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3.3 节最后的损失函数需要sum后才可以调用backward函数 #83

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3.3 节最后的损失函数需要sum后才可以调用backward函数 #83

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6 changes: 3 additions & 3 deletions docs/chapter03_DL-basics/3.3_linear-regression-pytorch.md
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Original file line number Diff line number Diff line change
Expand Up @@ -48,7 +48,7 @@ tensor([[-2.7723, -0.6627],
[ 0.2576, -0.2928],
[ 2.0475, -2.7440],
[ 1.0685, 1.1920],
[ 1.0996, 0.5106]])
[ 1.0996, 0.5106]])
tensor([ 0.9066, -0.6247, 9.3383, 3.6537, 3.1283, 17.0213, 5.6953, 17.6279,
2.2809, 4.6661])
```
Expand All @@ -68,7 +68,7 @@ class LinearNet(nn.Module):
def forward(self, x):
y = self.linear(x)
return y

net = LinearNet(num_inputs)
print(net) # 使用print可以打印出网络的结构
```
Expand Down Expand Up @@ -195,7 +195,7 @@ num_epochs = 3
for epoch in range(1, num_epochs + 1):
for X, y in data_iter:
output = net(X)
l = loss(output, y.view(-1, 1))
l = loss(output, y.view(-1, 1)).sum()
optimizer.zero_grad() # 梯度清零，等价于net.zero_grad()
l.backward()
optimizer.step()
Expand Down