I think an integer division by two should do the trick at least in this case
something like
tmp = torch.tensor([1,3,5,7]) 
tmp2 = tmp.div(2)

(and if you do not only got a LongTensor: tmp2 = tmp2.trunc())
However in a more general case you could simply generate some masks (I know its still a for loop but should be quite faster than accessing every single value):
range_mins = [2,4,6]
mask = torch.zeros_like(tmp)
for _min in range_mins:
    mask = mask.add((tmp > _min).long())