set_unlabeled_data_preprocess
code_loader.leap_binder.set_unlabeled_data_preprocess
The
leap_binder.set_unlabeled_data_preprocess binding function points to a preprocessing, similar to the Preprocessing Function, but points to unlabeled data lacking the ground-truth values.This is often used to prioritize samples for labeling, which can be done by using the Fetch Similar analysis.
code_loader.leap_binder.set_unlabeled_data_preprocess(
function=Callable[[], PreprocessResponse]
)
Args | Text |
|---|---|
function |
from code_loader import leap_binder
from code_loader.contract.datasetclasses import PreprocessingResponse
# Preprocessing Function
def unlabeled_preprocessing_func() -> PreprocessingResponse:
...
return PreprocessingResponse(length=len(unlabeled_df), data=unlabeled_df)
leap_binder.set_unlabeled_data_preprocess(function=unlabeled_preprocessing_func)
Full examples can be found at the Dataset Integration section of the following guides:
Last modified 10mo ago