code: def test_fbeta_multilable_with_extra_dimensions(self, device: str):
      self.predictions = self.predictions.to(device)
      self.targets = self.targets.to(device)
  
      fbeta = FBetaMultiLabelMeasure()
      fbeta(self.predictions.unsqueeze(1), self.targets.unsqueeze(1))
      metric = fbeta.get_metric()
      precisions = metric["precision"]
      recalls = metric["recall"]
      fscores = metric["fscore"]
  
      # check value
      assert_allclose(precisions, self.desired_precisions)
      assert_allclose(recalls, self.desired_recalls)
      assert_allclose(fscores, self.desired_fscores)
  
      # check type
      assert isinstance(precisions, List)
      assert isinstance(recalls, List)
      assert isinstance(fscores, List)
  
imports: from typing import Dict, List, Tuple, Union, Any
  import pytest
  import torch
  from allennlp.common.checks import ConfigurationError
  from allennlp.common.testing import AllenNlpTestCase, global_distributed_metric, multi_device, run_distributed_test
  from sklearn.metrics import precision_recall_fscore_support
  from torch.testing import assert_allclose
  from allennlp.training.metrics import FBetaMultiLabelMeasure
label_desc: Use image node_id 6 for calling the FBetaMultiLabelMeasureTest obj's underlying member method code with example usage: obj.test_fbeta_multilable_with_extra_dimensions(device) without return types