class_docstr: Test loss function for testing BoltOn model.
class_docstr_tok: ["Test","loss","function","for","testing","BoltOn","model","."]
code: def __init__(self, reg_lambda, c_arg, radius_constant, name="test"):
      super(TestLoss, self).__init__(name=name)
      self.reg_lambda = reg_lambda
      self.C = c_arg  # pylint: disable=invalid-name
      self.radius_constant = radius_constant
  
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 1 to create a new TestLoss object from inherited base classes: losses, StrongConvexMixin with example: obj = TestLoss(reg_lambda, c_arg, radius_constant, name)