code: def test_output_with_postfix():
      """Test that wrapper works with postfix."""
      base = MulticlassAccuracy(num_classes=3, average=None)
      metric = ClasswiseWrapper(
          MulticlassAccuracy(num_classes=3, average=None),
          postfix="_post",
      )
      for _ in range(2):
          preds = torch.randn(20, 3).softmax(dim=-1)
          target = torch.randint(3, (20,))
          val = metric(preds, target)
          val_base = base(preds, target)
          assert isinstance(val, dict)
          assert len(val) == 3
          for i in range(3):
              assert f"{i}_post" in val
              assert val[f"{i}_post"] == val_base[i]
  
file_path: torchmetrics/tests/unittests/wrappers/test_classwise.py
imports: import pytest
  import torch
  from torchmetrics import MetricCollection
  from torchmetrics.classification import MulticlassAccuracy, MulticlassF1Score, MulticlassRecall
  from torchmetrics.wrappers import ClasswiseWrapper
label_desc: Use image node_id 5 for calling a global function with example usage: test_output_with_postfix() without return types