预计所有张量都在同一个设备上，但发现至少有两个设备，cpu 和 cuda:0！关于数据知识
pytorch 452
原文标题 ：Expected all tensors to be on the same device, but found at least two devices, cpu and cuda:0! on DataLore
我正在使用 IntelliJ DataLore 训练基本的 VGG16 CNN，但是当我尝试使用 GPU 机器进行训练时，出现以下错误：
Traceback (most recent call last):
at block 20, line 1
at /data/workspace_files/train/trainer/training.py, line 115, in train(self, max_epochs)
at /data/workspace_files/train/trainer/training.py, line 46, in train_epoch(self, train_loader)
at /data/workspace_files/train/trainer/training.py, line 94, in forward_to_loss(self, step_images, step_labels)
at /opt/python/envs/default/lib/python3.8/site-packages/torch/nn/modules/module.py, line 1102, in _call_impl(self, *input, **kwargs)
at /data/workspace_files/models/vgg.py, line 49, in forward(self, x)
at /opt/python/envs/default/lib/python3.8/site-packages/torch/nn/modules/module.py, line 1102, in _call_impl(self, *input, **kwargs)
at /opt/python/envs/default/lib/python3.8/site-packages/torch/nn/modules/container.py, line 141, in forward(self, input)
at /opt/python/envs/default/lib/python3.8/site-packages/torch/nn/modules/module.py, line 1102, in _call_impl(self, *input, **kwargs)
at /opt/python/envs/default/lib/python3.8/site-packages/torch/nn/modules/linear.py, line 103, in forward(self, input)
at /opt/python/envs/default/lib/python3.8/site-packages/torch/nn/functional.py, line 1848, in linear(input, weight, bias)
RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cpu and cuda:0! (when checking argument for argument mat1 in method wrapper_addmm)
这是我的代码，所以你们可以查看它。
use_cuda = torch.cuda.is_available()
device = torch.device("cuda" if use_cuda else "cpu")
model = model.to(device)
在这段代码中，我使用 self.device 因为我将设备作为参数传递给类 Train
for _, (data, target) in tqdm(enumerate(train_loader, 1)):
self.optimizer.zero_grad()
step_images, step_labels = data.to(
self.device), target.to(self.device)
step_output, loss = self.forward_to_loss(step_images, step_labels)
我以前没有遇到过这个问题，所以我不知道 DataLore 是否缺少某些内容或我的代码有误。
希望你能帮我！
