code: def testNormalStandardDeviation(self):
      # scale will be broadcast to [7, 7, 7]
      loc = [1.0, 2.0, 3.0]
      scale = [7.0]
      power = [1.0]
  
      gnormal = generalized_normal.GeneralizedNormal(
          loc=self.make_input(loc),
          scale=self.make_input(scale),
          power=self.make_input(power),
          validate_args=True,
      )
  
      self.assertAllEqual((3,), gnormal.stddev().shape)
      reference = 7.0 * np.sqrt(2.0) * np.ones_like(loc)
      self.assertAllClose(reference, self.evaluate(gnormal.stddev()))
  
imports: import math
  import numpy
  from scipy import stats
  from scipy.special import gamma
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import generalized_normal
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 16 for calling the _GeneralizedNormalTest obj's underlying member method code with example usage: obj.testNormalStandardDeviation() without return types