def img2img_transformer2d_base():
  """Base params for img2img 2d attention."""
  hparams = image_transformer2d_base()
  # learning related flags
  hparams.layer_preprocess_sequence = "n"
  hparams.layer_postprocess_sequence = "da"
  # This version seems to benefit from a higher learning rate.
  hparams.learning_rate = 0.2
  hparams.layer_prepostprocess_dropout = 0.1
  hparams.learning_rate_warmup_steps = 12000
  hparams.filter_size = 2048
  hparams.num_encoder_layers = 4
  hparams.num_decoder_layers = 8
  hparams.bottom["inputs"] = modalities.image_channel_embeddings_bottom
  hparams.dec_attention_type = cia.AttentionType.LOCAL_2D
  hparams.block_raster_scan = True
  return hparams
Base params for img2img 2d attention.