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MNT Fix build when SKLEARN_OPENMP_PARALLELISM_ENABLED=False #24682

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Merged
merged 6 commits into from
Oct 19, 2022
Merged

MNT Fix build when SKLEARN_OPENMP_PARALLELISM_ENABLED=False #24682

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dfd970b
MNT Fix build when SKLEARN_OPENMP_PARALLELISM_ENABLED=False
lesteve Oct 17, 2022
5d52786
Use _openmp_thread_num
lesteve Oct 18, 2022
fdf9b38
openmp import not needed anymore
lesteve Oct 18, 2022
58970ff
trigger
lesteve Oct 18, 2022
0973d2f
Mention OpenMP helpers in the doc
lesteve Oct 18, 2022
f4d92dc
Merge branch 'main' into fix-pyodide-build
glemaitre Oct 18, 2022
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13 changes: 10 additions & 3 deletions doc/developers/performance.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -341,9 +341,16 @@ memory alignment, direct blas calls...
Using OpenMP
------------

Since scikit-learn can be built without OpenMP, it's necessary to
protect each direct call to OpenMP. This can be done using the following
syntax::
Since scikit-learn can be built without OpenMP, it's necessary to protect each
direct call to OpenMP.

There are some helpers in
[sklearn/utils/_openmp_helpers.pyx](https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/utils/_openmp_helpers.pyx)
that you can reuse for the main useful functionalities and already have the
necessary protection to be built without OpenMP.

If the helpers are not enough, you need to protect your OpenMP code using the
following syntax::

# importing OpenMP
IF SKLEARN_OPENMP_PARALLELISM_ENABLED:
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4 changes: 2 additions & 2 deletions sklearn/metrics/_pairwise_distances_reduction/_base.pyx.tp
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Original file line number Diff line number Diff line change
@@ -1,5 +1,4 @@
cimport numpy as cnp
cimport openmp

from cython cimport final
from cython.operator cimport dereference as deref
Expand Down Expand Up @@ -73,7 +72,8 @@ cpdef DTYPE_t[::1] _sqeuclidean_row_norms32(
)

with nogil, parallel(num_threads=num_threads):
thread_num = openmp.omp_get_thread_num()
thread_num = _openmp_thread_num()

for i in prange(n, schedule='static'):
# Upcasting the i-th row of X from float32 to float64
for j in range(d):
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