code: def main(_):
      ed.set_seed(42)
  
      # MODEL
      z = MultivariateNormalTriL(
          loc=tf.ones(2),
          scale_tril=tf.cholesky(tf.constant([[1.0, 0.8], [0.8, 1.0]])),
      )
  
      # INFERENCE
      qz = Empirical(params=tf.get_variable("qz/params", [2000, 2]))
  
      inference = ed.SGLD({z: qz})
      inference.run(step_size=5.0)
  
      # CRITICISM
      sess = ed.get_session()
      mean, stddev = sess.run([qz.mean(), qz.stddev()])
      print("Inferred posterior mean:")
      print(mean)
      print("Inferred posterior stddev:")
      print(stddev)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import edward
  import tensorflow
  from edward.models import Empirical, MultivariateNormalTriL
label_desc: Use image node_id 1 for calling a global function with example usage: main(_) without return types