code: def testNormalInverseGaussianScipyLogPdf(self):
      loc_v = self.dtype(0.0)
      scale_v = self.dtype(1.0)
      tailweight_v = self.dtype(1.0)
      skewness_v = self.dtype(0.2)
      x_v = np.array([3.0, 3.1, 4.0, 5.0, 6.0, 7.0]).astype(self.dtype)
      normal_inverse_gaussian = nig.NormalInverseGaussian(
          loc_v, scale_v, tailweight_v, skewness_v, validate_args=True
      )
  
      log_prob = normal_inverse_gaussian.log_prob(x_v)
      self.assertAllClose(
          self.evaluate(log_prob),
          stats.norminvgauss(
              a=tailweight_v, b=skewness_v, loc=loc_v, scale=scale_v
          ).logpdf(x_v),
      )
  
      pdf = normal_inverse_gaussian.prob(x_v)
      self.assertAllClose(
          self.evaluate(pdf),
          stats.norminvgauss(
              a=tailweight_v, b=skewness_v, loc=loc_v, scale=scale_v
          ).pdf(x_v),
      )
  
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 4 for calling the _NormalInverseGaussianTest obj's underlying member method code with example usage: obj.testNormalInverseGaussianScipyLogPdf() without return types