import tensorflow as tf

            tf.expand_dims(tf.nn.softmax(logits_reversed), 4))

  for output in sorted(outputs_to_predictions):
    predictions = outputs_to_predictions[output]
    # Compute average prediction across different scales and flipped images.
    predictions = tf.reduce_mean(tf.concat(predictions, 4), axis=4)
    outputs_to_predictions[output] = tf.argmax(predictions, 3)

  return outputs_to_predictions


def predict_labels(images, model_options, image_pyramid=None):
