code: def discriminator(x, reuse=False):
      with tf.variable_scope("Discriminator", reuse=reuse):
          x = tflearn.conv_2d(x, 64, 5, activation="tanh")
          x = tflearn.avg_pool_2d(x, 2)
          x = tflearn.conv_2d(x, 128, 5, activation="tanh")
          x = tflearn.avg_pool_2d(x, 2)
          x = tflearn.fully_connected(x, 1024, activation="tanh")
          x = tflearn.fully_connected(x, 2)
          x = tf.nn.softmax(x)
          return x
  
file_path: tflearn/examples/images/dcgan.py
imports: from __future__ import division, print_function, absolute_import
  import matplotlib.pyplot
  import numpy
  import tensorflow.compat.v1
  import tflearn
  import tflearn.datasets.mnist
label_desc: Use image node_id 2 for calling a global function with example usage: discriminator(x, reuse) and returns: x