def transformer_big():
  """HParams for transformer big model on WMT."""
  hparams = transformer_base()
  hparams.hidden_size = 1024
  hparams.filter_size = 4096
  # Reduce batch size to 2048 from 4096 to be able to train the model on a GPU
  # with 12 GB memory. For example, NVIDIA TITAN V GPU.
  hparams.batch_size = 2048
  hparams.num_heads = 16
  hparams.layer_prepostprocess_dropout = 0.3
  return hparams
def transformer_big ( ) : hparams = transformer_base ( ) hparams . hidden_size = 1024 hparams . filter_size = 4096 hparams . batch_size = 2048 hparams . num_heads = 16 hparams . layer_prepostprocess_dropout = 0.3 return hparams
HParams for transformer big model on WMT.