error when training, using the CIFAR100 dataset writing by dataset.py

[lqin0818]

Traceback (most recent call last):
File "D:/Study/VGG/train.py", line 190, in
train(epoch)
File "D:/Study/VGG/train.py", line 30, in train
outputs = net(images)
File "C:\Users\qinli.conda\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "C:\Users\qinli.conda\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl
return forward_call(*args, **kwargs)
File "D:\Study\VGG\vgg_m.py", line 34, in forward
x = self.features(x)
File "C:\Users\qinli.conda\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "C:\Users\qinli.conda\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\qinli.conda\envs\pytorch\lib\site-packages\torch\nn\modules\container.py", line 217, in forward
input = module(input)
File "C:\Users\qinli.conda\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "C:\Users\qinli.conda\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\qinli.conda\envs\pytorch\lib\site-packages\torch\nn\modules\conv.py", line 460, in forward
return self._conv_forward(input, self.weight, self.bias)
File "C:\Users\qinli.conda\envs\pytorch\lib\site-packages\torch\nn\modules\conv.py", line 456, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
RuntimeError: Input type (__int64) and bias type (float) should be the same

[lqin0818]

the model used was VGG11

[EarlyBloomer-byte]

Yeah, VGG11 was used. Check the READme for more information.