code: def mean_squared_error(true, pred):
      """L2 distance between tensors true and pred.
  
      Args:
        true: the ground truth image.
        pred: the predicted image.
      Returns:
        mean squared error between ground truth and predicted image.
      """
      result = tf.reduce_sum(
          tf.squared_difference(true, pred)
      ) / tf.to_float(tf.size(pred))
      return result
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from six.moves import reduce
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import common_video
  from tensor2tensor.models.video import epva_params
  from tensor2tensor.models.video import sv2p
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
  from tensorflow.contrib.framework.python.ops import arg_scope
  from tensorflow.contrib.slim.python.slim.nets import vgg
label_desc: Use image node_id 10 for calling a global function with example usage: mean_squared_error(true, pred) and returns: result