code: def _test_batch(images, targets):
      assert images.shape == (2, 3, 4, 4)
      assert torch.all(images == 1.0)
  
      assert targets["cls"][0].dtype == torch.float
      assert len(targets["cls"]) == 2
      assert torch.all(
          targets["cls"][0] == tensor([1, 2], dtype=torch.float)
      )
  
      assert targets["bbox"][0].dtype == torch.float
      assert len(targets["bbox"]) == 2
      expected_bboxes = tensor(
          [[2, 1, 4, 3], [20, 10, 40, 30]], dtype=torch.float
      )
      assert torch.all(targets["bbox"][0] == expected_bboxes)
  
file_path: icevision/tests/models/efficient_det/test_dataloaders.py
imports: import pytest
  from icevision.all import *
  from icevision.models.ross import efficientdet
label_desc: Use image node_id 5 for calling a global function with example usage: _test_batch(images, targets) without return types