You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
To what extent can R-tree be guaranteed to be deterministic?
We're using R-tree in TorchGeo for ML, where reproducibility of experiments and data splits is very important. Currently, we populate an R-tree index with a list of files, then use index.intersection(index.bounds) to iterate over all files. We've had a number of issues in the past with sets/dicts and want to make sure we're using R-tree correctly as well. By determinism, I mean that given the same random seed, all code reproduces the same results exactly.
As far as I can tell, files are returned in insertion order. Is this behavior guaranteed? Are there any other parts of R-tree that may not be deterministic?
The text was updated successfully, but these errors were encountered:
To what extent can R-tree be guaranteed to be deterministic?
We're using R-tree in TorchGeo for ML, where reproducibility of experiments and data splits is very important. Currently, we populate an R-tree index with a list of files, then use
index.intersection(index.bounds)
to iterate over all files. We've had a number of issues in the past with sets/dicts and want to make sure we're using R-tree correctly as well. By determinism, I mean that given the same random seed, all code reproduces the same results exactly.As far as I can tell, files are returned in insertion order. Is this behavior guaranteed? Are there any other parts of R-tree that may not be deterministic?
The text was updated successfully, but these errors were encountered: