iter

Author: glemaitre

imblearn/utils/_tags.py

@@ -32,70 +32,69 @@ class SamplerTags:
 
         sample_indices: bool = False
 
+    @dataclass(**_dataclass_args())
+    class Tags:
+        """Tags for the estimator.
+
+        See :ref:`estimator_tags` for more information.
+
+        Parameters
+        ----------
+        estimator_type : str or None
+            The type of the estimator. Can be one of:
+            - "classifier"
+            - "regressor"
+            - "transformer"
+            - "clusterer"
+            - "outlier_detector"
+            - "density_estimator"
+
+        target_tags : :class:`TargetTags`
+            The target(y) tags.
+
+        transformer_tags : :class:`TransformerTags` or None
+            The transformer tags.
+
+        classifier_tags : :class:`ClassifierTags` or None
+            The classifier tags.
+
+        regressor_tags : :class:`RegressorTags` or None
+            The regressor tags.
+
+        sampler_tags : :class:`SamplerTags` or None
+            The sampler tags.
+
+        array_api_support : bool, default=False
+            Whether the estimator supports Array API compatible inputs.
+
+        no_validation : bool, default=False
+            Whether the estimator skips input-validation. This is only meant for
+            stateless and dummy transformers!
+
+        non_deterministic : bool, default=False
+            Whether the estimator is not deterministic given a fixed ``random_state``.
+
+        requires_fit : bool, default=True
+            Whether the estimator requires to be fitted before calling one of
+            `transform`, `predict`, `predict_proba`, or `decision_function`.
+
+        _skip_test : bool, default=False
+            Whether to skip common tests entirely. Don't use this unless
+            you have a *very good* reason.
+
+        input_tags : :class:`InputTags`
+            The input data(X) tags.
+        """
 
-@dataclass(**_dataclass_args())
-class Tags:
-    """Tags for the estimator.
-
-    See :ref:`estimator_tags` for more information.
-
-    Parameters
-    ----------
-    estimator_type : str or None
-        The type of the estimator. Can be one of:
-        - "classifier"
-        - "regressor"
-        - "transformer"
-        - "clusterer"
-        - "outlier_detector"
-        - "density_estimator"
-
-    target_tags : :class:`TargetTags`
-        The target(y) tags.
-
-    transformer_tags : :class:`TransformerTags` or None
-        The transformer tags.
-
-    classifier_tags : :class:`ClassifierTags` or None
-        The classifier tags.
-
-    regressor_tags : :class:`RegressorTags` or None
-        The regressor tags.
-
-    sampler_tags : :class:`SamplerTags` or None
-        The sampler tags.
-
-    array_api_support : bool, default=False
-        Whether the estimator supports Array API compatible inputs.
-
-    no_validation : bool, default=False
-        Whether the estimator skips input-validation. This is only meant for
-        stateless and dummy transformers!
-
-    non_deterministic : bool, default=False
-        Whether the estimator is not deterministic given a fixed ``random_state``.
-
-    requires_fit : bool, default=True
-        Whether the estimator requires to be fitted before calling one of
-        `transform`, `predict`, `predict_proba`, or `decision_function`.
-
-    _skip_test : bool, default=False
-        Whether to skip common tests entirely. Don't use this unless
-        you have a *very good* reason.
-
-    input_tags : :class:`InputTags`
-        The input data(X) tags.
-    """
-
-    estimator_type: str | None
-    target_tags: TargetTags
-    transformer_tags: TransformerTags | None
-    classifier_tags: ClassifierTags | None
-    regressor_tags: RegressorTags | None
-    sampler_tags: SamplerTags | None
-    array_api_support: bool = False
-    no_validation: bool = False
-    non_deterministic: bool = False
-    requires_fit: bool = True
-    _skip_test: bool = False
-    input_tags: InputTags = field(default_factory=InputTags)
+        estimator_type: str | None
+        target_tags: TargetTags
+        transformer_tags: TransformerTags | None
+        classifier_tags: ClassifierTags | None
+        regressor_tags: RegressorTags | None
+        sampler_tags: SamplerTags | None
+        array_api_support: bool = False
+        no_validation: bool = False
+        non_deterministic: bool = False
+        requires_fit: bool = True
+        _skip_test: bool = False
+        input_tags: InputTags = field(default_factory=InputTags)