Doc, Test Fixes in Normalize (#1063)

* updates on normalize

* test fixes

* Update test_transforms.py

test/test_transforms.py

@@ -820,6 +820,11 @@ def samples_from_standard_normal(tensor):
         # Checking if Normalize can be printed as string
         transforms.Normalize(mean, std).__repr__()
 
+        # Checking the optional in-place behaviour
+        tensor = torch.rand((1, 16, 16))
+        tensor_inplace = transforms.Normalize((0.5,), (0.5,), inplace=True)(tensor)
+        assert torch.equal(tensor, tensor_inplace)
+
     def test_normalize_different_dtype(self):
         for dtype1 in [torch.float32, torch.float64]:
             img = torch.rand(3, 10, 10, dtype=dtype1)

torchvision/transforms/functional.py

@@ -200,6 +200,7 @@ def normalize(tensor, mean, std, inplace=False):
         tensor (Tensor): Tensor image of size (C, H, W) to be normalized.
         mean (sequence): Sequence of means for each channel.
         std (sequence): Sequence of standard deviations for each channel.
+        inplace(bool,optional): Bool to make this operation inplace.
 
     Returns:
         Tensor: Normalized Tensor image.

torchvision/transforms/transforms.py

@@ -146,6 +146,8 @@ class Normalize(object):
     Args:
         mean (sequence): Sequence of means for each channel.
         std (sequence): Sequence of standard deviations for each channel.
+        inplace(bool,optional): Bool to make this operation in-place.
+
     """
 
     def __init__(self, mean, std, inplace=False):