class_docstr: CVNet
  
  Args:
      resnet_depth (`int`):
          ResNet depth.
      reduction_dim (`int`):
          Reduction dimension of ResNet.
code: def extract_global_descriptor(self, im_q):
      # compute query features
      q = self.encoder_q(im_q)[0]
      q = nn.functional.normalize(q, dim=1)
      return q
  
file_path: towhee/towhee/models/cvnet/cvnet.py
imports: from functools import reduce
  from operator import add
  import torch
  from torch import nn
  from towhee.models.cvnet.cvnet_utils import extract_feat_res_pycls, get_configs
  from towhee.models.cvnet.cvnet_block import CVLearner, Correlation
  from towhee.models.cvnet.resnet import ResNet
  from towhee.models.utils import create_model
label_desc: Use image node_id 3 for calling the CVNet obj's underlying member method code with example usage: obj.extract_global_descriptor(im_q) and returns: q