code: def fetch_fashion_mnist(
      return_X_y: bool = False,
  ) -> Union[Bunch, Tuple[np.ndarray, np.ndarray]]:
      """
      Loads the Fashion MNIST dataset.
  
      Parameters
      ----------
      return_X_y:
          If ``True``, an `N x M x P` array of data points and `N`-array of labels are returned
          instead of a dict.
  
      Returns
      -------
      If ``return_X_y=False``, a Bunch object with fields 'data', 'targets' and 'target_names'
      is returned. Otherwise an array with data points and an array of labels is returned.
      """
  
      target_names = {
          0: "T-shirt/top",
          1: "Trouser",
          2: "Pullover",
          3: "Dress",
          4: "Coat",
          5: "Sandal",
          6: "Shirt",
          7: "Sneaker",
          8: "Bag",
          9: "Ankle boot",
      }
  
      data, labels = keras.datasets.fashion_mnist.load_data()[0]
  
      if return_X_y:
          return data, labels
  
      return Bunch(data=data, target=labels, target_names=target_names)
  
imports: from typing import Tuple, Union
  import tensorflow.keras
  import numpy
  from alibi.utils.data import Bunch
label_desc: Use image node_id 1 for calling a global function with example usage: fetch_fashion_mnist(return_X_y) and returns: Bunch, data,  labels