“火炬”功能的CPU版本

Question

是否有接收CPU输入的torch.\u C.\u nn.nll\u损耗功能？我没有足够的GPU内存来运行我的函数，所以我尝试在CPU上运行所有的东西。 这是我的具体错误（查看anaconda文件）

Traceback (most recent call last):
  File "plot_parametric_pytorch.py", line 395, in <module>
    val_result = validate(val_loader, model, criterion, 0)
  File "plot_parametric_pytorch.py", line 228, in validate
    training=False, optimizer=None)
  File "plot_parametric_pytorch.py", line 169, in forward
    loss = criterion(output, target_var)
  File "/home/klee/anaconda3/envs/sharpenv/lib/python3.7/site-packages/torch/nn/modules/module.py", line 550, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/klee/anaconda3/envs/sharpenv/lib/python3.7/site-packages/torch/nn/modules/loss.py", line 932, in forward
    ignore_index=self.ignore_index, reduction=self.reduction)
  File "/home/klee/anaconda3/envs/sharpenv/lib/python3.7/site-packages/torch/nn/functional.py", line 2317, in cross_entropy
    return nll_loss(log_softmax(input, 1), target, weight, None, ignore_index, None, reduction)
  File "/home/klee/anaconda3/envs/sharpenv/lib/python3.7/site-packages/torch/nn/functional.py", line 2115, in nll_loss
    ret = torch._C._nn.nll_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index)
RuntimeError: Expected object of device type cuda but got device type cpu for argument #1 'self' in call to _thnn_nll_loss_forward

Answer 1

nll_loss适用于CPU和GPU，但输入和目标需要在同一设备上。您的设备位于不同的设备上，其中第一个（output）位于CPU上，而第二个（target_var）位于GPU上

您需要将target_var放到CPU上

loss = criterion(output, target_var.cpu())