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