Hi, this is the example given in the document 7 (I modified the numbers just to show a simple example of 1 in and 1 out LSTM):
>>> rnn = nn.LSTM(1, 100, 4)
>>> input = Variable(torch.randn(1, 1, 1))
>>> h0 = Variable(torch.randn(4, 1, 100))
>>> c0 = Variable(torch.randn(4, 1, 100))
>>> output, hn = rnn(input, (h0, c0))

This gives an output dimension of  [1, 1, 100].
How do I reduce it to be of a size [1, 1, 1] (basic 1 in 1 out LSTM)? I tried a linear layer and it didn’t work (loss not decreasing properly). I could only make a simple LSTM work with 1 hidden state at the moment.
Any ideas?