code: def test_dataloader():
      dataset = get_dataset()
      loader = DataLoader(dataset, batch_size=2)
  
      iterations = 0
      for data in loader:
          iterations += 1
  
          assert isinstance(data, tuple)
          assert (
              len(data) == 2
          )  # data[0] = image tensor, data[1] = targets dictionary
          assert isinstance(data[0], list)
          assert (
              len(data[0]) == 1
          )  # only one image in data[0] since label.xml contains one image only.
  
          assert isinstance(data[0][0], torch.Tensor)
          assert "boxes" in data[1][0] and "labels" in data[1][0]
  
      assert "boxes" in dataset[0][1] and "labels" in dataset[0][1]
      assert iterations == 1
  
file_path: detecto/detecto/tests/test_core.py
imports: import torch
  from detecto.core import *
  from detecto.utils import read_image
  from .helpers import get_dataset, get_image, get_model, empty_predictor
  from torchvision import transforms
  from torchvision.models.detection.faster_rcnn import FastRCNNPredictor
label_desc: Use image node_id 3 for calling a global function with example usage: test_dataloader() without return types