def matmul(self, weights: Tensor) -> 'Ele':
""" A much faster trick:
L' = max(0, w) * L + min(0, w) * U
U' = max(0, w) * U + min(0, w) * L
"""
pos_ws, neg_ws = divide_pos_neg(weights)
newl_pos = self._lb.matmul(pos_ws)
newl_neg = self._ub.matmul(neg_ws)
newl = newl_pos + newl_neg
newu_pos = self._ub.matmul(pos_ws)
newu_neg = self._lb.matmul(neg_ws)
newu = newu_pos + newu_neg
return Ele(newl, newu)
def __mul__(self, flt) -> 'Ele':
if isinstance(flt, Tensor) and flt.dim() == 1 and flt.shape[0] == self.size()[-1]:
# each output vector dimension has its own factor
pos_ws, neg_ws = divide_pos_neg(flt)
newl_pos = self._lb * (pos_ws)
newl_neg = self._ub * (neg_ws)
newl = newl_pos + newl_neg
newu_pos = self._ub * (pos_ws)
newu_neg = self._lb * (neg_ws)
newu = newu_pos + newu_neg
return Ele(newl, newu)
elif not (isinstance(flt, float) or isinstance(flt, int)):
raise ValueError('Unsupported multiplication with', str(flt), type(flt))
flt = float(flt)
if flt >= 0:
return Ele(self._lb * flt, self._ub * flt)
else:
return Ele(self._ub * flt, self._lb * flt)