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|
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?