code: def test_classes_data_torch_tensor(self, net_cls, module_cls, data):
      X = torch.as_tensor(data[0])
      y = torch.as_tensor(np.arange(len(X)) % 10)
  
      net = net_cls(module_cls, max_epochs=0).fit(X, y)
      assert (net.classes_ == [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]).all()
  
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 15 for calling the TestNeuralNet obj's underlying member method code with example usage: obj.test_classes_data_torch_tensor(net_cls, module_cls, data) without return types