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Fixed weighted mean everywhere #407
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This commit reintroduces the features that were present in `LambdaTransform`, but only allowing registered functions. While being stricter, that allows for closer scaffolding and raising errors early on, so that users cannot provide functions that will not be (de)serializable later on. As there are a few failure modes, the focus is on providing detailed error messages to enable users to solve problems without external help.
This enables specialized, manually specified schedules, as for example required in diffusion models for inference. Closes #402.
Add class for custom transforms to adapter, similar to `LambdaTransform`.
Enable integration with fixed, non-uniform schedule.
vpratz
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Apr 13, 2025
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Looks good to me, thanks for the quick fix.
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