No, I meant if your GPU memory is filling up and you thus cannot allocate any more data on the device.
You can check the memory usage via nvidia-smi or in your script via e.g. torch.cuda.memory_allocated().
Are you using custom CUDA code or did you execute cuda-memcheck just on the complete PyTorch model?