"nll_loss_forward_reduce_cuda_kernel_2d_index" not implemented for 'Int'的原因

"nll_loss_forward_reduce_cuda_kernel_2d_index" not implemented for 'Int'的原因可能是因为在使用该函数时传入的参数类型不正确。该函数可能只支持特定的数据类型，例如float或double，而传入的参数类型为整数类型（int）。

另一个可能的原因是该函数没有实现对整数类型的支持。这可能是由于实现限制或者开发人员没有为整数类型实现该函数。

解决方法可能是检查传入该函数的参数类型是否正确，并尝试使用支持的数据类型。如果没有支持整数类型的实现，可以考虑使用其他函数或者尝试自行实现该功能。

相关问题

"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Alternatively, this error may be caused by a missing or outdated library.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.

RuntimeError: "nll_loss_forward_reduce_cuda_kernel_2d_index" not implemented for 'int'

这个错误通常出现在使用 PyTorch 进行训练时，损失函数的输入数据类型不正确。

`nll_loss_forward_reduce_cuda_kernel_2d_index` 是 PyTorch 中计算负对数似然损失的函数，它要求输入的标签数据类型为 LongTensor 类型，而你的输入数据类型是 int 类型，所以会报错。

解决方法是将标签数据类型转换为 LongTensor 类型，可以使用 `label = label.long()` 将标签转换成 LongTensor 类型。