def METHOD_NAME(self) -> ndarray:
    """Return a dense numpy array."""
    if len(self.shape) == 1:
        return coo_matrix(
            (self.data, (self.indices[0], np.zeros_like(self.indices[0]))),
            shape=self.shape + (1,),
        ).METHOD_NAME().T[0]
    elif len(self.shape) == 2:
        return self.tocsr().METHOD_NAME()
    # slow implementation for testing N-tensors
    out = np.zeros(self.shape)
    for itr in range(self.indices.shape[1]):
        out[tuple(self.indices[:, itr])] += self.data[itr]
    return out