code: def testNormalInverseGaussianShape(self):
      loc = tf.ones([2, 1, 1, 1], dtype=self.dtype)
      scale = tf.ones([1, 3, 1, 1], dtype=self.dtype)
      tailweight = 2 * tf.ones([1, 1, 5, 1], dtype=self.dtype)
      skewness = tf.ones([1, 1, 1, 7], dtype=self.dtype)
      normal_inverse_gaussian = nig.NormalInverseGaussian(
          loc, scale, tailweight, skewness, validate_args=True
      )
  
      self.assertAllEqual(
          self.evaluate(normal_inverse_gaussian.batch_shape_tensor()),
          (2, 3, 5, 7),
      )
      self.assertEqual(
          normal_inverse_gaussian.batch_shape,
          tf.TensorShape([2, 3, 5, 7]),
      )
      self.assertAllEqual(
          self.evaluate(normal_inverse_gaussian.event_shape_tensor()),
          [],
      )
      self.assertEqual(
          normal_inverse_gaussian.event_shape, tf.TensorShape([])
      )
  
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 1 for calling the _NormalInverseGaussianTest obj's underlying member method code with example usage: obj.testNormalInverseGaussianShape() without return types