original_docstring: Produces multiple transformations of the same batch.
docstring: Produces multiple transformations of the same batch.
docstring_tokens: Produces multiple transformations of the same batch .
code: def map_fn(image, label):
        """Produces multiple transformations of the same batch."""
        if is_training and FLAGS.train_mode == 'pretrain':
          xs = []
          for _ in range(2):  # Two transformations
            xs.append(preprocess_fn_pretrain(image))
          image = tf.concat(xs, -1)
        else:
          image = preprocess_fn_finetune(image)
        label = tf.one_hot(label, num_classes)
        return image, label
code_tokens: def map_fn ( image , label ) : if is_training and FLAGS . train_mode == 'pretrain' : xs = [ ] for _ in range ( 2 ) : xs . append ( preprocess_fn_pretrain ( image ) ) image = tf . concat ( xs , - 1 ) else : image = preprocess_fn_finetune ( image ) label = tf . one_hot ( label , num_classes ) return image , label
short_docstring: Produces multiple transformations of the same batch.
short_docstring_tokens: Produces multiple transformations of the same batch .
comment: """Produces multiple transformations of the same batch."""$SEP$# Two transformations