class_docstr: Test loss function for testing BoltOn model.
class_docstr_tok: ["Test","loss","function","for","testing","BoltOn","model","."]
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 call(self, y_true, y_pred):
      """Loss function that is minimized at the mean of the input points."""
      return 0.5 * tf.reduce_sum(
          tf.math.squared_difference(y_true, y_pred), axis=1
      )
  
imports: import unittest
  from absl.testing import parameterized
  import tensorflow.compat.v1
  from tensorflow.compat.v1.python import ops
  from tensorflow.compat.v1.python.framework import test_util
  from tensorflow.compat.v1.python.keras import keras_parameterized
  from tensorflow.compat.v1.python.keras import losses
  from tensorflow.compat.v1.python.keras.initializers import constant
  from tensorflow.compat.v1.python.keras.models import Model
  from tensorflow.compat.v1.python.keras.optimizer_v2.optimizer_v2 import OptimizerV2
  from tensorflow.compat.v1.python.keras.regularizers import L1L2
  from tensorflow.compat.v1.python.platform import test
  from tensorflow_privacy.privacy.bolt_on import optimizers
  from tensorflow_privacy.privacy.bolt_on.losses import StrongConvexMixin
label_desc: Use image node_id 6 for calling the TestLoss obj's underlying member method code with example usage: obj.call(y_true, y_pred) and returns: unknown