code: def test_gan_inference(self):
      with self.test_session():
          (
              N,
              D,
              W_1,
              W_2,
              W_3,
              b_1,
              b_2,
              X,
              y,
              X_train,
              y_train,
          ) = self._test()
  
          with tf.variable_scope("Gen"):
              theta = tf.get_variable("theta", [1])
              y = tf.cast(y, tf.float32) * theta
  
          def discriminator(x):
              w = tf.get_variable("w", [1])
              return w * tf.cast(x, tf.float32)
  
          inference = ed.GANInference(
              data={y: tf.cast(y_train, tf.float32), X: X_train},
              discriminator=discriminator,
          )
          inference.run(n_iter=1)
  
file_path: edward/tests/inferences/bayesian_nn_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import edward
  import numpy
  import tensorflow
  from edward.models import Empirical, Bernoulli, Normal
label_desc: Use image node_id 2 for calling the test_inference_bayesian_nn_class obj's underlying member method code with example usage: obj.test_gan_inference() and returns: unknown