code: def test_multiple_item_batch():
      multi_view_collate = MultiViewCollate()
      img1 = [torch.randn((3, 224, 224)) for _ in range(5)]
      label1 = 1
      fname1 = "image1.jpg"
      img2 = [torch.randn((3, 224, 224)) for _ in range(5)]
      label2 = 2
      fname2 = "image2.jpg"
      batch = [(img1, label1, fname1), (img2, label2, fname2)]
      views, labels, fnames = multi_view_collate(batch)
      assert len(views) == 5
      assert views[0].shape == (2, 3, 224, 224)
      assert torch.equal(labels, torch.tensor([1, 2], dtype=torch.long))
      assert fnames == ["image1.jpg", "image2.jpg"]
  
file_path: lightly/tests/data/test_multi_view_collate.py
imports: from typing import List, Tuple, Union
  from warnings import warn
  import torch
  from torch import Tensor
  from lightly.data.multi_view_collate import MultiViewCollate
label_desc: Use image node_id 3 for calling a global function with example usage: test_multiple_item_batch() without return types