class_docstr: Wrapper class on top of the Keras-native data generators. These can either be generator functions,
  `keras.utils.Sequence` or Keras-specific data generators (`keras.preprocessing.image.ImageDataGenerator`).
docstr: Provide the next batch for training in the form of a tuple `(x, y)`. The generator should loop over the data
  indefinitely.
  
  :return: A tuple containing a batch of data `(x, y)`.
code: def get_batch(self) -> tuple:
      """
      Provide the next batch for training in the form of a tuple `(x, y)`. The generator should loop over the data
      indefinitely.
  
      :return: A tuple containing a batch of data `(x, y)`.
      """
      if inspect.isgeneratorfunction(self.iterator):
          return next(self.iterator)
  
      iter_ = iter(self.iterator)
      return next(iter_)
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import abc
  import inspect
  import logging
  from typing import Any, Dict, Generator, Iterator, Optional, Tuple, Union, TYPE_CHECKING
  import numpy
label_desc: Use image node_id 2 for calling the KerasDataGenerator obj's underlying member method code with example usage: obj.get_batch() and returns: next, next