Cleanup prototype dataset implementation

test/builtin_dataset_mocks.py

@@ -68,7 +68,7 @@ def prepare(self, home, config):
 
         mock_info = self._parse_mock_info(self.mock_data_fn(root, config))
 
-        with unittest.mock.patch.object(datasets.utils.Dataset2, "__init__"):
+        with unittest.mock.patch.object(datasets.utils.Dataset, "__init__"):
             required_file_names = {
                 resource.file_name for resource in datasets.load(self.name, root=root, **config)._resources()
             }

test/test_prototype_builtin_datasets.py

@@ -59,7 +59,7 @@ def test_smoke(self, test_home, dataset_mock, config):
 
         dataset = datasets.load(dataset_mock.name, **config)
 
-        if not isinstance(dataset, datasets.utils.Dataset2):
+        if not isinstance(dataset, datasets.utils.Dataset):
             raise AssertionError(f"Loading the dataset should return an Dataset, but got {type(dataset)} instead.")
 
     @parametrize_dataset_mocks(DATASET_MOCKS)

test/test_prototype_datasets_utils.py

@@ -5,7 +5,7 @@
 import torch
 from datasets_utils import make_fake_flo_file
 from torchvision.datasets._optical_flow import _read_flo as read_flo_ref
-from torchvision.prototype.datasets.utils import HttpResource, GDriveResource
+from torchvision.prototype.datasets.utils import HttpResource, GDriveResource, Dataset
 from torchvision.prototype.datasets.utils._internal import read_flo, fromfile
 
 
@@ -101,3 +101,21 @@ def preprocess_sentinel(path):
         assert redirected_resource.file_name == file_name
         assert redirected_resource.sha256 == sha256_sentinel
         assert redirected_resource._preprocess is preprocess_sentinel
+
+
+def test_missing_dependency_error():
+    class DummyDataset(Dataset):
+        def __init__(self):
+            super().__init__(root="root", dependencies=("fake_dependency",))
+
+        def _resources(self):
+            pass
+
+        def _datapipe(self, resource_dps):
+            pass
+
+        def __len__(self):
+            pass
+
+    with pytest.raises(ModuleNotFoundError, match="depends on the third-party package 'fake_dependency'"):
+        DummyDataset()

torchvision/prototype/datasets/_api.py

@@ -2,12 +2,12 @@
 from typing import Any, Dict, List, Callable, Type, Optional, Union, TypeVar
 
 from torchvision.prototype.datasets import home
-from torchvision.prototype.datasets.utils import Dataset2
+from torchvision.prototype.datasets.utils import Dataset
 from torchvision.prototype.utils._internal import add_suggestion
 
 
 T = TypeVar("T")
-D = TypeVar("D", bound=Type[Dataset2])
+D = TypeVar("D", bound=Type[Dataset])
 
 BUILTIN_INFOS: Dict[str, Dict[str, Any]] = {}
 
@@ -56,7 +56,7 @@ def info(name: str) -> Dict[str, Any]:
     return find(BUILTIN_INFOS, name)
 
 
-def load(name: str, *, root: Optional[Union[str, pathlib.Path]] = None, **config: Any) -> Dataset2:
+def load(name: str, *, root: Optional[Union[str, pathlib.Path]] = None, **config: Any) -> Dataset:
     dataset_cls = find(BUILTIN_DATASETS, name)
 
     if root is None:

torchvision/prototype/datasets/_builtin/caltech.py

@@ -9,29 +9,26 @@
     Filter,
     IterKeyZipper,
 )
-from torchvision.prototype.datasets.utils import Dataset2, DatasetInfo, HttpResource, OnlineResource
+from torchvision.prototype.datasets.utils import Dataset, HttpResource, OnlineResource
 from torchvision.prototype.datasets.utils._internal import (
     INFINITE_BUFFER_SIZE,
     read_mat,
     hint_sharding,
     hint_shuffling,
-    BUILTIN_DIR,
+    read_categories_file,
 )
 from torchvision.prototype.features import Label, BoundingBox, _Feature, EncodedImage
 
 from .._api import register_dataset, register_info
 
 
-CALTECH101_CATEGORIES, *_ = zip(*DatasetInfo.read_categories_file(BUILTIN_DIR / "caltech101.categories"))
-
-
 @register_info("caltech101")
 def _caltech101_info() -> Dict[str, Any]:
-    return dict(categories=CALTECH101_CATEGORIES)
+    return dict(categories=read_categories_file("caltech101"))
 
 
 @register_dataset("caltech101")
-class Caltech101(Dataset2):
+class Caltech101(Dataset):
     """
     - **homepage**: http://www.vision.caltech.edu/Image_Datasets/Caltech101
     - **dependencies**:
@@ -152,16 +149,13 @@ def _generate_categories(self) -> List[str]:
         return sorted({pathlib.Path(path).parent.name for path, _ in dp})
 
 
-CALTECH256_CATEGORIES, *_ = zip(*DatasetInfo.read_categories_file(BUILTIN_DIR / "caltech256.categories"))
-
-
 @register_info("caltech256")
 def _caltech256_info() -> Dict[str, Any]:
-    return dict(categories=CALTECH256_CATEGORIES)
+    return dict(categories=read_categories_file("caltech256"))
 
 
 @register_dataset("caltech256")
-class Caltech256(Dataset2):
+class Caltech256(Dataset):
     """
     - **homepage**: http://www.vision.caltech.edu/Image_Datasets/Caltech256
     """

torchvision/prototype/datasets/_builtin/celeba.py

@@ -10,7 +10,7 @@
     IterKeyZipper,
 )
 from torchvision.prototype.datasets.utils import (
-    Dataset2,
+    Dataset,
     GDriveResource,
     OnlineResource,
 )
@@ -68,7 +68,7 @@ def _info() -> Dict[str, Any]:
 
 
 @register_dataset(NAME)
-class CelebA(Dataset2):
+class CelebA(Dataset):
     """
     - **homepage**: https://mmlab.ie.cuhk.edu.hk/projects/CelebA.html
     """