pytorch用优化器优化张量

x = torch.ones(1, 5, requires_grad=True)

optimizer = optim.Adam({x}, lr=0.004)

for i in range(50):

    optimizer.zero_grad()

    x1=torch.Tensor([1,2,3,4,5])

    #l=torch.sum(x-x1)

    l=torch.sqrt(torch.sum((x1-x)**2))

    l.backward()

    optimizer.step()

    print(l,x)