1. 13 Apr, 2022 1 commit
    • Tim Hatch's avatar
      apply import merging for fbcode/vision/fair (2 of 2) · 34bbb3ad
      Tim Hatch authored
      Summary:
      Applies new import merging and sorting from µsort v1.0.
      
      When merging imports, µsort will make a best-effort to move associated
      comments to match merged elements, but there are known limitations due to
      the diynamic nature of Python and developer tooling. These changes should
      not produce any dangerous runtime changes, but may require touch-ups to
      satisfy linters and other tooling.
      
      Note that µsort uses case-insensitive, lexicographical sorting, which
      results in a different ordering compared to isort. This provides a more
      consistent sorting order, matching the case-insensitive order used when
      sorting import statements by module name, and ensures that "frog", "FROG",
      and "Frog" always sort next to each other.
      
      For details on µsort's sorting and merging semantics, see the user guide:
      https://usort.readthedocs.io/en/stable/guide.html#sorting
      
      Reviewed By: bottler
      
      Differential Revision: D35553814
      
      fbshipit-source-id: be49bdb6a4c25264ff8d4db3a601f18736d17be1
      34bbb3ad
  2. 04 Jan, 2022 1 commit
    • Jeremy Reizenstein's avatar
      Update license for company name · 9eeb456e
      Jeremy Reizenstein authored
      Summary: Update all FB license strings to the new format.
      
      Reviewed By: patricklabatut
      
      Differential Revision: D33403538
      
      fbshipit-source-id: 97a4596c5c888f3c54f44456dc07e718a387a02c
      9eeb456e
  3. 12 Aug, 2021 1 commit
    • Nikhila Ravi's avatar
      Ball Query · 103da633
      Nikhila Ravi authored
      Summary:
      Implementation of ball query from PointNet++.  This function is similar to KNN (find the neighbors in p2 for all points in p1). These are the key differences:
      -  It will return the **first** K neighbors within a specified radius as opposed to the **closest** K neighbors.
      - As all the points in p2 do not need to be considered to find the closest K, the algorithm is much faster than KNN when p2 has a large number of points.
      - The neighbors are not sorted
      - Due to the radius threshold it is not guaranteed that there will be K neighbors even if there are more than K points in p2.
      - The padding value for `idx` is -1 instead of 0.
      
      # Note:
      - Some of the code is very similar to KNN so it could be possible to modify the KNN forward kernels to support ball query.
      - Some users might want to use kNN with ball query - for this we could provide a wrapper function around the current `knn_points` which enables applying the radius threshold afterwards as an alternative. This could be called `ball_query_knn`.
      
      Reviewed By: jcjohnson
      
      Differential Revision: D30261362
      
      fbshipit-source-id: 66b6a7e0114beff7164daf7eba21546ff41ec450
      103da633