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Readme says that Keras backend support input_dim > 1. I have tried to set the input_dim greater than one, and the model throws an error during the first training epoch.
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Similar to #453, but training NBEATS() with a val_series, I am getting:
`RuntimeError: Tensor for argument #2 'mat1' is on CPU, but expected it to be on GPU (while checking arguments for addmm)`
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I am deciding on a model for my agriculture dataset where crop growth is measured.
For that dataset, I have past data, such as the previously used amounts of fertilizers and past weather data.
For…
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Hello,
I just trained my first model on darts while using a gpu and cuda. All worked fine through training, but I ran into an issue when I go for a model prediction.
AttributeError: 'Tensor' obj…
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HI
I ddin't find any documentation related to saving the trained model. I want to save my model for further usage.
Thanks
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My model (DeepAR) is performing way better than I think it should.
I've done some hunting and it appears that even in test mode `input_vector` at this [point](https://github.com/jdb78/pytorch-forec…
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It appears when using NBEATs model while Generic_architecture is set to False that there is a tensor assigned to CPU while the rest is GPU:
RuntimeError Traceback (most r…
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**Describe the bug**
When calling "historical_forecast" or "predict" on a fittel TCN model trained using GPUs.
Happens right after calling the method.
**To Reproduce**
Steps to reproduce the …
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Hi,
thanks for the great library.
I have an usability question.
I have trained an NBeats model on a dataframe containing 16 time series as in the example (https://pytorch-forecasting.readthedoc…
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https://github.com/cchallu/nbeatsx
I think we should implement nbeatsx in pytorch-forecasting.Nbeats is not able to use exogenous variables while nbeatsx can.