The train() and eval() call change the internal self.training flag, so you could grep for it in the source folder (grep -r self.training).
Currently it seems these modules are affected by it in the PyTorch core:

Quantization modules
Dropout
InstanceNorm
BatchNorm
RNN (probably only if using cudnn, as different implementations will be called)
RReLU

Besides that all custom nn.Modules might of course use this flag internally.