code: def base_architecture(args):
      args.encoder_pretrained_embed = getattr(
          args, "encoder_pretrained_embed", None
      )
      args.encoder_embed_dim = getattr(args, "encoder_embed_dim", 512)
      args.encoder_ffn_embed_dim = getattr(
          args, "encoder_ffn_embed_dim", 2048
      )
      args.encoder_layers = getattr(args, "encoder_layers", 6)
      args.encoder_attention_heads = getattr(
          args, "encoder_attention_heads", 8
      )
      args.encoder_freeze_embed = getattr(
          args, "encoder_freeze_embed", False
      )
      args.encoder_learned_pos = getattr(
          args, "encoder_learned_pos", False
      )
      args.encoder_normalize_before = getattr(
          args, "encoder_normalize_before", False
      )
      args.decoder_pretrained_embed = getattr(
          args, "decoder_pretrained_embed", None
      )
      args.decoder_embed_dim = getattr(
          args, "decoder_embed_dim", args.encoder_embed_dim
      )
      args.decoder_layers = getattr(args, "decoder_layers", 2)
      args.decoder_attention_heads = getattr(
          args, "decoder_attention_heads", 8
      )
      args.decoder_reduced_attention_dim = getattr(
          args, "decoder_reduced_attention_dim", None
      )
      args.decoder_lstm_units = getattr(args, "decoder_lstm_units", 512)
      args.decoder_out_embed_dim = getattr(
          args, "decoder_out_embed_dim", 256
      )
      args.decoder_freeze_embed = getattr(
          args, "decoder_freeze_embed", False
      )
      args.attention_dropout = getattr(args, "attention_dropout", 0.0)
      args.relu_dropout = getattr(args, "relu_dropout", 0.0)
      args.dropout = getattr(args, "dropout", 0.1)
      vocab_reduction.set_arg_defaults(args)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from fairseq import utils
  from fairseq.models import FairseqEncoderDecoderModel, FairseqIncrementalDecoder, register_model, register_model_architecture, transformer
  from fairseq.modules import MultiheadAttention
  from pytorch_translate import multilingual_model, transformer, vocab_reduction
  from pytorch_translate.utils import torch_find
label_desc: Use image node_id 1 for calling a global function with example usage: base_architecture(args) without return types