forked from scikit-learn/scikit-learn
-
Notifications
You must be signed in to change notification settings - Fork 0
/
setup.py
executable file
·640 lines (570 loc) · 22.5 KB
/
setup.py
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
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
#! /usr/bin/env python
#
# Copyright (C) 2007-2009 Cournapeau David <[email protected]>
# 2010 Fabian Pedregosa <[email protected]>
# License: 3-clause BSD
import importlib
import os
import platform
import shutil
import sys
import traceback
from os.path import join
from setuptools import Command, Extension, setup
from setuptools.command.build_ext import build_ext
try:
import builtins
except ImportError:
# Python 2 compat: just to be able to declare that Python >=3.8 is needed.
import __builtin__ as builtins
# This is a bit (!) hackish: we are setting a global variable so that the main
# sklearn __init__ can detect if it is being loaded by the setup routine, to
# avoid attempting to load components that aren't built yet.
# TODO: can this be simplified or removed since the switch to setuptools
# away from numpy.distutils?
builtins.__SKLEARN_SETUP__ = True
DISTNAME = "scikit-learn"
DESCRIPTION = "A set of python modules for machine learning and data mining"
with open("README.rst") as f:
LONG_DESCRIPTION = f.read()
MAINTAINER = "Andreas Mueller"
MAINTAINER_EMAIL = "[email protected]"
URL = "https://scikit-learn.org"
DOWNLOAD_URL = "https://pypi.org/project/scikit-learn/#files"
LICENSE = "new BSD"
PROJECT_URLS = {
"Bug Tracker": "https://github.com/scikit-learn/scikit-learn/issues",
"Documentation": "https://scikit-learn.org/stable/documentation.html",
"Source Code": "https://github.com/scikit-learn/scikit-learn",
}
# We can actually import a restricted version of sklearn that
# does not need the compiled code
import sklearn # noqa
import sklearn._min_dependencies as min_deps # noqa
from sklearn._build_utils import _check_cython_version # noqa
from sklearn.externals._packaging.version import parse as parse_version # noqa
VERSION = sklearn.__version__
# Custom clean command to remove build artifacts
class CleanCommand(Command):
description = "Remove build artifacts from the source tree"
user_options = []
def initialize_options(self):
pass
def finalize_options(self):
pass
def run(self):
# Remove c files if we are not within a sdist package
cwd = os.path.abspath(os.path.dirname(__file__))
remove_c_files = not os.path.exists(os.path.join(cwd, "PKG-INFO"))
if remove_c_files:
print("Will remove generated .c files")
if os.path.exists("build"):
shutil.rmtree("build")
for dirpath, dirnames, filenames in os.walk("sklearn"):
for filename in filenames:
root, extension = os.path.splitext(filename)
if extension in [".so", ".pyd", ".dll", ".pyc"]:
os.unlink(os.path.join(dirpath, filename))
if remove_c_files and extension in [".c", ".cpp"]:
pyx_file = str.replace(filename, extension, ".pyx")
if os.path.exists(os.path.join(dirpath, pyx_file)):
os.unlink(os.path.join(dirpath, filename))
if remove_c_files and extension == ".tp":
if os.path.exists(os.path.join(dirpath, root)):
os.unlink(os.path.join(dirpath, root))
for dirname in dirnames:
if dirname == "__pycache__":
shutil.rmtree(os.path.join(dirpath, dirname))
# Custom build_ext command to set OpenMP compile flags depending on os and
# compiler. Also makes it possible to set the parallelism level via
# and environment variable (useful for the wheel building CI).
# build_ext has to be imported after setuptools
class build_ext_subclass(build_ext):
def finalize_options(self):
build_ext.finalize_options(self)
if self.parallel is None:
# Do not override self.parallel if already defined by
# command-line flag (--parallel or -j)
parallel = os.environ.get("SKLEARN_BUILD_PARALLEL")
if parallel:
self.parallel = int(parallel)
if self.parallel:
print("setting parallel=%d " % self.parallel)
def build_extensions(self):
from sklearn._build_utils.openmp_helpers import get_openmp_flag
# Always use NumPy 1.7 C API for all compiled extensions.
# See: https://numpy.org/doc/stable/reference/c-api/deprecations.html
DEFINE_MACRO_NUMPY_C_API = (
"NPY_NO_DEPRECATED_API",
"NPY_1_7_API_VERSION",
)
for ext in self.extensions:
ext.define_macros.append(DEFINE_MACRO_NUMPY_C_API)
if sklearn._OPENMP_SUPPORTED:
openmp_flag = get_openmp_flag()
for e in self.extensions:
e.extra_compile_args += openmp_flag
e.extra_link_args += openmp_flag
build_ext.build_extensions(self)
def run(self):
# Specifying `build_clib` allows running `python setup.py develop`
# fully from a fresh clone.
self.run_command("build_clib")
build_ext.run(self)
cmdclass = {
"clean": CleanCommand,
"build_ext": build_ext_subclass,
}
def check_package_status(package, min_version):
"""
Returns a dictionary containing a boolean specifying whether given package
is up-to-date, along with the version string (empty string if
not installed).
"""
package_status = {}
try:
module = importlib.import_module(package)
package_version = module.__version__
package_status["up_to_date"] = parse_version(package_version) >= parse_version(
min_version
)
package_status["version"] = package_version
except ImportError:
traceback.print_exc()
package_status["up_to_date"] = False
package_status["version"] = ""
req_str = "scikit-learn requires {} >= {}.\n".format(package, min_version)
instructions = (
"Installation instructions are available on the "
"scikit-learn website: "
"https://scikit-learn.org/stable/install.html\n"
)
if package_status["up_to_date"] is False:
if package_status["version"]:
raise ImportError(
"Your installation of {} {} is out-of-date.\n{}{}".format(
package, package_status["version"], req_str, instructions
)
)
else:
raise ImportError(
"{} is not installed.\n{}{}".format(package, req_str, instructions)
)
extension_config = {
"__check_build": [
{"sources": ["_check_build.pyx"]},
],
"": [
{"sources": ["_isotonic.pyx"]},
],
"_loss": [
{"sources": ["_loss.pyx.tp"]},
],
"cluster": [
{"sources": ["_dbscan_inner.pyx"], "language": "c++", "include_np": True},
{"sources": ["_hierarchical_fast.pyx"], "language": "c++", "include_np": True},
{"sources": ["_k_means_common.pyx"], "include_np": True},
{"sources": ["_k_means_lloyd.pyx"], "include_np": True},
{"sources": ["_k_means_elkan.pyx"], "include_np": True},
{"sources": ["_k_means_minibatch.pyx"], "include_np": True},
],
"cluster._hdbscan": [
{"sources": ["_linkage.pyx"], "include_np": True},
{"sources": ["_reachability.pyx"], "include_np": True},
{"sources": ["_tree.pyx"], "include_np": True},
],
"datasets": [
{
"sources": ["_svmlight_format_fast.pyx"],
"include_np": True,
"compile_for_pypy": False,
}
],
"decomposition": [
{"sources": ["_online_lda_fast.pyx"], "include_np": True},
{"sources": ["_cdnmf_fast.pyx"], "include_np": True},
],
"ensemble": [
{"sources": ["_gradient_boosting.pyx"], "include_np": True},
],
"ensemble._hist_gradient_boosting": [
{"sources": ["_gradient_boosting.pyx"], "include_np": True},
{"sources": ["histogram.pyx"], "include_np": True},
{"sources": ["splitting.pyx"], "include_np": True},
{"sources": ["_binning.pyx"], "include_np": True},
{"sources": ["_predictor.pyx"], "include_np": True},
{"sources": ["_bitset.pyx"], "include_np": True},
{"sources": ["common.pyx"], "include_np": True},
{"sources": ["utils.pyx"], "include_np": True},
],
"feature_extraction": [
{"sources": ["_hashing_fast.pyx"], "language": "c++", "include_np": True},
],
"linear_model": [
{"sources": ["_cd_fast.pyx"], "include_np": True},
{"sources": ["_sgd_fast.pyx.tp"], "include_np": True},
{"sources": ["_sag_fast.pyx.tp"], "include_np": True},
],
"manifold": [
{"sources": ["_utils.pyx"], "include_np": True},
{"sources": ["_barnes_hut_tsne.pyx"], "include_np": True},
],
"metrics": [
{"sources": ["_pairwise_fast.pyx"], "include_np": True},
{
"sources": ["_dist_metrics.pyx.tp", "_dist_metrics.pxd.tp"],
"include_np": True,
},
],
"metrics.cluster": [
{"sources": ["_expected_mutual_info_fast.pyx"], "include_np": True},
],
"metrics._pairwise_distances_reduction": [
{
"sources": ["_datasets_pair.pyx.tp", "_datasets_pair.pxd.tp"],
"language": "c++",
"include_np": True,
"extra_compile_args": ["-std=c++11"],
},
{
"sources": ["_middle_term_computer.pyx.tp", "_middle_term_computer.pxd.tp"],
"language": "c++",
"extra_compile_args": ["-std=c++11"],
},
{
"sources": ["_base.pyx.tp", "_base.pxd.tp"],
"language": "c++",
"include_np": True,
"extra_compile_args": ["-std=c++11"],
},
{
"sources": ["_argkmin.pyx.tp", "_argkmin.pxd.tp"],
"language": "c++",
"include_np": True,
"extra_compile_args": ["-std=c++11"],
},
{
"sources": ["_argkmin_classmode.pyx.tp"],
"language": "c++",
"include_np": True,
"extra_compile_args": ["-std=c++11"],
},
{
"sources": ["_radius_neighbors.pyx.tp", "_radius_neighbors.pxd.tp"],
"language": "c++",
"include_np": True,
"extra_compile_args": ["-std=c++11"],
},
{
"sources": ["_radius_neighbors_classmode.pyx.tp"],
"language": "c++",
"include_np": True,
"extra_compile_args": ["-std=c++11"],
},
],
"preprocessing": [
{"sources": ["_csr_polynomial_expansion.pyx"]},
{
"sources": ["_target_encoder_fast.pyx"],
"include_np": True,
"language": "c++",
"extra_compile_args": ["-std=c++11"],
},
],
"neighbors": [
{"sources": ["_binary_tree.pxi.tp"], "include_np": True},
{"sources": ["_ball_tree.pyx.tp"], "include_np": True},
{"sources": ["_kd_tree.pyx.tp"], "include_np": True},
{"sources": ["_partition_nodes.pyx"], "language": "c++", "include_np": True},
{"sources": ["_quad_tree.pyx"], "include_np": True},
],
"svm": [
{
"sources": ["_newrand.pyx"],
"include_np": True,
"include_dirs": [join("src", "newrand")],
"language": "c++",
# Use C++11 random number generator fix
"extra_compile_args": ["-std=c++11"],
},
{
"sources": ["_libsvm.pyx"],
"depends": [
join("src", "libsvm", "libsvm_helper.c"),
join("src", "libsvm", "libsvm_template.cpp"),
join("src", "libsvm", "svm.cpp"),
join("src", "libsvm", "svm.h"),
join("src", "newrand", "newrand.h"),
],
"include_dirs": [
join("src", "libsvm"),
join("src", "newrand"),
],
"libraries": ["libsvm-skl"],
"extra_link_args": ["-lstdc++"],
"include_np": True,
},
{
"sources": ["_liblinear.pyx"],
"libraries": ["liblinear-skl"],
"include_dirs": [
join("src", "liblinear"),
join("src", "newrand"),
join("..", "utils"),
],
"include_np": True,
"depends": [
join("src", "liblinear", "tron.h"),
join("src", "liblinear", "linear.h"),
join("src", "liblinear", "liblinear_helper.c"),
join("src", "newrand", "newrand.h"),
],
"extra_link_args": ["-lstdc++"],
},
{
"sources": ["_libsvm_sparse.pyx"],
"libraries": ["libsvm-skl"],
"include_dirs": [
join("src", "libsvm"),
join("src", "newrand"),
],
"include_np": True,
"depends": [
join("src", "libsvm", "svm.h"),
join("src", "newrand", "newrand.h"),
join("src", "libsvm", "libsvm_sparse_helper.c"),
],
"extra_link_args": ["-lstdc++"],
},
],
"tree": [
{
"sources": ["_tree.pyx"],
"language": "c++",
"include_np": True,
"optimization_level": "O3",
},
{"sources": ["_splitter.pyx"], "include_np": True, "optimization_level": "O3"},
{"sources": ["_criterion.pyx"], "include_np": True, "optimization_level": "O3"},
{"sources": ["_utils.pyx"], "include_np": True, "optimization_level": "O3"},
],
"utils": [
{"sources": ["sparsefuncs_fast.pyx"], "include_np": True},
{"sources": ["_cython_blas.pyx"]},
{"sources": ["arrayfuncs.pyx"]},
{
"sources": ["murmurhash.pyx", join("src", "MurmurHash3.cpp")],
"include_dirs": ["src"],
"include_np": True,
},
{"sources": ["_fast_dict.pyx"], "language": "c++"},
{"sources": ["_openmp_helpers.pyx"]},
{"sources": ["_seq_dataset.pyx.tp", "_seq_dataset.pxd.tp"], "include_np": True},
{
"sources": ["_weight_vector.pyx.tp", "_weight_vector.pxd.tp"],
"include_np": True,
},
{"sources": ["_random.pyx"], "include_np": True},
{"sources": ["_typedefs.pyx"]},
{"sources": ["_heap.pyx"]},
{"sources": ["_sorting.pyx"]},
{"sources": ["_vector_sentinel.pyx"], "language": "c++", "include_np": True},
{"sources": ["_isfinite.pyx"]},
],
}
# Paths in `libraries` must be relative to the root directory because `libraries` is
# passed directly to `setup`
libraries = [
(
"libsvm-skl",
{
"sources": [
join("sklearn", "svm", "src", "libsvm", "libsvm_template.cpp"),
],
"depends": [
join("sklearn", "svm", "src", "libsvm", "svm.cpp"),
join("sklearn", "svm", "src", "libsvm", "svm.h"),
join("sklearn", "svm", "src", "newrand", "newrand.h"),
],
# Use C++11 to use the random number generator fix
"extra_compiler_args": ["-std=c++11"],
"extra_link_args": ["-lstdc++"],
},
),
(
"liblinear-skl",
{
"sources": [
join("sklearn", "svm", "src", "liblinear", "linear.cpp"),
join("sklearn", "svm", "src", "liblinear", "tron.cpp"),
],
"depends": [
join("sklearn", "svm", "src", "liblinear", "linear.h"),
join("sklearn", "svm", "src", "liblinear", "tron.h"),
join("sklearn", "svm", "src", "newrand", "newrand.h"),
],
# Use C++11 to use the random number generator fix
"extra_compiler_args": ["-std=c++11"],
"extra_link_args": ["-lstdc++"],
},
),
]
def configure_extension_modules():
# Skip cythonization as we do not want to include the generated
# C/C++ files in the release tarballs as they are not necessarily
# forward compatible with future versions of Python for instance.
if "sdist" in sys.argv or "--help" in sys.argv:
return []
import numpy
from sklearn._build_utils import cythonize_extensions, gen_from_templates
is_pypy = platform.python_implementation() == "PyPy"
np_include = numpy.get_include()
default_optimization_level = "O2"
if os.name == "posix":
default_libraries = ["m"]
else:
default_libraries = []
default_extra_compile_args = []
build_with_debug_symbols = (
os.environ.get("SKLEARN_BUILD_ENABLE_DEBUG_SYMBOLS", "0") != "0"
)
if os.name == "posix":
if build_with_debug_symbols:
default_extra_compile_args.append("-g")
else:
# Setting -g0 will strip symbols, reducing the binary size of extensions
default_extra_compile_args.append("-g0")
cython_exts = []
for submodule, extensions in extension_config.items():
submodule_parts = submodule.split(".")
parent_dir = join("sklearn", *submodule_parts)
for extension in extensions:
if is_pypy and not extension.get("compile_for_pypy", True):
continue
# Generate files with Tempita
tempita_sources = []
sources = []
for source in extension["sources"]:
source = join(parent_dir, source)
new_source_path, path_ext = os.path.splitext(source)
if path_ext != ".tp":
sources.append(source)
continue
# `source` is a Tempita file
tempita_sources.append(source)
# Only include source files that are pyx files
if os.path.splitext(new_source_path)[-1] == ".pyx":
sources.append(new_source_path)
gen_from_templates(tempita_sources)
# Do not progress if we only have a tempita file which we don't
# want to include like the .pxi.tp extension. In such a case
# sources would be empty.
if not sources:
continue
# By convention, our extensions always use the name of the first source
source_name = os.path.splitext(os.path.basename(sources[0]))[0]
if submodule:
name_parts = ["sklearn", submodule, source_name]
else:
name_parts = ["sklearn", source_name]
name = ".".join(name_parts)
# Make paths start from the root directory
include_dirs = [
join(parent_dir, include_dir)
for include_dir in extension.get("include_dirs", [])
]
if extension.get("include_np", False):
include_dirs.append(np_include)
depends = [
join(parent_dir, depend) for depend in extension.get("depends", [])
]
extra_compile_args = (
extension.get("extra_compile_args", []) + default_extra_compile_args
)
optimization_level = extension.get(
"optimization_level", default_optimization_level
)
if os.name == "posix":
extra_compile_args.append(f"-{optimization_level}")
else:
extra_compile_args.append(f"/{optimization_level}")
libraries_ext = extension.get("libraries", []) + default_libraries
new_ext = Extension(
name=name,
sources=sources,
language=extension.get("language", None),
include_dirs=include_dirs,
libraries=libraries_ext,
depends=depends,
extra_link_args=extension.get("extra_link_args", None),
extra_compile_args=extra_compile_args,
)
cython_exts.append(new_ext)
return cythonize_extensions(cython_exts)
def setup_package():
python_requires = ">=3.8"
required_python_version = (3, 8)
metadata = dict(
name=DISTNAME,
maintainer=MAINTAINER,
maintainer_email=MAINTAINER_EMAIL,
description=DESCRIPTION,
license=LICENSE,
url=URL,
download_url=DOWNLOAD_URL,
project_urls=PROJECT_URLS,
version=VERSION,
long_description=LONG_DESCRIPTION,
classifiers=[
"Intended Audience :: Science/Research",
"Intended Audience :: Developers",
"License :: OSI Approved :: BSD License",
"Programming Language :: C",
"Programming Language :: Python",
"Topic :: Software Development",
"Topic :: Scientific/Engineering",
"Development Status :: 5 - Production/Stable",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX",
"Operating System :: Unix",
"Operating System :: MacOS",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: Implementation :: CPython",
"Programming Language :: Python :: Implementation :: PyPy",
],
cmdclass=cmdclass,
python_requires=python_requires,
install_requires=min_deps.tag_to_packages["install"],
package_data={
"": ["*.csv", "*.gz", "*.txt", "*.pxd", "*.rst", "*.jpg", "*.css"]
},
zip_safe=False, # the package can run out of an .egg file
extras_require={
key: min_deps.tag_to_packages[key]
for key in ["examples", "docs", "tests", "benchmark"]
},
)
commands = [arg for arg in sys.argv[1:] if not arg.startswith("-")]
if not all(
command in ("egg_info", "dist_info", "clean", "check") for command in commands
):
if sys.version_info < required_python_version:
required_version = "%d.%d" % required_python_version
raise RuntimeError(
"Scikit-learn requires Python %s or later. The current"
" Python version is %s installed in %s."
% (required_version, platform.python_version(), sys.executable)
)
check_package_status("numpy", min_deps.NUMPY_MIN_VERSION)
check_package_status("scipy", min_deps.SCIPY_MIN_VERSION)
_check_cython_version()
metadata["ext_modules"] = configure_extension_modules()
metadata["libraries"] = libraries
setup(**metadata)
if __name__ == "__main__":
setup_package()