Fix fill parameter for PIL pad (#2515)

* fix fill parameter for PIL pad

* add test

* fix

* lint

test/test_transforms.py

@@ -390,6 +390,14 @@ class Tester(unittest.TestCase):
         with self.assertRaises(ValueError):
             transforms.Pad((1, 2, 3, 4, 5))
 
+    def test_pad_with_mode_F_images(self):
+        pad = 2
+        transform = transforms.Pad(pad)
+
+        img = Image.new("F", (10, 10))
+        padded_img = transform(img)
+        self.assertSequenceEqual(padded_img.size, [edge_size + 2 * pad for edge_size in img.size])
+
     def test_lambda(self):
         trans = transforms.Lambda(lambda x: x.add(10))
         x = torch.randn(10)

torchvision/transforms/functional_pil.py

@@ -261,19 +261,14 @@ def pad(img, padding, fill=0, padding_mode="constant"):
         raise ValueError("Padding mode should be either constant, edge, reflect or symmetric")
 
     if padding_mode == "constant":
-        if isinstance(fill, numbers.Number):
-            fill = (fill,) * len(img.getbands())
-        if len(fill) != len(img.getbands()):
-            raise ValueError("fill should have the same number of elements "
-                             "as the number of channels in the image "
-                             "({}), got {} instead".format(len(img.getbands()), len(fill)))
+        opts = _parse_fill(fill, img, "2.3.0", name="fill")
         if img.mode == "P":
             palette = img.getpalette()
-            image = ImageOps.expand(img, border=padding, fill=fill)
+            image = ImageOps.expand(img, border=padding, **opts)
             image.putpalette(palette)
             return image
 
-        return ImageOps.expand(img, border=padding, fill=fill)
+        return ImageOps.expand(img, border=padding, **opts)
     else:
         if isinstance(padding, int):
             pad_left = pad_right = pad_top = pad_bottom = padding
@@ -367,8 +362,8 @@ def resize(img, size, interpolation=Image.BILINEAR):
 
 
 @torch.jit.unused
-def _parse_fill(fill, img, min_pil_version):
-    """Helper function to get the fill color for rotate and perspective transforms.
+def _parse_fill(fill, img, min_pil_version, name="fillcolor"):
+    """Helper function to get the fill color for rotate, perspective transforms, and pad.
 
     Args:
         fill (n-tuple or int or float): Pixel fill value for area outside the transformed
@@ -377,6 +372,7 @@ def _parse_fill(fill, img, min_pil_version):
         img (PIL Image): Image to be filled.
         min_pil_version (str): The minimum PILLOW version for when the ``fillcolor`` option
             was first introduced in the calling function. (e.g. rotate->5.2.0, perspective->5.0.0)
+        name (str): Name of the ``fillcolor`` option in the output. Defaults to ``"fillcolor"``.
 
     Returns:
         dict: kwarg for ``fillcolor``
@@ -401,7 +397,7 @@ def _parse_fill(fill, img, min_pil_version):
                "bands of the image ({} != {})")
         raise ValueError(msg.format(len(fill), num_bands))
 
-    return {"fillcolor": fill}
+    return {name: fill}
 
 
 @torch.jit.unused