code: def testInverseGaussianSampleMultidimensionalVariance(self):
      loc_v = 3.0
      concentration_v = np.array([np.arange(1, 11)])
      n = int(1e6)
      dist = inverse_gaussian.InverseGaussian(
          self.make_tensor(loc_v),
          self.make_tensor(concentration_v),
          validate_args=True,
      )
      samples = dist.sample(n, seed=test_util.test_seed())
      sample_values = self.evaluate(samples)
  
      if self.use_static_shape:
          self.assertEqual(samples.shape, (n, 1, 10))
      self.assertEqual(sample_values.shape, (n, 1, 10))
      self.assertAllClose(
          sample_values.var(axis=0),
          _scipy_invgauss(loc_v, concentration_v).var(),
          rtol=0.02,
          atol=0,
      )
  
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 21 for calling the _InverseGaussianTest obj's underlying member method code with example usage: obj.testInverseGaussianSampleMultidimensionalVariance() without return types