本文介绍了pytorch 如何从张量中删除 cuda()的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我收到 TypeError: expected torch.LongTensor (got torch.cuda.FloatTensor).
如何将 torch.cuda.FloatTensor 转换为 torch.LongTensor?
Traceback (most recent call last):
File "train_v2.py", line 110, in <module>
main()
File "train_v2.py", line 81, in main
model.update(batch)
File "/home/Desktop/squad_vteam/src/model.py", line 131, in update
loss_adv = self.adversarial_loss(batch, loss, self.network.lexicon_encoder.embedding.weight, y)
File "/home/Desktop/squad_vteam/src/model.py", line 94, in adversarial_loss
adv_embedding = torch.LongTensor(adv_embedding)
TypeError: expected torch.LongTensor (got torch.cuda.FloatTensor)
推荐答案
您有一个浮点张量 f 并且想要将其转换为 long，您执行 long_tensor = f.long()
You have a float tensor f and want to convert it to long, you do long_tensor = f.long()
您有 cuda 张量，即数据在 gpu 上并且想要将其移动到 cpu，您可以执行 cuda_tensor.cpu().
You have cuda tensor i.e data is on gpu and want to move it to cpu you can do cuda_tensor.cpu().
所以要将 torch.cuda.Float 张量 A 转换为 torch.long，请执行 A.long().cpu()
So to convert a torch.cuda.Float tensor A to torch.long do A.long().cpu()
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