Hi and first of all thanks for your job on Nixtla library 🙌 I'm currently fitting

neuralforecast

Temporal Fusion Transformers to some retail dataset and doing kind of a parallel with DeepAR training procedure (requiring

context_length

+

prediction_length

parameters) I wonder what would happen during training with series that are just the length of the

input_size

parameter. E.g. : if a series is 156-week long and my

input_size

model parameter is

156

, how are such series handled during training ? Are they padded with

0

in the past? Are they discarded? Cheers 🤓

Hi @Matthieu ANTUNES -LYON-! Yes, each batch is padded with 0s on the left based on the longest time series. You will need to also set

start_padding_enabled

to True so that those very short ts (with length < input + h) are used during training

Hi Christian, thanks for your prompt reply. Crystal clear, much appreciated 😄