code: def int2str(self, int_value):
      
      if self._int2str:
        # Maybe should support batched np array/eager tensors, to allow things
        # like
        # out_ids = model(inputs)
        # labels = cifar10.info.features['label'].int2str(out_ids)
        return self._int2str[int_value]
  
      # No names provided, return str(int)
      if not 0 <= int_value < self._num_classes:
        raise ValueError("Invalid integer class label %d" % int_value)
      return tf.compat.as_text(str(int_value))
docs: Conversion integer => class name string.