class_docstr: Generate statistics.
docstr: (Experimental) Return a copy set to a specific partition index.
  
  If supported, a partitioned StatsGenerator should completely process a
  subset of features or cross features matching its partition index. Each
  partitioned copy will receive the same RecordBatch inputs.
  
  Args:
    index: The feature partition index of the copy.
    num_partitions: The overall number of feature partitions.
  
  Returns:
    A StatsGenerator of the same type as self.
  
  Raises:
    NotImplementedError.
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code: def _copy_for_partition_index(
      self, index: int, num_partitions: int
  ) -> "StatsGenerator":
      """(Experimental) Return a copy set to a specific partition index.
  
      If supported, a partitioned StatsGenerator should completely process a
      subset of features or cross features matching its partition index. Each
      partitioned copy will receive the same RecordBatch inputs.
  
      Args:
        index: The feature partition index of the copy.
        num_partitions: The overall number of feature partitions.
  
      Returns:
        A StatsGenerator of the same type as self.
  
      Raises:
        NotImplementedError.
      """
      raise NotImplementedError(
          "_copy_for_partition_index not implemented for %s" % self.name
      )
  
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 4 for calling the StatsGenerator obj's underlying member method code with example usage: obj._copy_for_partition_index(index, num_partitions) without return types