diff --git a/app_train.py b/app_train.py
index 8980dcf..071398f 100644
--- a/app_train.py
+++ b/app_train.py
@@ -5,4 +5,4 @@ from PytorchBoot.runners.trainer import DefaultTrainer
 class TrainApp:
     @staticmethod
     def start():
-        DefaultTrainer("configs/train_config.yaml").run()
\ No newline at end of file
+        DefaultTrainer("configs/server/train_config.yaml").run()
\ No newline at end of file
diff --git a/core/pipeline.py b/core/pipeline.py
index f4dba95..2203c30 100644
--- a/core/pipeline.py
+++ b/core/pipeline.py
@@ -5,7 +5,7 @@ import PytorchBoot.stereotype as stereotype
 from PytorchBoot.factory.component_factory import ComponentFactory
 from PytorchBoot.utils import Log
 
-@stereotype.pipeline("nbv_reconstruction_pipeline", comment="should be tested")
+@stereotype.pipeline("nbv_reconstruction_pipeline")
 class NBVReconstructionPipeline(nn.Module):
     def __init__(self, config):
         super(NBVReconstructionPipeline, self).__init__()
@@ -72,7 +72,6 @@ class NBVReconstructionPipeline(nn.Module):
         pose_feat_seq_list = []
         
         for scanned_pts,scanned_n_to_1_pose_9d in zip(scanned_pts_batch,scanned_n_to_1_pose_9d_batch):
-            print(scanned_n_to_1_pose_9d.shape)
             scanned_pts = scanned_pts.to(best_to_1_pose_9d_batch.device)
             scanned_n_to_1_pose_9d = scanned_n_to_1_pose_9d.to(best_to_1_pose_9d_batch.device)
             pts_feat_seq_list.append(self.pts_encoder.encode_points(scanned_pts))