class_docstr: Tests correctness of the power transformation.
class_docstr_tok: ["Tests","correctness","of","the","power","transformation","."]
code: def testVariableTailweight(self):
      x = tf.Variable(1.0)
      b = sinh_arcsinh.SinhArcsinh(tailweight=x, validate_args=True)
      self.evaluate(x.initializer)
      self.assertIs(x, b.tailweight)
      self.assertEqual((), self.evaluate(b.forward(0.5)).shape)
      with self.assertRaisesOpError(
          "Argument `tailweight` must be positive."
      ):  # pylint:disable=g-error-prone-assert-raises
          with tf.control_dependencies([x.assign(-1.0)]):
              self.assertEqual((), self.evaluate(b.forward(0.5)).shape)
  
file_path: probability/tensorflow_probability/python/bijectors/sinh_arcsinh_test.py
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector_test_util
  from tensorflow_probability.python.bijectors import sinh_arcsinh
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 12 for calling the SinhArcsinhTest obj's underlying member method code with example usage: obj.testVariableTailweight() without return types