class_docstr: A stats generator which counts the number of missing values in a path.
class_docstr_tok: ["A","stats","generator","which","counts","the","number","of","missing","values","in","a","path","."]
docstr: Generates a unique key for this instance.
  
  Returns:
    The unique key for this set of init args.
docstr_tok: ["Generates","a","unique","key","for","this","instance",".","Returns",":","The","unique","key","for","this","set","of","init","args","."]
code: def get_key(self) -> Tuple[Union[Text, types.FeaturePath], ...]:
      """Generates a unique key for this instance.
  
      Returns:
        The unique key for this set of init args.
      """
      return CountMissingGenerator.key(self._path, self._required_paths)
  
file_path: data-validation/tensorflow_data_validation/statistics/generators/constituents/count_missing_generator.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  from tensorflow_data_validation import types
  from tensorflow_data_validation.statistics.generators import input_batch
  from tensorflow_data_validation.statistics.generators import stats_generator
  from typing import Iterable, Optional, Text, Tuple, Union
label_desc: Use image node_id 3 for calling the CountMissingGenerator obj's underlying member method code with example usage: obj.get_key() and returns: CountMissingGenerator