code: def fconv_lm_dauphin_gbw(args):
      layers = "[(512, 5)]"
      layers += " + [(128, 1, 0), (128, 5, 0), (512, 1, 3)] * 3"
      layers += " + [(512, 1, 0), (512, 5, 0), (1024, 1, 3)] * 3"
      layers += " + [(1024, 1, 0), (1024, 5, 0), (2048, 1, 3)] * 6"
      layers += " + [(1024, 1, 0), (1024, 5, 0), (4096, 1, 3)]"
      args.decoder_embed_dim = getattr(args, "decoder_embed_dim", 128)
      args.decoder_layers = getattr(args, "decoder_layers", layers)
      args.decoder_attention = getattr(
          args, "decoder_attention", "False"
      )
      args.adaptive_softmax_cutoff = getattr(
          args, "adaptive_softmax_cutoff", "10000,50000,200000"
      )
      base_lm_architecture(args)
  
file_path: fairseq/fairseq/models/fconv_lm.py
imports: from fairseq import utils
  from fairseq.models import FairseqLanguageModel, register_model, register_model_architecture
  from fairseq.models.fconv import FConvDecoder
  from fairseq.utils import safe_hasattr
label_desc: Use image node_id 3 for calling a global function with example usage: fconv_lm_dauphin_gbw(args) without return types