code: def SwinTransformerTrunk(
      model_config: AttrDict, model_name: str
  ) -> nn.Module:
      config = model_config.TRUNK.SWIN_TRANSFORMER
      return SwinTransformer(
          img_size=config.IMAGE_SIZE,
          patch_size=config.PATCH_SIZE,
          in_chans=3,
          embed_dim=config.EMBED_DIM,
          depths=config.DEPTHS,
          num_heads=config.NUM_HEADS,
          window_size=config.WINDOW_SIZE,
          mlp_ratio=config.MLP_RATIO,
          qkv_bias=config.QKV_BIAS,
          qk_scale=config.QK_SCALE if config.QK_SCALE else None,
          drop_rate=config.DROPOUT_RATE,
          attn_drop_rate=config.ATTENTION_DROPOUT_RATE,
          drop_path_rate=config.DROP_PATH_RATE,
          norm_layer=nn.LayerNorm,
          ape=False,
          patch_norm=True,
          use_checkpoint=False,
      )
  
imports: import math
  from functools import lru_cache
  from typing import List, Optional
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.checkpoint
  from vissl.config import AttrDict
  from vissl.models.model_helpers import DropPath, rearrange, to_2tuple, trunc_normal_
  from vissl.models.trunks import register_model_trunk
label_desc: Use image node_id 5 for calling a global function with example usage: SwinTransformerTrunk(model_config, model_name) and returns: SwinTransformer