code: def testNormalInverseGaussianVarianceScale1(self):
      loc_v = (
          np.linspace(-10.0, 10.0, 5)
          .astype(self.dtype)
          .reshape((5, 1, 1, 1))
      )
      scale_v = self.dtype(1.0)
      tailweight_v = np.array([2.0, 0.5], dtype=self.dtype).reshape(
          (2, 1)
      )
      skewness_v = 0.5 * tailweight_v
      normal_inverse_gaussian = nig.NormalInverseGaussian(
          loc_v, scale_v, tailweight_v, skewness_v, validate_args=True
      )
      self.assertAllClose(
          self.evaluate(normal_inverse_gaussian.variance()),
          stats.norminvgauss(
              a=tailweight_v, b=skewness_v, loc=loc_v, scale=scale_v
          ).var(),
      )
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import normal_inverse_gaussian
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 7 for calling the _NormalInverseGaussianTest obj's underlying member method code with example usage: obj.testNormalInverseGaussianVarianceScale1() without return types