Sequence to Sequence Forecasting
**Problem:** You are given a sequence-to-sequence dataset with input and output sequences. Your task is to forecast the future values of the output sequence using a suitable algorithm.
**Example:** Suppose we have a dataset with input sequences of length 10 and output sequences of length 20. We want to forecast the future values of the output sequence using a suitable algorithm.
**Constraints:** You should use a suitable algorithm (e.g., LSTM, GRU) to handle the sequence-to-sequence nature of the dataset.
Test Cases
Test Case 1
Input:
[[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50]]Expected:
[[51.0,52.0,53.0,54.0,55.0,56.0,57.0,58.0,59.0,60.0,61.0,62.0,63.0,64.0,65.0,66.0,67.0,68.0,69.0,70.0]]Test Case 2
Input:
[[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50]]Expected:
[[51.0,52.0,53.0,54.0,55.0,56.0,57.0,58.0,59.0,60.0,61.0,62.0,63.0,64.0,65.0,66.0,67.0,68.0,69.0,70.0]]+ 3 hidden test cases