Run RawKNNClassifier._predict_fc
as parallel to avoid memory issues
#9
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Closes #8 by creating a
joblib.Parallel
job to retrieve predictions for a feature collection. Options are provided for specifying the size of the batch (chunk_size
) and the number of threads to use (num_threads
). Once all neighbors are retrieved, the result is stitched back together into anee.FeatureCollection
.Note that this is a way to do this server-side, but that may not be the best workflow for this use case. Typically, one wants to run the feature collection mode to do cross-validation on the plots used to fit the model or run a new set of targets. We are investigating the possibility of: 1) converting the feature collection client-side; and 2) using
sknnr
to run the prediction locally.We will keep this PR open as we decide on the best path forward.