class_docstr: Tests correctness of the power transformation.
class_docstr_tok: ["Tests","correctness","of","the","power","transformation","."]
code: def testSkew(self):
      # Will broadcast together to shape [3, 2].
      x = [-1.0, 1.0]
      skewness = [[-1.0], [0.0], [1.0]]
      bijector = sinh_arcsinh.SinhArcsinh(
          skewness=skewness, validate_args=True
      )
      y = self.evaluate(bijector.forward(x))
  
      # For skew < 0, |forward(-1)| > |forward(1)|
      self.assertGreater(np.abs(y[0, 0]), np.abs(y[0, 1]))
  
      # For skew = 0, |forward(-1)| = |forward(1)|
      self.assertAllClose(np.abs(y[1, 0]), np.abs(y[1, 1]))
  
      # For skew > 0, |forward(-1)| < |forward(1)|
      self.assertLess(np.abs(y[2, 0]), np.abs(y[2, 1]))
  
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 2 for calling the SinhArcsinhTest obj's underlying member method code with example usage: obj.testSkew() without return types