Hi! I came across this code during Jan's presentation at Woods Hole for the DL course. I was really interested in the idea and am attempting to use it with a large dataset, starting with training the cycleGAN. I have not yet had any problem running the code normally, but I was hoping someone could point me in the right direction for where to implement GPU parallelization.
was hoping to follow https://pytorch.org/tutorials/beginner/blitz/data_parallel_tutorial.html#create-model-and-dataparallel
I have tried a few things, both in train.py, init.py (in models), but I cannot find the right place to use nn.DataParallel.
Any suggestions? I am rather new at this so I may have overlooked something obvious.
Hi! I came across this code during Jan's presentation at Woods Hole for the DL course. I was really interested in the idea and am attempting to use it with a large dataset, starting with training the cycleGAN. I have not yet had any problem running the code normally, but I was hoping someone could point me in the right direction for where to implement GPU parallelization.
was hoping to follow https://pytorch.org/tutorials/beginner/blitz/data_parallel_tutorial.html#create-model-and-dataparallel
I have tried a few things, both in train.py, init.py (in models), but I cannot find the right place to use nn.DataParallel.
Any suggestions? I am rather new at this so I may have overlooked something obvious.