class_docstr: Well tested because this is a simple override of the base class.
code: def testMeanWithBroadcastLoc(self):
      mu = [-1.0]
      diag = [1.0, -5]
      dist = mvn_diag.MultivariateNormalDiag(
          mu, diag, validate_args=True
      )
      self.assertAllEqual([-1.0, -1.0], self.evaluate(dist.mean()))
  
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 6 for calling the MultivariateNormalDiagTest obj's underlying member method code with example usage: obj.testMeanWithBroadcastLoc() without return types