Add support for new __sklearn_tags__

cebra/integrations/sklearn/cebra.py

@@ -30,8 +30,10 @@
 import pkg_resources
 import sklearn.utils.validation as sklearn_utils_validation
 import torch
+import sklearn
 from sklearn.base import BaseEstimator
 from sklearn.base import TransformerMixin
+from sklearn.utils.metaestimators import available_if
 from torch import nn
 
 import cebra.data
@@ -41,6 +43,11 @@
 import cebra.models
 import cebra.solver
 
+def check_version(estimator):
+    # NOTE(stes): required as a check for the old way of specifying tags
+    # https://github.com/scikit-learn/scikit-learn/pull/29677#issuecomment-2334229165
+    from packaging import version
+    return version.parse(sklearn.__version__) < version.parse("1.6.dev")
 
 def _init_loader(
     is_cont: bool,
@@ -1294,6 +1301,15 @@ def fit_transform(
                  callback_frequency=callback_frequency)
         return self.transform(X)
 
+    def __sklearn_tags__(self):
+        # NOTE(stes): from 1.6.dev, this is the new way to specify tags
+        # https://scikit-learn.org/dev/developers/develop.html
+        # https://github.com/scikit-learn/scikit-learn/pull/29677#issuecomment-2334229165
+        tags = super().__sklearn_tags__()
+        tags.non_deterministic = True
+        return tags
+
+    @available_if(check_version)
     def _more_tags(self):
         # NOTE(stes): This tag is needed as seeding is not fully implemented in the
         # current version of CEBRA.