Migration Guide¶
Version 1.2 of lightonopu
and lightonml
introduce API changes, requiring action on your code:
lightonopu
¶
We noticed that in some situations, two successive transforms on related data can have inconsistent result, fitting the OPU on input data fixes this.
The previous methods transform1d
and transform2d
are still provided for compatibility, but you will get a deprecation warning on calling them. To migrate your code, do the following:
If you do several transform operations on related data (like train and test), first call
fit1d
orfit2d
on one of the data, and thentransform
(notice the 1d/2d suffix is removed)Alternatively, replace
transform1d
/transform2d
calls byfit_transform1d
/fit_transform2d
to get rid of the deprecation warning.
lightonml
¶
Similarly to lightonopu
, the OPUMap
objects in lightonml.projections.sklearn
and lightonml.projections.torch
now also have a fit
method. It can be called explicitly, or it will be called automatically when the first transform is performed. The migration procedure is similar:
- If you do several transform operations on related data (like train and test), first call fit
on one of the data, and then transform
, or forward
in the case of the Pytorch wrapper
- Alternatively, replace transform
calls by fit_transform
for the Scikit-learn wrapper.