# PyTorch LSTM with varying time steps

Is it possible to create an LSTM in PyTorch where the time steps are varying? For example, heights where measurements are taken at various times. The data might look like this:

Person id Inches tall Date
1 12 2020-01-01
1 15 2020-03-09
1 32 2020-04-01
1 40 2021-01-01
2 38 2020-05-20
...

Given a history of 4 heights and dates, I'd like to get a prediction of a height at a particular date:

lstm(torch.tensor[(21, '2020-01-02'),
(23, '2020-02-02'),
(29, '2020-04-12'),
(41, '2020-12-02')],
'2022-01-01')


I passed in '2022-01-01' after the 4 tuples above because I want to get the prediction for my height on this date.

Is this possible? How can I do this?