def pnorm(weights, tau):
    normB = torch.norm(weights, 2, 1)
    ws = weights.clone()
    for i in range(0, weights.shape[0]):
        ws[i] = (ws[i] / torch.pow(normB[i], tau))
    return ws
def pnorm(weights, tau):
    normB = torch.norm(weights, 2, 1)
    ws = weights.clone()
    for i in range(0, weights.shape[0]):
        ws[i] = (ws[i] / torch.pow(normB[i], tau))
    return ws