diff options
| author | Marc Glisse <marc.glisse@inria.fr> | 2020-04-12 21:57:51 +0200 |
|---|---|---|
| committer | Marc Glisse <marc.glisse@inria.fr> | 2020-04-12 21:57:51 +0200 |
| commit | 83a1bc1fb6124a35d515f4836d2e830f3dbdf0e7 (patch) | |
| tree | 09f15b27fac2f7279788c1d0db3c03cdeb12b4f7 /src/python/test/test_dtm.py | |
| parent | f9a933862050ca95b3a96d7a8572d62f7f2205a9 (diff) | |
Parallelize the "precomputed" case of knn
It is supposed to be possible to compile numpy with openmp, but it looks
like it isn't done in any of the usual packages.
It may be possible to refactor that code so there is less redundancy.
Diffstat (limited to 'src/python/test/test_dtm.py')
| -rwxr-xr-x | src/python/test/test_dtm.py | 3 |
1 files changed, 3 insertions, 0 deletions
diff --git a/src/python/test/test_dtm.py b/src/python/test/test_dtm.py index 37934fdb..bc0d3698 100755 --- a/src/python/test/test_dtm.py +++ b/src/python/test/test_dtm.py @@ -33,6 +33,9 @@ def test_dtm_compare_euclidean(): dtm = DistanceToMeasure(k, metric="precomputed") r4 = dtm.fit_transform(d) assert r4 == pytest.approx(r0) + dtm = DistanceToMeasure(k, metric="precomputed", n_jobs=2) + r4b = dtm.fit_transform(d) + assert r4b == pytest.approx(r0) dtm = DistanceToMeasure(k, implementation="keops") r5 = dtm.fit_transform(pts) assert r5 == pytest.approx(r0) |