Traceback (most recent call last): File "/home/bder73002/hpy/ConvNextV2_Demo/train+.py", line 280, in <module> train_loss, train_acc = train(model_ft, DEVICE, train_loader, optimizer, epoch,model_ema) File "/home/bder73002/hpy/ConvNextV2_Demo/train+.py", line 46, in train loss = torch.nan_to_num(criterion_train(output, targets)) # 计算loss File "/home/bder73002/anaconda3/envs/python3.9.2/lib/python3.9/site-packages/torch/nn/modules/module.py", line 889, in _call_impl result = self.forward(*input, **kwargs) File "/home/bder73002/hpy/ConvNextV2_Demo/models/utils.py", line 182, in forward ldam_loss = self.ldam_loss(x, target) File "/home/bder73002/anaconda3/envs/python3.9.2/lib/python3.9/site-packages/torch/nn/modules/module.py", line 889, in _call_impl result = self.forward(*input, **kwargs) File "/home/bder73002/hpy/ConvNextV2_Demo/models/utils.py", line 148, in forward index.scatter_(1, target.data.view(-1, 1), 1) IndexError: scatter_(): Expected dtype int64 for index.
时间: 2023-12-15 21:04:30 浏览: 24
这个错误提示是在使用 PyTorch 进行训练时出现的。出现这个错误的原因是在执行 index.scatter_() 操作时,index 的数据类型应该是 int64,但实际上它的数据类型不是 int64。
你可以检查一下代码,看一下 index 的数据类型是否正确,如果不正确,可以使用 index = index.long() 将其转换为 int64 数据类型。另外,还需要确保 target 的数据类型也是 int64。
希望这能解决你的问题!
相关问题
Traceback ( most recent call last ) :File " C:/python/kfc.py " , line 8
Traceback (most recent call last): File "C:/python/kfc.py", line 8
这是Python中的错误追踪信息,通常在程序出现错误时会显示。它告诉我们在哪个文件的哪一行出现了错误。
具体来说,"Traceback (most recent call last)" 表示错误追踪的开始,它告诉我们下面的信息是最近一次调用的错误。
"File "C:/python/kfc.py", line 8" 表示错误发生在文件 "C:/python/kfc.py" 的第8行。
如果你想解决这个错误,可以打开 "C:/python/kfc.py" 文件,并检查第8行的代码,看看是否有语法错误或逻辑错误。
Traceback (most recent call last): File "/home/bder73002/hpy/ConvNextV2_Demo/train+.py", line 275, in <module> train_loss, train_acc = train(model_ft, DEVICE, train_loader, optimizer, epoch,model_ema) File "/home/bder73002/hpy/ConvNextV2_Demo/train+.py", line 48, in train loss = torch.nan_to_num(criterion_train(output, targets)) # 计算loss File "/home/bder73002/anaconda3/envs/python3.9.2/lib/python3.9/site-packages/torch/nn/modules/module.py", line 889, in _call_impl result = self.forward(*input, **kwargs) File "/home/bder73002/hpy/ConvNextV2_Demo/models/losses.py", line 56, in forward focal_loss = self.focal_loss(x, target) File "/home/bder73002/anaconda3/envs/python3.9.2/lib/python3.9/site-packages/torch/nn/modules/module.py", line 889, in _call_impl result = self.forward(*input, **kwargs) File "/home/bder73002/hpy/ConvNextV2_Demo/models/losses.py", line 21, in forward return focal_loss(F.cross_entropy(input, target, reduction='none', weight=self.weight), self.gamma) File "/home/bder73002/anaconda3/envs/python3.9.2/lib/python3.9/site-packages/torch/nn/functional.py", line 2693, in cross_entropy return nll_loss(log_softmax(input, 1), target, weight, None, ignore_index, None, reduction) File "/home/bder73002/anaconda3/envs/python3.9.2/lib/python3.9/site-packages/torch/nn/functional.py", line 2388, in nll_loss ret = torch._C._nn.nll_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index) RuntimeError: Expected object of scalar type Long but got scalar type Float for argument #2 'target' in call to _thnn_nll_loss_forward
这个错误的原因是你的标签数据类型不一致。cross_entropy函数要求输入的target必须是Long类型的张量,但是你传入的target是Float类型的标量。你需要将标签转换为Long类型的张量。可以使用以下代码将标签转换为Long类型:
```python
targets = targets.long()
```
将其添加到你的代码中即可。