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import torch | |
class GaussianNoise(object): | |
def __init__(self, mean=0., std=1.): | |
self.std = std | |
self.mean = mean | |
def __call__(self, tensor): | |
return tensor + torch.randn(tensor.size()) * self.std + self.mean | |
def __repr__(self): | |
return self.__class__.__name__ + '(mean={0}, std={1})'.format(self.mean, self.std) | |
if __name__ == "__main__": | |
pass | |