import torch
import numpy
import torch.nn.functional as F
from torch.autograd import Variable

x = torch.randn(1,10)
w = torch.randn(2,10,requires_grad=True)

o = torch.sigmoid([email protected]())
print(o.shape)

loss = F.mse_loss(torch.ones(1,2),o)##平方差损失
print(loss.shape)

loss.backward()
print(w.grad)

torch.Size([1, 2])
torch.Size([])
tensor([[-0.0059, -0.0482, -0.0712,  0.0172,  0.0735,  0.0953, -0.0761, -0.1083,
          0.0385,  0.0079],
        [-0.0122, -0.1006, -0.1487,  0.0360,  0.1533,  0.1989, -0.1588, -0.2259,
          0.0802,  0.0165]])