code: def test_swin_transformer(self):
      name = "swin_small_patch4_window7_224"
      tfms = transforms.Compose(
          [
              transforms.Resize([256, 256]),
              transforms.CenterCrop([224, 224]),
              transforms.ToTensor(),
              transforms.Normalize(
                  [0.485, 0.456, 0.406], [0.229, 0.224, 0.225]
              ),
          ]
      )
  
      img = tfms(self.img).unsqueeze(0)
      arch, model_cfg = build_configs(name)
      model = SwinTransformer(**arch)
      load_pretrained_weights(model, name, model_cfg)
      model.eval()
      # out = model(self.img)
      # scores = torch.nn.functional.softmax(out, 1)
      with torch.no_grad():
          outputs = model(img).squeeze(0)
      for idx in torch.topk(outputs, k=1).indices.tolist():
          # prob = torch.softmax(self.outputs, -1)[idx].item()
          # label = self.labels_map[idx]
          # p = prob * 100
          self.assertEqual(
              "giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca",
              self.labels_map[idx],
          )
  
file_path: towhee/tests/unittests/models/swin_transformer/test_swin_transformer.py
imports: import unittest
  import json
  import torch
  from torchvision import transforms
  import os
  from towhee.utils.pil_utils import PILImage
  from towhee.models.swin_transformer.configs import build_configs
  from towhee.models.swin_transformer.model import SwinTransformer
  from towhee.models.utils.pretrained_utils import load_pretrained_weights
  from tests.unittests import MODEL_RESOURCE
label_desc: Use image node_id 1 for calling the SwinTransformerTest obj's underlying member method code with example usage: obj.test_swin_transformer() without return types