fix some typo errors (#48185)

* fix some typo errors

function rotate: format errors.
function to_grayscale: missing one sentences to explain num_output_chanels

* Update functional.py

* test=docs_preview

* Update functional.py

* Update functional.py

* Update functional.py

* Update functional.py

* Update functional.py

Co-authored-by: Ligoml <39876205+Ligoml@users.noreply.github.com>

Author: enkilee

python/paddle/vision/transforms/functional.py

@@ -269,18 +269,18 @@ def center_crop(img, output_size):
         PIL.Image or np.array: Cropped image.
 
     Examples:
-    .. code-block:: python
+        .. code-block:: python
 
-        import numpy as np
-        from PIL import Image
-        from paddle.vision.transforms import functional as F
+            import numpy as np
+            from PIL import Image
+            from paddle.vision.transforms import functional as F
 
-        fake_img = (np.random.rand(256, 300, 3) * 255.).astype('uint8')
+            fake_img = (np.random.rand(256, 300, 3) * 255.).astype('uint8')
 
-        fake_img = Image.fromarray(fake_img)
+            fake_img = Image.fromarray(fake_img)
 
-        cropped_img = F.center_crop(fake_img, (150, 100))
-        print(cropped_img.size)
+            cropped_img = F.center_crop(fake_img, (150, 100))
+            print(cropped_img.size)
     """
     if not (
         _is_pil_image(img) or _is_numpy_image(img) or _is_tensor_image(img)
@@ -764,7 +764,7 @@ def rotate(
             Origin is the upper left corner.
             Default is the center of the image.
         fill (3-list|3-tuple or int): RGB pixel fill value for area outside the rotated image.
-            If int, it is used for all channels respectively.
+            If int, it is used for all channels respectively. Default value is 0.
 
 
     Returns:
@@ -919,7 +919,8 @@ def to_grayscale(img, num_output_channels=1):
 
     Args:
         img (PIL.Image|np.array): Image to be converted to grayscale.
-
+        num_output_channels (int, optional): The number of channels for the output
+            image. Single channel. Default: 1.
     Returns:
         PIL.Image or np.array: Grayscale version of the image.
             if num_output_channels = 1 : returned image is single channel