hello
my source
# ReEig Layer
def cal_rect_cov(features):
#     features=features.detach().cpu()
    result=[]
#     features=torch.tensor(features,requires_grad=True)
    for i in range(features.shape[0]):
        s_f,v_f=torch.eig(features[i], eigenvectors=True)
        s_f_convert=[]
        for i in range(len(s_f)):
            s_f_convert.append(s_f[i][0])
        s_f_convert = torch.stack(s_f_convert)
        s_f2=torch.clamp(s_f_convert,0.0001,10000)
        s_f2=torch.diag(s_f2)
        features_t=torch.matmul(torch.matmul(v_f,s_f2),v_f.t())
        result.append(features_t)
    result = torch.stack(result)
#     result=result.cuda()
    return result

loss calculate is successful
but
loss.backward()
in this source, error like this
the derivative for ‘eig’ is not implemented
i don’t know why this error occured.
plz help me
thank you