class_docstr: Test class for `MultilabelStatScores` metric.
class_docstr_tok: ["Test","class","for","`","MultilabelStatScores","`","metric","."]
docstr: Test dtype support of the metric on GPU.
code: def test_multilabel_stat_scores_dtype_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=MultilabelStatScores,
          metric_functional=multilabel_stat_scores,
          metric_args={
              "num_labels": NUM_CLASSES,
              "threshold": THRESHOLD,
          },
          dtype=dtype,
      )
  
imports: from functools import partial
  import numpy
  import pytest
  import torch
  from scipy.special import expit
  from sklearn.metrics import confusion_matrix
  from torchmetrics.classification.stat_scores import BinaryStatScores, MulticlassStatScores, MultilabelStatScores, StatScores
  from torchmetrics.functional.classification.stat_scores import binary_stat_scores, multiclass_stat_scores, multilabel_stat_scores
  from torchmetrics.metric import Metric
  from unittests import NUM_CLASSES, THRESHOLD
  from unittests.classification.inputs import _binary_cases, _multiclass_cases, _multilabel_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 TestMultilabelStatScores obj's underlying member method code with example usage: obj.test_multilabel_stat_scores_dtype_gpu(inputs, dtype) without return types