code: def test_value(
      self, y_pred, y, softmax, to_onehot, average, expected_value
  ):
      y_pred_trans = Compose([ToTensor(), Activations(softmax=softmax)])
      y_trans = Compose([ToTensor(), AsDiscrete(to_onehot=to_onehot)])
      y_pred = torch.stack(
          [y_pred_trans(i) for i in decollate_batch(y_pred)], dim=0
      )
      y = torch.stack([y_trans(i) for i in decollate_batch(y)], dim=0)
      result = compute_roc_auc(y_pred=y_pred, y=y, average=average)
      np.testing.assert_allclose(expected_value, result, rtol=1e-5)
  
file_path: MONAI/tests/test_compute_roc_auc.py
imports: from __future__ import annotations
  import unittest
  import numpy
  import torch
  from parameterized import parameterized
  from monai.data import decollate_batch
  from monai.metrics import ROCAUCMetric, compute_roc_auc
  from monai.transforms import Activations, AsDiscrete, Compose, ToTensor
label_desc: Use image node_id 1 for calling the TestComputeROCAUC obj's underlying member method code with example usage: obj.test_value(y_pred, y, softmax, to_onehot, average, expected_value) without return types