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Backporting fixes:

• Fix type annotation for device in PyTorchPredictor #3094 by @lostella
• extend exception for invalid offset_name #3115 by @Borda

Backporting:

• Fix Rotbaum serialization and deserialization #3068 by @pantanurag555
• Fix Rotbaum to handle short series #3073 by @leica2023

Backporting:

• Fix Rotbaum serialization and deserialization #3068 by @pantanurag555
• Fix Rotbaum to handle short series #3073 by @leica2023

Backporting fixes:

• Fix iterable.Cached. #3060 by @jaheba
• Torch: Remove double caching of dataset. #3061 by @jaheba

Backporting fixes:

• Fix edge cases in metric computation #3037 (@lostella)
• Refactor tests for ev.aggregations #3038 (@lostella)
• Add plt.show() to README #3043 (@lostella)
• Rotbaum: Add item-id to forecast. #3049 (@jaheba)
• Fix mypy checks #3052 (@lostella)

Backporting fixes:

• Fix edge cases in metric computation #3037 (@lostella)
• Refactor tests for ev.aggregations #3038 (@lostella)
• Rotbaum: Add item-id to forecast. #3049 (@jaheba)
• Fix mypy checks #3052 (@lostella)

Release notes coming soon

Fixing issues with updated requirements, which would prevent the package from installing alongside old versions of PyTorch Lightning:

• Fix lightning import (#3018 by @shchur)
• Update requirements-pytorch.txt (#3019 by @shchur)