def transformer_tall_train_tied():
  """Tied means train 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 = 2e-4
  hparams.learning_rate_warmup_steps = 8000
  # Set train steps to learning_rate_decay_steps or less
  hparams.learning_rate_decay_steps = 150000
  hparams.multiproblem_target_eval_only = True
  hparams.multiproblem_reweight_label_loss = True
  hparams.multiproblem_label_weight = 1.0
  hparams.optimizer = "true_adam"
  return hparams
Tied means train CNN/DM summarization as LM.
tensor2tensor/models/transformer.py