Allowing 'F' mode for 1 channel FloatTensor (#1100)

* to_pil_image updates

* lint

* Update test_transforms.py

* Update test_transforms.py

test/test_transforms.py

@@ -528,6 +528,11 @@ class Tester(unittest.TestCase):
                 img = transform(img_data)
                 assert img.mode == mode
                 assert np.allclose(expected_output, to_tensor(img).numpy())
+        # 'F' mode for torch.FloatTensor
+        img_F_mode = transforms.ToPILImage(mode='F')(img_data_float)
+        assert img_F_mode.mode == 'F'
+        assert np.allclose(np.array(Image.fromarray(img_data_float.squeeze(0).numpy(), mode='F')),
+                           np.array(img_F_mode))
 
     def test_1_channel_ndarray_to_pil_image(self):
         img_data_float = torch.Tensor(4, 4, 1).uniform_().numpy()

torchvision/transforms/functional.py

@@ -135,7 +135,7 @@ def to_pil_image(pic, mode=None):
             pic = np.expand_dims(pic, 2)
 
     npimg = pic
-    if isinstance(pic, torch.FloatTensor):
+    if isinstance(pic, torch.FloatTensor) and mode != 'F':
         pic = pic.mul(255).byte()
     if isinstance(pic, torch.Tensor):
         npimg = np.transpose(pic.numpy(), (1, 2, 0))