code: def test_multitask_topk_accuracy():
      # Test multitask_topk_accuracy with input for two tasks
      preds = MULTI_PREDS
      labels = MULTI_LABELS
      k = (1, 3, 5)
  
      top1, top3, top5 = multitask_topk_accuracy(preds, labels, k)
      top1_value = top1.double().mean()
      top3_value = top3.double().mean()
      top5_value = top5.double().mean()
      assert top1_value.cpu() == pytest.approx(1 / 5)
      assert top3_value.cpu() == pytest.approx(2 / 5)
      assert top5_value.cpu() == pytest.approx(3 / 5)
  
imports: import pytest
  import torch
  from kale.predict.losses import multitask_topk_accuracy, topk_accuracy
label_desc: Use image node_id 2 for calling a global function with example usage: test_multitask_topk_accuracy() without return types