Add support for new __sklearn_tags__

.github/workflows/build.yml

@@ -19,10 +19,16 @@ jobs:
         # as well as selected previous versions on
         # https://pytorch.org/get-started/previous-versions/
         torch-version: ["2.2.2", "2.4.0"]
+        sklearn-version: ["latest"]
         include:
           - os: windows-latest
             torch-version: 2.4.0
             python-version: "3.10"
+            sklearn-version: "latest"
+          - os: ubuntu-latest 
+            torch-version: 2.4.0
+            python-version: "3.10"
+            sklearn-version: "legacy"
 
     runs-on: ${{ matrix.os }}
 
@@ -32,7 +38,7 @@ jobs:
         uses: actions/cache@v3
         with:
           path: ~/.cache/pip
-          key: pip-os_${{ runner.os }}-python_${{ matrix.python-version }}-torch_${{ matrix.torch-version }}
+          key: pip-os_${{ runner.os }}-python_${{ matrix.python-version }}-torch_${{ matrix.torch-version }}-sklearn_${{ matrix.sklearn-version }}
 
       - name: Checkout code
         uses: actions/checkout@v2
@@ -48,6 +54,11 @@ jobs:
           python -m pip install torch==${{ matrix.torch-version }} --extra-index-url https://download.pytorch.org/whl/cpu
           pip install '.[dev,datasets,integrations]'
 
+      - name: Check sklearn legacy version 
+        if: matrix.sklearn-version == 'legacy'
+        run: |
+          pip install scikit-learn==1.4.2 '.[dev,datasets,integrations]'
+
       - name: Run the formatter
         run: |
           make format

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,
@@ -364,7 +371,7 @@ def _load_cebra_with_sklearn_backend(cebra_info: Dict) -> "CEBRA":
     return cebra_
 
 
-class CEBRA(BaseEstimator, TransformerMixin):
+class CEBRA(TransformerMixin, BaseEstimator):
     """CEBRA model defined as part of a ``scikit-learn``-like API.
 
     Attributes:
@@ -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.