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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 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