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Fix: removed input re-normalization by rin inside io_processor #2160

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Jan 13, 2024
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Fix: removed input re-normalization by rin inside io_processor #2160

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7a33d75
prevented input re-normalization by rin using .clone() inside `io_pro…
FourierMourier Jan 12, 2024
ffde571
Update CHANGELOG.md
dennisbader Jan 13, 2024
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2 changes: 1 addition & 1 deletion CHANGELOG.md
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Expand Up @@ -12,7 +12,7 @@ but cannot always guarantee backwards compatibility. Changes that may **break co
**Improved**

**Fixed**

- Fixed a bug when using a `TorchForecastingModel` with `use_reversible_instance_norm=True` and predicting with `n > output_chunk_length`. The input normalized multiple times. [#2160](https://github.com/unit8co/darts/pull/2160) by [FourierMourier](https://github.com/FourierMourier).
### For developers of the library:

## [0.27.1](https://github.com/unit8co/darts/tree/0.27.1) (2023-12-10)
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3 changes: 2 additions & 1 deletion darts/models/forecasting/pl_forecasting_module.py
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Expand Up @@ -50,7 +50,8 @@ def forward_wrapper(self, *args, **kwargs):

# x is input batch tuple which by definition has the past features in the first element starting with the
# first n target features
x: Tuple = args[0][0]
# assuming `args[0][0]` is torch.Tensor we could clone it to prevent target re-normalization
x: Tuple = args[0][0].clone()
# apply reversible instance normalization
x[:, :, : self.n_targets] = self.rin(x[:, :, : self.n_targets])
# run the forward pass
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