code: def testScaleRegularizationLoss(self, distribution):
      # Without strategy - num replicas = 1
      reg_losses = constant_op.constant([2.5, 6.2, 5.0])
      loss = nn_impl_distribute.scale_regularization_loss(reg_losses)
      self.assertAllClose(self.evaluate(loss), (2.5 + 6.2 + 5.0))
  
      # With strategy - num replicas = 2
      with distribution.scope():
          per_replica_losses = distribution.run(
              nn_impl_distribute.scale_regularization_loss,
              args=(reg_losses,),
          )
          loss = distribution.reduce(
              "SUM", per_replica_losses, axis=None
          )
          self.assertAllClose(self.evaluate(loss), (2.5 + 6.2 + 5.0))
  
imports: from absl.testing import parameterized
  from tensorflow.python.distribute import combinations
  from tensorflow.python.distribute import strategy_combinations
  from tensorflow.python.eager import context
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import nn_impl_distribute
  from tensorflow.python.platform import test
label_desc: Use image node_id 14 for calling the LossUtilitiesTest obj's underlying member method code with example usage: obj.testScaleRegularizationLoss(distribution) without return types