Use joint transform in Cityscapes (#1024)

* Use joint transform in Cityscapes

* Add transforms doc

torchvision/datasets/cityscapes.py

@@ -21,6 +21,8 @@ class Cityscapes(VisionDataset):
             and returns a transformed version. E.g, ``transforms.RandomCrop``
         target_transform (callable, optional): A function/transform that takes in the
             target and transforms it.
+        transforms (callable, optional): A function/transform that takes input sample and its target as entry
+            and returns a transformed version.
 
     Examples:
 
@@ -95,8 +97,8 @@ class Cityscapes(VisionDataset):
     ]
 
     def __init__(self, root, split='train', mode='fine', target_type='instance',
-                 transform=None, target_transform=None):
-        super(Cityscapes, self).__init__(root)
+                 transform=None, target_transform=None, transforms=None):
+        super(Cityscapes, self).__init__(root, transforms, transform, target_transform)
         self.transform = transform
         self.target_transform = target_transform
         self.mode = 'gtFine' if mode == 'fine' else 'gtCoarse'
@@ -163,11 +165,8 @@ class Cityscapes(VisionDataset):
 
         target = tuple(targets) if len(targets) > 1 else targets[0]
 
-        if self.transform:
-            image = self.transform(image)
-
-        if self.target_transform:
-            target = self.target_transform(target)
+        if self.transforms is not None:
+            image, target = self.transforms(image, target)
 
         return image, target