code: def base_architecture(args):
      args.dropout = getattr(args, "dropout", 0.2)
      args.output_frame_dim = getattr(args, "output_frame_dim", 80)
      args.speaker_embed_dim = getattr(args, "speaker_embed_dim", 64)
      # FFT blocks
      args.fft_hidden_dim = getattr(args, "fft_hidden_dim", 1024)
      args.fft_kernel_size = getattr(args, "fft_kernel_size", 9)
      args.attention_dropout = getattr(args, "attention_dropout", 0.0)
      args.encoder_layers = getattr(args, "encoder_layers", 4)
      args.encoder_embed_dim = getattr(args, "encoder_embed_dim", 256)
      args.encoder_attention_heads = getattr(
          args, "encoder_attention_heads", 2
      )
      args.decoder_layers = getattr(args, "decoder_layers", 4)
      args.decoder_embed_dim = getattr(args, "decoder_embed_dim", 256)
      args.decoder_attention_heads = getattr(
          args, "decoder_attention_heads", 2
      )
      # variance predictor
      args.var_pred_n_bins = getattr(args, "var_pred_n_bins", 256)
      args.var_pred_hidden_dim = getattr(
          args, "var_pred_hidden_dim", 256
      )
      args.var_pred_kernel_size = getattr(
          args, "var_pred_kernel_size", 3
      )
      args.var_pred_dropout = getattr(args, "var_pred_dropout", 0.5)
      # postnet
      args.add_postnet = getattr(args, "add_postnet", False)
      args.postnet_dropout = getattr(args, "postnet_dropout", 0.5)
      args.postnet_layers = getattr(args, "postnet_layers", 5)
      args.postnet_conv_dim = getattr(args, "postnet_conv_dim", 512)
      args.postnet_conv_kernel_size = getattr(
          args, "postnet_conv_kernel_size", 5
      )
  
imports: import logging
  import torch
  from torch import nn
  from fairseq import utils
  from fairseq.data.data_utils import lengths_to_padding_mask
  from fairseq.models import FairseqEncoder, FairseqEncoderModel, register_model, register_model_architecture
  from fairseq.models.text_to_speech.hub_interface import TTSHubInterface
  from fairseq.models.text_to_speech.tacotron2 import Postnet
  from fairseq.modules import FairseqDropout, LayerNorm, MultiheadAttention, PositionalEmbedding
label_desc: Use image node_id 3 for calling a global function with example usage: base_architecture(args) without return types