code: def test_inceptionv4_encoder():
      backbone = inceptionv4(pretrained=False)
      backbone.last_linear = None
  
      net = E.InceptionV4Encoder(
          pretrained=False, layers=[0, 1, 2, 3, 4]
      ).cuda()
  
      print(count_parameters(net))
  
      x = torch.randn((4, 3, 512, 512)).cuda()
  
      out = net(x)
      for fm in out:
          print(fm.size())
  
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 4 for calling a global function with example usage: test_inceptionv4_encoder() without return types