code: def gen_latent(x, hidden_units):
      net = tf.layers.dense(x, hidden_units, activation=leakyrelu)
      net = tf.layers.dense(net, FLAGS.d, activation=None)
      return net + np.sqrt(FLAGS.encoder_variance) * np.random.normal(
          0.0, 1.0, [FLAGS.M, FLAGS.d]
      )
  
file_path: edward/examples/bigan.py
imports: from __future__ import absolute_import
  from __future__ import print_function
  from __future__ import division
  import edward
  import matplotlib.pyplot
  import matplotlib.gridspec
  import numpy
  import os
  import tensorflow
  from observations import mnist
label_desc: Use image node_id 3 for calling a global function with example usage: gen_latent(x, hidden_units) and returns: unknown