code: def testInverseGaussianMean(self):
      loc_v = [2.0, 3.0, 2.5]
      concentration_v = [1.4, 2.0, 2.5]
      dist = inverse_gaussian.InverseGaussian(
          self.make_tensor(loc_v),
          self.make_tensor(concentration_v),
          validate_args=True,
      )
      if self.use_static_shape:
          self.assertEqual(dist.mean().shape, (3,))
      self.assertAllClose(
          self.evaluate(dist.mean()),
          _scipy_invgauss(
              np.array(loc_v), np.array(concentration_v)
          ).mean(),
      )
  
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 14 for calling the _InverseGaussianTest obj's underlying member method code with example usage: obj.testInverseGaussianMean() without return types