code: def test_raises_error_on_wrong_input():
      """Test that errors are raised on wrong input."""
      with pytest.raises(
          ValueError,
          match="Expected argument `metric` to be an instance of `torchmetrics.Metric` but.*",
      ):
          ClasswiseWrapper([])
  
      with pytest.raises(
          ValueError,
          match="Expected argument `labels` to either be `None` or a list of strings.*",
      ):
          ClasswiseWrapper(MulticlassAccuracy(num_classes=3), "hest")
  
      with pytest.raises(
          ValueError,
          match="Expected argument `prefix` to either be `None` or a string.*",
      ):
          ClasswiseWrapper(MulticlassAccuracy(num_classes=3), prefix=1)
  
      with pytest.raises(
          ValueError,
          match="Expected argument `postfix` to either be `None` or a string.*",
      ):
          ClasswiseWrapper(MulticlassAccuracy(num_classes=3), postfix=1)
  
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 1 for calling a global function with example usage: test_raises_error_on_wrong_input() without return types