Q: forecasting with TFT - forecast results are very flat I'm using TFT (Temporal Fusion Transformer) from Pytorch-forecating for the first time for my forecasting project. Im quite confused by a few things:

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*forecasted time series is very flat, what are the possible reasons for this? is it my train data set is too short? the train data set length is between 1 max_encoder_length and 2 times of max_encoder_length, ratio of max_encoder_length:max_prediction_length is 4:1;


*how does optimize_hyperparameters work? will it update the model with best parameters after being run? or I should manually update the model with output values of the process? Im asking because after I run it, nothing seem happened, the model remain unchanged.
