code: def test_valid_input_thresholds(metric, thresholds):
      """Test valid formats of the threshold argument."""
      with pytest.warns(None) as record:
          metric(min_precision=0.5, thresholds=thresholds)
      assert len(record) == 0
  
imports: from functools import partial
  import numpy
  import pytest
  import torch
  from scipy.special import expit
  from scipy.special import softmax
  from sklearn.metrics import precision_recall_curve
  from torchmetrics.classification.recall_fixed_precision import BinaryRecallAtFixedPrecision, MulticlassRecallAtFixedPrecision, MultilabelRecallAtFixedPrecision, RecallAtFixedPrecision
  from torchmetrics.functional.classification.recall_fixed_precision import binary_recall_at_fixed_precision, multiclass_recall_at_fixed_precision, multilabel_recall_at_fixed_precision
  from torchmetrics.metric import Metric
  from unittests import NUM_CLASSES
  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 a global function with example usage: test_valid_input_thresholds(metric, thresholds) without return types