code: def get_random_remapping(old_size, new_size):
      base = np.arange(old_size)
      indices = np.concatenate(
          [base, np.random.choice(base, new_size - old_size)]
      )
  
      magnifier = get_magnifier(old_size, indices)
      return indices, magnifier
  
imports: from .basic_model import BasicModel
  import tensorflow
  import numpy
  import copy
label_desc: Use image node_id 4 for calling a global function with example usage: get_random_remapping(old_size, new_size) and returns: indices,  magnifier