code: def net_with_bceloss(self, net_cls, module_cls, data):
      # binary classification should also work with BCELoss
      net = net_cls(
          module_cls,
          module__output_nonlin=torch.nn.Sigmoid(),
          criterion=torch.nn.BCELoss,
          lr=1,
      )
      X, y = data
      net.fit(X, y)
      return net
  
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 22 for calling the TestNeuralNetBinaryClassifier obj's underlying member method code with example usage: obj.net_with_bceloss(net_cls, module_cls, data) and returns: net