code: def transformer_vaswani_wmt_en_de_big(args):
      args.encoder_embed_dim = getattr(args, "encoder_embed_dim", 1024)
      args.encoder_ffn_embed_dim = getattr(
          args, "encoder_ffn_embed_dim", 4096
      )
      args.encoder_attention_heads = getattr(
          args, "encoder_attention_heads", 16
      )
      args.encoder_normalize_before = getattr(
          args, "encoder_normalize_before", False
      )
      args.decoder_embed_dim = getattr(args, "decoder_embed_dim", 1024)
      args.decoder_ffn_embed_dim = getattr(
          args, "decoder_ffn_embed_dim", 4096
      )
      args.decoder_attention_heads = getattr(
          args, "decoder_attention_heads", 16
      )
      args.dropout = getattr(args, "dropout", 0.3)
      base_architecture(args)
  
imports: from fairseq.dataclass.utils import gen_parser_from_dataclass
  from fairseq.models import register_model, register_model_architecture
  from fairseq.models.transformer.transformer_config import TransformerConfig, DEFAULT_MAX_SOURCE_POSITIONS, DEFAULT_MAX_TARGET_POSITIONS, DEFAULT_MIN_PARAMS_TO_WRAP
  from fairseq.models.transformer.transformer_base import TransformerModelBase
label_desc: Use image node_id 5 for calling a global function with example usage: transformer_vaswani_wmt_en_de_big(args) without return types