Fix KBinsDiscretizer bin_edges_

rapidsai · May 16, 2022 · cec1b57 · cec1b57
1 parent 15aba09
commit cec1b57
Showing 1 changed file with 8 additions and 4 deletions.
diff --git a/python/cuml/_thirdparty/sklearn/preprocessing/_discretization.py b/python/cuml/_thirdparty/sklearn/preprocessing/_discretization.py
@@ -135,7 +135,7 @@ class KBinsDiscretizer(TransformerMixin,
 
     """
 
-    bin_edges_ = CumlArrayDescriptor()
+    bin_edges_internal_ = CumlArrayDescriptor()
     n_bins_ = CumlArrayDescriptor()
 
     @_deprecate_pos_args(version="21.06")
@@ -234,7 +234,7 @@ def fit(self, X, y=None) -> "KBinsDiscretizer":
                                   'decreasing the number of bins.' % jj)
                     n_bins[jj] = len(bin_edges[jj]) - 1
 
-        self.bin_edges_ = bin_edges
+        self.bin_edges_internal_ = bin_edges
         self.n_bins_ = n_bins
 
         if 'onehot' in self.encode:
@@ -303,7 +303,7 @@ def transform(self, X) -> SparseCumlArray:
             raise ValueError("Incorrect number of features. Expecting {}, "
                              "received {}.".format(n_features, Xt.shape[1]))
 
-        bin_edges = self.bin_edges_
+        bin_edges = self.bin_edges_internal_
         for jj in range(Xt.shape[1]):
             # Values which are close to a bin edge are susceptible to numeric
             # instability. Add eps to X so these values are binned correctly
@@ -353,9 +353,13 @@ def inverse_transform(self, Xt) -> SparseCumlArray:
                              "received {}.".format(n_features, Xinv.shape[1]))
 
         for jj in range(n_features):
-            bin_edges = self.bin_edges_[jj]
+            bin_edges = self.bin_edges_internal_[jj]
             bin_centers = (bin_edges[1:] + bin_edges[:-1]) * 0.5
             idxs = np.asnumpy(Xinv[:, jj])
             Xinv[:, jj] = bin_centers[idxs.astype(np.int32)]
 
         return Xinv
+
+    @property
+    def bin_edges_(self):
+        return self.bin_edges_internal_