diff --git a/examples/new_project_templates/lightning_module_template.py b/examples/new_project_templates/lightning_module_template.py
index 72c740ccd7..2b3cd0a8a4 100644
--- a/examples/new_project_templates/lightning_module_template.py
+++ b/examples/new_project_templates/lightning_module_template.py
@@ -159,19 +159,11 @@ class LightningTemplateModel(LightningModule):
         dataset = MNIST(root=self.hparams.data_root, train=train, transform=transform, download=True)
 
         # when using multi-node we need to add the datasampler
-        print('-'*100)
-        print(self.trainer.world_size, self.trainer.proc_rank)
-        print('-'*100)
-        train_sampler = DistributedSampler(dataset, num_replicas=self.trainer.world_size, rank=self.trainer.proc_rank)
-        # try:
-        #     if self.hparams.nb_gpu_nodes > 1:
-        #         print('-'*100)
-        #         print(self.trainer.world_size, self.trainer.proc_rank)
-        #         print('-'*100)
-        #         train_sampler = DistributedSampler(dataset, num_replicas=self.trainer.world_size, rank=self.trainer.proc_rank)
-        # except Exception as e:
-        #     print('no sampler')
-        #     train_sampler = None
+        try:
+            if self.hparams.nb_gpu_nodes > 1:
+                train_sampler = DistributedSampler(dataset, num_replicas=self.trainer.world_size, rank=self.trainer.proc_rank)
+        except Exception as e:
+            train_sampler = None
 
         should_shuffle = train_sampler is None
         loader = DataLoader(