MAINT use public import for metadata routing (#1113)

imblearn/base.py

@@ -9,12 +9,19 @@
 import numpy as np
 from sklearn.base import BaseEstimator, OneToOneFeatureMixin
 from sklearn.preprocessing import label_binarize
+from sklearn.utils._metadata_requests import METHODS
 from sklearn.utils.multiclass import check_classification_targets
 
 from .utils import check_sampling_strategy, check_target_type
 from .utils._sklearn_compat import _fit_context, get_tags, validate_data
 from .utils._validation import ArraysTransformer
 
+if "fit_predict" not in METHODS:
+    METHODS.append("fit_predict")
+if "fit_transform" not in METHODS:
+    METHODS.append("fit_transform")
+METHODS.append("fit_resample")
+
 
 class SamplerMixin(metaclass=ABCMeta):
     """Mixin class for samplers with abstract method.

imblearn/pipeline.py

@@ -21,18 +21,18 @@
 from sklearn.base import clone
 from sklearn.exceptions import NotFittedError
 from sklearn.utils import Bunch
-from sklearn.utils._metadata_requests import (
-    METHODS,
+from sklearn.utils._param_validation import HasMethods
+from sklearn.utils.fixes import parse_version
+from sklearn.utils.metadata_routing import (
     MetadataRouter,
     MethodMapping,
     _routing_enabled,
     get_routing_for_object,
 )
-from sklearn.utils._param_validation import HasMethods
-from sklearn.utils.fixes import parse_version
 from sklearn.utils.metaestimators import available_if
 from sklearn.utils.validation import check_is_fitted, check_memory
 
+from .base import METHODS
 from .utils._sklearn_compat import (
     _fit_context,
     _print_elapsed_time,
@@ -43,12 +43,6 @@
     validate_params,
 )
 
-if "fit_predict" not in METHODS:
-    METHODS.append("fit_predict")
-if "fit_transform" not in METHODS:
-    METHODS.append("fit_transform")
-METHODS.append("fit_resample")
-
 __all__ = ["Pipeline", "make_pipeline"]