diff --git a/deepspeech/exps/deepspeech2/model.py b/deepspeech/exps/deepspeech2/model.py
index 5c6c5fa18..91b7a1bfe 100644
--- a/deepspeech/exps/deepspeech2/model.py
+++ b/deepspeech/exps/deepspeech2/model.py
@@ -29,8 +29,8 @@ from deepspeech.io.sampler import SortagradBatchSampler
 from deepspeech.io.sampler import SortagradDistributedBatchSampler
 from deepspeech.models.ds2 import DeepSpeech2InferModel
 from deepspeech.models.ds2 import DeepSpeech2Model
-from deepspeech.models.ds2_online import DeepSpeech2InferModelOnline
-from deepspeech.models.ds2_online import DeepSpeech2ModelOnline
+#from deepspeech.models.ds2_online import DeepSpeech2InferModelOnline
+#from deepspeech.models.ds2_online import DeepSpeech2ModelOnline
 from deepspeech.training.gradclip import ClipGradByGlobalNormWithLog
 from deepspeech.training.trainer import Trainer
 from deepspeech.utils import error_rate
@@ -122,25 +122,15 @@ class DeepSpeech2Trainer(Trainer):
 
     def setup_model(self):
         config = self.config
-        if (config.model.apply_online == False):
-            model = DeepSpeech2Model(
-                feat_size=self.train_loader.collate_fn.feature_size,
-                dict_size=self.train_loader.collate_fn.vocab_size,
-                num_conv_layers=config.model.num_conv_layers,
-                num_rnn_layers=config.model.num_rnn_layers,
-                rnn_size=config.model.rnn_layer_size,
-                use_gru=config.model.use_gru,
-                share_rnn_weights=config.model.share_rnn_weights)
-        else:
-            model = DeepSpeech2ModelOnline(
-                feat_size=self.train_loader.collate_fn.feature_size,
-                dict_size=self.train_loader.collate_fn.vocab_size,
-                num_conv_layers=config.model.num_conv_layers,
-                num_rnn_layers=config.model.num_rnn_layers,
-                rnn_size=config.model.rnn_layer_size,
-                use_gru=config.model.use_gru,
-                share_rnn_weights=config.model.share_rnn_weights)
-    
+        model = DeepSpeech2Model(
+            feat_size=self.train_loader.collate_fn.feature_size,
+            dict_size=self.train_loader.collate_fn.vocab_size,
+            num_conv_layers=config.model.num_conv_layers,
+            num_rnn_layers=config.model.num_rnn_layers,
+            rnn_size=config.model.rnn_layer_size,
+            use_gru=config.model.use_gru,
+            share_rnn_weights=config.model.share_rnn_weights)
+
         if self.parallel:
             model = paddle.DataParallel(model)
 
@@ -347,7 +337,7 @@ class DeepSpeech2Tester(DeepSpeech2Trainer):
         else:
             infer_model = DeepSpeech2InferModelOnline.from_pretrained(
                 self.test_loader, self.config, self.args.checkpoint_path)
-    
+
         infer_model.eval()
         feat_dim = self.test_loader.collate_fn.feature_size
         static_model = paddle.jit.to_static(
@@ -384,25 +374,15 @@ class DeepSpeech2Tester(DeepSpeech2Trainer):
 
     def setup_model(self):
         config = self.config
-        if config.model.apply_online == False:
-            model = DeepSpeech2Model(
-                feat_size=self.test_loader.collate_fn.feature_size,
-                dict_size=self.test_loader.collate_fn.vocab_size,
-                num_conv_layers=config.model.num_conv_layers,
-                num_rnn_layers=config.model.num_rnn_layers,
-                rnn_size=config.model.rnn_layer_size,
-                use_gru=config.model.use_gru,
-                share_rnn_weights=config.model.share_rnn_weights)
-        else:
-            model = DeepSpeech2ModelOnline(
-                feat_size=self.test_loader.collate_fn.feature_size,
-                dict_size=self.test_loader.collate_fn.vocab_size,
-                num_conv_layers=config.model.num_conv_layers,
-                num_rnn_layers=config.model.num_rnn_layers,
-                rnn_size=config.model.rnn_layer_size,
-                use_gru=config.model.use_gru,
-                share_rnn_weights=config.model.share_rnn_weights)
-    
+        model = DeepSpeech2Model(
+            feat_size=self.test_loader.collate_fn.feature_size,
+            dict_size=self.test_loader.collate_fn.vocab_size,
+            num_conv_layers=config.model.num_conv_layers,
+            num_rnn_layers=config.model.num_rnn_layers,
+            rnn_size=config.model.rnn_layer_size,
+            use_gru=config.model.use_gru,
+            share_rnn_weights=config.model.share_rnn_weights)
+
         self.model = model
         logger.info("Setup model!")