class_docstr: Test loss function for testing BoltOn model.
class_docstr_tok: ["Test","loss","function","for","testing","BoltOn","model","."]
docstr: Radius, R, of the hypothesis space W.
  
  W is a convex set that forms the hypothesis space.
  
  Returns:
    a tensor
docstr_tok: ["Radius",",","R",",","of","the","hypothesis","space","W.","W","is","a","convex","set","that","forms","the","hypothesis","space",".","Returns",":","a","tensor"]
code: def radius(self):
      """Radius, R, of the hypothesis space W.
  
      W is a convex set that forms the hypothesis space.
  
      Returns:
        a tensor
      """
      return _ops.convert_to_tensor_v2(
          self.radius_constant, dtype=tf.float32
      )
  
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 2 for calling the TestLoss obj's underlying member method code with example usage: obj.radius() and returns: _ops