revert enum usage for single use constants

Author: pmeier

torchvision/prototype/datasets/_builtin/clevr.py

@@ -1,4 +1,3 @@
-import enum
 import functools
 import io
 import pathlib
@@ -25,11 +24,6 @@
 from torchvision.prototype.features import Label
 
 
-class CLEVRDemux(enum.IntEnum):
-    IMAGES = 0
-    SCENES = 1
-
-
 class CLEVR(Dataset):
     def _make_info(self) -> DatasetInfo:
         return DatasetInfo(
@@ -49,9 +43,9 @@ def resources(self, config: DatasetConfig) -> List[OnlineResource]:
     def _classify_archive(self, data: Tuple[str, Any]) -> Optional[int]:
         path = pathlib.Path(data[0])
         if path.parents[1].name == "images":
-            return CLEVRDemux.IMAGES
+            return 0
         elif path.parent.name == "scenes":
-            return CLEVRDemux.SCENES
+            return 1
         else:
             return None
 

torchvision/prototype/datasets/_builtin/coco.py

@@ -1,4 +1,3 @@
-import enum
 import functools
 import io
 import pathlib
@@ -38,11 +37,6 @@
 from torchvision.prototype.utils._internal import FrozenMapping
 
 
-class CocoDemux(enum.IntEnum):
-    IMAGES_META = 0
-    ANNS_META = 1
-
-
 class Coco(Dataset):
     def _make_info(self) -> DatasetInfo:
         name = "coco"
@@ -150,9 +144,9 @@ def _filter_meta_files(self, data: Tuple[str, Any], *, split: str, year: str, an
     def _classify_meta(self, data: Tuple[str, Any]) -> Optional[int]:
         key, _ = data
         if key == "images":
-            return CocoDemux.IMAGES_META
+            return 0
         elif key == "annotations":
-            return CocoDemux.ANNS_META
+            return 1
         else:
             return None
 

torchvision/prototype/datasets/_builtin/mnist.py

@@ -1,5 +1,4 @@
 import abc
-import enum
 import functools
 import io
 import operator
@@ -233,11 +232,6 @@ def _make_info(self) -> DatasetInfo:
     }
 
 
-class EMNISTDemux(enum.IntEnum):
-    IMAGES = 0
-    LABELS = 1
-
-
 class EMNIST(_MNISTBase):
     def _make_info(self) -> DatasetInfo:
         return DatasetInfo(
@@ -279,9 +273,9 @@ def _classify_archive(self, data: Tuple[str, Any], *, config: DatasetConfig) ->
         path = pathlib.Path(data[0])
         (images_file, _), (labels_file, _) = self._files_and_checksums(config)
         if path.name == images_file:
-            return EMNISTDemux.IMAGES
+            return 0
         elif path.name == labels_file:
-            return EMNISTDemux.LABELS
+            return 1
         else:
             return None
 
@@ -326,7 +320,6 @@ def _make_datapipe(
         decoder: Optional[Callable[[io.IOBase], torch.Tensor]],
     ) -> IterDataPipe[Dict[str, Any]]:
         archive_dp = resource_dps[0]
-
         images_dp, labels_dp = Demultiplexer(
             archive_dp,
             2,

torchvision/prototype/datasets/_builtin/sbd.py

@@ -1,4 +1,3 @@
-import enum
 import functools
 import io
 import pathlib
@@ -34,12 +33,6 @@
 )
 
 
-class SBDDemux(enum.IntEnum):
-    SPLIT = 0
-    IMAGES = 1
-    ANNS = 2
-
-
 class SBD(Dataset):
     def _make_info(self) -> DatasetInfo:
         return DatasetInfo(
@@ -70,12 +63,12 @@ def _classify_archive(self, data: Tuple[str, Any]) -> Optional[int]:
         parent, grandparent, *_ = path.parents
 
         if parent.name == "dataset":
-            return SBDDemux.SPLIT
+            return 0
         elif grandparent.name == "dataset":
             if parent.name == "img":
-                return SBDDemux.IMAGES
+                return 1
             elif parent.name == "cls":
-                return SBDDemux.ANNS
+                return 2
             else:
                 return None
         else:

torchvision/prototype/datasets/_builtin/voc.py

@@ -1,4 +1,3 @@
-import enum
 import functools
 import io
 import pathlib
@@ -32,13 +31,6 @@
     hint_shuffling,
 )
 
-
-class VOCDemux(enum.IntEnum):
-    SPLIT = 0
-    IMAGES = 1
-    ANNS = 2
-
-
 HERE = pathlib.Path(__file__).parent
 
 
@@ -83,11 +75,11 @@ def _is_in_folder(self, data: Tuple[str, Any], *, name: str, depth: int = 1) ->
 
     def _classify_archive(self, data: Tuple[str, Any], *, config: DatasetConfig) -> Optional[int]:
         if self._is_in_folder(data, name="ImageSets", depth=2):
-            return VOCDemux.SPLIT
+            return 0
         elif self._is_in_folder(data, name="JPEGImages"):
-            return VOCDemux.IMAGES
+            return 1
         elif self._is_in_folder(data, name=self._ANNS_FOLDER[config.task]):
-            return VOCDemux.ANNS
+            return 2
         else:
             return None