floattensor和longtensor区别
时间: 2023-04-29 10:05:42 浏览: 89
FloatTensor和LongTensor是PyTorch中两种不同的数据类型。FloatTensor是32位浮点数数据类型,用于存储实数。而LongTensor是64位有符号整数数据类型,用于存储整数,可以用于索引、标签等需要整数表示的场景。两种类型在使用时需要注意数据类型的匹配,如张量相加的两个张量应该具有相同的数据类型。
相关问题
torch.longtensor()和torch.floattensor的区别
torch.longtensor()和torch.floattensor()的区别在于它们创建的张量的数据类型不同。torch.longtensor()创建的张量的数据类型为整型(long),而torch.floattensor()创建的张量的数据类型为浮点型(float)。这意味着,如果你需要处理整数数据,你应该使用torch.longtensor(),如果你需要处理浮点数数据,你应该使用torch.floattensor()。
RuntimeError: Input type (torch.cuda.LongTensor) and weight type (torch.cuda.FloatTensor) should be the same
This error occurs when you are trying to perform an operation on a tensor and its corresponding weight, but their data types do not match. In this specific case, you are trying to perform an operation on a tensor of type `torch.cuda.LongTensor` and its corresponding weight of type `torch.cuda.FloatTensor`.
To resolve this error, you need to ensure that the data types of the tensor and its weight are the same. You can do this by converting one of them to match the other.
For example, if you want to convert the weight to type `torch.cuda.LongTensor`, you can use the `.long()` method to convert it:
```
weight = weight.long()
```
Alternatively, if you want to convert the tensor to type `torch.cuda.FloatTensor`, you can use the `.float()` method to convert it:
```
tensor = tensor.float()
```
Once you have converted one of the variables to match the other, you should be able to perform the operation without any issues.