code: def test_dict():
      a = {"data": [1, 2, 3, 4, 5], "label": 0}
      b = {"data": [5, 7], "label": 1}
      c = {"data": [1, 2, 3], "label": 0}
  
      collate_fn = DictCollator(
          {"data": PadCollator(), "label": StackCollator()}
      )
      sample = collate_fn((a, b, c))
  
      assert torch.all(
          sample["data"]
          == torch.as_tensor(
              [[1, 2, 3, 4, 5], [5, 7, 0, 0, 0], [1, 2, 3, 0, 0]]
          )
      )
      assert torch.all(sample["label"] == torch.as_tensor([0, 1, 0]))
  
imports: import torch
  from autogluon.multimodal.data.collator import DictCollator, ListCollator, PadCollator, StackCollator, TupleCollator
label_desc: Use image node_id 5 for calling a global function with example usage: test_dict() without return types