class_docstr: View of statistics for a dataset (slice).
class_docstr_tok: ["View","of","statistics","for","a","dataset","(","slice",")","."]
docstr: Retrieve a cross-feature if it exists, or None.
docstr_tok: ["Retrieve","a","cross-feature","if","it","exists",",","or","None","."]
code: def get_cross_feature(
      self,
      x_path: Union[str, types.FeaturePath, Iterable[str]],
      y_path: Union[str, types.FeaturePath, Iterable[str]],
  ) -> Optional["CrossFeatureView"]:
      """Retrieve a cross-feature if it exists, or None."""
  
      x_path = _normalize_feature_id(x_path)
      y_path = _normalize_feature_id(y_path)
      self._init_index()
      feature_id = (x_path, y_path)
      index = self._cross_feature_map.get(feature_id, None)
      if index is None:
          return None
      return CrossFeatureView(self._statistics.cross_features[index])
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import logging
  from typing import Dict, Iterable, Optional, Sequence, Text, Tuple, Union
  import numpy
  import pyarrow
  import tensorflow
  from tensorflow_data_validation import constants
  from tensorflow_data_validation import types
  from tensorflow_data_validation.arrow import arrow_util
  from tensorflow_data_validation.utils import artifacts_io_impl
  from tensorflow_data_validation.utils import io_util
  from tfx_bsl import statistics
  from tfx_bsl.arrow import array_util
  from google.protobuf import text_format
  from tensorflow_metadata.proto.v0 import statistics_pb2
label_desc: Use image node_id 5 for calling the DatasetView obj's underlying member method code with example usage: obj.get_cross_feature(x_path, y_path) and returns: CrossFeatureView, None