code: def G_wgan(G, D, opt, training_set, minibatch_size):
      _ = opt
      latents = tf.random_normal(
          [minibatch_size] + G.input_shapes[0][1:]
      )
      labels = training_set.get_random_labels_tf(minibatch_size)
      fake_images_out = G.get_output_for(
          latents, labels, is_training=True
      )
      fake_scores_out = D.get_output_for(
          fake_images_out, labels, is_training=True
      )
      loss = -fake_scores_out
      return loss, None
  
file_path: insightface/reconstruction/ostec/external/stylegan2/training/loss.py
imports: import numpy
  import tensorflow
  import dnnlib.tflib
  from dnnlib.tflib.autosummary import autosummary
label_desc: Use image node_id 6 for calling a global function with example usage: G_wgan(G, D, opt, training_set, minibatch_size) and returns: loss,  None