class_docstr: Test class for `BinaryROC` metric.
class_docstr_tok: ["Test","class","for","`","BinaryROC","`","metric","."]
docstr: Test that different types of `thresholds` argument lead to same result.
code: def test_binary_roc_threshold_arg(self, inputs, threshold_fn):
      """Test that different types of `thresholds` argument lead to same result."""
      preds, target = inputs
      for pred, true in zip(preds, target):
          p1, r1, t1 = binary_roc(pred, true, thresholds=None)
          p2, r2, t2 = binary_roc(
              pred, true, thresholds=threshold_fn(t1.flip(0))
          )
          assert torch.allclose(p1, p2)
          assert torch.allclose(r1, r2)
          assert torch.allclose(t1, t2)
  
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 roc_curve
  from torchmetrics.classification.roc import ROC, BinaryROC, MulticlassROC, MultilabelROC
  from torchmetrics.functional.classification.roc import binary_roc, multiclass_roc, multilabel_roc
  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 6 for calling the TestBinaryROC obj's underlying member method code with example usage: obj.test_binary_roc_threshold_arg(inputs, threshold_fn) without return types