def test_build_dataset(random_matrix, with_y, expected):
X = random_matrix
mod = TorchAutoencoder()
if with_y:
dataset = mod.build_dataset(X, X)
else:
dataset = mod.build_dataset(X)
result = next(iter(dataset))
assert len(result) == expected
def test_build_dataset_input_dim(random_matrix, early_stopping):
X = random_matrix
mod = TorchAutoencoder(early_stopping=early_stopping)
dataset = mod.build_dataset(X)
assert mod.input_dim == X.shape[1]