module.parameters() should only return unique parameters ? #29

In [141]: L = nn.Linear(10,10)
     ...: S = nn.Sequential()
     ...: S.add_module('a', L)
     ...: S.add_module('b', L)
     ...: len(list(S.parameters()))
     ...:
Out[141]: 4

Listing shared parameters multiple times seems wrong... because for example SGD will end up accumulating the gradients twice (I think).

Also from a theoretical point of view I would say this model only has 110 parameters, not 220.