no problem. and to do something like this in pytorch you would just do something like:
output, (hx, cx) = model((input, (hx, cx))
and then in def forward:
def forward(self, inputs):
x, (hx, cx) = inputs
x = x.view(x.size(0), -1)
hx, cx = self.lstm(x, (hx, cx))
x = hx
return x, (hx, cx)
obviously a lot of other stuff in there for your desired outputs but thats the underlying basics to it