code: def discriminator_loss(true_output, fake_output):
      true_loss = cross_entropy(tf.ones_like(true_output), true_output)
      fake_loss = cross_entropy(tf.zeros_like(fake_output), fake_output)
      tot_loss = true_loss + fake_loss
      return tot_loss
  
file_path: adversarial-robustness-toolbox/examples/backdoor_attack_dgm_trail.py
imports: import numpy
  import tensorflow
  from art.attacks.poisoning.backdoor_attack_dgm.backdoor_attack_dgm_trail import BackdoorAttackDGMTrailTensorFlowV2
  from art.estimators.gan.tensorflow import TensorFlowV2GAN
  from art.estimators.generation.tensorflow import TensorFlowV2Generator
  from art.estimators.classification.tensorflow import TensorFlowV2Classifier
label_desc: Use image node_id 3 for calling a global function with example usage: discriminator_loss(true_output, fake_output) and returns: tot_loss