Replace torchvision.datasets.utils with functionality from torchdata

torchvision/prototype/datasets/_builtin/__init__.py

@@ -1,22 +1,26 @@
 from .caltech import Caltech101, Caltech256
-from .celeba import CelebA
+
+# from .celeba import CelebA
 from .cifar import Cifar10, Cifar100
-from .clevr import CLEVR
-from .coco import Coco
-from .country211 import Country211
-from .cub200 import CUB200
-from .dtd import DTD
-from .eurosat import EuroSAT
+
+# from .clevr import CLEVR
+# from .coco import Coco
+# from .country211 import Country211
+# from .cub200 import CUB200
+# from .dtd import DTD
+# from .eurosat import EuroSAT
 from .fer2013 import FER2013
-from .food101 import Food101
-from .gtsrb import GTSRB
+
+# from .food101 import Food101
+# from .gtsrb import GTSRB
 from .imagenet import ImageNet
-from .mnist import MNIST, FashionMNIST, KMNIST, EMNIST, QMNIST
-from .oxford_iiit_pet import OxfordIIITPet
-from .pcam import PCAM
-from .sbd import SBD
-from .semeion import SEMEION
-from .stanford_cars import StanfordCars
-from .svhn import SVHN
-from .usps import USPS
-from .voc import VOC
+
+# from .mnist import MNIST, FashionMNIST, KMNIST, EMNIST, QMNIST
+# from .oxford_iiit_pet import OxfordIIITPet
+# from .pcam import PCAM
+# from .sbd import SBD
+# from .semeion import SEMEION
+# from .stanford_cars import StanfordCars
+# from .svhn import SVHN
+# from .usps import USPS
+# from .voc import VOC

torchvision/prototype/datasets/_builtin/caltech.py

@@ -9,7 +9,7 @@
     Filter,
     IterKeyZipper,
 )
-from torchvision.prototype.datasets.utils import Dataset, GDriveResource, OnlineResource
+from torchvision.prototype.datasets.utils import Dataset, OnlineResource
 from torchvision.prototype.datasets.utils._internal import (
     INFINITE_BUFFER_SIZE,
     read_mat,
@@ -49,13 +49,13 @@ def __init__(
         )
 
     def _resources(self) -> List[OnlineResource]:
-        images = GDriveResource(
+        images = OnlineResource.from_gdrive(
             "137RyRjvTBkBiIfeYBNZBtViDHQ6_Ewsp",
             file_name="101_ObjectCategories.tar.gz",
             sha256="af6ece2f339791ca20f855943d8b55dd60892c0a25105fcd631ee3d6430f9926",
             preprocess="decompress",
         )
-        anns = GDriveResource(
+        anns = OnlineResource.from_gdrive(
             "175kQy3UsZ0wUEHZjqkUDdNVssr7bgh_m",
             file_name="Annotations.tar",
             sha256="1717f4e10aa837b05956e3f4c94456527b143eec0d95e935028b30aff40663d8",
@@ -173,7 +173,7 @@ def __init__(
 
     def _resources(self) -> List[OnlineResource]:
         return [
-            GDriveResource(
+            OnlineResource.from_gdrive(
                 "1r6o0pSROcV1_VwT4oSjA2FBUSCWGuxLK",
                 file_name="256_ObjectCategories.tar",
                 sha256="08ff01b03c65566014ae88eb0490dbe4419fc7ac4de726ee1163e39fd809543e",

torchvision/prototype/datasets/_builtin/cifar.py

@@ -10,7 +10,7 @@
     Filter,
     Mapper,
 )
-from torchvision.prototype.datasets.utils import Dataset, HttpResource, OnlineResource
+from torchvision.prototype.datasets.utils import Dataset, OnlineResource
 from torchvision.prototype.datasets.utils._internal import (
     hint_shuffling,
     path_comparator,
@@ -58,7 +58,7 @@ def _is_data_file(self, data: Tuple[str, BinaryIO]) -> Optional[int]:
 
     def _resources(self) -> List[OnlineResource]:
         return [
-            HttpResource(
+            OnlineResource.from_http(
                 f"https://www.cs.toronto.edu/~kriz/{self._FILE_NAME}",
                 sha256=self._SHA256,
             )

torchvision/prototype/datasets/_builtin/fer2013.py

@@ -3,11 +3,7 @@
 
 import torch
 from torchdata.datapipes.iter import IterDataPipe, Mapper, CSVDictParser
-from torchvision.prototype.datasets.utils import (
-    Dataset,
-    OnlineResource,
-    KaggleDownloadResource,
-)
+from torchvision.prototype.datasets.utils import Dataset, ManualDownloadResource
 from torchvision.prototype.datasets.utils._internal import (
     hint_sharding,
     hint_shuffling,
@@ -43,8 +39,8 @@ def __init__(
         "test": "dec8dfe8021e30cd6704b85ec813042b4a5d99d81cb55e023291a94104f575c3",
     }
 
-    def _resources(self) -> List[OnlineResource]:
-        archive = KaggleDownloadResource(
+    def _resources(self) -> List[ManualDownloadResource]:
+        archive = ManualDownloadResource.from_kaggle(
             "https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge",
             file_name=f"{self._split}.csv.zip",
             sha256=self._CHECKSUMS[self._split],

torchvision/prototype/datasets/_builtin/imagenet.py

@@ -14,11 +14,7 @@
     TarArchiveLoader,
     Enumerator,
 )
-from torchvision.prototype.datasets.utils import (
-    OnlineResource,
-    ManualDownloadResource,
-    Dataset,
-)
+from torchvision.prototype.datasets.utils import ManualDownloadResource, Dataset
 from torchvision.prototype.datasets.utils._internal import (
     INFINITE_BUFFER_SIZE,
     getitem,
@@ -41,11 +37,6 @@ def _info() -> Dict[str, Any]:
     return dict(categories=categories, wnids=wnids)
 
 
-class ImageNetResource(ManualDownloadResource):
-    def __init__(self, **kwargs: Any) -> None:
-        super().__init__("Register on https://image-net.org/ and follow the instructions there.", **kwargs)
-
-
 class ImageNetDemux(enum.IntEnum):
     META = 0
     LABEL = 1
@@ -80,16 +71,22 @@ def __init__(
         "test_v10102019": "9cf7f8249639510f17d3d8a0deb47cd22a435886ba8e29e2b3223e65a4079eb4",
     }
 
-    def _resources(self) -> List[OnlineResource]:
-        name = "test_v10102019" if self._split == "test" else self._split
-        images = ImageNetResource(
-            file_name=f"ILSVRC2012_img_{name}.tar",
-            sha256=self._IMAGES_CHECKSUMS[name],
+    def _imagenet_resource(self, *, file_name: str, sha256: str) -> ManualDownloadResource:
+        return ManualDownloadResource(
+            "https://image-net.org/",
+            instructions="Register on https://image-net.org/ and follow the instructions there.",
+            file_name=file_name,
+            sha256=sha256,
         )
-        resources: List[OnlineResource] = [images]
+
+    def _resources(self) -> List[ManualDownloadResource]:
+        name = "test_v10102019" if self._split == "test" else self._split
+        images = self._imagenet_resource(file_name=f"ILSVRC2012_img_{name}.tar", sha256=self._IMAGES_CHECKSUMS[name])
+
+        resources = [images]
 
         if self._split == "val":
-            devkit = ImageNetResource(
+            devkit = self._imagenet_resource(
                 file_name="ILSVRC2012_devkit_t12.tar.gz",
                 sha256="b59243268c0d266621fd587d2018f69e906fb22875aca0e295b48cafaa927953",
             )

torchvision/prototype/datasets/utils/__init__.py

@@ -1,3 +1,3 @@
 from . import _internal  # usort: skip
 from ._dataset import Dataset
-from ._resource import OnlineResource, HttpResource, GDriveResource, ManualDownloadResource, KaggleDownloadResource
+from ._resource import OnlineResource, ManualDownloadResource

torchvision/prototype/datasets/utils/_dataset.py

@@ -42,7 +42,7 @@ def __iter__(self) -> Iterator[Dict[str, Any]]:
         yield from self._dp
 
     @abc.abstractmethod
-    def _resources(self) -> List[OnlineResource]:
+    def _resources(self) -> Sequence[OnlineResource]:
         pass
 
     @abc.abstractmethod