code: def map_fn(input_slice: Dict[str, tf.Tensor]):
      updated = input_slice
      image = to_default_float(updated["image"]) / 255.0
      label = to_default_float(updated["label"])
      return tf.reshape(image, [-1, image_size]), label
  
file_path: GPflow/doc/sphinx/notebooks/tailor/gp_nn.pct.py
imports: from typing import Dict, Optional, Tuple
  import numpy
  import tensorflow
  import tensorflow_datasets
  from scipy.cluster.vq import kmeans2
  import gpflow
  from gpflow.ci_utils import reduce_in_tests
  from gpflow.utilities import to_default_float
label_desc: Use image node_id 1 for calling a global function with example usage: map_fn(input_slice) and returns: tf,  label