class_docstr: Data generator with an optional increasing batch size.
class_docstr_tok: ["Data","generator","with","an","optional","increasing","batch","size","."]
docstr: Gets batch at position `index`.
  
  Arguments:
      index: position of the batch in the Sequence.
  
  Returns:
      A batch (tuple of input data and target data).
docstr_tok: ["Gets","batch","at","position","`","index","`",".","Arguments",":","index",":","position","of","the","batch","in","the","Sequence",".","Returns",":","A","batch","(","tuple","of","input","data","and","target","data",")","."]
code: def __getitem__(self, index: int) -> Tuple[Any, Any]:
      """Gets batch at position `index`.
  
      Arguments:
          index: position of the batch in the Sequence.
  
      Returns:
          A batch (tuple of input data and target data).
      """
      start = index * self._current_batch_size
      end = start + self._current_batch_size
  
      # return input and target data, as our target data is inside the input
      # data return None for the target data
      return self.prepare_batch(self._data, start, end), None
  
imports: import math
  from typing import List, Union, Text, Optional, Any, Tuple, Dict, cast
  import logging
  import scipy.sparse
  import numpy
  from tensorflow.keras.utils import Sequence
  from rasa.utils.tensorflow.constants import SEQUENCE, BALANCED
  from rasa.utils.tensorflow.model_data import RasaModelData, Data, FeatureArray
label_desc: Use image node_id 3 for calling the RasaBatchDataGenerator obj's underlying member method code with example usage: obj.__getitem__(index) and returns: self,  None