Set of hyperparameters.

def distill_resnet_32_to_15_cifar20x5():
  """Set of hyperparameters."""
  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