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Adding sklearn min. dependencies for all versions #1022

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Feb 18, 2021
Merged

Adding sklearn min. dependencies for all versions #1022

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Neeratyoy Feb 15, 2021
8442576
All flow dependencies for sklearn>0.24 will change now
Neeratyoy Feb 16, 2021
ffb4a2d
Dep. string change only for OpenML>v0.11
Neeratyoy Feb 18, 2021
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Dep. string change only for OpenML>v0.11
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@Neeratyoy
Neeratyoy committed Feb 18, 2021
commit ffb4a2d72db28c8ab7e47c2d88710bbd0a292022
38 changes: 29 additions & 9 deletions openml/extensions/sklearn/extension.py
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Expand Up @@ -224,17 +224,37 @@ def _min_dependency_str(cls, sklearn_version: str) -> str:
-------
str
"""
if LooseVersion(sklearn_version) >= "0.24":
openml_major_version = int(LooseVersion(openml.__version__).version[1])
# This explicit check is necessary to support existing entities on the OpenML servers
# that used the fixed dependency string (in the else block)
if openml_major_version > 11:
# OpenML v0.11 onwards supports sklearn>=0.24
# assumption: 0.24 onwards sklearn should contain a _min_dependencies.py file with
# variables declared for extracting minimum dependency for that version
from sklearn import _min_dependencies as _mindep

dependency_list = {
"numpy": "{}".format(_mindep.NUMPY_MIN_VERSION),
"scipy": "{}".format(_mindep.SCIPY_MIN_VERSION),
"joblib": "{}".format(_mindep.JOBLIB_MIN_VERSION),
"threadpoolctl": "{}".format(_mindep.THREADPOOLCTL_MIN_VERSION),
}
if LooseVersion(sklearn_version) >= "0.24":
from sklearn import _min_dependencies as _mindep

dependency_list = {
"numpy": "{}".format(_mindep.NUMPY_MIN_VERSION),
"scipy": "{}".format(_mindep.SCIPY_MIN_VERSION),
"joblib": "{}".format(_mindep.JOBLIB_MIN_VERSION),
"threadpoolctl": "{}".format(_mindep.THREADPOOLCTL_MIN_VERSION),
}
elif LooseVersion(sklearn_version) >= "0.23":
dependency_list = {
"numpy": "1.13.3",
"scipy": "0.19.1",
"joblib": "0.11",
"threadpoolctl": "2.0.0",
}
if LooseVersion(sklearn_version).version[2] == 0:
dependency_list.pop("threadpoolctl")
elif LooseVersion(sklearn_version) >= "0.21":
dependency_list = {"numpy": "1.11.0", "scipy": "0.17.0", "joblib": "0.11"}
elif LooseVersion(sklearn_version) >= "0.19":
dependency_list = {"numpy": "1.8.2", "scipy": "0.13.3"}
else:
dependency_list = {"numpy": "1.6.1", "scipy": "0.9"}
else:
# this is INCORRECT for sklearn versions >= 0.19 and < 0.24
# given that OpenML has existing flows uploaded with such dependency information,
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