code: def test_densenet():
      from torchvision.models import densenet121
  
      net1 = E.DenseNet121Encoder(pretrained=False)
      net2 = densenet121(pretrained=False)
      net2.classifier = None
  
      print(count_parameters(net1), count_parameters(net2))
  
file_path: pytorch-toolbelt/tests/test_encoders.py
imports: import pytest
  import torch
  import pytorch_toolbelt.modules.encoders
  from pytorch_toolbelt.modules import AbstractEncoder
  from pytorch_toolbelt.modules.backbone.inceptionv4 import inceptionv4
  from pytorch_toolbelt.utils.torch_utils import maybe_cuda, count_parameters, describe_outputs
  from pytorch_toolbelt.modules.encoders import timm
label_desc: Use image node_id 5 for calling a global function with example usage: test_densenet() without return types