312bd4d73a175079af9bde2cf46a4c187232d14e,pygsp/operators/operator.py,,grad,#Any#Any#,45

Before Change

        Gradient living on the edges

    
    if hasattr(G, "lap_type"):
        if G.lap_type == "combinatorial":
            raise NotImplementedError("Not implemented yet. However ask Nathanael it is very easy.")

    D = grad_mat(G)
    gr = D * s

    if s.dtype == "float32":

After Change

        Gradient living on the edges

    
    if G.N != np.shape(s)[0]:
        raise ValueError("Signal size is different from the number of nodes.")

    D = grad_mat(G)
    gr = D * s

    if s.dtype == "float32":

Instances