class_docstr: Well tested because this is a simple override of the base class.
code: def testEntropy(self):
      mu = [-1.0, 1]
      diag = [-1.0, 5]
      diag_mat = np.diag(diag)
      scipy_mvn = stats.multivariate_normal(mean=mu, cov=diag_mat**2)
      dist = mvn_diag.MultivariateNormalDiag(
          mu, diag, validate_args=True
      )
      self.assertAllClose(
          scipy_mvn.entropy(), self.evaluate(dist.entropy()), atol=1e-4
      )
  
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 7 for calling the MultivariateNormalDiagTest obj's underlying member method code with example usage: obj.testEntropy() without return types