You can debug these CUDA Runtime Errors best if you run your code on CPU. This will give you a more useful traceback error.
But Most of the time CUDA Runtime Errors can be the cause of some index mismatching so like you tried to train a network with 10 output nodes on a dataset with 100 labels.

(Taken from here 1.)
Which is exactly what your screenshot is showing.
Keep in mind that CIFAR-10 and MNIST have 10 classes but CIFAR-100 has 100 classes.
Did you maybe forget to change the
self.fc2 = nn.Linear(64, 10)

to
self.fc2 = nn.Linear(64, 100)

?