code: def __init__(
      self,
      x,
      batch_size: int = 512,
      max_size: int = 10000,
      validation_f: float = 0.1,
  ):
      self._x = x
      self._max_size = max_size
      self._validation_size = min(
          int(max_size * validation_f),
          self._x.shape[0] - self._max_size,
      )
      self._index = np.arange(x.shape[0])
      self._batch_size = batch_size
  
file_path: AIX360/aix360/algorithms/nncontrastive/utils.py
imports: import math
  import numpy
  from tensorflow.keras.utils import Sequence
  from sklearn.model_selection import StratifiedShuffleSplit
label_desc: Use image node_id 1 to create a new AESampler object from inherited base classes: Sequence with example: obj = AESampler(x, batch_size, max_size, validation_f)