RuntimeError: 预计所有张量都在同一设备上，但发​​现至少有两个设备，cuda:0 和 cpu！恢复训练时

问题描述

我在 gpu 上训练时保存了一个检查点.重新加载检查点并继续训练后，我收到以下错误.

I saved a checkpoint while trainig on gpu.after reloading the checkpoint and continue training i get the following error.

Traceback (most recent call last):
  File "main.py", line 140, in <module>
    train(model,optimizer,train_loader,val_loader,criteria=args.criterion,epoch=epoch,batch=batch)
  File "main.py", line 71, in train
    optimizer.step()
  File "/opt/conda/lib/python3.7/site-packages/torch/autograd/grad_mode.py", line 26, in decorate_context
    return func(*args, **kwargs)
  File "/opt/conda/lib/python3.7/site-packages/torch/optim/sgd.py", line 106, in step
    buf.mul_(momentum).add_(d_p, alpha=1 - dampening)
RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!

我的训练代码是:

def train(model,optimizer,train_loader,val_loader,criteria,epoch=0,batch=0):
    batch_count = batch
    if criteria == 'l1':
        criterion = L1_imp_Loss()
    elif criteria == 'l2':
        criterion = L2_imp_Loss()
    if args.gpu and torch.cuda.is_available():
        model.cuda()
        criterion = criterion.cuda()

    print(f'{datetime.datetime.now().time().replace(microsecond=0)} Starting to train..')

    while epoch <= args.epochs-1:
        print(f'********{datetime.datetime.now().time().replace(microsecond=0)} Epoch#: {epoch+1} / {args.epochs}')
        model.train()
        interval_loss, total_loss= 0,0
        for i , (input,target) in enumerate(train_loader):
            batch_count += 1
            if args.gpu and torch.cuda.is_available():
                input, target = input.cuda(), target.cuda()
            input, target = input.float(), target.float()
            pred = model(input)
            loss = criterion(pred,target)
            optimizer.zero_grad()
            loss.backward()
            optimizer.step()
            ....

保存过程发生在每个 epoch 结束后.

the saving proccess happend after finishing each epoch.

torch.save({'epoch': epoch,'batch':batch_count,'model_state_dict': model.state_dict(),'optimizer_state_dict':
                    optimizer.state_dict(),'loss': total_loss/len(train_loader),'train_set':args.train_set,'val_set':args.val_set,'args':args}, f'{args.weights_dir}/FastDepth_Final.pth')

我不知道为什么我会收到这个错误.args.gpu == True ，我将模型、所有数据和损失函数传递给 cuda，不知何故 cpu 上仍然有一个张量，有人能找出问题所在吗?

I cant figure why i get this error.args.gpu == True , and Im passing the model, all data, and loss function to cuda, somehow there is still a tensor on cpu, could anyone figure out whats wrong?

谢谢.

推荐答案

可能有一个 问题，设备参数开启:

There might be an issue with the device parameters are on:

如果您需要通过 .cuda() 将模型移动到 GPU，请在为其构建优化器之前执行此操作..cuda() 之后的模型参数将与调用之前的对象不同.
通常，在构建和使用优化器时，您应该确保优化参数位于一致的位置.

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