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I am getting the error in the environment:
Error in purrr::map(., .f = function(df) { : ℹ In index: 1. Caused by error in `pkg.env$pd$Timestamp()`: ! attempt to apply non-function Error in `purrr::…
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Test model and evaluate MAPE
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### Expected behavior
Code:
```
from pytorch_forecasting.models import NBeats, BaseModel
from pytorch_lightning import Trainer, LightningModule
model = NBeats()
trainer.fit(model, train, val…
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### Description
It would be great to have a new feature that combines both direct and recursive forecasting strategies within the neuralforecast library. Currently, direct forecasting models like NHI…
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Hi, I was exploring the repository and noticed that the loss metrics import statement in `nbeats.py` was missing some of the import statements causing errors in line 361 to 367.
Current the statemen…
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I am quite new and I am still trying to understand how NBEATS is handling exogenous variables, I know the architecture is not designed for that, and this issue is overcome in NBEATx
How are handl…
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Hi.
Trying to implement a **custom loss function** patching the default `MASE()` object (which inherits from `MultiHorizonMetric()` and `Metric()`).
I am debugging the `loss` computation to hunt…
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I'm trying to run a version with the "Alternative Padding Strategy" suggested in 18.1. Everything has worked well until Model 6 NBEATS ensemble. I've tried adjusting the nbeats() arguments, but the …
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Hi, presently I'm getting the good accuracy for my data using "NBEATS & N-Hits" Models from Darts library. But I am also want to use "future_covariates" to above models. Is there any possibility to do…
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- PyTorch-Forecasting version: 0.9.0
- PyTorch version: 1.10.0
- Python version: 3.7.9
- Operating System: MacOS
### Expected behavior
After training N-BEATS model with NBeats.from_dataset() …