class_docstr: Builds a Enqueuer from a PyDataset.
  
  Args:
      py_dataset: A `keras.utils.PyDataset` object.
      use_multiprocessing: use multiprocessing if True, otherwise threading
      shuffle: whether to shuffle the data at the beginning of each epoch
code: def __init__(
      self, py_dataset, use_multiprocessing=False, shuffle=False
  ):
      super().__init__(py_dataset, use_multiprocessing)
      self.shuffle = shuffle
  
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 1 to create a new OrderedEnqueuer object from inherited base classes: PyDatasetEnqueuer with example: obj = OrderedEnqueuer(py_dataset, use_multiprocessing, shuffle)