PyTorch 训练加速

PyTorch Dataloader 加速

参考源码：

https://github.com/NVIDIA/apex/blob/f5cd5ae937f168c763985f627bbf850648ea5f3f/examples/imagenet/main_amp.py#L256

class data_prefetcher(): def __init__(self, loader): self.loader = iter(loader) self.stream = torch.cuda.Stream() self.mean = torch.tensor([0.485 * 255, 0.456 * 255, 0.406 * 255]).cuda().view(1,3,1,1) self.std = torch.tensor([0.229 * 255, 0.224 * 255, 0.225 * 255]).cuda().view(1,3,1,1) # With Amp, it isn't necessary to manually convert data to half. # if args.fp16: # self.mean = self.mean.half() # self.std = self.std.half() self.preload()
 def preload(self): try: self.next_input, self.next_target = next(sel
 

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原文链接：blog.csdn.net/jacke121/article/details/91976786