LSTM::permute_hidden breaks Liskov substitution principle #43072
Description
While working on PR #43068, I found a method on LSTM which breaks the Liskov substitution principle. The class LSTM inherits from RNNBase and redefines a method called permute_hidden which returns two tensors (ref):
class LSTM(RNNBase):
...
def permute_hidden(self, hx, permutation):
# type: (Tuple[Tensor, Tensor], Optional[Tensor]) -> Tuple[Tensor, Tensor]
if permutation is None:
return hx
return apply_permutation(hx[0], permutation), apply_permutation(hx[1], permutation)RNNBase defines this method returning only one tensor (ref)
class RNNBase(torch.nn.module):
...
def permute_hidden(self, hx, permutation):
# type: (Tensor, Optional[Tensor]) -> Tensor
if permutation is None:
return hx
return apply_permutation(hx, permutation)Given this difference, it is not possible to correctly type permute_hidden because of the Liskov substitution principle. Should LSTM not inherit from RNNBase?