class_docstr: Adapter for `keras.utils.PyDataset` instances.
code: def get_tf_dataset(self):
      from keras.utils.module_utils import tensorflow as tf
  
      if self._output_signature is None:
          self._set_tf_output_signature()
  
      ds = tf.data.Dataset.from_generator(
          self.get_numpy_iterator,
          output_signature=self._output_signature,
      )
      if self.shuffle:
          ds = ds.shuffle(8)
      ds = ds.prefetch(tf.data.AUTOTUNE)
      return ds
  
imports: import multiprocessing.dummy
  import queue
  import random
  import threading
  import time
  import warnings
  import weakref
  from contextlib import closing
  import numpy
  import tree
  from keras.api_export import keras_export
  from keras.trainers.data_adapters import data_adapter_utils
  from keras.trainers.data_adapters.data_adapter import DataAdapter
label_desc: Use image node_id 6 for calling the PyDatasetAdapter obj's underlying member method code with example usage: obj.get_tf_dataset() and returns: ds