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Fix deprecation warning force_all_finite -> ensure_all_finite from 1.7 to 1.8 #206

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Fix deprecation warning force_all_finite -> ensure_all_finite from 1.7 to 1.8 #206

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aaf912f
Fix deprecation warning force_all_finite -> ensure_all_finite
icarosadero Dec 17, 2024
74fc232
Merge branch 'main' into icarosadero-patch-2
stes Dec 17, 2024
2ca1163
Added version compatibility for sklearn 1.8+
icarosadero Dec 17, 2024
3e4ee86
checkpoint
icarosadero Dec 17, 2024
3ba6bc6
Update cebra/integrations/sklearn/utils.py
icarosadero Dec 18, 2024
128257b
Update cebra/integrations/sklearn/utils.py
icarosadero Dec 18, 2024
5770dfa
Update cebra/integrations/sklearn/utils.py
icarosadero Dec 18, 2024
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84 changes: 59 additions & 25 deletions cebra/integrations/sklearn/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,6 +27,10 @@

import cebra.helper

from packaging import version
from sklearn import __version__ as sklearn_version
sklearn_version = version.parse(sklearn_version)

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def update_old_param(old: dict, new: dict, kwargs: dict, default) -> tuple:
"""Handle deprecated arguments of a function until they are replaced.
Expand Down Expand Up @@ -74,19 +78,35 @@ def check_input_array(X: npt.NDArray, *, min_samples: int) -> npt.NDArray:
Returns:
The converted and validated array.
"""
return sklearn_utils_validation.check_array(
X,
accept_sparse=False,
accept_large_sparse=False,
dtype=("float16", "float32", "float64"),
order=None,
copy=False,
force_all_finite=True,
ensure_2d=True,
allow_nd=False,
ensure_min_samples=min_samples,
ensure_min_features=1,
)

if sklearn_version < version.parse("1.8"):
return sklearn_utils_validation.check_array(
X,
accept_sparse=False,
accept_large_sparse=False,
dtype=("float16", "float32", "float64"),
order=None,
copy=False,
force_all_finite=True,
ensure_2d=True,
allow_nd=False,
ensure_min_samples=min_samples,
ensure_min_features=1,
)
else:
return sklearn_utils_validation.check_array(
X,
accept_sparse=False,
accept_large_sparse=False,
dtype=("float16", "float32", "float64"),
order=None,
copy=False,
ensure_all_finite=True,
ensure_2d=True,
allow_nd=False,
ensure_min_samples=min_samples,
ensure_min_features=1,
)
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def check_label_array(y: npt.NDArray, *, min_samples: int):
Expand All @@ -105,18 +125,32 @@ def check_label_array(y: npt.NDArray, *, min_samples: int):
Returns:
The converted and validated labels.
"""
return sklearn_utils_validation.check_array(
y,
accept_sparse=False,
accept_large_sparse=False,
dtype="numeric",
order=None,
copy=False,
force_all_finite=True,
ensure_2d=False,
allow_nd=False,
ensure_min_samples=min_samples,
)
if sklearn_version < version.parse("1.8"):
return sklearn_utils_validation.check_array(
y,
accept_sparse=False,
accept_large_sparse=False,
dtype="numeric",
order=None,
copy=False,
force_all_finite=True,
ensure_2d=False,
allow_nd=False,
ensure_min_samples=min_samples,
)
else:
return sklearn_utils_validation.check_array(
y,
accept_sparse=False,
accept_large_sparse=False,
dtype="numeric",
order=None,
copy=False,
ensure_all_finite=True,
ensure_2d=False,
allow_nd=False,
ensure_min_samples=min_samples,
)
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def check_device(device: str) -> str:
Expand Down
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