I am trying to run your implementation for the adversarial attack on the pre-trained "fcn8s-atonce" segmentation model:
According to the GAP_seg.py script arguments, the --gpu_ids flag can be set to -1 (to run it on CPU). Is the code compatible with CPU run?
When trying to run the code on 2 GPUs, I am encountering "CUDA memory" issues. What is the configuration that you used for the implementation? What Pytorch/torchvision/CUDA versions, with how much CUDA memory?
I am not sure if the semantic segmentation code is compatible with CPU and can be run on multiple GPUs. We checked these with classification though, and they work.
Hi,
I am trying to run your implementation for the adversarial attack on the pre-trained "fcn8s-atonce" segmentation model:
GAP_seg.py
script arguments, the--gpu_ids
flag can be set to -1 (to run it on CPU). Is the code compatible with CPU run?Thanks