Input and output Dimension of LSTM RNN
You can convert input to vectors of labels + day number . E.g: 

(First column is day-number, rest of the columns indicate presence/absence of a label)


[[ 1 0 1 0 0 0 0 .......]
 [ 2 1 0 0 1 0 0 .......]
 [ 3 1 1 1 1 0 0 .......]
 [ 4 1 0 1 1 0 0 .......]
 [ 5 1 1 0 1 0 0 .......]]

(5000, 201)



Output should be a vector of probabilities for individual labels.

This article has an example :

https://machinelearningmastery.com/multivariate-time-series-forecasting-lstms-keras/