code: def _confusion_count_to_proto(
      values_count: Tuple[
          Tuple[
              _ConfusionFeatureValue,
              _ConfusionFeatureValue,
              types.FeatureName,
          ],
          int,
      ]
  ) -> feature_skew_results_pb2.ConfusionCount:
      """Convert a confusion count tuple and count to string."""
      (base_val, test_val, feature_name), count = values_count
      cc = feature_skew_results_pb2.ConfusionCount(
          feature_name=feature_name, count=count
      )
      cc.base.bytes_value = base_val
      cc.test.bytes_value = test_val
      return cc
  
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 9 for calling a global function with example usage: _confusion_count_to_proto(values_count) and returns: cc