simplify tests and move code around

Author: jameslamb

python/cuml/dask/ensemble/base.py

@@ -257,6 +257,23 @@ def _get_json(self):
             combined_dump.extend(obj)
         return json.dumps(combined_dump)
 
+    def get_combined_model(self):
+        """
+        Return single-GPU model for serialization.
+
+        Returns
+        -------
+
+        model : Trained single-GPU model or None if the model has not
+               yet been trained.
+        """
+
+        # set internal model if it hasn't been accessed before
+        if self._get_internal_model() is None:
+            self._set_internal_model(self._concat_treelite_models())
+
+        return BaseEstimator.get_combined_model(self)
+
 
 def _func_fit(model, input_data, convert_dtype):
     X = concatenate([item[0] for item in input_data])

python/cuml/dask/ensemble/randomforestclassifier.py

@@ -206,23 +206,6 @@ def get_summary_text(self):
         """
         return self._get_summary_text()
 
-    def get_combined_model(self):
-        """
-        Return single-GPU model for serialization.
-
-        Returns
-        -------
-
-        model : Trained single-GPU model or None if the model has not
-               yet been trained.
-        """
-
-        # set internal model if it hasn't been accessed before
-        if self._get_internal_model() is None:
-            self._set_internal_model(self._concat_treelite_models())
-
-        return BaseEstimator.get_combined_model(self)
-
     def get_detailed_text(self):
         """
         Obtain the detailed information for the random forest model, as text

python/cuml/dask/ensemble/randomforestregressor.py

@@ -206,23 +206,6 @@ def get_summary_text(self):
         """
         return self._get_summary_text()
 
-    def get_combined_model(self):
-        """
-        Return single-GPU model for serialization.
-
-        Returns
-        -------
-
-        model : Trained single-GPU model or None if the model has not
-               yet been trained.
-        """
-
-        # set internal model if it hasn't been accessed before
-        if self._get_internal_model() is None:
-            self._set_internal_model(self._concat_treelite_models())
-
-        return BaseEstimator.get_combined_model(self)
-
     def get_detailed_text(self):
         """
         Obtain the detailed information for the random forest model, as text

python/cuml/test/dask/test_random_forest.py

@@ -443,24 +443,13 @@ def predict_with_json_rf_regressor(rf, x):
 def test_rf_get_combined_model_right_aftter_fit(client, estimator_type):
     max_depth = 3
     n_estimators = 5
-    X, y = make_classification(
-        n_samples=350,
-        n_features=20,
-        n_clusters_per_class=1,
-        n_informative=10,
-        random_state=123,
-        n_classes=2
-    )
+    X, y = make_classification()
     X = X.astype(np.float32)
     if estimator_type == 'classification':
         cu_rf_mg = cuRFC_mg(
             max_features=1.0,
             max_samples=1.0,
             n_bins=16,
-            split_algo=0,
-            split_criterion=0,
-            min_samples_leaf=2,
-            seed=23707,
             n_streams=1,
             n_estimators=n_estimators,
             max_leaves=-1,
@@ -472,9 +461,6 @@ def test_rf_get_combined_model_right_aftter_fit(client, estimator_type):
             max_features=1.0,
             max_samples=1.0,
             n_bins=16,
-            split_algo=0,
-            min_samples_leaf=2,
-            seed=23707,
             n_streams=1,
             n_estimators=n_estimators,
             max_leaves=-1,