class_docstr: Trainer for a classifier that always predicts the correct value.
code: def __init__(self, data):
      self.data = data
      self.vars_to_save = []
  
imports: import logging
  import os
  from .adversarial_dense import entropy_y_x
  from .adversarial_dense import get_loss_vat
  import numpy
  import tensorflow
  from .trainer_base import batch_iterator
  from .trainer_base import Trainer
label_desc: Use image node_id 1 to create a new TrainerPerfectClassification object from inherited base classes: Trainer with example: obj = TrainerPerfectClassification(data)