code: def unpadded_mse(
      predictions, labels, weights_fn=common_layers.weights_all
  ):
      predictions = tf.to_float(predictions)
      labels = tf.to_float(labels)
      weights = weights_fn(labels)
      error = tf.pow(predictions - labels, 2)
      mean_error = tf.reduce_mean(error * weights)
      return mean_error, tf.reduce_sum(weights)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import six
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import modalities
  from tensor2tensor.utils import bleu_hook
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import rouge
  from tensor2tensor.utils import sari_hook
  import tensorflow.compat.v1
  from tensorflow.python.util import tf_inspect
label_desc: Use image node_id 3 for calling a global function with example usage: unpadded_mse(predictions, labels, weights_fn) and returns: mean_error,  tf