class_docstr: Test svt model
code: def test_cvnet_r101(self):
      if torch.cuda.is_available() is True:
          self.query_image = self.query_image.cuda()
          self.key_image = self.key_image.cuda()
      model = cvnet.create_model(
          model_name="CVNet_R101",
          pretrained=False,
          resnet_depth=101,
          reduction_dim=2048,
      )
      score = model(self.query_image, self.key_image).unsqueeze(-1)
      self.assertTrue(score.shape == (1, 1))
      global_descriptor = model.extract_global_descriptor(
          self.query_image
      )
      self.assertTrue(global_descriptor.shape == (1, 2048))
      query_feature = model.extract_featuremap(self.query_image)
      key_feature = model.extract_featuremap(self.key_image)
      self.assertTrue(query_feature[0].shape == (1, 1024, 2, 2))
      self.assertTrue(key_feature[0].shape == (1, 1024, 2, 2))
      final_score = (
          model.extract_score_with_featuremap(
              query_feature, key_feature
          )
          .unsqueeze(-1)
          .unsqueeze(-1)
      )
      self.assertTrue(final_score.shape == (1, 1))
  
imports: import unittest
  import torch
  from towhee.models import cvnet
label_desc: Use image node_id 1 for calling the TestCVNet obj's underlying member method code with example usage: obj.test_cvnet_r101() without return types