Doc changes (#711)

* doc change

* doc changes

* lint_checks

* Update transforms.py

torchvision/transforms/functional.py

@@ -77,7 +77,7 @@ def to_tensor(pic):
         img = 255 * torch.from_numpy(np.array(pic, np.uint8, copy=False))
     else:
         img = torch.ByteTensor(torch.ByteStorage.from_buffer(pic.tobytes()))
-    # PIL image mode: L, P, I, F, RGB, YCbCr, RGBA, CMYK
+    # PIL image mode: L, LA, P, I, F, RGB, YCbCr, RGBA, CMYK
     if pic.mode == 'YCbCr':
         nchannel = 3
     elif pic.mode == 'I;16':

torchvision/transforms/transforms.py

@@ -73,7 +73,11 @@ class ToTensor(object):
     """Convert a ``PIL Image`` or ``numpy.ndarray`` to tensor.
 
     Converts a PIL Image or numpy.ndarray (H x W x C) in the range
-    [0, 255] to a torch.FloatTensor of shape (C x H x W) in the range [0.0, 1.0].
+    [0, 255] to a torch.FloatTensor of shape (C x H x W) in the range [0.0, 1.0]
+    if the PIL Image belongs to one of the modes (L, LA, P, I, F, RGB, YCbCr, RGBA, CMYK, 1)
+    or if the numpy.ndarray has dtype = np.uint8
+
+    In the other cases, tensors are returned without scaling.
     """
 
     def __call__(self, pic):