Fix LogisticRegression.decision_function output shape

Previously this would return `(n_classes, n_rows)` for multiclass,
whereas sklearn returns `(n_rows, n_classes)`.

python/cuml/cuml/linear_model/logistic_regression.pyx

@@ -455,9 +455,7 @@ class LogisticRegression(UniversalBase,
                             log_proba=False) -> CumlArray:
         _num_classes = self.classes_.shape[0]
 
-        scores = cp.asarray(
-            self.decision_function(X, convert_dtype=convert_dtype), order="F"
-        ).T
+        scores = self.decision_function(X, convert_dtype=convert_dtype).to_output("cupy")
         if _num_classes == 2:
             proba = cp.zeros((scores.shape[0], 2))
             proba[:, 1] = 1 / (1 + cp.exp(-scores.ravel()))

python/cuml/cuml/solvers/qn.pyx

@@ -1,4 +1,4 @@
-# Copyright (c) 2019-2024, NVIDIA CORPORATION.
+# Copyright (c) 2019-2025, NVIDIA CORPORATION.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -662,7 +662,9 @@ class QN(Base,
         Returns
         ----------
         y: array-like (device)
-            Dense matrix (floats or doubles) of shape (n_samples, n_classes)
+            Dense matrix (floats or doubles) of shape (n_samples,), or
+            (n_samples, n_classes) if more than 2 classes.
+
         """
         coefs = self.coef_
         dtype = coefs.dtype
@@ -776,7 +778,7 @@ class QN(Base,
 
         del X_m
 
-        return scores
+        return scores.to_output("array").T
 
     @generate_docstring(
         X='dense_sparse',

python/cuml/cuml/tests/test_linear_model.py

@@ -717,8 +717,6 @@ def test_logistic_regression_decision_function(
     sklog.classes_ = np.arange(num_classes)
 
     cu_dec_func = culog.decision_function(X_test)
-    if cu_dec_func.shape[0] > 2:  # num_classes
-        cu_dec_func = cu_dec_func.T
     sk_dec_func = sklog.decision_function(X_test)
 
     assert array_equal(cu_dec_func, sk_dec_func)