class_docstr: Test class for `TweedieDevianceScore` metric.
class_docstr_tok: ["Test","class","for","`","TweedieDevianceScore","`","metric","."]
docstr: Test dtype support of the metric on GPU.
docstr_tok: ["Test","dtype","support","of","the","metric","on","GPU","."]
code: def test_deviance_scores_half_gpu(self, preds, target, power):
      """Test dtype support of the metric on GPU."""
      metric_args = {"power": power}
      self.run_precision_test_gpu(
          preds,
          target,
          metric_module=TweedieDevianceScore,
          metric_functional=tweedie_deviance_score,
          metric_args=metric_args,
      )
  
imports: from functools import partial
  import pytest
  import torch
  from sklearn.metrics import mean_tweedie_deviance
  from torch import Tensor
  from torchmetrics.functional.regression.tweedie_deviance import tweedie_deviance_score
  from torchmetrics.regression.tweedie_deviance import TweedieDevianceScore
  from unittests import BATCH_SIZE, NUM_BATCHES, _Input
  from unittests.helpers import seed_all
  from unittests.helpers.testers import MetricTester
label_desc: Use image node_id 5 for calling the TestDevianceScore obj's underlying member method code with example usage: obj.test_deviance_scores_half_gpu(preds, target, power) without return types