RuntimeError：预期的标量类型 Float 但发现 Double

Question

我的代码如下：

net = nn.Linear(54, 7)
optimizer = optim.SGD(net.parameters(), lr=lr, momentum=0)
logloss = torch.nn.CrossEntropyLoss()
for i in range(niter):
    optimizer.zero_grad()
    y_2 = torch.from_numpy(np.array(y, dtype='float64'))
    X_2 = torch.from_numpy(np.array(X, dtype='float64'))
    outputs = net(X_2)
    print(loss)
    loss.backward()
    optimizer.step()

我收到以下错误消息

---> 57             outputs = net(X_2)
     58             print(np.shape(outputs))
     59             loss = logloss(outputs, y_2)

~\AppData\Local\Programs\Python\Python39\lib\site-packages\torch\nn\modules\module.py in _call_impl(self, *input, **kwargs)
   1049         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1050                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1051             return forward_call(*input, **kwargs)
   1052         # Do not call functions when jit is used
   1053         full_backward_hooks, non_full_backward_hooks = [], []

~\AppData\Local\Programs\Python\Python39\lib\site-packages\torch\nn\modules\linear.py in forward(self, input)
     94 
     95     def forward(self, input: Tensor) -> Tensor:
---> 96         return F.linear(input, self.weight, self.bias)
     97 
     98     def extra_repr(self) -> str:

~\AppData\Local\Programs\Python\Python39\lib\site-packages\torch\nn\functional.py in linear(input, weight, bias)
   1845     if has_torch_function_variadic(input, weight):
   1846         return handle_torch_function(linear, (input, weight), input, weight, bias=bias)
-> 1847     return torch._C._nn.linear(input, weight, bias)
   1848 
   1849 

RuntimeError: expected scalar type Float but found Double

你能具体说明我的问题吗，谢谢。我除了我已经通过torch.from_numpy(np.array(y, dtype='float64')) 将结果转换为浮点数，但不起作用。

Answer 1

您需要将您的张量转换为 float32，可以使用 dtype='float32' 或在您的输入张量上调用 float()。