Refactor the `get_weights` API (#5006)

* Change the `default` weights mechanism to sue Enum aliases.

* Change `get_weights` to work with full Enum names and make it public.

* Applying improvements from code review.

torchvision/prototype/models/mobilenetv2.py

@@ -25,8 +25,8 @@ class MobileNet_V2_Weights(WeightsEnum):
             "acc@1": 71.878,
             "acc@5": 90.286,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 def mobilenet_v2(weights: Optional[MobileNet_V2_Weights] = None, progress: bool = True, **kwargs: Any) -> MobileNetV2:

torchvision/prototype/models/mobilenetv3.py

@@ -54,7 +54,6 @@ class MobileNet_V3_Large_Weights(WeightsEnum):
             "acc@1": 74.042,
             "acc@5": 91.340,
         },
-        default=False,
     )
     ImageNet1K_V2 = Weights(
         url="https://download.pytorch.org/models/mobilenet_v3_large-5c1a4163.pth",
@@ -65,8 +64,8 @@ class MobileNet_V3_Large_Weights(WeightsEnum):
             "acc@1": 75.274,
             "acc@5": 92.566,
         },
-        default=True,
     )
+    default = ImageNet1K_V2
 
 
 class MobileNet_V3_Small_Weights(WeightsEnum):
@@ -79,8 +78,8 @@ class MobileNet_V3_Small_Weights(WeightsEnum):
             "acc@1": 67.668,
             "acc@5": 87.402,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 def mobilenet_v3_large(

torchvision/prototype/models/quantization/googlenet.py

@@ -38,8 +38,8 @@ class GoogLeNet_QuantizedWeights(WeightsEnum):
             "acc@1": 69.826,
             "acc@5": 89.404,
         },
-        default=True,
     )
+    default = ImageNet1K_FBGEMM_V1
 
 
 def googlenet(

torchvision/prototype/models/quantization/inception.py

@@ -37,8 +37,8 @@ class Inception_V3_QuantizedWeights(WeightsEnum):
             "acc@1": 77.176,
             "acc@5": 93.354,
         },
-        default=True,
     )
+    default = ImageNet1K_FBGEMM_V1
 
 
 def inception_v3(

torchvision/prototype/models/quantization/mobilenetv2.py

@@ -38,8 +38,8 @@ class MobileNet_V2_QuantizedWeights(WeightsEnum):
             "acc@1": 71.658,
             "acc@5": 90.150,
         },
-        default=True,
     )
+    default = ImageNet1K_QNNPACK_V1
 
 
 def mobilenet_v2(

torchvision/prototype/models/quantization/mobilenetv3.py

@@ -71,8 +71,8 @@ class MobileNet_V3_Large_QuantizedWeights(WeightsEnum):
             "acc@1": 73.004,
             "acc@5": 90.858,
         },
-        default=True,
     )
+    default = ImageNet1K_QNNPACK_V1
 
 
 def mobilenet_v3_large(

torchvision/prototype/models/quantization/resnet.py

@@ -73,8 +73,8 @@ class ResNet18_QuantizedWeights(WeightsEnum):
             "acc@1": 69.494,
             "acc@5": 88.882,
         },
-        default=True,
     )
+    default = ImageNet1K_FBGEMM_V1
 
 
 class ResNet50_QuantizedWeights(WeightsEnum):
@@ -87,7 +87,6 @@ class ResNet50_QuantizedWeights(WeightsEnum):
             "acc@1": 75.920,
             "acc@5": 92.814,
         },
-        default=False,
     )
     ImageNet1K_FBGEMM_V2 = Weights(
         url="https://download.pytorch.org/models/quantized/resnet50_fbgemm-23753f79.pth",
@@ -98,8 +97,8 @@ class ResNet50_QuantizedWeights(WeightsEnum):
             "acc@1": 80.282,
             "acc@5": 94.976,
         },
-        default=True,
     )
+    default = ImageNet1K_FBGEMM_V2
 
 
 class ResNeXt101_32X8D_QuantizedWeights(WeightsEnum):
@@ -112,7 +111,6 @@ class ResNeXt101_32X8D_QuantizedWeights(WeightsEnum):
             "acc@1": 78.986,
             "acc@5": 94.480,
         },
-        default=False,
     )
     ImageNet1K_FBGEMM_V2 = Weights(
         url="https://download.pytorch.org/models/quantized/resnext101_32x8_fbgemm-ee16d00c.pth",
@@ -123,8 +121,8 @@ class ResNeXt101_32X8D_QuantizedWeights(WeightsEnum):
             "acc@1": 82.574,
             "acc@5": 96.132,
         },
-        default=True,
     )
+    default = ImageNet1K_FBGEMM_V2
 
 
 def resnet18(

torchvision/prototype/models/quantization/shufflenetv2.py

@@ -69,8 +69,8 @@ class ShuffleNet_V2_X0_5_QuantizedWeights(WeightsEnum):
             "acc@1": 57.972,
             "acc@5": 79.780,
         },
-        default=True,
     )
+    default = ImageNet1K_FBGEMM_V1
 
 
 class ShuffleNet_V2_X1_0_QuantizedWeights(WeightsEnum):
@@ -83,8 +83,8 @@ class ShuffleNet_V2_X1_0_QuantizedWeights(WeightsEnum):
             "acc@1": 68.360,
             "acc@5": 87.582,
         },
-        default=True,
     )
+    default = ImageNet1K_FBGEMM_V1
 
 
 def shufflenet_v2_x0_5(

torchvision/prototype/models/regnet.py

@@ -74,8 +74,8 @@ class RegNet_Y_400MF_Weights(WeightsEnum):
             "acc@1": 74.046,
             "acc@5": 91.716,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class RegNet_Y_800MF_Weights(WeightsEnum):
@@ -88,8 +88,8 @@ class RegNet_Y_800MF_Weights(WeightsEnum):
             "acc@1": 76.420,
             "acc@5": 93.136,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class RegNet_Y_1_6GF_Weights(WeightsEnum):
@@ -102,8 +102,8 @@ class RegNet_Y_1_6GF_Weights(WeightsEnum):
             "acc@1": 77.950,
             "acc@5": 93.966,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class RegNet_Y_3_2GF_Weights(WeightsEnum):
@@ -116,8 +116,8 @@ class RegNet_Y_3_2GF_Weights(WeightsEnum):
             "acc@1": 78.948,
             "acc@5": 94.576,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class RegNet_Y_8GF_Weights(WeightsEnum):
@@ -130,8 +130,8 @@ class RegNet_Y_8GF_Weights(WeightsEnum):
             "acc@1": 80.032,
             "acc@5": 95.048,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class RegNet_Y_16GF_Weights(WeightsEnum):
@@ -144,8 +144,8 @@ class RegNet_Y_16GF_Weights(WeightsEnum):
             "acc@1": 80.424,
             "acc@5": 95.240,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class RegNet_Y_32GF_Weights(WeightsEnum):
@@ -158,8 +158,8 @@ class RegNet_Y_32GF_Weights(WeightsEnum):
             "acc@1": 80.878,
             "acc@5": 95.340,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class RegNet_X_400MF_Weights(WeightsEnum):
@@ -172,8 +172,8 @@ class RegNet_X_400MF_Weights(WeightsEnum):
             "acc@1": 72.834,
             "acc@5": 90.950,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class RegNet_X_800MF_Weights(WeightsEnum):
@@ -186,8 +186,8 @@ class RegNet_X_800MF_Weights(WeightsEnum):
             "acc@1": 75.212,
             "acc@5": 92.348,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class RegNet_X_1_6GF_Weights(WeightsEnum):
@@ -200,8 +200,8 @@ class RegNet_X_1_6GF_Weights(WeightsEnum):
             "acc@1": 77.040,
             "acc@5": 93.440,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class RegNet_X_3_2GF_Weights(WeightsEnum):
@@ -214,8 +214,8 @@ class RegNet_X_3_2GF_Weights(WeightsEnum):
             "acc@1": 78.364,
             "acc@5": 93.992,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class RegNet_X_8GF_Weights(WeightsEnum):
@@ -228,8 +228,8 @@ class RegNet_X_8GF_Weights(WeightsEnum):
             "acc@1": 79.344,
             "acc@5": 94.686,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class RegNet_X_16GF_Weights(WeightsEnum):
@@ -242,8 +242,8 @@ class RegNet_X_16GF_Weights(WeightsEnum):
             "acc@1": 80.058,
             "acc@5": 94.944,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class RegNet_X_32GF_Weights(WeightsEnum):
@@ -256,8 +256,8 @@ class RegNet_X_32GF_Weights(WeightsEnum):
             "acc@1": 80.622,
             "acc@5": 95.248,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 def regnet_y_400mf(weights: Optional[RegNet_Y_400MF_Weights] = None, progress: bool = True, **kwargs: Any) -> RegNet:

torchvision/prototype/models/resnet.py

@@ -64,8 +64,8 @@ class ResNet18_Weights(WeightsEnum):
             "acc@1": 69.758,
             "acc@5": 89.078,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class ResNet34_Weights(WeightsEnum):
@@ -78,8 +78,8 @@ class ResNet34_Weights(WeightsEnum):
             "acc@1": 73.314,
             "acc@5": 91.420,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class ResNet50_Weights(WeightsEnum):
@@ -92,7 +92,6 @@ class ResNet50_Weights(WeightsEnum):
             "acc@1": 76.130,
             "acc@5": 92.862,
         },
-        default=False,
     )
     ImageNet1K_V2 = Weights(
         url="https://download.pytorch.org/models/resnet50-f46c3f97.pth",
@@ -103,8 +102,8 @@ class ResNet50_Weights(WeightsEnum):
             "acc@1": 80.674,
             "acc@5": 95.166,
         },
-        default=True,
     )
+    default = ImageNet1K_V2
 
 
 class ResNet101_Weights(WeightsEnum):
@@ -117,7 +116,6 @@ class ResNet101_Weights(WeightsEnum):
             "acc@1": 77.374,
             "acc@5": 93.546,
         },
-        default=False,
     )
     ImageNet1K_V2 = Weights(
         url="https://download.pytorch.org/models/resnet101-cd907fc2.pth",
@@ -128,8 +126,8 @@ class ResNet101_Weights(WeightsEnum):
             "acc@1": 81.886,
             "acc@5": 95.780,
         },
-        default=True,
     )
+    default = ImageNet1K_V2
 
 
 class ResNet152_Weights(WeightsEnum):
@@ -142,7 +140,6 @@ class ResNet152_Weights(WeightsEnum):
             "acc@1": 78.312,
             "acc@5": 94.046,
         },
-        default=False,
     )
     ImageNet1K_V2 = Weights(
         url="https://download.pytorch.org/models/resnet152-f82ba261.pth",
@@ -153,8 +150,8 @@ class ResNet152_Weights(WeightsEnum):
             "acc@1": 82.284,
             "acc@5": 96.002,
         },
-        default=True,
     )
+    default = ImageNet1K_V2
 
 
 class ResNeXt50_32X4D_Weights(WeightsEnum):
@@ -167,7 +164,6 @@ class ResNeXt50_32X4D_Weights(WeightsEnum):
             "acc@1": 77.618,
             "acc@5": 93.698,
         },
-        default=False,
     )
     ImageNet1K_V2 = Weights(
         url="https://download.pytorch.org/models/resnext50_32x4d-1a0047aa.pth",
@@ -178,8 +174,8 @@ class ResNeXt50_32X4D_Weights(WeightsEnum):
             "acc@1": 81.198,
             "acc@5": 95.340,
         },
-        default=True,
     )
+    default = ImageNet1K_V2
 
 
 class ResNeXt101_32X8D_Weights(WeightsEnum):
@@ -192,7 +188,6 @@ class ResNeXt101_32X8D_Weights(WeightsEnum):
             "acc@1": 79.312,
             "acc@5": 94.526,
         },
-        default=False,
     )
     ImageNet1K_V2 = Weights(
         url="https://download.pytorch.org/models/resnext101_32x8d-110c445d.pth",
@@ -203,8 +198,8 @@ class ResNeXt101_32X8D_Weights(WeightsEnum):
             "acc@1": 82.834,
             "acc@5": 96.228,
         },
-        default=True,
     )
+    default = ImageNet1K_V2
 
 
 class Wide_ResNet50_2_Weights(WeightsEnum):
@@ -217,7 +212,6 @@ class Wide_ResNet50_2_Weights(WeightsEnum):
             "acc@1": 78.468,
             "acc@5": 94.086,
         },
-        default=False,
     )
     ImageNet1K_V2 = Weights(
         url="https://download.pytorch.org/models/wide_resnet50_2-9ba9bcbe.pth",
@@ -228,8 +222,8 @@ class Wide_ResNet50_2_Weights(WeightsEnum):
             "acc@1": 81.602,
             "acc@5": 95.758,
         },
-        default=True,
     )
+    default = ImageNet1K_V2
 
 
 class Wide_ResNet101_2_Weights(WeightsEnum):
@@ -242,7 +236,6 @@ class Wide_ResNet101_2_Weights(WeightsEnum):
             "acc@1": 78.848,
             "acc@5": 94.284,
         },
-        default=False,
     )
     ImageNet1K_V2 = Weights(
         url="https://download.pytorch.org/models/wide_resnet101_2-d733dc28.pth",
@@ -253,8 +246,8 @@ class Wide_ResNet101_2_Weights(WeightsEnum):
             "acc@1": 82.510,
             "acc@5": 96.020,
         },
-        default=True,
     )
+    default = ImageNet1K_V2
 
 
 def resnet18(weights: Optional[ResNet18_Weights] = None, progress: bool = True, **kwargs: Any) -> ResNet:

torchvision/prototype/models/segmentation/deeplabv3.py

@@ -40,8 +40,8 @@ class DeepLabV3_ResNet50_Weights(WeightsEnum):
             "mIoU": 66.4,
             "acc": 92.4,
         },
-        default=True,
     )
+    default = CocoWithVocLabels_V1
 
 
 class DeepLabV3_ResNet101_Weights(WeightsEnum):
@@ -54,8 +54,8 @@ class DeepLabV3_ResNet101_Weights(WeightsEnum):
             "mIoU": 67.4,
             "acc": 92.4,
         },
-        default=True,
     )
+    default = CocoWithVocLabels_V1
 
 
 class DeepLabV3_MobileNet_V3_Large_Weights(WeightsEnum):
@@ -68,8 +68,8 @@ class DeepLabV3_MobileNet_V3_Large_Weights(WeightsEnum):
             "mIoU": 60.3,
             "acc": 91.2,
         },
-        default=True,
     )
+    default = CocoWithVocLabels_V1
 
 
 def deeplabv3_resnet50(

torchvision/prototype/models/segmentation/fcn.py

@@ -30,8 +30,8 @@ class FCN_ResNet50_Weights(WeightsEnum):
             "mIoU": 60.5,
             "acc": 91.4,
         },
-        default=True,
     )
+    default = CocoWithVocLabels_V1
 
 
 class FCN_ResNet101_Weights(WeightsEnum):
@@ -44,8 +44,8 @@ class FCN_ResNet101_Weights(WeightsEnum):
             "mIoU": 63.7,
             "acc": 91.9,
         },
-        default=True,
     )
+    default = CocoWithVocLabels_V1
 
 
 def fcn_resnet50(

torchvision/prototype/models/segmentation/lraspp.py

@@ -25,8 +25,8 @@ class LRASPP_MobileNet_V3_Large_Weights(WeightsEnum):
             "mIoU": 57.9,
             "acc": 91.2,
         },
-        default=True,
     )
+    default = CocoWithVocLabels_V1
 
 
 def lraspp_mobilenet_v3_large(

torchvision/prototype/models/shufflenetv2.py

@@ -57,8 +57,8 @@ class ShuffleNet_V2_X0_5_Weights(WeightsEnum):
             "acc@1": 69.362,
             "acc@5": 88.316,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class ShuffleNet_V2_X1_0_Weights(WeightsEnum):
@@ -70,8 +70,8 @@ class ShuffleNet_V2_X1_0_Weights(WeightsEnum):
             "acc@1": 60.552,
             "acc@5": 81.746,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class ShuffleNet_V2_X1_5_Weights(WeightsEnum):

torchvision/prototype/models/squeezenet.py

@@ -30,8 +30,8 @@ class SqueezeNet1_0_Weights(WeightsEnum):
             "acc@1": 58.092,
             "acc@5": 80.420,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class SqueezeNet1_1_Weights(WeightsEnum):
@@ -43,8 +43,8 @@ class SqueezeNet1_1_Weights(WeightsEnum):
             "acc@1": 58.178,
             "acc@5": 80.624,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 def squeezenet1_0(weights: Optional[SqueezeNet1_0_Weights] = None, progress: bool = True, **kwargs: Any) -> SqueezeNet:

torchvision/prototype/models/vgg.py

@@ -57,8 +57,8 @@ class VGG11_Weights(WeightsEnum):
             "acc@1": 69.020,
             "acc@5": 88.628,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class VGG11_BN_Weights(WeightsEnum):
@@ -70,8 +70,8 @@ class VGG11_BN_Weights(WeightsEnum):
             "acc@1": 70.370,
             "acc@5": 89.810,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class VGG13_Weights(WeightsEnum):
@@ -83,8 +83,8 @@ class VGG13_Weights(WeightsEnum):
             "acc@1": 69.928,
             "acc@5": 89.246,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class VGG13_BN_Weights(WeightsEnum):
@@ -96,8 +96,8 @@ class VGG13_BN_Weights(WeightsEnum):
             "acc@1": 71.586,
             "acc@5": 90.374,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class VGG16_Weights(WeightsEnum):
@@ -109,7 +109,6 @@ class VGG16_Weights(WeightsEnum):
             "acc@1": 71.592,
             "acc@5": 90.382,
         },
-        default=True,
     )
     # We port the features of a VGG16 backbone trained by amdegroot because unlike the one on TorchVision, it uses the
     # same input standardization method as the paper. Only the `features` weights have proper values, those on the
@@ -127,8 +126,8 @@ class VGG16_Weights(WeightsEnum):
             "acc@1": float("nan"),
             "acc@5": float("nan"),
         },
-        default=False,
     )
+    default = ImageNet1K_V1
 
 
 class VGG16_BN_Weights(WeightsEnum):
@@ -140,8 +139,8 @@ class VGG16_BN_Weights(WeightsEnum):
             "acc@1": 73.360,
             "acc@5": 91.516,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class VGG19_Weights(WeightsEnum):
@@ -153,8 +152,8 @@ class VGG19_Weights(WeightsEnum):
             "acc@1": 72.376,
             "acc@5": 90.876,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 class VGG19_BN_Weights(WeightsEnum):
@@ -166,8 +165,8 @@ class VGG19_BN_Weights(WeightsEnum):
             "acc@1": 74.218,
             "acc@5": 91.842,
         },
-        default=True,
     )
+    default = ImageNet1K_V1
 
 
 def vgg11(weights: Optional[VGG11_Weights] = None, progress: bool = True, **kwargs: Any) -> VGG:

torchvision/prototype/models/video/resnet.py

@@ -68,8 +68,8 @@ class R3D_18_Weights(WeightsEnum):
             "acc@1": 52.75,
             "acc@5": 75.45,
         },
-        default=True,
     )
+    default = Kinetics400_V1
 
 
 class MC3_18_Weights(WeightsEnum):
@@ -81,8 +81,8 @@ class MC3_18_Weights(WeightsEnum):
             "acc@1": 53.90,
             "acc@5": 76.29,
         },
-        default=True,
     )
+    default = Kinetics400_V1
 
 
 class R2Plus1D_18_Weights(WeightsEnum):
@@ -94,8 +94,8 @@ class R2Plus1D_18_Weights(WeightsEnum):
             "acc@1": 57.50,
             "acc@5": 78.81,
         },
-        default=True,
     )
+    default = Kinetics400_V1
 
 
 def r3d_18(weights: Optional[R3D_18_Weights] = None, progress: bool = True, **kwargs: Any) -> VideoResNet: