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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def resample(self, seed=None):
 """Resample the dataset. Args: seed (int, optional):
 Seed for resampling. By default no seed is used. """

        if seed is not None:
            gen = torch.manual_seed(seed)
        else:
            gen = torch.default_generator

        if self.replacement:
            self.perm = torch.LongTensor(len(self)).random_(
                len(self.dataset), generator=gen)
        else:
            self.perm = torch.randperm(
                len(self.dataset), generator=gen).narrow(0, 0, len(self))