code: def test_high_learning_rate(self, net_cls, module_cls, data):
      # regression test for nan loss with high learning rates issue #481
      net = net_cls(
          module_cls, max_epochs=2, lr=2, optimizer=torch.optim.Adam
      )
      net.fit(*data)
      assert np.any(~np.isnan(net.history[:, "train_loss"]))
  
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 12 for calling the TestNeuralNet obj's underlying member method code with example usage: obj.test_high_learning_rate(net_cls, module_cls, data) without return types