code: def distill_resnet_32_to_15_cifar20x5():
    
    hparams = distill_base()
    hparams.teacher_model = "resnet"
    hparams.teacher_hparams = "resnet_cifar_32"
    hparams.student_model = "resnet"
    hparams.student_hparams = "resnet_cifar_15"
  
    hparams.optimizer_momentum_nesterov = True
    # (base_lr=0.1) * (batch_size=128*8 (on TPU, or 8 GPUs)=1024) / (256.)
    hparams.teacher_learning_rate = 0.25 * 128. * 8. / 256.
    hparams.student_learning_rate = 0.2 * 128. * 8. / 256.
    hparams.learning_rate_decay_scheme = "piecewise"
    hparams.add_hparam("learning_rate_boundaries", [40000, 60000, 80000])
    hparams.add_hparam("learning_rate_multiples", [0.1, 0.01, 0.001])
  
    hparams.task_balance = 0.28
    hparams.distill_temperature = 2.0
  
    hparams.num_classes = 20
  
    return hparams
docs: Set of hyperparameters.