docstr: Loss function that is minimized at the mean of the input points.
docstr_tok: ["Loss","function","that","is","minimized","at","the","mean","of","the","input","points","."]
code: def _loss(self, val0, val1):
      """Loss function that is minimized at the mean of the input points."""
      return 0.5 * tf.reduce_sum(
          input_tensor=tf.math.squared_difference(val0, val1), axis=1
      )
  
imports: import os
  import unittest
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow import estimator
  from tensorflow.compat.v1 import estimator
  from tensorflow_privacy.privacy.dp_query import gaussian_query
  from tensorflow_privacy.privacy.optimizers import dp_optimizer
label_desc: Use image node_id 2 for calling the DPOptimizerTest obj's underlying member method code with example usage: obj._loss(val0, val1) and returns: unknown