code: def __init__(
      self,
      x_set,
      y_set,
      sample_weight=None,
      batch_size=32,
      delay=0,
      **kwargs,
  ):
      super().__init__(**kwargs)
      self.x, self.y = x_set, y_set
      self.batch_size = batch_size
      self.sample_weight = sample_weight
      self.delay = delay
  
imports: import math
  import time
  import numpy
  import tensorflow
  from absl.testing import parameterized
  from keras import testing
  from keras.trainers.data_adapters import py_dataset_adapter
  from keras.utils.rng_utils import set_random_seed
label_desc: Use image node_id 1 to create a new ExamplePyDataset object from inherited base classes: py_dataset_adapter with example: obj = ExamplePyDataset(x_set, y_set, sample_weight, batch_size, delay)