def METHOD_NAME(
    n_samples=1000, n_features=1000, representation="dense", dtype=np.float32
):
    if representation == "dense":
        X = np.random.RandomState(0).random_sample((n_samples, n_features))
        X = X.astype(dtype, copy=False)
    else:
        X = sp.random(
            n_samples,
            n_features,
            density=0.05,
            format="csr",
            dtype=dtype,
            random_state=0,
        )
    X, X_val = train_test_split(X, test_size=0.1, random_state=0)
    return X, X_val, None, None