  import tensorflow
  from tensorflow_data_validation import types
  from tensorflow_data_validation.api import stats_api
  from tensorflow_data_validation.api import validation_api
  from tensorflow_data_validation.coders import csv_decoder
  from tensorflow_data_validation.statistics import stats_impl
  from tensorflow_data_validation.statistics import stats_options
  from tensorflow_data_validation.utils import io_util
  from tensorflow_data_validation.utils import stats_gen_lib
  from tensorflow_data_validation.utils import stats_util
  from tfx_bsl.coders import example_coder
  from tfx_bsl.tfxio import tf_example_record
  from tensorflow_metadata.proto.v0 import statistics_pb2
label_desc: Use image node_id 4 for calling a global function with example usage: _try_unwrap(maybe_collection) and returns: maybe_collection, next, maybe_collection