def test_train_valid_test_split(dataset):
splitter = RandomSplitter()
train_ind, valid_ind, test_ind = splitter.train_valid_test_split(dataset)
assert type(train_ind) == numpy.ndarray
assert train_ind.shape[0] == 8
assert valid_ind.shape[0] == 1
assert test_ind.shape[0] == 1
def test_train_valid_test_split_ndarray_return_dataset(ndarray_dataset):
splitter = RandomSplitter()
train, valid, test = splitter.train_valid_test_split(ndarray_dataset,
return_index=False)
assert type(train) == numpy.ndarray
assert type(valid) == numpy.ndarray
assert type(test) == numpy.ndarray
assert len(train) == 8
assert len(valid) == 1
assert len(test) == 1
def test_train_valid_test_split_return_dataset(dataset):
splitter = RandomSplitter()
train, valid, test = splitter.train_valid_test_split(dataset,
return_index=False)
assert type(train) == NumpyTupleDataset
assert type(valid) == NumpyTupleDataset
assert type(test) == NumpyTupleDataset
assert len(train) == 8
assert len(valid) == 1
assert len(test) == 1