Solved by PengZhenghao in post #2 
              
              
                In the document, the examples using LSTM look like: 
>>> rnn = nn.LSTM(10, 20, 2)
>>> input = torch.randn(5, 3, 10)
>>> h0 = torch.randn(2, 3, 20)
>>> c0 = torch.randn(2, 3, 20)
>>> output, (hn, cn) = rnn(input, (h0, c0))

Where (hn, cn) contains the hidden state and cell state of current LSTM. So y…