Document that datasets support pathlib.Path (#8321)

Co-authored-by: Philip Meier <github.pmeier@posteo.de>

torchvision/datasets/svhn.py

 import os.path
-from typing import Any, Callable, Optional, Tuple
+from pathlib import Path
+from typing import Any, Callable, Optional, Tuple, Union
 
 import numpy as np
 from PIL import Image
@@ -19,7 +20,7 @@ class SVHN(VisionDataset):
         This class needs `scipy <https://docs.scipy.org/doc/>`_ to load data from `.mat` format.
 
     Args:
-        root (string): Root directory of the dataset where the data is stored.
+        root (str or ``pathlib.Path``): Root directory of the dataset where the data is stored.
         split (string): One of {'train', 'test', 'extra'}.
             Accordingly dataset is selected. 'extra' is Extra training set.
         transform (callable, optional): A function/transform that takes in a PIL image
@@ -52,7 +53,7 @@ class SVHN(VisionDataset):
 
     def __init__(
         self,
-        root: str,
+        root: Union[str, Path],
         split: str = "train",
         transform: Optional[Callable] = None,
         target_transform: Optional[Callable] = None,

torchvision/datasets/ucf101.py

 import os
-from typing import Any, Callable, Dict, List, Optional, Tuple
+from pathlib import Path
+from typing import Any, Callable, Dict, List, Optional, Tuple, Union
 
 from torch import Tensor
 
@@ -28,7 +29,7 @@ class UCF101(VisionDataset):
     Internally, it uses a VideoClips object to handle clip creation.
 
     Args:
-        root (string): Root directory of the UCF101 Dataset.
+        root (str or ``pathlib.Path``): Root directory of the UCF101 Dataset.
         annotation_path (str): path to the folder containing the split files;
             see docstring above for download instructions of these files
         frames_per_clip (int): number of frames in a clip.
@@ -52,7 +53,7 @@ class UCF101(VisionDataset):
 
     def __init__(
         self,
-        root: str,
+        root: Union[str, Path],
         annotation_path: str,
         frames_per_clip: int,
         step_between_clips: int = 1,

torchvision/datasets/usps.py

 import os
-from typing import Any, Callable, Optional, Tuple
+from pathlib import Path
+from typing import Any, Callable, Optional, Tuple, Union
 
 import numpy as np
 from PIL import Image
@@ -15,7 +16,7 @@ class USPS(VisionDataset):
     and make pixel values in ``[0, 255]``.
 
     Args:
-        root (string): Root directory of dataset to store``USPS`` data files.
+        root (str or ``pathlib.Path``): Root directory of dataset to store``USPS`` data files.
         train (bool, optional): If True, creates dataset from ``usps.bz2``,
             otherwise from ``usps.t.bz2``.
         transform (callable, optional): A function/transform that takes in a PIL image
@@ -43,7 +44,7 @@ class USPS(VisionDataset):
 
     def __init__(
         self,
-        root: str,
+        root: Union[str, Path],
         train: bool = True,
         transform: Optional[Callable] = None,
         target_transform: Optional[Callable] = None,

torchvision/datasets/vision.py

 import os
-from typing import Any, Callable, List, Optional, Tuple
+from pathlib import Path
+from typing import Any, Callable, List, Optional, Tuple, Union
 
 import torch.utils.data as data
 
@@ -29,7 +30,7 @@ class VisionDataset(data.Dataset):
 
     def __init__(
         self,
-        root: str = None,  # type: ignore[assignment]
+        root: Union[str, Path] = None,  # type: ignore[assignment]
         transforms: Optional[Callable] = None,
         transform: Optional[Callable] = None,
         target_transform: Optional[Callable] = None,

torchvision/datasets/voc.py

 import collections
 import os
+from pathlib import Path
+from typing import Any, Callable, Dict, List, Optional, Tuple, Union
 from xml.etree.ElementTree import Element as ET_Element
 
-from .vision import VisionDataset
-
 try:
     from defusedxml.ElementTree import parse as ET_parse
 except ImportError:
     from xml.etree.ElementTree import parse as ET_parse
-from typing import Any, Callable, Dict, List, Optional, Tuple
 
 from PIL import Image
 
 from .utils import download_and_extract_archive, verify_str_arg
+from .vision import VisionDataset
 
 DATASET_YEAR_DICT = {
     "2012": {
@@ -67,7 +67,7 @@ class _VOCBase(VisionDataset):
 
     def __init__(
         self,
-        root: str,
+        root: Union[str, Path],
         year: str = "2012",
         image_set: str = "train",
         download: bool = False,
@@ -121,7 +121,7 @@ class VOCSegmentation(_VOCBase):
     """`Pascal VOC <http://host.robots.ox.ac.uk/pascal/VOC/>`_ Segmentation Dataset.
 
     Args:
-        root (string): Root directory of the VOC Dataset.
+        root (str or ``pathlib.Path``): Root directory of the VOC Dataset.
         year (string, optional): The dataset year, supports years ``"2007"`` to ``"2012"``.
         image_set (string, optional): Select the image_set to use, ``"train"``, ``"trainval"`` or ``"val"``. If
             ``year=="2007"``, can also be ``"test"``.
@@ -165,7 +165,7 @@ class VOCDetection(_VOCBase):
     """`Pascal VOC <http://host.robots.ox.ac.uk/pascal/VOC/>`_ Detection Dataset.
 
     Args:
-        root (string): Root directory of the VOC Dataset.
+        root (str or ``pathlib.Path``): Root directory of the VOC Dataset.
         year (string, optional): The dataset year, supports years ``"2007"`` to ``"2012"``.
         image_set (string, optional): Select the image_set to use, ``"train"``, ``"trainval"`` or ``"val"``. If
             ``year=="2007"``, can also be ``"test"``.

torchvision/datasets/widerface.py

 import os
 from os.path import abspath, expanduser
+from pathlib import Path
+
 from typing import Any, Callable, Dict, List, Optional, Tuple, Union
 
 import torch
@@ -13,7 +15,7 @@ class WIDERFace(VisionDataset):
     """`WIDERFace <http://shuoyang1213.me/WIDERFACE/>`_ Dataset.
 
     Args:
-        root (string): Root directory where images and annotations are downloaded to.
+        root (str or ``pathlib.Path``): Root directory where images and annotations are downloaded to.
             Expects the following folder structure if download=False:
 
             .. code::
@@ -55,7 +57,7 @@ class WIDERFace(VisionDataset):
 
     def __init__(
         self,
-        root: str,
+        root: Union[str, Path],
         split: str = "train",
         transform: Optional[Callable] = None,
         target_transform: Optional[Callable] = None,