def iwslt_baseline_tpu():
  """HParams for Transformer model on TPU."""
  hparams = transformer.transformer_base()
  transformer.update_hparams_for_tpu(hparams)
  hparams.hidden_size = 256
  hparams.filter_size = 1024
  hparams.num_hidden_layers = 5
  hparams.num_heads = 2
  hparams.layer_prepostprocess_dropout = 0.1
  hparams.attention_dropout = 0.1
  hparams.relu_dropout = 0.1
  hparams.dropout = 0.1
  hparams.add_hparam("pos_attn", False)
  return hparams
HParams for Transformer model on TPU.
tensor2tensor/models/research/transformer_vae_flow_prior.py