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I saw that for some other algorithms for timeseries data it is advised to remove trend and seasonality before doing the prediction (ex: ARIMA and LSTM)

I figured out from the paper that SageMaker's DeepAR deals internally with seasonality, but does the same thing stands for trend?
Let's say I have multiple timeseries, where some of them have positive, and some have negative trend. Should I remove trend and then use DeepAR prediction, or should I just ignore it and let DeepAR handle it?

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