code: def SwinTransformer_base_patch4_window7_224(**kwargs):
      model = SwinTransformer(
          pretrain_img_size=224,
          embed_dim=128,
          depths=[2, 2, 18, 2],
          num_heads=[4, 8, 16, 32],
          window_size=7,
          **kwargs,
      )
  
      return model
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  import numpy
  from paddleseg.cvlibs import manager
  from paddleseg.utils import utils
  from paddleseg.models.backbones.transformer_utils import *
label_desc: Use image node_id 5 for calling a global function with example usage: SwinTransformer_base_patch4_window7_224() and returns: model