code: def _fully_connected(self, x, out_dim):
          
          x = tf.reshape(x, [self.hps.batch_size, -1])
          w = tf.get_variable(
              "DW", [x.get_shape()[1], out_dim],
              initializer=tf.uniform_unit_scaling_initializer(factor=1.0))
          b = tf.get_variable(
              "biases", [out_dim], initializer=tf.constant_initializer())
          return tf.nn.xw_plus_b(x, w, b)
docs: FullyConnected layer for final output.