"nll_loss_out_frame" not implemented for 'Long'
时间: 2024-05-18 22:11:52 浏览: 17
这个错误通常是由于在计算损失时,目标张量的数据类型不正确引起的。`nll_loss` 是一个计算负对数似然损失的函数,它通常用于分类问题。在使用 `nll_loss` 时,目标张量的数据类型应该是整数类型的。如果你的目标张量是浮点类型的,你需要将其转换为整数类型的张量。你可以使用 `.long()` 方法将浮点类型的张量转换为整数类型的张量。
相关问题
RuntimeError: "nll_loss_forward_reduce_cuda_kernel_2d_index" not implemented for 'Int'
这个错误通常是由于数据类型不匹配导致的。在 PyTorch 中,`nll_loss` 函数的输入参数通常是浮点数类型的张量,而不是整数类型的张量。
你可以尝试将输入张量转换为浮点数类型,例如使用 `.float()` 方法将整数类型的张量转换为浮点数类型的张量:
```python
import torch
# 创建一个整数类型的张量
x = torch.tensor([1, 2, 3], dtype=torch.int)
# 将整数类型的张量转换为浮点数类型的张量
x = x.float()
# 使用 nll_loss 函数对张量进行计算
loss = torch.nn.functional.nll_loss(x, ...)
```
如果你仍然遇到问题,请提供更多的上下文和代码,以便更好地帮助你解决问题。
"nll_loss_forward_reduce_cuda_kernel_2d_index" not implemented for 'Int'
As an AI language model, I cannot provide the specific solution without additional context. However, this error message typically indicates that there is a type mismatch between the expected data type and the actual data type being passed to the function.
In this case, it seems that the function "nll_loss_forward_reduce_cuda_kernel_2d_index" is expecting a data type other than 'Int'. You may need to check the input data and ensure that it matches the expected data type.
Alternatively, this error may be caused by a missing or outdated library. You should check that you have the necessary dependencies installed and that they are up to date.
If you are still having trouble resolving the issue, you may need to provide more context or seek help from a technical support forum or community.
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