Hi, this is the example given in the document (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?