class_docstr: Well tested because this is a simple override of the base class.
code: def testScalarParams(self):
      mu = -1.0
      diag = -5.0
      with self.assertRaisesRegexp(ValueError, "at least 1 dimension"):
          mvn_diag.MultivariateNormalDiag(mu, diag)
  
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 2 for calling the MultivariateNormalDiagTest obj's underlying member method code with example usage: obj.testScalarParams() without return types