class_docstr: API for identifying anomalous examples.
  
  Validates each input example against the schema provided in `options` and
  outputs (anomaly reason, anomalous example) tuples.
  
  Note: This transform requires that the input PCollection consist of pyarrow
  RecordBatches that have a single row (i.e., batch size == 1).
class_docstr_tok: ["API","for","identifying","anomalous","examples",".","Validates","each","input","example","against","the","schema","provided","in","`","options","`","and","outputs","(","anomaly","reason",",","anomalous","example",")","tuples",".","Note",":","This","transform","requires","that","the","input","PCollection","consist","of","pyarrow","RecordBatches","that","have","a","single","row","(","i.e.",",","batch","size","==","1",")","."]
code: def options(self, options) -> None:
      if not isinstance(options, stats_options.StatsOptions):
          raise ValueError("options must be a `StatsOptions` object.")
      if options.schema is None:
          raise ValueError("options must include a schema.")
      self._options = options
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import itertools
  import logging
  from typing import Callable, Iterable, List, Optional, Text, Tuple, Set
  import apache_beam
  import pyarrow
  import tensorflow
  from tensorflow_data_validation import constants
  from tensorflow_data_validation import types
  from tensorflow_data_validation.anomalies.proto import custom_validation_config_pb2
  from tensorflow_data_validation.anomalies.proto import validation_config_pb2
  from tensorflow_data_validation.anomalies.proto import validation_metadata_pb2
  from tensorflow_data_validation.api import validation_options
  from tensorflow_data_validation.pywrap.tensorflow_data_validation_extension import validation
  from tensorflow_data_validation.skew import feature_skew_detector
  from tensorflow_data_validation.skew.protos import feature_skew_results_pb2
  from tensorflow_data_validation.statistics import stats_impl
  from tensorflow_data_validation.statistics import stats_options
  from tensorflow_data_validation.utils import anomalies_util
  from tensorflow_data_validation.utils import slicing_util
  from tensorflow_data_validation.utils import stats_util
  from tensorflow_metadata.proto.v0 import anomalies_pb2
  from tensorflow_metadata.proto.v0 import schema_pb2
  from tensorflow_metadata.proto.v0 import statistics_pb2
label_desc: Use image node_id 3 for calling the IdentifyAnomalousExamples obj's underlying member method code with example usage: obj.options(options) without return types