transformer-time-series-prediction

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I believe that `input = torch.stack([item[0] for item in data]).view((input_window,batch_len,1))` should be changed to `input = torch.stack([item[0] for item in data]).T.unsqueeze(-1)`. This is because the orders are not correct if...

dyhan316

single-variable prediction

2

This seems to be a single-variable prediction, which only uses the sequence information of the own variables of the time signal, does not use other features

Pyramiding

Hello, for multi-steps predict, how to get the x, label y tensor? Would you like to use the seq 1-100 to demostrcate it?

aanxud888

why don't you use the transformer decoder?

1

as the tittle said.

tomly2019m

Result reproducibility

5

I have not been able to get the same same results as those presented here. Not even after 1000 epochs. In the code the number if epochs is 10 and...

hmate9

About model output

3

Thank you very much for the code. I applied the model to load decomposition, but I found that the final output is a straight line. Is it because there is...

13995976382

why multi-step predict future only use one prediction, rather than use the length of output_window like [-output_window:]

2

https://github.com/oliverguhr/transformer-time-series-prediction/blob/570d39bc0bbd61c823626ec9ca8bb5696c068187/transformer-multistep.py#L210

Jin-Xi

A bug when I add encoder layers

2

Thanks very much for your code. However, there are some difference between your code and the tutorial of PyTorch: [SEQUENCE-TO-SEQUENCE MODELING WITH NN.TRANSFORMER AND TORCHTEXT](https://pytorch.org/tutorials/beginner/transformer_tutorial.html) in `class TransAm` According to...

RuifMaxx