code: def testInverseGaussianFullyReparameterized(self):
      concentration = tf.constant(4.0)
      loc = tf.constant(3.0)
      _, [grad_concentration, grad_loc] = gradient.value_and_gradient(
          lambda a, b: inverse_gaussian.InverseGaussian(
              a, b, validate_args=True
          ).sample(  # pylint: disable=g-long-lambda
              100, seed=test_util.test_seed()
          ),
          [concentration, loc],
      )
      self.assertIsNotNone(grad_concentration)
      self.assertIsNotNone(grad_loc)
  
imports: import numpy
  from scipy import misc
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import inverse_gaussian
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 22 for calling the _InverseGaussianTest obj's underlying member method code with example usage: obj.testInverseGaussianFullyReparameterized() without return types