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| author | Sebastian Berg <sebastian@sipsolutions.net> | 2021-03-23 18:33:15 -0500 |
|---|---|---|
| committer | Sebastian Berg <sebastian@sipsolutions.net> | 2021-03-23 18:34:02 -0500 |
| commit | 10ee4e04091cccfb90832071b04b84dc8866d6ff (patch) | |
| tree | b71ca0af86ec95e77ddb986344641e827b0c5484 | |
| parent | 0b61abaed5049c148c30766db01b00a940b9b2f8 (diff) | |
| download | numpy-10ee4e04091cccfb90832071b04b84dc8866d6ff.tar.gz | |
DOC: Link all three PRs and use the first PR as the "base" (filename)
| -rw-r--r-- | doc/release/upcoming_changes/15271.performance.rst | 16 |
1 files changed, 0 insertions, 16 deletions
diff --git a/doc/release/upcoming_changes/15271.performance.rst b/doc/release/upcoming_changes/15271.performance.rst deleted file mode 100644 index 43502fb79..000000000 --- a/doc/release/upcoming_changes/15271.performance.rst +++ /dev/null @@ -1,16 +0,0 @@ -Reduced call overheads with keyword arguments ---------------------------------------------- -In the following cases NumPy now has a much reduced call -overhead: - -* The array creation functions ``np.asarray``, - ``np.asanyarray``, ``np.ascontiguousarray``, and - ``np.asfortranarray``. These are now always as fast - as ``np.array`` itself. -* Universal functions (partially limited to Python 3.8+). -* Many NumPy array methods when keyword arguments are used. - -This can lead to large performance improvements for some -function calls when working with small arrays. -For functions improved here, the use of keyword arguments -will only have a minimal performance impact. |