src/utils.py [54:71]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        self.inv_s = (self.max - self.min) / (range[1] - range[0])
        self.inv_s[self.inv_s == 0.0] = 1.0
        self.s = 1.0 / self.inv_s

    def reset(self):
        self.s = torch.ones_like(self.s)
        self.inv_s = torch.ones_like(self.s)
        self.min = torch.zeros_like(self.s)

    def transform(self, tensor: torch.tensor):
        t, remainder = self._t(tensor)
        t.sub_(self.min).mul_(self.s).add_(self.range[0])
        return self._inv_t(t, remainder)

    def inv_transform(self, tensor: torch.tensor):
        t, remainder = self._t(tensor)
        t.sub_(self.range[0]).mul_(self.inv_s.to(t.device)).add_(self.min.to(t.device))
        return self._inv_t(t, remainder)
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



src/utils.py [91:108]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        self.inv_s = (self.max - self.min) / (range[1] - range[0])
        self.inv_s[self.inv_s == 0.0] = 1.0
        self.s = 1.0 / self.inv_s

    def reset(self):
        self.s = torch.ones_like(self.s)
        self.inv_s = torch.ones_like(self.s)
        self.min = torch.zeros_like(self.s)

    def transform(self, tensor: torch.tensor):
        t, remainder = self._t(tensor)
        t.sub_(self.min).mul_(self.s).add_(self.range[0])
        return self._inv_t(t, remainder)

    def inv_transform(self, tensor: torch.tensor):
        t, remainder = self._t(tensor)
        t.sub_(self.range[0]).mul_(self.inv_s.to(t.device)).add_(self.min.to(t.device))
        return self._inv_t(t, remainder)
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -