text: import pytest
  from utils.fakes import *
  import sys
  from fastai.gen_doc.doctest import this_tests
  
  ## run: pytest tests/test_basic_data.py -s
  
  
  # filename: test_basic_data.py
  
  ## Test Cases
  
      ## TO DO: Function intercept_args
  
      ## TO DO: Class DeviceDataLoader
  
  ## Class DataBunch
  
  def test_DataBunch_Create():
      x_train,y_train =  fake_basedata(n_in=3, batch_size=6),fake_basedata(n_in=3, batch_size=6)
      x_valid,y_valid =  fake_basedata(n_in=3, batch_size=3),fake_basedata(n_in=3, batch_size=3)
      bs=5
      train_ds,valid_ds = TensorDataset(x_train, y_train),TensorDataset(x_valid, y_valid)
      data = DataBunch.create(train_ds, valid_ds, bs=bs)
      this_tests(data.create)
  
      assert 3 == len(data.train_dl)
      assert 18 == len(data.train_ds)
      assert 2 == len(data.valid_dl)
      assert 9 == len(data.valid_ds)
  
  ## TO DO (?)ideally, call one_batch with type dataloader
  def test_DataBunch_onebatch():
      data = fake_data(n_in=4, n_out=5, batch_size=6)
      this_tests(data.one_batch)
      x,y = data.one_batch()
      assert 4 == x[0].shape[0]
      assert 6 == x.shape[0]
      assert 6 == y.shape[0]
  
  
  def test_DataBunch_oneitem():
      data = fake_data()
      this_tests(data.one_item)
      x,y = data.one_item(item=1)
      assert 1 == x.shape[0]
      assert 1 == y.shape[0]
  
  
  def test_DataBunch_show_batch(capsys):
       data = fake_data()
       this_tests(data.show_batch)
       data.show_batch()
       captured = capsys.readouterr()
       match = re.findall(r'tensor', captured.out)
       assert match
  
  ## TO DO: check over file created ?
  ##def test_DataBunch_export():
  ##     data = fake_data()
  ##     data.export()
  
  def test_DeviceDataLoader_getitem():
      class DictDataset(Dataset):
          def __getitem__(self, idx):
              return {"a":np.ones((3,)),"b":np.zeros((2,))}
          def __len__(self):
              return 10
  
      ds = DictDataset()
      next(iter(DeviceDataLoader.create(ds)))
  