code: def base_architecture(args):
      args.encoder_embed_path = getattr(
          args, "encoder_embed_path", 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_normalize_before = getattr(
          args, "encoder_normalize_before", False
      )
      args.encoder_learned_pos = getattr(
          args, "encoder_learned_pos", False
      )
      args.decoder_embed_path = getattr(
          args, "decoder_embed_path", None
      )
      args.decoder_embed_dim = getattr(
          args, "decoder_embed_dim", args.encoder_embed_dim
      )
      args.decoder_ffn_embed_dim = getattr(
          args, "decoder_ffn_embed_dim", args.encoder_ffn_embed_dim
      )
      args.decoder_layers = getattr(args, "decoder_layers", 6)
      args.decoder_attention_heads = getattr(
          args, "decoder_attention_heads", 8
      )
      args.decoder_normalize_before = getattr(
          args, "decoder_normalize_before", False
      )
      args.decoder_learned_pos = getattr(
          args, "decoder_learned_pos", 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)
      args.adaptive_softmax_cutoff = getattr(
          args, "adaptive_softmax_cutoff", None
      )
      args.adaptive_softmax_dropout = getattr(
          args, "adaptive_softmax_dropout", 0
      )
      args.share_decoder_input_output_embed = getattr(
          args, "share_decoder_input_output_embed", False
      )
      args.share_all_embeddings = getattr(
          args, "share_all_embeddings", False
      )
      args.no_token_positional_embeddings = getattr(
          args, "no_token_positional_embeddings", False
      )
      args.decoder_out_embed_dim = getattr(
          args, "decoder_out_embed_dim", None
      )
      args.decoder_input_dim = getattr(
          args, "decoder_input_dim", args.decoder_embed_dim
      )
  
      args.decoder_aan_ffn = getattr(args, "decoder_aan_ffn", True)
      args.decoder_aan_ffn_use_embed_dim = getattr(
          args, "decoder_aan_ffn_use_embed_dim", False
      )
      args.decoder_aan_gating = getattr(
          args, "decoder_aan_gating", True
      )
      args.decoder_aan_more_dropouts = getattr(
          args, "decoder_aan_more_dropouts", ""
      )
      vocab_reduction.set_arg_defaults(args)
  
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
  from fairseq import options, utils
  from fairseq.models import FairseqEncoderDecoderModel, FairseqIncrementalDecoder, register_model, register_model_architecture, transformer
  from fairseq.modules import AdaptiveSoftmax, LearnedPositionalEmbedding, MultiheadAttention, SinusoidalPositionalEmbedding
  from pytorch_translate import transformer, vocab_reduction
  from pytorch_translate.average_attention import AverageAttention, AverageWindowAttention
  from pytorch_translate.utils import torch_find
label_desc: Use image node_id 5 for calling a global function with example usage: base_architecture(args) without return types