ENH Make get_param_names a class method to match Scikit-learn

python/cuml/cuml/_thirdparty/sklearn/preprocessing/_data.py

@@ -326,7 +326,8 @@ def _reset(self):
             del self.data_max_
             del self.data_range_
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return super().get_param_names() + [
             "feature_range",
             "copy"

python/cuml/cuml/_thirdparty/sklearn/preprocessing/_discretization.py

@@ -158,7 +158,8 @@ def __init__(self, n_bins=5, *, encode='onehot', strategy='quantile'):
         self.encode = encode
         self.strategy = strategy
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return super().get_param_names() + [
             "n_bins",
             "encode",

python/cuml/cuml/_thirdparty/sklearn/preprocessing/_imputation.py

@@ -243,7 +243,8 @@ def __init__(self, *, missing_values=np.nan, strategy="mean",
         self.fill_value = fill_value
         self.copy = copy
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return super().get_param_names() + [
             "strategy",
             "fill_value",

python/cuml/cuml/dask/cluster/dbscan.py

@@ -160,5 +160,6 @@ def fit_predict(self, X, out_dtype="int32"):
         self.fit(X, out_dtype)
         return self.get_combined_model().labels_
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return list(self.kwargs.keys())

python/cuml/cuml/dask/cluster/kmeans.py

@@ -302,5 +302,6 @@ def score(self, X, sample_weight=None):
             cp.asarray(self.client.compute(scores, sync=True)) * -1.0
         )
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return list(self.kwargs.keys())

python/cuml/cuml/dask/decomposition/pca.py

@@ -215,7 +215,8 @@ def inverse_transform(self, X, delayed=True):
         """
         return self._inverse_transform(X, n_dims=2, delayed=delayed)
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return list(self.kwargs.keys())
 
     @staticmethod

python/cuml/cuml/dask/decomposition/tsvd.py

@@ -177,7 +177,8 @@ def inverse_transform(self, X, delayed=True):
         """
         return self._inverse_transform(X, n_dims=2, delayed=delayed)
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return list(self.kwargs.keys())
 
     @staticmethod

python/cuml/cuml/dask/linear_model/linear_regression.py

@@ -106,7 +106,8 @@ def predict(self, X, delayed=True):
         """
         return self._predict(X, delayed=delayed)
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return list(self.kwargs.keys())
 
     @staticmethod

python/cuml/cuml/dask/linear_model/ridge.py

@@ -114,7 +114,8 @@ def predict(self, X, delayed=True):
         """
         return self._predict(X, delayed=delayed)
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return list(self.kwargs.keys())
 
     @staticmethod

python/cuml/cuml/decomposition/incremental_pca.py

@@ -449,7 +449,8 @@ def transform(self, X, convert_dtype=False) -> CumlArray:
         else:
             return super().transform(X)
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         # Skip super() since we dont pass any extra parameters in __init__
         return Base.get_param_names(self) + self._hyperparams
 

python/cuml/cuml/feature_extraction/_tfidf.py

@@ -301,7 +301,8 @@ def idf_(self, value):
             (value, 0), shape=(n_features, n_features), dtype=cp.float32
         )
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return super().get_param_names() + [
             "norm",
             "use_idf",

python/cuml/cuml/linear_model/lasso.py

@@ -165,5 +165,6 @@ def __init__(
             verbose=verbose,
         )
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return list(set(super().get_param_names()) - {"l1_ratio"})

python/cuml/cuml/multiclass/multiclass.py

@@ -192,7 +192,8 @@ def decision_function(self, X) -> CumlArray:
         with cuml.internals.exit_internal_api():
             return self.multiclass_estimator.decision_function(X)
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return super().get_param_names() + ["estimator", "strategy"]
 
 

python/cuml/cuml/naive_bayes/naive_bayes.py

@@ -724,7 +724,8 @@ def _joint_log_likelihood(self, X):
 
         return cp.array(joint_log_likelihood).T
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return super().get_param_names() + ["priors", "var_smoothing"]
 
 

python/cuml/cuml/neighbors/kernel_density.py

@@ -225,7 +225,8 @@ def __init__(
         if kernel not in VALID_KERNELS:
             raise ValueError("invalid kernel: '{0}'".format(kernel))
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return super().get_param_names() + [
             "bandwidth",
             "kernel",

python/cuml/cuml/preprocessing/LabelEncoder.py

@@ -284,7 +284,8 @@ def inverse_transform(self, y: cudf.Series) -> cudf.Series:
 
         return res
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return super().get_param_names() + [
             "handle_unknown",
         ]

python/cuml/cuml/preprocessing/TargetEncoder.py

@@ -508,7 +508,8 @@ def _get_output_type(self, x):
             return "numpy"
         return "cupy"
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return [
             "n_folds",
             "smooth",

python/cuml/cuml/preprocessing/encoders.py

@@ -602,7 +602,8 @@ def get_feature_names(self, input_features=None):
 
         return np.array(feature_names, dtype=object)
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return super().get_param_names() + [
             "categories",
             "drop",

python/cuml/cuml/preprocessing/label.py

@@ -287,7 +287,8 @@ def inverse_transform(self, y, threshold=None) -> CumlArray:
 
         return invert_labels(y_mapped, self.classes_)
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return super().get_param_names() + [
             "neg_label",
             "pos_label",

python/cuml/cuml/svm/linear_svc.py

@@ -173,7 +173,8 @@ def loss(self, loss: str):
             )
         self.__loss = loss
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return list(
             {
                 "handle",

python/cuml/cuml/svm/linear_svr.py

@@ -152,7 +152,8 @@ def loss(self, loss: str):
             )
         self.__loss = loss
 
-    def get_param_names(self):
+    @classmethod
+    def get_param_names(cls):
         return list(
             {
                 "handle",