code: def _make_updated_descriptions(
      reasons: List[anomalies_pb2.AnomalyInfo.Reason],
  ) -> Tuple[Text, Text]:
      """Returns descriptions based on the specified reasons."""
      # If we only have one reason, use its descriptions. Alternatively, if the only
      # reasons for the anomaly are of type SCHEMA_NEW_COLUMN, then just use one of
      # them for the description.
      if len(reasons) == 1 or all(
          reason.type == anomalies_pb2.AnomalyInfo.SCHEMA_NEW_COLUMN
          for reason in reasons
      ):
          return (reasons[0].description, reasons[0].short_description)
      else:
          return (
              " ".join([reason.description for reason in reasons]),
              MULTIPLE_ERRORS_SHORT_DESCRIPTION,
          )
  
file_path: data-validation/tensorflow_data_validation/utils/anomalies_util.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import Iterable, FrozenSet, List, Text, Tuple
  import pyarrow
  from tensorflow_data_validation import types
  from tensorflow_data_validation.utils import io_util
  from google.protobuf import text_format
  from tensorflow_metadata.proto.v0 import anomalies_pb2
label_desc: Use image node_id 1 for calling a global function with example usage: _make_updated_descriptions(reasons) and returns: reasons,  reasons, str,  MULTIPLE_ERRORS_SHORT_DESCRIPTION