class_docstr: Test class for `MulticlassExactMatch` metric.
class_docstr_tok: ["Test","class","for","`","MulticlassExactMatch","`","metric","."]
docstr: Test dtype support of the metric on GPU.
docstr_tok: ["Test","dtype","support","of","the","metric","on","GPU","."]
code: def test_multiclass_exact_match_half_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=MulticlassExactMatch,
          metric_functional=multiclass_exact_match,
          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 torchmetrics.classification.exact_match import ExactMatch, MulticlassExactMatch, MultilabelExactMatch
  from torchmetrics.functional.classification.exact_match import multiclass_exact_match, multilabel_exact_match
  from torchmetrics.metric import Metric
  from unittests import NUM_CLASSES, THRESHOLD
  from unittests.classification.inputs import _multiclass_cases, _multilabel_cases
  from unittests.helpers import seed_all
  from unittests.helpers.testers import MetricTester, inject_ignore_index
label_desc: Use image node_id 5 for calling the TestMulticlassExactMatch obj's underlying member method code with example usage: obj.test_multiclass_exact_match_half_gpu(inputs, dtype) without return types