diff --git a/datasets/imagenet.py b/datasets/imagenet.py
index b5610533..2968737e 100644
--- a/datasets/imagenet.py
+++ b/datasets/imagenet.py
@@ -5,8 +5,8 @@ from PIL import Image
 import torchvision.transforms as transforms
 
 BASEDIR = "/home/batman/imagenet"
-train_files = open(os.path.join(BASEDIR, "train_files")).read().split("\n")
-val_files = open(os.path.join(BASEDIR, "val_files")).read().split("\n")
+train_files = open(os.path.join(BASEDIR, "train_files")).read().strip().split("\n")
+val_files = open(os.path.join(BASEDIR, "val_files")).read().strip().split("\n")
 ci = json.load(open(os.path.join(BASEDIR, "imagenet_class_index.json")))
 cir = {v[0]: int(k) for k,v in ci.items()}
 
diff --git a/examples/train_efficientnet.py b/examples/train_efficientnet.py
index 0a348d80..a193fd77 100644
--- a/examples/train_efficientnet.py
+++ b/examples/train_efficientnet.py
@@ -1,4 +1,5 @@
 import os
+import traceback
 import time
 import numpy as np
 from models.efficientnet import EfficientNet
@@ -53,7 +54,10 @@ if __name__ == "__main__":
     from multiprocessing import Process, Queue
     def loader(q):
       while 1:
-        q.put(fetch_batch(BS))
+        try:
+          q.put(fetch_batch(BS))
+        except Exception:
+          traceback.print_exc()
     q = Queue(16)
     for i in range(2):
       p = Process(target=loader, args=(q,))