diff --git a/orcaexample/kinetics.py b/orcaexample/kinetics.py
index 449867e6d..f747b451c 100644
--- a/orcaexample/kinetics.py
+++ b/orcaexample/kinetics.py
@@ -95,22 +95,22 @@ def loss_creator(config):
                        )
     val_stats = orca_estimator.evaluate(data=validation_data_creator(cfg,cfg.TEST.BATCH_SIZE))
     print("===> Validation Complete: Top1Accuracy {}".format(val_stats["Accuracy"]))
-# elif args.backend in ["ray", "spark"]:
-#     orca_estimator = Estimator.from_torch(model=model_creator,
-#                                           optimizer=optim_creator,
-#                                           loss=loss_creator,
-#                                           metrics=[Accuracy()],
-#                                           backend=args.backend,
-#                                           config=cfg,
-#                                           model_dir=os.getcwd(),
-#                                           use_tqdm=True)
-#     orca_estimator.fit(data=train_loader_creator,
-#                        validation_data=validation_data_creator,
-#                        batch_size=cfg.TRAIN.BATCH_SIZE,
-#                        epochs=cfg.SOLVER.MAX_EPOCH)
-#     val_stats = orca_estimator.evaluate(data=validation_data_creator, batch_size=cfg.TEST.BATCH_SIZE)
-#     print("===> Validation Complete: Top1Accuracy {}".format(val_stats["Accuracy"]))
-#     orca_estimator.shutdown()
+elif args.backend in ["ray", "spark"]:
+    orca_estimator = Estimator.from_torch(model=model_creator,
+                                          optimizer=optim_creator,
+                                          loss=loss_creator,
+                                          metrics=[Accuracy()],
+                                          backend=args.backend,
+                                          config=cfg,
+                                          model_dir=os.getcwd(),
+                                          use_tqdm=True)
+    orca_estimator.fit(data=train_loader_creator,
+                       validation_data=validation_data_creator,
+                       batch_size=cfg.TRAIN.BATCH_SIZE,
+                       epochs=cfg.SOLVER.MAX_EPOCH)
+    val_stats = orca_estimator.evaluate(data=validation_data_creator, batch_size=cfg.TEST.BATCH_SIZE)
+    print("===> Validation Complete: Top1Accuracy {}".format(val_stats["Accuracy"]))
+    orca_estimator.shutdown()
 else:
     invalidInputError(False, "Only bigdl, ray, and spark are supported "
                         "as the backend, but got {}".format(args.backend))