diff --git a/torchvision/datasets/lsun.py b/torchvision/datasets/lsun.py
index e165b957c67..731461e8a8d 100644
--- a/torchvision/datasets/lsun.py
+++ b/torchvision/datasets/lsun.py
@@ -12,22 +12,23 @@
 
 
 class LSUNClass(data.Dataset):
-    def __init__(self, db_path, transform=None, target_transform=None):
+    def __init__(self, root, transform=None, target_transform=None):
         import lmdb
-        self.db_path = db_path
-        self.env = lmdb.open(db_path, max_readers=1, readonly=True, lock=False,
+        self.root = os.path.expanduser(root)
+        self.transform = transform
+        self.target_transform = target_transform
+
+        self.env = lmdb.open(root, max_readers=1, readonly=True, lock=False,
                              readahead=False, meminit=False)
         with self.env.begin(write=False) as txn:
             self.length = txn.stat()['entries']
-        cache_file = '_cache_' + db_path.replace('/', '_')
+        cache_file = '_cache_' + root.replace('/', '_')
         if os.path.isfile(cache_file):
             self.keys = pickle.load(open(cache_file, "rb"))
         else:
             with self.env.begin(write=False) as txn:
                 self.keys = [key for key, _ in txn.cursor()]
             pickle.dump(self.keys, open(cache_file, "wb"))
-        self.transform = transform
-        self.target_transform = target_transform
 
     def __getitem__(self, index):
         img, target = None, None
@@ -60,7 +61,7 @@ class LSUN(data.Dataset):
     `LSUN <http://lsun.cs.princeton.edu>`_ dataset.
 
     Args:
-        db_path (string): Root directory for the database files.
+        root (string): Root directory for the database files.
         classes (string or list): One of {'train', 'val', 'test'} or a list of
             categories to load. e,g. ['bedroom_train', 'church_train'].
         transform (callable, optional): A function/transform that  takes in an PIL image
@@ -69,13 +70,16 @@ class LSUN(data.Dataset):
             target and transforms it.
     """
 
-    def __init__(self, db_path, classes='train',
+    def __init__(self, root, classes='train',
                  transform=None, target_transform=None):
         categories = ['bedroom', 'bridge', 'church_outdoor', 'classroom',
                       'conference_room', 'dining_room', 'kitchen',
                       'living_room', 'restaurant', 'tower']
         dset_opts = ['train', 'val', 'test']
-        self.db_path = db_path
+        self.root = os.path.expanduser(root)
+        self.transform = transform
+        self.target_transform = target_transform
+
         if type(classes) == str and classes in dset_opts:
             if classes == 'test':
                 classes = [classes]
@@ -102,7 +106,7 @@ def __init__(self, db_path, classes='train',
         self.dbs = []
         for c in self.classes:
             self.dbs.append(LSUNClass(
-                db_path=db_path + '/' + c + '_lmdb',
+                root=root + '/' + c + '_lmdb',
                 transform=transform))
 
         self.indices = []
@@ -112,7 +116,6 @@ def __init__(self, db_path, classes='train',
             self.indices.append(count)
 
         self.length = count
-        self.target_transform = target_transform
 
     def __getitem__(self, index):
         """
@@ -146,6 +149,7 @@ def __repr__(self):
         fmt_str = 'Dataset ' + self.__class__.__name__ + '\n'
         fmt_str += '    Number of datapoints: {}\n'.format(self.__len__())
         fmt_str += '    Root Location: {}\n'.format(self.root)
+        fmt_str += '    Classes: {}\n'.format(self.classes)
         tmp = '    Transforms (if any): '
         fmt_str += '{0}{1}\n'.format(tmp, self.transform.__repr__().replace('\n', '\n' + ' ' * len(tmp)))
         tmp = '    Target Transforms (if any): '