Uploaded Test files
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venv/Lib/site-packages/sklearn/_build_utils/__init__.py
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venv/Lib/site-packages/sklearn/_build_utils/__init__.py
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"""
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Utilities useful during the build.
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"""
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# author: Andy Mueller, Gael Varoquaux
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# license: BSD
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import os
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import sklearn
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import contextlib
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from distutils.version import LooseVersion
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from .pre_build_helpers import basic_check_build
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from .openmp_helpers import check_openmp_support
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DEFAULT_ROOT = 'sklearn'
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# The following places need to be in sync with regard to Cython version:
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# - .circleci config file
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# - sklearn/_build_utils/__init__.py
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# - advanced installation guide
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CYTHON_MIN_VERSION = '0.28.5'
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def _check_cython_version():
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message = ('Please install Cython with a version >= {0} in order '
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'to build a scikit-learn from source.').format(
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CYTHON_MIN_VERSION)
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try:
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import Cython
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except ModuleNotFoundError:
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# Re-raise with more informative error message instead:
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raise ModuleNotFoundError(message)
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if LooseVersion(Cython.__version__) < CYTHON_MIN_VERSION:
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message += (' The current version of Cython is {} installed in {}.'
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.format(Cython.__version__, Cython.__path__))
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raise ValueError(message)
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def cythonize_extensions(top_path, config):
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"""Check that a recent Cython is available and cythonize extensions"""
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_check_cython_version()
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from Cython.Build import cythonize
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# Fast fail before cythonization if compiler fails compiling basic test
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# code even without OpenMP
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basic_check_build()
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# check simple compilation with OpenMP. If it fails scikit-learn will be
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# built without OpenMP and the test test_openmp_supported in the test suite
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# will fail.
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# `check_openmp_support` compiles a small test program to see if the
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# compilers are properly configured to build with OpenMP. This is expensive
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# and we only want to call this function once.
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# The result of this check is cached as a private attribute on the sklearn
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# module (only at build-time) to be used twice:
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# - First to set the value of SKLEARN_OPENMP_PARALLELISM_ENABLED, the
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# cython build-time variable passed to the cythonize() call.
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# - Then in the build_ext subclass defined in the top-level setup.py file
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# to actually build the compiled extensions with OpenMP flags if needed.
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sklearn._OPENMP_SUPPORTED = check_openmp_support()
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n_jobs = 1
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with contextlib.suppress(ImportError):
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import joblib
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if LooseVersion(joblib.__version__) > LooseVersion("0.13.0"):
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# earlier joblib versions don't account for CPU affinity
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# constraints, and may over-estimate the number of available
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# CPU particularly in CI (cf loky#114)
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n_jobs = joblib.cpu_count()
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config.ext_modules = cythonize(
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config.ext_modules,
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nthreads=n_jobs,
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compile_time_env={
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'SKLEARN_OPENMP_PARALLELISM_ENABLED': sklearn._OPENMP_SUPPORTED},
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compiler_directives={'language_level': 3})
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def gen_from_templates(templates, top_path):
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"""Generate cython files from a list of templates"""
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# Lazy import because cython is not a runtime dependency.
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from Cython import Tempita
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for template in templates:
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outfile = template.replace('.tp', '')
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# if the template is not updated, no need to output the cython file
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if not (os.path.exists(outfile) and
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os.stat(template).st_mtime < os.stat(outfile).st_mtime):
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with open(template, "r") as f:
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tmpl = f.read()
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tmpl_ = Tempita.sub(tmpl)
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with open(outfile, "w") as f:
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f.write(tmpl_)
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"""Generates submodule to allow deprecation of submodules and keeping git
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blame."""
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from pathlib import Path
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from contextlib import suppress
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# TODO: Remove the whole file in 0.24
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# This is a set of 4-tuples consisting of
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# (new_module_name, deprecated_path, correct_import_path, importee)
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# importee is used by test_import_deprecations to check for DeprecationWarnings
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_DEPRECATED_MODULES = [
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('_mocking', 'sklearn.utils.mocking', 'sklearn.utils',
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'MockDataFrame'),
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('_bagging', 'sklearn.ensemble.bagging', 'sklearn.ensemble',
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'BaggingClassifier'),
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('_base', 'sklearn.ensemble.base', 'sklearn.ensemble',
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'BaseEnsemble'),
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('_forest', 'sklearn.ensemble.forest', 'sklearn.ensemble',
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'RandomForestClassifier'),
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('_gb', 'sklearn.ensemble.gradient_boosting', 'sklearn.ensemble',
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'GradientBoostingClassifier'),
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('_iforest', 'sklearn.ensemble.iforest', 'sklearn.ensemble',
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'IsolationForest'),
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('_voting', 'sklearn.ensemble.voting', 'sklearn.ensemble',
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'VotingClassifier'),
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('_weight_boosting', 'sklearn.ensemble.weight_boosting',
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'sklearn.ensemble', 'AdaBoostClassifier'),
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('_classes', 'sklearn.tree.tree', 'sklearn.tree',
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'DecisionTreeClassifier'),
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('_export', 'sklearn.tree.export', 'sklearn.tree', 'export_graphviz'),
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('_rbm', 'sklearn.neural_network.rbm', 'sklearn.neural_network',
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'BernoulliRBM'),
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('_multilayer_perceptron', 'sklearn.neural_network.multilayer_perceptron',
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'sklearn.neural_network', 'MLPClassifier'),
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('_weight_vector', 'sklearn.utils.weight_vector', 'sklearn.utils',
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'WeightVector'),
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('_seq_dataset', 'sklearn.utils.seq_dataset', 'sklearn.utils',
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'ArrayDataset32'),
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('_fast_dict', 'sklearn.utils.fast_dict', 'sklearn.utils', 'IntFloatDict'),
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('_affinity_propagation', 'sklearn.cluster.affinity_propagation_',
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'sklearn.cluster', 'AffinityPropagation'),
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('_bicluster', 'sklearn.cluster.bicluster', 'sklearn.cluster',
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'SpectralBiclustering'),
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('_birch', 'sklearn.cluster.birch', 'sklearn.cluster', 'Birch'),
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('_dbscan', 'sklearn.cluster.dbscan_', 'sklearn.cluster', 'DBSCAN'),
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('_agglomerative', 'sklearn.cluster.hierarchical', 'sklearn.cluster',
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'FeatureAgglomeration'),
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('_kmeans', 'sklearn.cluster.k_means_', 'sklearn.cluster', 'KMeans'),
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('_mean_shift', 'sklearn.cluster.mean_shift_', 'sklearn.cluster',
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'MeanShift'),
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('_optics', 'sklearn.cluster.optics_', 'sklearn.cluster', 'OPTICS'),
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('_spectral', 'sklearn.cluster.spectral', 'sklearn.cluster',
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'SpectralClustering'),
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('_base', 'sklearn.mixture.base', 'sklearn.mixture', 'BaseMixture'),
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('_gaussian_mixture', 'sklearn.mixture.gaussian_mixture',
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'sklearn.mixture', 'GaussianMixture'),
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('_bayesian_mixture', 'sklearn.mixture.bayesian_mixture',
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'sklearn.mixture', 'BayesianGaussianMixture'),
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('_empirical_covariance', 'sklearn.covariance.empirical_covariance_',
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'sklearn.covariance', 'EmpiricalCovariance'),
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('_shrunk_covariance', 'sklearn.covariance.shrunk_covariance_',
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'sklearn.covariance', 'ShrunkCovariance'),
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('_robust_covariance', 'sklearn.covariance.robust_covariance',
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'sklearn.covariance', 'MinCovDet'),
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('_graph_lasso', 'sklearn.covariance.graph_lasso_',
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'sklearn.covariance', 'GraphicalLasso'),
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('_elliptic_envelope', 'sklearn.covariance.elliptic_envelope',
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'sklearn.covariance', 'EllipticEnvelope'),
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('_cca', 'sklearn.cross_decomposition.cca_',
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'sklearn.cross_decomposition', 'CCA'),
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('_pls', 'sklearn.cross_decomposition.pls_',
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'sklearn.cross_decomposition', 'PLSSVD'),
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('_base', 'sklearn.svm.base', 'sklearn.svm', 'BaseLibSVM'),
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('_bounds', 'sklearn.svm.bounds', 'sklearn.svm', 'l1_min_c'),
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('_classes', 'sklearn.svm.classes', 'sklearn.svm', 'SVR'),
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('_libsvm', 'sklearn.svm.libsvm', 'sklearn.svm', 'fit'),
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('_libsvm_sparse', 'sklearn.svm.libsvm_sparse', 'sklearn.svm',
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'set_verbosity_wrap'),
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('_liblinear', 'sklearn.svm.liblinear', 'sklearn.svm', 'train_wrap'),
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('_base', 'sklearn.decomposition.base', 'sklearn.decomposition',
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'BaseEstimator'),
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('_dict_learning', 'sklearn.decomposition.dict_learning',
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'sklearn.decomposition', 'MiniBatchDictionaryLearning'),
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('_cdnmf_fast', 'sklearn.decomposition.cdnmf_fast',
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'sklearn.decomposition', '__dict__'),
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('_factor_analysis', 'sklearn.decomposition.factor_analysis',
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'sklearn.decomposition', 'FactorAnalysis'),
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('_fastica', 'sklearn.decomposition.fastica_', 'sklearn.decomposition',
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'FastICA'),
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('_incremental_pca', 'sklearn.decomposition.incremental_pca',
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'sklearn.decomposition', 'IncrementalPCA'),
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('_kernel_pca', 'sklearn.decomposition.kernel_pca',
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'sklearn.decomposition', 'KernelPCA'),
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('_nmf', 'sklearn.decomposition.nmf', 'sklearn.decomposition', 'NMF'),
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('_lda', 'sklearn.decomposition.online_lda',
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'sklearn.decomposition', 'LatentDirichletAllocation'),
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('_online_lda_fast', 'sklearn.decomposition.online_lda_fast',
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'sklearn.decomposition', 'mean_change'),
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('_pca', 'sklearn.decomposition.pca', 'sklearn.decomposition', 'PCA'),
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('_sparse_pca', 'sklearn.decomposition.sparse_pca',
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'sklearn.decomposition', 'SparsePCA'),
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('_truncated_svd', 'sklearn.decomposition.truncated_svd',
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'sklearn.decomposition', 'TruncatedSVD'),
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('_gpr', 'sklearn.gaussian_process.gpr', 'sklearn.gaussian_process',
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'GaussianProcessRegressor'),
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('_gpc', 'sklearn.gaussian_process.gpc', 'sklearn.gaussian_process',
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'GaussianProcessClassifier'),
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('_base', 'sklearn.datasets.base', 'sklearn.datasets', 'get_data_home'),
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('_california_housing', 'sklearn.datasets.california_housing',
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'sklearn.datasets', 'fetch_california_housing'),
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('_covtype', 'sklearn.datasets.covtype', 'sklearn.datasets',
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'fetch_covtype'),
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('_kddcup99', 'sklearn.datasets.kddcup99', 'sklearn.datasets',
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'fetch_kddcup99'),
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('_lfw', 'sklearn.datasets.lfw', 'sklearn.datasets',
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'fetch_lfw_people'),
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('_olivetti_faces', 'sklearn.datasets.olivetti_faces', 'sklearn.datasets',
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'fetch_olivetti_faces'),
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('_openml', 'sklearn.datasets.openml', 'sklearn.datasets', 'fetch_openml'),
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('_rcv1', 'sklearn.datasets.rcv1', 'sklearn.datasets', 'fetch_rcv1'),
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('_samples_generator', 'sklearn.datasets.samples_generator',
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'sklearn.datasets', 'make_classification'),
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('_species_distributions', 'sklearn.datasets.species_distributions',
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'sklearn.datasets', 'fetch_species_distributions'),
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('_svmlight_format_io', 'sklearn.datasets.svmlight_format',
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'sklearn.datasets', 'load_svmlight_file'),
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('_twenty_newsgroups', 'sklearn.datasets.twenty_newsgroups',
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'sklearn.datasets', 'strip_newsgroup_header'),
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('_dict_vectorizer', 'sklearn.feature_extraction.dict_vectorizer',
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'sklearn.feature_extraction', 'DictVectorizer'),
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('_hash', 'sklearn.feature_extraction.hashing',
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'sklearn.feature_extraction', 'FeatureHasher'),
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('_stop_words', 'sklearn.feature_extraction.stop_words',
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'sklearn.feature_extraction.text', 'ENGLISH_STOP_WORDS'),
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('_base', 'sklearn.linear_model.base', 'sklearn.linear_model',
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'LinearRegression'),
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('_cd_fast', 'sklearn.linear_model.cd_fast', 'sklearn.linear_model',
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'sparse_enet_coordinate_descent'),
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('_bayes', 'sklearn.linear_model.bayes', 'sklearn.linear_model',
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'BayesianRidge'),
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('_coordinate_descent', 'sklearn.linear_model.coordinate_descent',
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'sklearn.linear_model', 'Lasso'),
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('_huber', 'sklearn.linear_model.huber', 'sklearn.linear_model',
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'HuberRegressor'),
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('_least_angle', 'sklearn.linear_model.least_angle',
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'sklearn.linear_model', 'LassoLarsCV'),
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('_logistic', 'sklearn.linear_model.logistic', 'sklearn.linear_model',
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'LogisticRegression'),
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('_omp', 'sklearn.linear_model.omp', 'sklearn.linear_model',
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'OrthogonalMatchingPursuit'),
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('_passive_aggressive', 'sklearn.linear_model.passive_aggressive',
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'sklearn.linear_model', 'PassiveAggressiveClassifier'),
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('_perceptron', 'sklearn.linear_model.perceptron', 'sklearn.linear_model',
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'Perceptron'),
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('_ransac', 'sklearn.linear_model.ransac', 'sklearn.linear_model',
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'RANSACRegressor'),
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('_ridge', 'sklearn.linear_model.ridge', 'sklearn.linear_model',
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'Ridge'),
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('_sag', 'sklearn.linear_model.sag', 'sklearn.linear_model',
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'get_auto_step_size'),
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('_sag_fast', 'sklearn.linear_model.sag_fast', 'sklearn.linear_model',
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'MultinomialLogLoss64'),
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('_sgd_fast', 'sklearn.linear_model.sgd_fast', 'sklearn.linear_model',
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'Hinge'),
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('_stochastic_gradient', 'sklearn.linear_model.stochastic_gradient',
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'sklearn.linear_model', 'SGDClassifier'),
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('_theil_sen', 'sklearn.linear_model.theil_sen', 'sklearn.linear_model',
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'TheilSenRegressor'),
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('_bicluster', 'sklearn.metrics.cluster.bicluster',
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'sklearn.metrics.cluster', 'consensus_score'),
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('_supervised', 'sklearn.metrics.cluster.supervised',
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'sklearn.metrics.cluster', 'entropy'),
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('_unsupervised', 'sklearn.metrics.cluster.unsupervised',
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'sklearn.metrics.cluster', 'silhouette_score'),
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('_expected_mutual_info_fast',
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'sklearn.metrics.cluster.expected_mutual_info_fast',
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'sklearn.metrics.cluster', 'expected_mutual_information'),
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('_base', 'sklearn.metrics.base', 'sklearn.metrics', 'combinations'),
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('_classification', 'sklearn.metrics.classification', 'sklearn.metrics',
|
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'accuracy_score'),
|
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('_regression', 'sklearn.metrics.regression', 'sklearn.metrics',
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'max_error'),
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('_ranking', 'sklearn.metrics.ranking', 'sklearn.metrics', 'roc_curve'),
|
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('_pairwise_fast', 'sklearn.metrics.pairwise_fast', 'sklearn.metrics',
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'np'),
|
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('_scorer', 'sklearn.metrics.scorer', 'sklearn.metrics', 'get_scorer'),
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|
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('_partial_dependence', 'sklearn.inspection.partial_dependence',
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'sklearn.inspection', 'partial_dependence'),
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('_ball_tree', 'sklearn.neighbors.ball_tree', 'sklearn.neighbors',
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'BallTree'),
|
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('_base', 'sklearn.neighbors.base', 'sklearn.neighbors',
|
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'VALID_METRICS'),
|
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('_classification', 'sklearn.neighbors.classification',
|
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'sklearn.neighbors', 'KNeighborsClassifier'),
|
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('_dist_metrics', 'sklearn.neighbors.dist_metrics', 'sklearn.neighbors',
|
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'DistanceMetric'),
|
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('_graph', 'sklearn.neighbors.graph', 'sklearn.neighbors',
|
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'KNeighborsTransformer'),
|
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('_kd_tree', 'sklearn.neighbors.kd_tree', 'sklearn.neighbors',
|
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'KDTree'),
|
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('_kde', 'sklearn.neighbors.kde', 'sklearn.neighbors',
|
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'KernelDensity'),
|
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('_lof', 'sklearn.neighbors.lof', 'sklearn.neighbors',
|
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'LocalOutlierFactor'),
|
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('_nca', 'sklearn.neighbors.nca', 'sklearn.neighbors',
|
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'NeighborhoodComponentsAnalysis'),
|
||||
('_nearest_centroid', 'sklearn.neighbors.nearest_centroid',
|
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'sklearn.neighbors', 'NearestCentroid'),
|
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('_quad_tree', 'sklearn.neighbors.quad_tree', 'sklearn.neighbors',
|
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'CELL_DTYPE'),
|
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('_regression', 'sklearn.neighbors.regression', 'sklearn.neighbors',
|
||||
'KNeighborsRegressor'),
|
||||
('_typedefs', 'sklearn.neighbors.typedefs', 'sklearn.neighbors',
|
||||
'DTYPE'),
|
||||
('_unsupervised', 'sklearn.neighbors.unsupervised', 'sklearn.neighbors',
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'NearestNeighbors'),
|
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|
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('_isomap', 'sklearn.manifold.isomap', 'sklearn.manifold', 'Isomap'),
|
||||
('_locally_linear', 'sklearn.manifold.locally_linear', 'sklearn.manifold',
|
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'LocallyLinearEmbedding'),
|
||||
('_mds', 'sklearn.manifold.mds', 'sklearn.manifold', 'MDS'),
|
||||
('_spectral_embedding', 'sklearn.manifold.spectral_embedding_',
|
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'sklearn.manifold', 'SpectralEmbedding'),
|
||||
('_t_sne', 'sklearn.manifold.t_sne', 'sklearn.manifold', 'TSNE'),
|
||||
|
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('_label_propagation', 'sklearn.semi_supervised.label_propagation',
|
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'sklearn.semi_supervised', 'LabelPropagation'),
|
||||
|
||||
('_data', 'sklearn.preprocessing.data', 'sklearn.preprocessing',
|
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'Binarizer'),
|
||||
('_label', 'sklearn.preprocessing.label', 'sklearn.preprocessing',
|
||||
'LabelEncoder'),
|
||||
|
||||
('_base', 'sklearn.feature_selection.base', 'sklearn.feature_selection',
|
||||
'SelectorMixin'),
|
||||
('_from_model', 'sklearn.feature_selection.from_model',
|
||||
'sklearn.feature_selection', 'SelectFromModel'),
|
||||
('_mutual_info', 'sklearn.feature_selection.mutual_info',
|
||||
'sklearn.feature_selection', 'mutual_info_regression'),
|
||||
('_rfe', 'sklearn.feature_selection.rfe',
|
||||
'sklearn.feature_selection.rfe', 'RFE'),
|
||||
('_univariate_selection',
|
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'sklearn.feature_selection.univariate_selection',
|
||||
'sklearn.feature_selection', 'chi2'),
|
||||
('_variance_threshold',
|
||||
'sklearn.feature_selection.variance_threshold',
|
||||
'sklearn.feature_selection', 'VarianceThreshold'),
|
||||
|
||||
('_testing', 'sklearn.utils.testing', 'sklearn.utils',
|
||||
'all_estimators'),
|
||||
]
|
||||
|
||||
|
||||
_FILE_CONTENT_TEMPLATE = """
|
||||
# THIS FILE WAS AUTOMATICALLY GENERATED BY deprecated_modules.py
|
||||
import sys
|
||||
# mypy error: Module X has no attribute y (typically for C extensions)
|
||||
from . import {new_module_name} # type: ignore
|
||||
from {relative_dots}externals._pep562 import Pep562
|
||||
from {relative_dots}utils.deprecation import _raise_dep_warning_if_not_pytest
|
||||
|
||||
deprecated_path = '{deprecated_path}'
|
||||
correct_import_path = '{correct_import_path}'
|
||||
|
||||
_raise_dep_warning_if_not_pytest(deprecated_path, correct_import_path)
|
||||
|
||||
def __getattr__(name):
|
||||
return getattr({new_module_name}, name)
|
||||
|
||||
if not sys.version_info >= (3, 7):
|
||||
Pep562(__name__)
|
||||
"""
|
||||
|
||||
|
||||
def _get_deprecated_path(deprecated_path):
|
||||
deprecated_parts = deprecated_path.split(".")
|
||||
deprecated_parts[-1] = deprecated_parts[-1] + ".py"
|
||||
return Path(*deprecated_parts)
|
||||
|
||||
|
||||
def _create_deprecated_modules_files():
|
||||
"""Add submodules that will be deprecated. A file is created based
|
||||
on the deprecated submodule's name. When this submodule is imported a
|
||||
deprecation warning will be raised.
|
||||
"""
|
||||
for (new_module_name, deprecated_path,
|
||||
correct_import_path, _) in _DEPRECATED_MODULES:
|
||||
relative_dots = deprecated_path.count(".") * "."
|
||||
deprecated_content = _FILE_CONTENT_TEMPLATE.format(
|
||||
new_module_name=new_module_name,
|
||||
relative_dots=relative_dots,
|
||||
deprecated_path=deprecated_path,
|
||||
correct_import_path=correct_import_path)
|
||||
|
||||
with _get_deprecated_path(deprecated_path).open('w') as f:
|
||||
f.write(deprecated_content)
|
||||
|
||||
|
||||
def _clean_deprecated_modules_files():
|
||||
"""Removes submodules created by _create_deprecated_modules_files."""
|
||||
for _, deprecated_path, _, _ in _DEPRECATED_MODULES:
|
||||
with suppress(FileNotFoundError):
|
||||
_get_deprecated_path(deprecated_path).unlink()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
_clean_deprecated_modules_files()
|
||||
114
venv/Lib/site-packages/sklearn/_build_utils/openmp_helpers.py
Normal file
114
venv/Lib/site-packages/sklearn/_build_utils/openmp_helpers.py
Normal file
|
|
@ -0,0 +1,114 @@
|
|||
"""Helpers for OpenMP support during the build."""
|
||||
|
||||
# This code is adapted for a large part from the astropy openmp helpers, which
|
||||
# can be found at: https://github.com/astropy/astropy-helpers/blob/master/astropy_helpers/openmp_helpers.py # noqa
|
||||
|
||||
|
||||
import os
|
||||
import sys
|
||||
import textwrap
|
||||
import warnings
|
||||
import subprocess
|
||||
|
||||
from distutils.errors import CompileError, LinkError
|
||||
|
||||
from .pre_build_helpers import compile_test_program
|
||||
|
||||
|
||||
def get_openmp_flag(compiler):
|
||||
if hasattr(compiler, 'compiler'):
|
||||
compiler = compiler.compiler[0]
|
||||
else:
|
||||
compiler = compiler.__class__.__name__
|
||||
|
||||
if sys.platform == "win32" and ('icc' in compiler or 'icl' in compiler):
|
||||
return ['/Qopenmp']
|
||||
elif sys.platform == "win32":
|
||||
return ['/openmp']
|
||||
elif sys.platform == "darwin" and ('icc' in compiler or 'icl' in compiler):
|
||||
return ['-openmp']
|
||||
elif sys.platform == "darwin" and 'openmp' in os.getenv('CPPFLAGS', ''):
|
||||
# -fopenmp can't be passed as compile flag when using Apple-clang.
|
||||
# OpenMP support has to be enabled during preprocessing.
|
||||
#
|
||||
# For example, our macOS wheel build jobs use the following environment
|
||||
# variables to build with Apple-clang and the brew installed "libomp":
|
||||
#
|
||||
# export CPPFLAGS="$CPPFLAGS -Xpreprocessor -fopenmp"
|
||||
# export CFLAGS="$CFLAGS -I/usr/local/opt/libomp/include"
|
||||
# export CXXFLAGS="$CXXFLAGS -I/usr/local/opt/libomp/include"
|
||||
# export LDFLAGS="$LDFLAGS -Wl,-rpath,/usr/local/opt/libomp/lib
|
||||
# -L/usr/local/opt/libomp/lib -lomp"
|
||||
return []
|
||||
# Default flag for GCC and clang:
|
||||
return ['-fopenmp']
|
||||
|
||||
|
||||
def check_openmp_support():
|
||||
"""Check whether OpenMP test code can be compiled and run"""
|
||||
code = textwrap.dedent(
|
||||
"""\
|
||||
#include <omp.h>
|
||||
#include <stdio.h>
|
||||
int main(void) {
|
||||
#pragma omp parallel
|
||||
printf("nthreads=%d\\n", omp_get_num_threads());
|
||||
return 0;
|
||||
}
|
||||
""")
|
||||
|
||||
extra_preargs = os.getenv('LDFLAGS', None)
|
||||
if extra_preargs is not None:
|
||||
extra_preargs = extra_preargs.strip().split(" ")
|
||||
extra_preargs = [
|
||||
flag for flag in extra_preargs
|
||||
if flag.startswith(('-L', '-Wl,-rpath', '-l'))]
|
||||
|
||||
extra_postargs = get_openmp_flag
|
||||
|
||||
try:
|
||||
output = compile_test_program(code,
|
||||
extra_preargs=extra_preargs,
|
||||
extra_postargs=extra_postargs)
|
||||
|
||||
if 'nthreads=' in output[0]:
|
||||
nthreads = int(output[0].strip().split('=')[1])
|
||||
openmp_supported = len(output) == nthreads
|
||||
else:
|
||||
openmp_supported = False
|
||||
|
||||
except (CompileError, LinkError, subprocess.CalledProcessError):
|
||||
openmp_supported = False
|
||||
|
||||
if not openmp_supported:
|
||||
if os.getenv("SKLEARN_FAIL_NO_OPENMP"):
|
||||
raise CompileError("Failed to build with OpenMP")
|
||||
else:
|
||||
message = textwrap.dedent(
|
||||
"""
|
||||
|
||||
***********
|
||||
* WARNING *
|
||||
***********
|
||||
|
||||
It seems that scikit-learn cannot be built with OpenMP.
|
||||
|
||||
- Make sure you have followed the installation instructions:
|
||||
|
||||
https://scikit-learn.org/dev/developers/advanced_installation.html
|
||||
|
||||
- If your compiler supports OpenMP but you still see this
|
||||
message, please submit a bug report at:
|
||||
|
||||
https://github.com/scikit-learn/scikit-learn/issues
|
||||
|
||||
- The build will continue with OpenMP-based parallelism
|
||||
disabled. Note however that some estimators will run in
|
||||
sequential mode instead of leveraging thread-based
|
||||
parallelism.
|
||||
|
||||
***
|
||||
""")
|
||||
warnings.warn(message)
|
||||
|
||||
return openmp_supported
|
||||
|
|
@ -0,0 +1,70 @@
|
|||
"""Helpers to check build environment before actual build of scikit-learn"""
|
||||
|
||||
import os
|
||||
import sys
|
||||
import glob
|
||||
import tempfile
|
||||
import textwrap
|
||||
import subprocess
|
||||
|
||||
from distutils.sysconfig import customize_compiler
|
||||
from numpy.distutils.ccompiler import new_compiler
|
||||
|
||||
|
||||
def compile_test_program(code, extra_preargs=[], extra_postargs=[]):
|
||||
"""Check that some C code can be compiled and run"""
|
||||
ccompiler = new_compiler()
|
||||
customize_compiler(ccompiler)
|
||||
|
||||
# extra_(pre/post)args can be a callable to make it possible to get its
|
||||
# value from the compiler
|
||||
if callable(extra_preargs):
|
||||
extra_preargs = extra_preargs(ccompiler)
|
||||
if callable(extra_postargs):
|
||||
extra_postargs = extra_postargs(ccompiler)
|
||||
|
||||
start_dir = os.path.abspath('.')
|
||||
|
||||
with tempfile.TemporaryDirectory() as tmp_dir:
|
||||
try:
|
||||
os.chdir(tmp_dir)
|
||||
|
||||
# Write test program
|
||||
with open('test_program.c', 'w') as f:
|
||||
f.write(code)
|
||||
|
||||
os.mkdir('objects')
|
||||
|
||||
# Compile, test program
|
||||
ccompiler.compile(['test_program.c'], output_dir='objects',
|
||||
extra_postargs=extra_postargs)
|
||||
|
||||
# Link test program
|
||||
objects = glob.glob(
|
||||
os.path.join('objects', '*' + ccompiler.obj_extension))
|
||||
ccompiler.link_executable(objects, 'test_program',
|
||||
extra_preargs=extra_preargs,
|
||||
extra_postargs=extra_postargs)
|
||||
|
||||
# Run test program
|
||||
# will raise a CalledProcessError if return code was non-zero
|
||||
output = subprocess.check_output('./test_program')
|
||||
output = output.decode(sys.stdout.encoding or 'utf-8').splitlines()
|
||||
except Exception:
|
||||
raise
|
||||
finally:
|
||||
os.chdir(start_dir)
|
||||
|
||||
return output
|
||||
|
||||
|
||||
def basic_check_build():
|
||||
"""Check basic compilation and linking of C code"""
|
||||
code = textwrap.dedent(
|
||||
"""\
|
||||
#include <stdio.h>
|
||||
int main(void) {
|
||||
return 0;
|
||||
}
|
||||
""")
|
||||
compile_test_program(code)
|
||||
Loading…
Add table
Add a link
Reference in a new issue