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

    def preload(self):
        try:
            self.next_data_1, self.next_data_2 = next(self.loader)
        except StopIteration:
            self.next_data_1 = None
            self.next_data_2 = None
            return
        with torch.cuda.stream(self.stream):
            self.next_data_1 = self.next_data_1.cuda(non_blocking=True)
            self.next_data_2 = self.next_data_2.cuda(non_blocking=True)

    def next(self):
        torch.cuda.current_stream().wait_stream(self.stream)
        data_1, data_2 = self.next_data_1, self.next_data_2
        self.preload()
        return data_1, data_2

prefetcher = data_prefetcher(data_loader)
inputs, targets = prefetcher.next()
i = 0
while inputs is not None:
    #training process
    inputs, targets = prefetcher.next()
    i +=1