forked from scikit-learn/scikit-learn.github.io
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathparallelism.html
598 lines (518 loc) · 31.3 KB
/
parallelism.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
<!DOCTYPE html>
<!--[if IE 8]><html class="no-js lt-ie9" lang="en" > <![endif]-->
<!--[if gt IE 8]><!--> <html class="no-js" lang="en" > <!--<![endif]-->
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>8.3. Parallelism, resource management, and configuration — scikit-learn 1.0.dev0 documentation</title>
<link rel="canonical" href="http://scikit-learn.org/stable/computing/parallelism.html" />
<link rel="shortcut icon" href="../_static/favicon.ico"/>
<link rel="stylesheet" href="../_static/css/vendor/bootstrap.min.css" type="text/css" />
<link rel="stylesheet" href="../_static/gallery.css" type="text/css" />
<link rel="stylesheet" href="../_static/gallery-binder.css" type="text/css" />
<link rel="stylesheet" href="../_static/gallery-dataframe.css" type="text/css" />
<link rel="stylesheet" href="../_static/gallery-rendered-html.css" type="text/css" />
<link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
<script id="documentation_options" data-url_root="../" src="../_static/documentation_options.js"></script>
<script src="../_static/jquery.js"></script>
</head>
<body>
<nav id="navbar" class="sk-docs-navbar navbar navbar-expand-md navbar-light bg-light py-0">
<div class="container-fluid sk-docs-container px-0">
<a class="navbar-brand py-0" href="../index.html">
<img
class="sk-brand-img"
src="../_static/scikit-learn-logo-small.png"
alt="logo"/>
</a>
<button
id="sk-navbar-toggler"
class="navbar-toggler"
type="button"
data-toggle="collapse"
data-target="#navbarSupportedContent"
aria-controls="navbarSupportedContent"
aria-expanded="false"
aria-label="Toggle navigation"
>
<span class="navbar-toggler-icon"></span>
</button>
<div class="sk-navbar-collapse collapse navbar-collapse" id="navbarSupportedContent">
<ul class="navbar-nav mr-auto">
<li class="nav-item">
<a class="sk-nav-link nav-link" href="../install.html">Install</a>
</li>
<li class="nav-item">
<a class="sk-nav-link nav-link" href="../user_guide.html">User Guide</a>
</li>
<li class="nav-item">
<a class="sk-nav-link nav-link" href="../modules/classes.html">API</a>
</li>
<li class="nav-item">
<a class="sk-nav-link nav-link" href="../auto_examples/index.html">Examples</a>
</li>
<li class="nav-item">
<a class="sk-nav-link nav-link nav-more-item-mobile-items" href="../getting_started.html">Getting Started</a>
</li>
<li class="nav-item">
<a class="sk-nav-link nav-link nav-more-item-mobile-items" href="../tutorial/index.html">Tutorial</a>
</li>
<li class="nav-item">
<a class="sk-nav-link nav-link nav-more-item-mobile-items" href="../whats_new/v1.0.html">What's new</a>
</li>
<li class="nav-item">
<a class="sk-nav-link nav-link nav-more-item-mobile-items" href="../glossary.html">Glossary</a>
</li>
<li class="nav-item">
<a class="sk-nav-link nav-link nav-more-item-mobile-items" href="../developers/index.html">Development</a>
</li>
<li class="nav-item">
<a class="sk-nav-link nav-link nav-more-item-mobile-items" href="../faq.html">FAQ</a>
</li>
<li class="nav-item">
<a class="sk-nav-link nav-link nav-more-item-mobile-items" href="../support.html">Support</a>
</li>
<li class="nav-item">
<a class="sk-nav-link nav-link nav-more-item-mobile-items" href="../related_projects.html">Related packages</a>
</li>
<li class="nav-item">
<a class="sk-nav-link nav-link nav-more-item-mobile-items" href="../roadmap.html">Roadmap</a>
</li>
<li class="nav-item">
<a class="sk-nav-link nav-link nav-more-item-mobile-items" href="../about.html">About us</a>
</li>
<li class="nav-item">
<a class="sk-nav-link nav-link nav-more-item-mobile-items" href="https://github.com/scikit-learn/scikit-learn">GitHub</a>
</li>
<li class="nav-item">
<a class="sk-nav-link nav-link nav-more-item-mobile-items" href="https://scikit-learn.org/dev/versions.html">Other Versions and Download</a>
</li>
<li class="nav-item dropdown nav-more-item-dropdown">
<a class="sk-nav-link nav-link dropdown-toggle" href="#" id="navbarDropdown" role="button" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false">More</a>
<div class="dropdown-menu" aria-labelledby="navbarDropdown">
<a class="sk-nav-dropdown-item dropdown-item" href="../getting_started.html">Getting Started</a>
<a class="sk-nav-dropdown-item dropdown-item" href="../tutorial/index.html">Tutorial</a>
<a class="sk-nav-dropdown-item dropdown-item" href="../whats_new/v1.0.html">What's new</a>
<a class="sk-nav-dropdown-item dropdown-item" href="../glossary.html">Glossary</a>
<a class="sk-nav-dropdown-item dropdown-item" href="../developers/index.html">Development</a>
<a class="sk-nav-dropdown-item dropdown-item" href="../faq.html">FAQ</a>
<a class="sk-nav-dropdown-item dropdown-item" href="../support.html">Support</a>
<a class="sk-nav-dropdown-item dropdown-item" href="../related_projects.html">Related packages</a>
<a class="sk-nav-dropdown-item dropdown-item" href="../roadmap.html">Roadmap</a>
<a class="sk-nav-dropdown-item dropdown-item" href="../about.html">About us</a>
<a class="sk-nav-dropdown-item dropdown-item" href="https://github.com/scikit-learn/scikit-learn">GitHub</a>
<a class="sk-nav-dropdown-item dropdown-item" href="https://scikit-learn.org/dev/versions.html">Other Versions and Download</a>
</div>
</li>
</ul>
<div id="searchbox" role="search">
<div class="searchformwrapper">
<form class="search" action="../search.html" method="get">
<input class="sk-search-text-input" type="text" name="q" aria-labelledby="searchlabel" />
<input class="sk-search-text-btn" type="submit" value="Go" />
</form>
</div>
</div>
</div>
</div>
</nav>
<div class="d-flex" id="sk-doc-wrapper">
<input type="checkbox" name="sk-toggle-checkbox" id="sk-toggle-checkbox">
<label id="sk-sidemenu-toggle" class="sk-btn-toggle-toc btn sk-btn-primary" for="sk-toggle-checkbox">Toggle Menu</label>
<div id="sk-sidebar-wrapper" class="border-right">
<div class="sk-sidebar-toc-wrapper">
<div class="sk-sidebar-toc-logo">
<a href="../index.html">
<img
class="sk-brand-img"
src="../_static/scikit-learn-logo-small.png"
alt="logo"/>
</a>
</div>
<div class="btn-group w-100 mb-2" role="group" aria-label="rellinks">
<a href="computational_performance.html" role="button" class="btn sk-btn-rellink py-1" sk-rellink-tooltip="8.2. Computational Performance">Prev</a><a href="../computing.html" role="button" class="btn sk-btn-rellink py-1" sk-rellink-tooltip="8. Computing with scikit-learn">Up</a>
<a href="../modules/model_persistence.html" role="button" class="btn sk-btn-rellink py-1" sk-rellink-tooltip="9. Model persistence">Next</a>
</div>
<div class="alert alert-danger p-1 mb-2" role="alert">
<p class="text-center mb-0">
<strong>scikit-learn 1.0.dev0</strong><br/>
<a href="http://scikit-learn.org/dev/versions.html">Other versions</a>
</p>
</div>
<div class="alert alert-warning p-1 mb-2" role="alert">
<p class="text-center mb-0">
Please <a class="font-weight-bold" href="../about.html#citing-scikit-learn"><string>cite us</string></a> if you use the software.
</p>
</div>
<div class="sk-sidebar-toc">
<ul>
<li>
<a href="../user_guide.html" class="sk-toc-active">User Guide</a>
</li>
<ul>
<li>
<a href="../supervised_learning.html" class="">1. Supervised learning</a>
</li>
<li>
<a href="../unsupervised_learning.html" class="">2. Unsupervised learning</a>
</li>
<li>
<a href="../model_selection.html" class="">3. Model selection and evaluation</a>
</li>
<li>
<a href="../inspection.html" class="">4. Inspection</a>
</li>
<li>
<a href="../visualizations.html" class="">5. Visualizations</a>
</li>
<li>
<a href="../data_transforms.html" class="">6. Dataset transformations</a>
</li>
<li>
<a href="../datasets.html" class="">7. Dataset loading utilities</a>
</li>
<li>
<a href="../computing.html" class="sk-toc-active">8. Computing with scikit-learn</a>
<ul>
<li class="sk-toctree-l3">
<a href="scaling_strategies.html">8.1. Strategies to scale computationally: bigger data</a>
</li>
<li class="sk-toctree-l3">
<a href="computational_performance.html">8.2. Computational Performance</a>
</li>
<li class="sk-toctree-l3">
<a href="">8.3. Parallelism, resource management, and configuration</a>
</li>
</ul>
</li>
<li>
<a href="../modules/model_persistence.html" class="">9. Model persistence</a>
</li>
<li>
<a href="../common_pitfalls.html" class="">10. Common pitfalls and recommended practices</a>
</li>
</ul>
</ul>
</div>
</div>
</div>
<div id="sk-page-content-wrapper">
<div class="sk-page-content container-fluid body px-md-3" role="main">
<div class="section" id="parallelism-resource-management-and-configuration">
<h1><span class="section-number">8.3. </span>Parallelism, resource management, and configuration<a class="headerlink" href="#parallelism-resource-management-and-configuration" title="Permalink to this headline">¶</a></h1>
<div class="section" id="parallelism">
<span id="id1"></span><h2><span class="section-number">8.3.1. </span>Parallelism<a class="headerlink" href="#parallelism" title="Permalink to this headline">¶</a></h2>
<p>Some scikit-learn estimators and utilities can parallelize costly operations
using multiple CPU cores, thanks to the following components:</p>
<ul class="simple">
<li><p>via the <a class="reference external" href="https://joblib.readthedocs.io/en/latest/">joblib</a> library. In
this case the number of threads or processes can be controlled with the
<code class="docutils literal notranslate"><span class="pre">n_jobs</span></code> parameter.</p></li>
<li><p>via OpenMP, used in C or Cython code.</p></li>
</ul>
<p>In addition, some of the numpy routines that are used internally by
scikit-learn may also be parallelized if numpy is installed with specific
numerical libraries such as MKL, OpenBLAS, or BLIS.</p>
<p>We describe these 3 scenarios in the following subsections.</p>
<div class="section" id="joblib-based-parallelism">
<h3><span class="section-number">8.3.1.1. </span>Joblib-based parallelism<a class="headerlink" href="#joblib-based-parallelism" title="Permalink to this headline">¶</a></h3>
<p>When the underlying implementation uses joblib, the number of workers
(threads or processes) that are spawned in parallel can be controlled via the
<code class="docutils literal notranslate"><span class="pre">n_jobs</span></code> parameter.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Where (and how) parallelization happens in the estimators is currently
poorly documented. Please help us by improving our docs and tackle <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/issues/14228">issue
14228</a>!</p>
</div>
<p>Joblib is able to support both multi-processing and multi-threading. Whether
joblib chooses to spawn a thread or a process depends on the <strong>backend</strong>
that it’s using.</p>
<p>Scikit-learn generally relies on the <code class="docutils literal notranslate"><span class="pre">loky</span></code> backend, which is joblib’s
default backend. Loky is a multi-processing backend. When doing
multi-processing, in order to avoid duplicating the memory in each process
(which isn’t reasonable with big datasets), joblib will create a <a class="reference external" href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.memmap.html">memmap</a>
that all processes can share, when the data is bigger than 1MB.</p>
<p>In some specific cases (when the code that is run in parallel releases the
GIL), scikit-learn will indicate to <code class="docutils literal notranslate"><span class="pre">joblib</span></code> that a multi-threading
backend is preferable.</p>
<p>As a user, you may control the backend that joblib will use (regardless of
what scikit-learn recommends) by using a context manager:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">joblib</span> <span class="kn">import</span> <span class="n">parallel_backend</span>
<span class="k">with</span> <span class="n">parallel_backend</span><span class="p">(</span><span class="s1">'threading'</span><span class="p">,</span> <span class="n">n_jobs</span><span class="o">=</span><span class="mi">2</span><span class="p">):</span>
<span class="c1"># Your scikit-learn code here</span>
</pre></div>
</div>
<p>Please refer to the <a class="reference external" href="https://joblib.readthedocs.io/en/latest/parallel.html#thread-based-parallelism-vs-process-based-parallelism">joblib’s docs</a>
for more details.</p>
<p>In practice, whether parallelism is helpful at improving runtime depends on
many factors. It is usually a good idea to experiment rather than assuming
that increasing the number of workers is always a good thing. In some cases
it can be highly detrimental to performance to run multiple copies of some
estimators or functions in parallel (see oversubscription below).</p>
</div>
<div class="section" id="openmp-based-parallelism">
<h3><span class="section-number">8.3.1.2. </span>OpenMP-based parallelism<a class="headerlink" href="#openmp-based-parallelism" title="Permalink to this headline">¶</a></h3>
<p>OpenMP is used to parallelize code written in Cython or C, relying on
multi-threading exclusively. By default (and unless joblib is trying to
avoid oversubscription), the implementation will use as many threads as
possible.</p>
<p>You can control the exact number of threads that are used via the
<code class="docutils literal notranslate"><span class="pre">OMP_NUM_THREADS</span></code> environment variable:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><style type="text/css">
span.prompt1:before {
content: "$ ";
}
</style><span class="prompt1"><span class="nv">OMP_NUM_THREADS</span><span class="o">=</span><span class="m">4</span> python my_script.py</span>
</pre></div></div></div>
<div class="section" id="parallel-numpy-routines-from-numerical-libraries">
<h3><span class="section-number">8.3.1.3. </span>Parallel Numpy routines from numerical libraries<a class="headerlink" href="#parallel-numpy-routines-from-numerical-libraries" title="Permalink to this headline">¶</a></h3>
<p>Scikit-learn relies heavily on NumPy and SciPy, which internally call
multi-threaded linear algebra routines implemented in libraries such as MKL,
OpenBLAS or BLIS.</p>
<p>The number of threads used by the OpenBLAS, MKL or BLIS libraries can be set
via the <code class="docutils literal notranslate"><span class="pre">MKL_NUM_THREADS</span></code>, <code class="docutils literal notranslate"><span class="pre">OPENBLAS_NUM_THREADS</span></code>, and
<code class="docutils literal notranslate"><span class="pre">BLIS_NUM_THREADS</span></code> environment variables.</p>
<p>Please note that scikit-learn has no direct control over these
implementations. Scikit-learn solely relies on Numpy and Scipy.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>At the time of writing (2019), NumPy and SciPy packages distributed on
pypi.org (used by <code class="docutils literal notranslate"><span class="pre">pip</span></code>) and on the conda-forge channel are linked
with OpenBLAS, while conda packages shipped on the “defaults” channel
from anaconda.org are linked by default with MKL.</p>
</div>
</div>
<div class="section" id="oversubscription-spawning-too-many-threads">
<h3><span class="section-number">8.3.1.4. </span>Oversubscription: spawning too many threads<a class="headerlink" href="#oversubscription-spawning-too-many-threads" title="Permalink to this headline">¶</a></h3>
<p>It is generally recommended to avoid using significantly more processes or
threads than the number of CPUs on a machine. Over-subscription happens when
a program is running too many threads at the same time.</p>
<p>Suppose you have a machine with 8 CPUs. Consider a case where you’re running
a <a class="reference internal" href="../modules/generated/sklearn.model_selection.GridSearchCV.html#sklearn.model_selection.GridSearchCV" title="sklearn.model_selection.GridSearchCV"><code class="xref py py-class docutils literal notranslate"><span class="pre">GridSearchCV</span></code></a> (parallelized with joblib)
with <code class="docutils literal notranslate"><span class="pre">n_jobs=8</span></code> over a
<a class="reference internal" href="../modules/generated/sklearn.ensemble.HistGradientBoostingClassifier.html#sklearn.ensemble.HistGradientBoostingClassifier" title="sklearn.ensemble.HistGradientBoostingClassifier"><code class="xref py py-class docutils literal notranslate"><span class="pre">HistGradientBoostingClassifier</span></code></a> (parallelized with
OpenMP). Each instance of
<a class="reference internal" href="../modules/generated/sklearn.ensemble.HistGradientBoostingClassifier.html#sklearn.ensemble.HistGradientBoostingClassifier" title="sklearn.ensemble.HistGradientBoostingClassifier"><code class="xref py py-class docutils literal notranslate"><span class="pre">HistGradientBoostingClassifier</span></code></a> will spawn 8 threads
(since you have 8 CPUs). That’s a total of <code class="docutils literal notranslate"><span class="pre">8</span> <span class="pre">*</span> <span class="pre">8</span> <span class="pre">=</span> <span class="pre">64</span></code> threads, which
leads to oversubscription of physical CPU resources and to scheduling
overhead.</p>
<p>Oversubscription can arise in the exact same fashion with parallelized
routines from MKL, OpenBLAS or BLIS that are nested in joblib calls.</p>
<p>Starting from <code class="docutils literal notranslate"><span class="pre">joblib</span> <span class="pre">>=</span> <span class="pre">0.14</span></code>, when the <code class="docutils literal notranslate"><span class="pre">loky</span></code> backend is used (which
is the default), joblib will tell its child <strong>processes</strong> to limit the
number of threads they can use, so as to avoid oversubscription. In practice
the heuristic that joblib uses is to tell the processes to use <code class="docutils literal notranslate"><span class="pre">max_threads</span>
<span class="pre">=</span> <span class="pre">n_cpus</span> <span class="pre">//</span> <span class="pre">n_jobs</span></code>, via their corresponding environment variable. Back to
our example from above, since the joblib backend of
<a class="reference internal" href="../modules/generated/sklearn.model_selection.GridSearchCV.html#sklearn.model_selection.GridSearchCV" title="sklearn.model_selection.GridSearchCV"><code class="xref py py-class docutils literal notranslate"><span class="pre">GridSearchCV</span></code></a> is <code class="docutils literal notranslate"><span class="pre">loky</span></code>, each process will
only be able to use 1 thread instead of 8, thus mitigating the
oversubscription issue.</p>
<p>Note that:</p>
<ul class="simple">
<li><p>Manually setting one of the environment variables (<code class="docutils literal notranslate"><span class="pre">OMP_NUM_THREADS</span></code>,
<code class="docutils literal notranslate"><span class="pre">MKL_NUM_THREADS</span></code>, <code class="docutils literal notranslate"><span class="pre">OPENBLAS_NUM_THREADS</span></code>, or <code class="docutils literal notranslate"><span class="pre">BLIS_NUM_THREADS</span></code>)
will take precedence over what joblib tries to do. The total number of
threads will be <code class="docutils literal notranslate"><span class="pre">n_jobs</span> <span class="pre">*</span> <span class="pre"><LIB>_NUM_THREADS</span></code>. Note that setting this
limit will also impact your computations in the main process, which will
only use <code class="docutils literal notranslate"><span class="pre"><LIB>_NUM_THREADS</span></code>. Joblib exposes a context manager for
finer control over the number of threads in its workers (see joblib docs
linked below).</p></li>
<li><p>Joblib is currently unable to avoid oversubscription in a
multi-threading context. It can only do so with the <code class="docutils literal notranslate"><span class="pre">loky</span></code> backend
(which spawns processes).</p></li>
</ul>
<p>You will find additional details about joblib mitigation of oversubscription
in <a class="reference external" href="https://joblib.readthedocs.io/en/latest/parallel.html#avoiding-over-subscription-of-cpu-ressources">joblib documentation</a>.</p>
</div>
</div>
<div class="section" id="configuration-switches">
<h2><span class="section-number">8.3.2. </span>Configuration switches<a class="headerlink" href="#configuration-switches" title="Permalink to this headline">¶</a></h2>
<div class="section" id="python-runtime">
<h3><span class="section-number">8.3.2.1. </span>Python runtime<a class="headerlink" href="#python-runtime" title="Permalink to this headline">¶</a></h3>
<p><a class="reference internal" href="../modules/generated/sklearn.set_config.html#sklearn.set_config" title="sklearn.set_config"><code class="xref py py-func docutils literal notranslate"><span class="pre">sklearn.set_config</span></code></a> controls the following behaviors:</p>
<dl class="field-list simple">
<dt class="field-odd">assume_finite</dt>
<dd class="field-odd"><p>used to skip validation, which enables faster computations but may
lead to segmentation faults if the data contains NaNs.</p>
</dd>
<dt class="field-even">working_memory</dt>
<dd class="field-even"><p>the optimal size of temporary arrays used by some algorithms.</p>
</dd>
</dl>
</div>
<div class="section" id="environment-variables">
<span id="environment-variable"></span><h3><span class="section-number">8.3.2.2. </span>Environment variables<a class="headerlink" href="#environment-variables" title="Permalink to this headline">¶</a></h3>
<p>These environment variables should be set before importing scikit-learn.</p>
<dl class="field-list">
<dt class="field-odd">SKLEARN_SITE_JOBLIB</dt>
<dd class="field-odd"><p>When this environment variable is set to a non zero value,
scikit-learn uses the site joblib rather than its vendored version.
Consequently, joblib must be installed for scikit-learn to run.
Note that using the site joblib is at your own risks: the versions of
scikit-learn and joblib need to be compatible. Currently, joblib 0.11+
is supported. In addition, dumps from joblib.Memory might be incompatible,
and you might loose some caches and have to redownload some datasets.</p>
<div class="deprecated">
<p><span class="versionmodified deprecated">Deprecated since version 0.21: </span>As of version 0.21 this parameter has no effect, vendored joblib was
removed and site joblib is always used.</p>
</div>
</dd>
<dt class="field-even">SKLEARN_ASSUME_FINITE</dt>
<dd class="field-even"><p>Sets the default value for the <code class="docutils literal notranslate"><span class="pre">assume_finite</span></code> argument of
<a class="reference internal" href="../modules/generated/sklearn.set_config.html#sklearn.set_config" title="sklearn.set_config"><code class="xref py py-func docutils literal notranslate"><span class="pre">sklearn.set_config</span></code></a>.</p>
</dd>
<dt class="field-odd">SKLEARN_WORKING_MEMORY</dt>
<dd class="field-odd"><p>Sets the default value for the <code class="docutils literal notranslate"><span class="pre">working_memory</span></code> argument of
<a class="reference internal" href="../modules/generated/sklearn.set_config.html#sklearn.set_config" title="sklearn.set_config"><code class="xref py py-func docutils literal notranslate"><span class="pre">sklearn.set_config</span></code></a>.</p>
</dd>
<dt class="field-even">SKLEARN_SEED</dt>
<dd class="field-even"><p>Sets the seed of the global random generator when running the tests,
for reproducibility.</p>
</dd>
<dt class="field-odd">SKLEARN_SKIP_NETWORK_TESTS</dt>
<dd class="field-odd"><p>When this environment variable is set to a non zero value, the tests
that need network access are skipped. When this environment variable is
not set then network tests are skipped.</p>
</dd>
</dl>
</div>
</div>
</div>
</div>
<div class="container">
<footer class="sk-content-footer">
© 2007 - 2020, scikit-learn developers (BSD License).
<a href="../_sources/computing/parallelism.rst.txt" rel="nofollow">Show this page source</a>
</footer>
</div>
</div>
</div>
<script src="../_static/js/vendor/bootstrap.min.js"></script>
<script>
window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)};ga.l=+new Date;
ga('create', 'UA-22606712-2', 'auto');
ga('set', 'anonymizeIp', true);
ga('send', 'pageview');
</script>
<script async src='https://www.google-analytics.com/analytics.js'></script>
<script>
$(document).ready(function() {
/* Add a [>>>] button on the top-right corner of code samples to hide
* the >>> and ... prompts and the output and thus make the code
* copyable. */
var div = $('.highlight-python .highlight,' +
'.highlight-python3 .highlight,' +
'.highlight-pycon .highlight,' +
'.highlight-default .highlight')
var pre = div.find('pre');
// get the styles from the current theme
pre.parent().parent().css('position', 'relative');
var hide_text = 'Hide prompts and outputs';
var show_text = 'Show prompts and outputs';
// create and add the button to all the code blocks that contain >>>
div.each(function(index) {
var jthis = $(this);
if (jthis.find('.gp').length > 0) {
var button = $('<span class="copybutton">>>></span>');
button.attr('title', hide_text);
button.data('hidden', 'false');
jthis.prepend(button);
}
// tracebacks (.gt) contain bare text elements that need to be
// wrapped in a span to work with .nextUntil() (see later)
jthis.find('pre:has(.gt)').contents().filter(function() {
return ((this.nodeType == 3) && (this.data.trim().length > 0));
}).wrap('<span>');
});
// define the behavior of the button when it's clicked
$('.copybutton').click(function(e){
e.preventDefault();
var button = $(this);
if (button.data('hidden') === 'false') {
// hide the code output
button.parent().find('.go, .gp, .gt').hide();
button.next('pre').find('.gt').nextUntil('.gp, .go').css('visibility', 'hidden');
button.css('text-decoration', 'line-through');
button.attr('title', show_text);
button.data('hidden', 'true');
} else {
// show the code output
button.parent().find('.go, .gp, .gt').show();
button.next('pre').find('.gt').nextUntil('.gp, .go').css('visibility', 'visible');
button.css('text-decoration', 'none');
button.attr('title', hide_text);
button.data('hidden', 'false');
}
});
/*** Add permalink buttons next to glossary terms ***/
$('dl.glossary > dt[id]').append(function() {
return ('<a class="headerlink" href="#' +
this.getAttribute('id') +
'" title="Permalink to this term">¶</a>');
});
/*** Hide navbar when scrolling down ***/
// Returns true when headerlink target matches hash in url
(function() {
hashTargetOnTop = function() {
var hash = window.location.hash;
if ( hash.length < 2 ) { return false; }
var target = document.getElementById( hash.slice(1) );
if ( target === null ) { return false; }
var top = target.getBoundingClientRect().top;
return (top < 2) && (top > -2);
};
// Hide navbar on load if hash target is on top
var navBar = document.getElementById("navbar");
var navBarToggler = document.getElementById("sk-navbar-toggler");
var navBarHeightHidden = "-" + navBar.getBoundingClientRect().height + "px";
var $window = $(window);
hideNavBar = function() {
navBar.style.top = navBarHeightHidden;
};
showNavBar = function() {
navBar.style.top = "0";
}
if (hashTargetOnTop()) {
hideNavBar()
}
var prevScrollpos = window.pageYOffset;
hideOnScroll = function(lastScrollTop) {
if (($window.width() < 768) && (navBarToggler.getAttribute("aria-expanded") === 'true')) {
return;
}
if (lastScrollTop > 2 && (prevScrollpos <= lastScrollTop) || hashTargetOnTop()){
hideNavBar()
} else {
showNavBar()
}
prevScrollpos = lastScrollTop;
};
/*** high performance scroll event listener***/
var raf = window.requestAnimationFrame ||
window.webkitRequestAnimationFrame ||
window.mozRequestAnimationFrame ||
window.msRequestAnimationFrame ||
window.oRequestAnimationFrame;
var lastScrollTop = $window.scrollTop();
if (raf) {
loop();
}
function loop() {
var scrollTop = $window.scrollTop();
if (lastScrollTop === scrollTop) {
raf(loop);
return;
} else {
lastScrollTop = scrollTop;
hideOnScroll(lastScrollTop);
raf(loop);
}
}
})();
});
</script>
<script id="MathJax-script" async src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-chtml.js"></script>
<script src="https://scikit-learn.org/versionwarning.js"></script>
</body>
</html>