code: def feed_forward(self):
      # a new pop_batch_op for each gpu tower
      data_x = self.get_sampler()[0][0].pop_batch_op()
      features = tf.cast(
          data_x["vectors"], tf.float32, name="sampler_input"
      )
      features = tf.expand_dims(features, axis=-1, name="feature_input")
      noise = tf.random_uniform(tf.shape(features), 0.0, 1.0)
      real_logits, fake_logits, fake_features = self.net(
          features, noise
      )
      return fake_features, fake_logits, real_logits
  
imports: from __future__ import absolute_import, print_function
  import tensorflow
  from niftynet.application.base_application import BaseApplication
  from niftynet.engine.application_factory import ApplicationNetFactory
  from niftynet.engine.application_factory import OptimiserFactory
  from niftynet.engine.application_variables import CONSOLE
  from niftynet.engine.application_variables import TF_SUMMARIES
  from niftynet.engine.sampler_random_vector_v2 import RandomVectorSampler
  from niftynet.layer.convolution import ConvolutionalLayer
  from niftynet.layer.fully_connected import FullyConnectedLayer
  from niftynet.network.base_net import BaseNet
label_desc: Use image node_id 8 for calling the ToyApplication obj's underlying member method code with example usage: obj.feed_forward() and returns: fake_features,  fake_logits,  real_logits