code: def head_selection_s2t_transformer_s(args):
      args.encoder_embed_dim = getattr(args, "encoder_embed_dim", 256)
      args.encoder_ffn_embed_dim = getattr(
          args, "encoder_ffn_embed_dim", 256 * 8
      )
      args.encoder_attention_heads = getattr(
          args, "encoder_attention_heads", 4
      )
      args.decoder_attention_heads = getattr(
          args, "decoder_attention_heads", 4
      )
      args.dropout = getattr(args, "dropout", 0.1)
      base_architecture(args)
  
imports: import logging
  from typing import Dict, List, Optional
  from pathlib import Path
  import torch.nn
  from torch import Tensor
  from fairseq import checkpoint_utils
  from fairseq.models import register_model, register_model_architecture
  from fairseq.utils import safe_hasattr
  from fairseq.models.speech_to_text.s2t_transformer import S2TTransformerModel, S2TTransformerEncoder, TransformerDecoderScriptable
  from fairseq.models.speech_to_text.s2t_transformer import base_architecture
  from ..modules.attn_head_selector import AttnHeadSelector
  from ..modules.head_selection_transformer_layer import HeadSelectionTransformerEncoderLayer
  from .head_selection_transformer import HeadSelectionTransformerDecoder
label_desc: Use image node_id 2 for calling a global function with example usage: head_selection_s2t_transformer_s(args) without return types