class_docstr: Well tested because this is a simple override of the base class.
code: def testProbForLargeDimIsNotNan(self):
      # Verifies a fix for GitHub issue #223
      # (https://github.com/tensorflow/probability/issues/223)
      loc_ = np.tile([0.0], 1000)
      scale_diag_ = np.tile([0.1], 1000)
      dist_test = mvn_diag.MultivariateNormalDiag(loc_, scale_diag_)
  
      x_ = np.tile([1.0], 1000)
      p_ = self.evaluate(dist_test.prob(x_))
      self.assertFalse(np.isnan(p_))
  
imports: import os
  from absl.testing import parameterized
  import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import lognormal
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 18 for calling the MultivariateNormalDiagTest obj's underlying member method code with example usage: obj.testProbForLargeDimIsNotNan() without return types