Fixed python style.

Author: ajaysaini725

python/pyspark/ml/classification.py

@@ -1529,7 +1529,8 @@ def __init__(self, featuresCol="features", labelCol="label", predictionCol="pred
 
     @keyword_only
     @since("2.0.0")
-    def setParams(self, featuresCol=None, labelCol=None, predictionCol=None, classifier=None, parallelism=None):
+    def setParams(self, featuresCol=None, labelCol=None, predictionCol=None,
+                  classifier=None, parallelism=None):
         """
         setParams(self, featuresCol=None, labelCol=None, predictionCol=None, classifier=None):
         Sets params for OneVsRest.
@@ -1565,11 +1566,9 @@ def trainSingleClass(index):
                             (classifier.predictionCol, predictionCol)])
             return classifier.fit(trainingDataset, paramMap)
 
-        # TODO: Parallel training for all classes.
         pool = ThreadPool(processes=self.getParallelism())
 
         models = pool.map(trainSingleClass, range(numClasses))
-        #models = [trainSingleClass(i) for i in range(numClasses)]
 
         if handlePersistence:
             multiclassLabeled.unpersist()
@@ -1652,6 +1651,7 @@ def _to_java(self):
         _java_obj.setPredictionCol(self.getPredictionCol())
         return _java_obj
 
+
 class OneVsRestModel(Model, OneVsRestParams, MLReadable, MLWritable):
     """
     .. note:: Experimental

python/pyspark/ml/tests.py

@@ -1234,6 +1234,7 @@ def test_output_columns(self):
         output = model.transform(df)
         self.assertEqual(output.columns, ["label", "features", "prediction"])
 
+
 class ParOneVsRestTests(SparkSessionTestCase):
 
     def test_copy(self):
@@ -1261,6 +1262,7 @@ def test_output_columns(self):
         output = model.transform(df)
         self.assertEqual(output.columns, ["label", "features", "prediction"])
 
+
 class HashingTFTest(SparkSessionTestCase):
 
     def test_apply_binary_term_freqs(self):