class_docstr: Test class for `MulticlassCohenKappa` metric.
class_docstr_tok: ["Test","class","for","`","MulticlassCohenKappa","`","metric","."]
docstr: Test dtype support of the metric on GPU.
docstr_tok: ["Test","dtype","support","of","the","metric","on","GPU","."]
code: def test_multiclass_confusion_matrix_dtypes_gpu(self, inputs, dtype):
      """Test dtype support of the metric on GPU."""
      preds, target = inputs
      self.run_precision_test_gpu(
          preds=preds,
          target=target,
          metric_module=MulticlassCohenKappa,
          metric_functional=multiclass_cohen_kappa,
          metric_args={"num_classes": NUM_CLASSES},
          dtype=dtype,
      )
  
imports: from functools import partial
  import numpy
  import pytest
  import torch
  from scipy.special import expit
  from sklearn.metrics import cohen_kappa_score
  from torchmetrics.classification.cohen_kappa import BinaryCohenKappa, CohenKappa, MulticlassCohenKappa
  from torchmetrics.functional.classification.cohen_kappa import binary_cohen_kappa, multiclass_cohen_kappa
  from torchmetrics.metric import Metric
  from unittests import NUM_CLASSES, THRESHOLD
  from unittests.classification.inputs import _binary_cases, _multiclass_cases
  from unittests.helpers import seed_all
  from unittests.helpers.testers import MetricTester, inject_ignore_index, remove_ignore_index
label_desc: Use image node_id 5 for calling the TestMulticlassCohenKappa obj's underlying member method code with example usage: obj.test_multiclass_confusion_matrix_dtypes_gpu(inputs, dtype) without return types