从图形处理器中的60分钟闪电战训练PyTorch分类器时出错
从图形处理器中的60分钟闪电战训练PyTorch分类器时出错
提问于 2018-11-02 01:29:10
我在jupyter实验室通过他们的官方60分钟闪电战教程(使用他们的.ipynb文件，link to the tutorial)开始学习pytorch，并且已经成功地完成了它，直到使用gpu进行分类器的转换和训练。我想我已经成功地根据这些结果改变了网络、输入和标签的设备：
net=net.to(device)
net.fc1.weight.type()带输出：
'torch.cuda.FloatTensor'和：
inputs, labels = inputs.to(device), labels.to(device)
inputs.type(),labels.type()带输出：
('torch.cuda.FloatTensor', 'torch.cuda.LongTensor')在运行这些单元之后，我运行了用于训练模型的单元，其中包含以下代码：
for epoch in range(2): # loop over the dataset multiple times
running_loss = 0.0
for i, data in enumerate(trainloader, 0):
# get the inputs
inputs, labels = data
# zero the parameter gradients
optimizer.zero_grad()
# forward + backward + optimize
outputs = net(inputs)
loss = criterion(outputs, labels)
loss.backward()
optimizer.step()
# print statistics
running_loss += loss.item()
if i % 2000 == 1999: # print every 2000 mini-batches
print('[%d, %5d] loss: %.3f' %
(epoch + 1, i + 1, running_loss / 2000))
running_loss = 0.0
print('Finished Training') 并收到此错误：
RuntimeError Traceback (most recent call last)
<ipython-input-55-fe85c778b0e6> in <module>()
10
11 # forward + backward + optimize
---> 12 outputs = net(inputs)
13 loss = criterion(outputs, labels)
14 loss.backward()
~\Anaconda3\lib\site-packages\torch\nn\modules\module.py in __call__(self,
*input, **kwargs)
475 result = self._slow_forward(*input, **kwargs)
476 else:
--> 477 result = self.forward(*input, **kwargs)
478 for hook in self._forward_hooks.values():
479 hook_result = hook(self, input, result)
<ipython-input-52-725d44154459> in forward(self, x)
14
15 def forward(self, x):
--->16 x=self.conv1(x)
17 x = self.pool(F.relu(x))
18 x = self.pool(F.relu(self.conv2(x)))
~\Anaconda3\lib\site-packages\torch\nn\modules\module.py in __call__(self,
*input, **kwargs)
475 result = self._slow_forward(*input, **kwargs)
476 else:
--> 477 result = self.forward(*input, **kwargs)
478 for hook in self._forward_hooks.values():
479 hook_result = hook(self, input, result)
~\Anaconda3\lib\site-packages\torch\nn\modules\conv.py in forward(self,
input)
299 def forward(self, input):
300 return F.conv2d(input, self.weight, self.bias, self.stride,
--> 301 self.padding, self.dilation, self.groups)
302
303
RuntimeError: Expected object of type torch.FloatTensor but found type
torch.cuda.FloatTensor for argument #2 'weight' 为什么我会收到这个错误，我如何修复它？
回答 1
Stack Overflow用户
发布于 2018-12-02 03:30:00
您还需要在训练循环中将inputs和labels移动到GPU。
for i, data in enumerate(trainloader, 0):
# get the inputs
inputs, labels = data
# move to GPU
inputs = inputs.to(device)
labels = labels.to(device)
...页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/53106369
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