Pytorch 加载数据加速

利用DataPretcher加速

device = torch.device("cuda")

class DataPrefetcher():
    def __init__(self, loader):
        self.loader = iter(loader)
        self.stream = torch.cuda.Stream()
        self.preload()

    def preload(self):
        try:
            self.batch = next(self.loader)
        except StopIteration:
            self.batch = None
            return
        with torch.cuda.stream(self.stream):
            for k in self.batch:
                if k != 'meta':
                    self.batch[k] = self.batch[k].to(device=device, non_blocking=True)

    def next(self):
        torch.cuda.current_stream().wait_stream(self.stream)
        batch = self.batch
        self.preload()
        return batch

详情参考:https://tianws.github.io/skill/2019/08/27/gpu-volatile/

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