code: def transformer_wmt_en_de_big_t2t(args):
      args.encoder_normalize_before = getattr(
          args, "encoder_normalize_before", True
      )
      args.decoder_normalize_before = getattr(
          args, "decoder_normalize_before", True
      )
      args.attention_dropout = getattr(args, "attention_dropout", 0.1)
      args.activation_dropout = getattr(args, "activation_dropout", 0.1)
      transformer_vaswani_wmt_en_de_big(args)
  
imports: import torch
  import torch.nn
  from fairseq import utils
  from fairseq.models import FairseqEncoder, FairseqEncoderDecoderModel, FairseqIncrementalDecoder, register_model, register_model_architecture
  from fairseq.models.fairseq_encoder import EncoderOut
  from fairseq.modules import LayerNorm
  from lightseq.training.ops.pytorch.layer_base import TransformerEmbeddingLayerBase
  from lightseq.training.ops.pytorch.quantization import QuantLinear, disable_quant, enable_quant, ptq_mode, qat_mode
label_desc: Use image node_id 8 for calling a global function with example usage: transformer_wmt_en_de_big_t2t(args) without return types