Tied means fine-tune CNN/DM summarization as LM.

def transformer_tall_finetune_tied():
  """Tied means fine-tune CNN/DM summarization as LM."""
  hparams = transformer_tall()
  hparams.multiproblem_max_input_length = 750
  hparams.multiproblem_max_target_length = 100
  hparams.multiproblem_schedule_max_examples = 0
  hparams.learning_rate_schedule = ("linear_warmup*constant*cosdecay")
  hparams.learning_rate_constant = 5e-5
  hparams.learning_rate_warmup_steps = 100
  # Set train steps to learning_rate_decay_steps or less
  hparams.learning_rate_decay_steps = 80000
  hparams.multiproblem_target_eval_only = True
  hparams.multiproblem_reweight_label_loss = True
  hparams.multiproblem_label_weight = 1.0
  hparams.optimizer = "true_adam"
  return hparams