def to_gpu(self, gpu_ids: Union[int, list, ]):
if isinstance(gpu_ids, int):
gpu_ids = [gpu_ids]
self.gpu_ids = gpu_ids
self.device = (torch.device('cuda', self.gpu_ids[0])
if self.gpu_ids[0] >= 0 else torch.device('cpu'))
self.net.to(self.device)
if self.optimizer is not None:
move_optim(self.optimizer, self.device)
def to_gpu(self, gpu_ids: Union[int, list, ]) -> None:
"""Move network to specified GPU(s).
Parameters
----------
gpu_ids
GPU(s) on which to perform training or prediction.
"""
if isinstance(gpu_ids, int):
gpu_ids = [gpu_ids]
self.gpu_ids = gpu_ids
self.device = (torch.device('cuda', self.gpu_ids[0])
if self.gpu_ids[0] >= 0 else torch.device('cpu'))
self.net.to(self.device)
if self.optimizer is not None:
move_optim(self.optimizer, self.device)
