code: def test_that_gamma_fitting_example_runs(self):
      model = self._make_gamma_model()
      surrogate_posterior = (
          surrogate_posteriors.build_affine_surrogate_posterior(
              model.event_shape_tensor()[:-1],
              operators=[
                  [tf.linalg.LinearOperatorLowerTriangular],
                  [None, tf.linalg.LinearOperatorDiag],
              ],
              bijector=[softplus.Softplus(), softplus.Softplus()],
              base_distribution=logistic.Logistic,
              validate_args=True,
          )
      )
      self._test_fitting(model, surrogate_posterior)
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.bijectors import fill_triangular
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.bijectors import joint_map
  from tensorflow_probability.python.bijectors import masked_autoregressive
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import deterministic
  from tensorflow_probability.python.distributions import exponential
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import joint_distribution_coroutine
  from tensorflow_probability.python.distributions import joint_distribution_named
  from tensorflow_probability.python.distributions import joint_distribution_sequential
  from tensorflow_probability.python.distributions import laplace
  from tensorflow_probability.python.distributions import logistic
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.distributions import student_t
  from tensorflow_probability.python.experimental.vi import surrogate_posteriors
  from tensorflow_probability.python.internal import nest_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.internal import tf_keras
  from tensorflow_probability.python.vi import optimization
  from tensorflow.python.util import nest
label_desc: Use image node_id 6 for calling the AffineSurrogatePosterior obj's underlying member method code with example usage: obj.test_that_gamma_fitting_example_runs() without return types