code: def test_multilabel_accumulator_device(self):
      # Multiclass input data of shape (N, ) and (N, C)
  
      def _test(average, metric_device):
          pr = Precision(
              is_multilabel=True, average=average, device=metric_device
          )
  
          assert pr._updated is False
          assert pr._device == metric_device
  
          y_pred = torch.randint(0, 2, size=(10, 4, 20, 23))
          y = torch.randint(0, 2, size=(10, 4, 20, 23)).long()
          pr.update((y_pred, y))
  
          assert pr._updated is True
  
          assert (
              pr._numerator.device == metric_device
          ), f"{type(pr._numerator.device)}:{pr._numerator.device} vs {type(metric_device)}:{metric_device}"
  
          if average != "samples":
              # For average='samples', `_denominator` is of type `int` so it has not `device` member.
              assert (
                  pr._denominator.device == metric_device
              ), f"{type(pr._denominator.device)}:{pr._denominator.device} vs {type(metric_device)}:{metric_device}"
  
          if average == "weighted":
              assert (
                  pr._weight.device == metric_device
              ), f"{type(pr._weight.device)}:{pr._weight.device} vs "
              f"{type(metric_device)}:{metric_device}"
  
      metric_devices = [torch.device("cpu")]
      device = idist.device()
      if device.type != "xla":
          metric_devices.append(idist.device())
      for metric_device in metric_devices:
          _test(False, metric_device=metric_device)
          _test("macro", metric_device=metric_device)
          _test("micro", metric_device=metric_device)
          _test("weighted", metric_device=metric_device)
          _test("samples", metric_device=metric_device)
  
imports: import warnings
  import pytest
  import torch
  from sklearn.exceptions import UndefinedMetricWarning
  from sklearn.metrics import precision_score
  import ignite.distributed
  from ignite.exceptions import NotComputableError
  from ignite.metrics import Precision
label_desc: Use image node_id 4 for calling the TestDistributed obj's underlying member method code with example usage: obj.test_multilabel_accumulator_device() without return types