code: def test_empty_state_dict(metric, thresholds):
      """Test that metric have an empty state dict."""
      m = metric(thresholds=thresholds)
      assert m.state_dict() == {}, "Metric state dict should be empty."
  
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.precision_recall_curve import BinaryPrecisionRecallCurve, MulticlassPrecisionRecallCurve, MultilabelPrecisionRecallCurve, PrecisionRecallCurve
  from torchmetrics.functional.classification.precision_recall_curve import binary_precision_recall_curve, multiclass_precision_recall_curve, multilabel_precision_recall_curve
  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_empty_state_dict(metric, thresholds) without return types