How to split a dataset into train and test sets for time series (multiple step-multiple output forecasting)?
Assuming you have sales data for 36 month and you want to forecast for next 6 or 9
months. Lets create the train and test data at 70 and 30. 


  train data= 36*70/100= 26(rounding value of 25.2)
  test data= 10(leftout sample)


Now we'll build a model on train data and forecast values on test data(those 10 points), to measure model performance we use MAE or MSE, always MAE or MSE values should be less. Once you model is doing good then forecast for future 6 to 9 months. i.e multiple output in one time prediction.