code: def test_show_results(camvid_ds, backbone, monkeypatch):
      monkeypatch.setattr(plt, "show", lambda: None)
      _, valid_ds = camvid_ds
      model = deeplabv3.model(
          backbone=backbone(
              pretrained=False,
          ),
          num_classes=32,
      )
  
      model.eval()  # Needed to allow batch size of 1
  
      if torch.cuda.is_available():
          model.cuda()  # Needed when ran on machine with a GPU as data will be loaded on the device by default
          device = torch.device("cuda")
  
      else:
          device = torch.device("cpu")
  
      deeplabv3.show_results(model, valid_ds, device=device)
  
imports: import pytest
  from icevision.all import *
  from icevision.models.mmseg.models.deeplabv3.backbones import *
  from icevision.models.mmseg.models import *
  from icevision.models.interpretation import get_samples_losses
label_desc: Use image node_id 1 for calling a global function with example usage: test_show_results(camvid_ds, backbone, monkeypatch) without return types