code: def test_grid_search_with_roc_auc(self, net_fit, data):
      from sklearn.model_selection import GridSearchCV
  
      search = GridSearchCV(
          net_fit,
          {"max_epochs": [1, 2]},
          refit=False,
          cv=3,
          scoring="roc_auc",
      )
      search.fit(*data)
  
imports: from unittest.mock import Mock
  import numpy
  import pytest
  import torch
  from scipy.special import expit
  from sklearn.base import clone
  from torch import nn
  from skorch.tests.conftest import INFERENCE_METHODS
label_desc: Use image node_id 19 for calling the TestNeuralNetBinaryClassifier obj's underlying member method code with example usage: obj.test_grid_search_with_roc_auc(net_fit, data) without return types