code: def _get_confusion_feature_value(
      ex: tf.train.Example, name: types.FeatureName
  ) -> Optional[_ConfusionFeatureValue]:
      """Returns a value for a named feature for confusion analysis."""
      f = ex.features.feature.get(name, None)
      if f is None:
          return _MISSING_VALUE_PLACEHOLDER
      if f.int64_list.value:
          raise ValueError(
              "int64 features unsupported for confusion analysis."
          )
      if f.float_list.value:
          raise ValueError(
              "float features unsupported for confusion analysis."
          )
      if len(f.bytes_list.value) > 1:
          raise ValueError(
              "multivalent features unsupported for confusion analysis."
          )
      if not f.bytes_list.value:
          return _MISSING_VALUE_PLACEHOLDER
      return f.bytes_list.value[0]
  
imports: from typing import Any, Dict, Iterable, Iterator, List, Optional, Tuple, Union
  import apache_beam
  import farmhash
  import numpy
  import tensorflow
  from tensorflow_data_validation import constants
  from tensorflow_data_validation import types
  from tensorflow_data_validation.utils import artifacts_io_impl
  from tensorflow_data_validation.skew.protos import feature_skew_results_pb2
label_desc: Use image node_id 7 for calling a global function with example usage: _get_confusion_feature_value(ex, name) and returns: f, _MISSING_VALUE_PLACEHOLDER, _MISSING_VALUE_PLACEHOLDER