code: def make_vars(self):
      with tf.variable_scope("logit", reuse=tf.AUTO_REUSE):
          w = tf.get_variable(
              "DW",
              [self.dim, self.num_hid],
              initializer=tf.initializers.variance_scaling(
                  distribution="uniform"
              ),
          )
          b = tf.get_variable(
              "biases",
              [self.num_hid],
              initializer=tf.initializers.constant(),
          )
      return w, b
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow
  from cleverhans.serial import NoRefModel
label_desc: Use image node_id 3 for calling the Linear obj's underlying member method code with example usage: obj.make_vars() and returns: w,  b