RuntimeError:期望所有张量都在同一设备上,但发现至少两个设备,cuda:0和cpu!恢复训练时 [英] RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! when resuming training
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问题描述
当在GPU上进行训练时,我保存了一个检查点.重新加载检查点并继续训练后,我得到以下错误.
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()
....
保存过程在每个时期完成之后发生.
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')
我无法弄清楚为什么会出现此错误.args.gpu == True,我将模型,所有数据和损失函数传递给cuda,以某种方式在cpu上仍然有张量,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.
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