code: def train_test_feats(
      label, instances, featx=bag_of_words, fraction=0.75
  ):
      labeled_instances = [(featx(i), label) for i in instances]
  
      if fraction != 1.0:
          l = len(instances)
          cutoff = int(math.ceil(l * fraction))
          return labeled_instances[:cutoff], labeled_instances[cutoff:]
      else:
          return labeled_instances, labeled_instances
  
imports: import math
  from nltk import probability
label_desc: Use image node_id 5 for calling a global function with example usage: train_test_feats(label, instances, featx, fraction) and returns: labeled_instances,  labeled_instances, labeled_instances,  labeled_instances