code: def test_wrapper_class(metric, kwargs, base_metric=HingeLoss):
      """Test the wrapper class."""
      assert issubclass(base_metric, Metric)
      if metric is None:
          with pytest.raises(ValueError, match=r"Invalid *"):
              base_metric(**kwargs)
      else:
          instance = base_metric(**kwargs)
          assert isinstance(instance, metric)
          assert isinstance(instance, Metric)
  
imports: from functools import partial
  import numpy
  import pytest
  import torch
  from scipy.special import expit
  from scipy.special import softmax
  from sklearn.metrics import hinge_loss
  from sklearn.preprocessing import OneHotEncoder
  from torchmetrics.classification.hinge import BinaryHingeLoss, HingeLoss, MulticlassHingeLoss
  from torchmetrics.functional.classification.hinge import binary_hinge_loss, multiclass_hinge_loss
  from torchmetrics.metric import Metric
  from unittests import NUM_CLASSES
  from unittests.classification.inputs import _binary_cases, _multiclass_cases
  from unittests.helpers.testers import MetricTester, inject_ignore_index, remove_ignore_index
label_desc: Use image node_id 3 for calling a global function with example usage: test_wrapper_class(metric, kwargs, base_metric) without return types