code: def test_default_loss_does_call_sigmoid(
      self, net_cls, data, module_cls, monkeypatch
  ):
      mock = Mock(side_effect=lambda x: x)
      monkeypatch.setattr(torch, "sigmoid", mock)
  
      net = net_cls(module_cls, max_epochs=1, lr=0.1)
      X, y = data
      net.fit(X, y)
  
      net.predict_proba(X)
      assert mock.call_count > 0
  
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 17 for calling the TestNeuralNetBinaryClassifier obj's underlying member method code with example usage: obj.test_default_loss_does_call_sigmoid(net_cls, data, module_cls, monkeypatch) without return types