code: def swin_s3_base_224(pretrained=False, **kwargs) -> SwinTransformer:
      """Swin-S3-B @ 224x224, https://arxiv.org/abs/2111.14725"""
      model_args = dict(
          patch_size=4,
          window_size=(7, 7, 14, 7),
          embed_dim=96,
          depths=(2, 2, 30, 2),
          num_heads=(3, 6, 12, 24),
      )
      return _create_swin_transformer(
          "swin_s3_base_224",
          pretrained=pretrained,
          **dict(model_args, **kwargs),
      )
  
imports: import logging
  import math
  from typing import Callable, List, Optional, Tuple, Union
  import torch
  import torch.nn
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import PatchEmbed, Mlp, DropPath, ClassifierHead, to_2tuple, to_ntuple, trunc_normal_, _assert, use_fused_attn, resize_rel_pos_bias_table, resample_patch_embed
  from ._builder import build_model_with_cfg
  from ._features_fx import register_notrace_function
  from ._manipulate import checkpoint_seq, named_apply
  from ._registry import generate_default_cfgs, register_model, register_model_deprecations
  from .vision_transformer import get_init_weights_vit
label_desc: Use image node_id 15 for calling a global function with example usage: swin_s3_base_224(pretrained) and returns: _create_swin_transformer