Update scikit-learn imports for version 1.8.

And remove upper bounds on dependencies, to match main tabpfn package.

Author: oscarkey

pyproject.toml

@@ -7,9 +7,9 @@ name = "tabpfn-extensions"
 version = "0.2.2"
 dependencies = [
     "torch>=2.1,<3",
-    "pandas>=1.4.0,<3",
-    "scikit-learn>=1.6.0,<1.7",
-    "scipy>=1.11.1,<2",
+    "pandas>=1.4.0",
+    "scikit-learn>=1.6.0",
+    "scipy>=1.11.1",
     "tabpfn>=6.0.5,<8",
     "tabpfn-common-utils[telemetry-interactive]>=0.2.0",
 ]

src/tabpfn_extensions/misc/sklearn_compat.py

@@ -245,7 +245,7 @@ def _raise_for_params(params, owner, method):
                     f" details. Extra parameters passed are: {set(params)}",
                 )
 
-    def _is_pandas_df(X):
+    def is_pandas_df(X):
         """Return True if the X is a pandas dataframe."""
         try:
             pd = sys.modules["pandas"]
@@ -260,7 +260,6 @@ def _is_pandas_df(X):
     )
     from sklearn.utils.validation import (
         _is_fitted,  # noqa: F401
-        _is_pandas_df,  # noqa: F401
     )
 
 
@@ -861,3 +860,15 @@ def parametrize_with_checks(
         check_X_y,  # noqa: F401
         validate_data,  # noqa: F401
     )
+
+
+########################################################################################
+# Upgrading for scikit-learn 1.8
+########################################################################################
+
+
+if sklearn_version < parse_version("1.8"):
+    if sklearn_version >= parse_version("1.4"):
+        from sklearn.utils.validation import _is_pandas_df as is_pandas_df
+else:
+    from sklearn.utils._dataframe import is_pandas_df  # noqa: F401