code: def base_architecture(args):
      args.input_feat_per_channel = getattr(
          args, "input_feat_per_channel", 40
      )
      args.vggblock_enc_config = getattr(
          args, "vggblock_enc_config", DEFAULT_ENC_VGGBLOCK_CONFIG
      )
      args.transformer_enc_config = getattr(
          args, "transformer_enc_config", DEFAULT_ENC_TRANSFORMER_CONFIG
      )
      args.enc_output_dim = getattr(args, "enc_output_dim", 512)
      args.in_channels = getattr(args, "in_channels", 1)
      args.tgt_embed_dim = getattr(args, "tgt_embed_dim", 128)
      args.transformer_dec_config = getattr(
          args, "transformer_dec_config", DEFAULT_ENC_TRANSFORMER_CONFIG
      )
      args.conv_dec_config = getattr(
          args, "conv_dec_config", DEFAULT_DEC_CONV_CONFIG
      )
      args.transformer_context = getattr(
          args, "transformer_context", "None"
      )
  
imports: import argparse
  import math
  from collections.abc import Iterable
  import torch
  import torch.nn
  from examples.speech_recognition.data.data_utils import lengths_to_encoder_padding_mask
  from fairseq import utils
  from fairseq.models import FairseqEncoder, FairseqEncoderDecoderModel, FairseqEncoderModel, FairseqIncrementalDecoder, register_model, register_model_architecture
  from fairseq.modules import LinearizedConvolution, TransformerDecoderLayer, TransformerEncoderLayer, VGGBlock
label_desc: Use image node_id 7 for calling a global function with example usage: base_architecture(args) without return types