code: def testInverseGaussianLogPdfValidateArgs(self):
      batch_size = 2
      loc = self.make_tensor([2.0] * batch_size)
      concentration = self.make_tensor([2.0, 3.0])
      x = self.make_tensor([-1.0, 2.0])
      dist = inverse_gaussian.InverseGaussian(
          loc, concentration, validate_args=True
      )
  
      with self.assertRaisesOpError("must be non-negative."):
          self.evaluate(dist.log_prob(x))
  
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 7 for calling the _InverseGaussianTest obj's underlying member method code with example usage: obj.testInverseGaussianLogPdfValidateArgs() without return types