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]