class_docstr: Generate statistics.
docstr: Initializes a statistics generator.
  
  Args:
    name: A unique name associated with the statistics generator.
    schema: An optional schema for the dataset.
docstr_tok: ["Initializes","a","statistics","generator",".","Args",":","name",":","A","unique","name","associated","with","the","statistics","generator",".","schema",":","An","optional","schema","for","the","dataset","."]
code: def __init__(
      self, name: Text, schema: Optional[schema_pb2.Schema] = None
  ) -> None:
      """Initializes a statistics generator.
  
      Args:
        name: A unique name associated with the statistics generator.
        schema: An optional schema for the dataset.
      """
      self._name = name
      self._schema = schema
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
  from typing import Any, Dict, Generic, Hashable, Iterable, List, Optional, Text, TypeVar
  import apache_beam
  import pyarrow
  from tensorflow_data_validation import types
  from tensorflow_data_validation.statistics.generators import input_batch
  from tensorflow_metadata.proto.v0 import schema_pb2
  from tensorflow_metadata.proto.v0 import statistics_pb2
label_desc: Use image node_id 1 to create a new StatsGenerator object from inherited base classes: object with example: obj = StatsGenerator(name, schema)