code: def test_get_train_valid_sets_splitter_args(self):
      x = range(1, 101)
      y = range(1, 101)
  
      x = torch.Tensor(x)
      y = torch.Tensor(y)
  
      valid_split = 0.1
      shuffle = True
  
      torchbearer.cv_utils.train_valid_splitter = Mock(
          return_value=(x, y, x, y)
      )
      tvs = torchbearer.cv_utils.train_valid_splitter
  
      trainset, valset = get_train_valid_sets(
          x, y, None, valid_split, shuffle
      )
      self.assertEqual(tvs.call_count, 1)
      self.assertTrue(tvs.call_args[0][-1] == valid_split)
      self.assertTrue(
          list(tvs.call_args[0][0].numpy()) == list(x.numpy())
      )
      self.assertTrue(
          list(tvs.call_args[0][1].numpy()) == list(y.numpy())
      )
      self.assertTrue(tvs.call_args[1]["shuffle"] == shuffle)
  
file_path: torchbearer/tests/test_cv_utils.py
imports: import unittest
  from mock import Mock
  import torchbearer
  from torchbearer.cv_utils import *
label_desc: Use image node_id 9 for calling the TestCVUtils obj's underlying member method code with example usage: obj.test_get_train_valid_sets_splitter_args() without return types