Reinstate and deprecate `model_urls` and `quant_model_urls` (#5992)

* Reinstate and deprecate `model_urls` and `quant_model_urls`

* Apply suggestions from code review
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Move todo location

* Add alexnet

* Add densenet

* Add efficientnet

* Add googlenet.

* Add inception.

* Add mobilenetv3

* Add regnet

* Add resnet

* Add shufflenetv2

* Fix linter

* Add squeezenet

* Add vgg

* Add vit

* Add quantized googlenet

* Add quantized inceptionv3

* Add quantized mobilenet_v3

* Add quantized resnet

* Add quantized shufflenetv2

* Fix incorrect imports

* Add faster_rcnn

* Add fcos

* Add keypoint rcnn

* Add mask rcnn

* Add retinanet

* Add ssd

* Add ssdlite

* Add deeplabv3

* Add fcn

* Add lraspp.

* Add video resnet

* Removing weights for shufflenetv2_x1.5 and shufflenetv2_x2.0

* Update the comments
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

torchvision/models/quantization/shufflenetv2.py

@@ -298,3 +298,16 @@ def shufflenet_v2_x2_0(
     return _shufflenetv2(
         [4, 8, 4], [24, 244, 488, 976, 2048], weights=weights, progress=progress, quantize=quantize, **kwargs
     )
+
+
+# The dictionary below is internal implementation detail and will be removed in v0.15
+from .._utils import _ModelURLs
+from ..shufflenetv2 import model_urls  # noqa: F401
+
+
+quant_model_urls = _ModelURLs(
+    {
+        "shufflenetv2_x0.5_fbgemm": ShuffleNet_V2_X0_5_QuantizedWeights.IMAGENET1K_FBGEMM_V1.url,
+        "shufflenetv2_x1.0_fbgemm": ShuffleNet_V2_X1_0_QuantizedWeights.IMAGENET1K_FBGEMM_V1.url,
+    }
+)

torchvision/models/regnet.py

@@ -1330,3 +1330,27 @@ def regnet_x_32gf(*, weights: Optional[RegNet_X_32GF_Weights] = None, progress:
 
     params = BlockParams.from_init_params(depth=23, w_0=320, w_a=69.86, w_m=2.0, group_width=168, **kwargs)
     return _regnet(params, weights, progress, **kwargs)
+
+
+# The dictionary below is internal implementation detail and will be removed in v0.15
+from ._utils import _ModelURLs
+
+
+model_urls = _ModelURLs(
+    {
+        "regnet_y_400mf": RegNet_Y_400MF_Weights.IMAGENET1K_V1.url,
+        "regnet_y_800mf": RegNet_Y_800MF_Weights.IMAGENET1K_V1.url,
+        "regnet_y_1_6gf": RegNet_Y_1_6GF_Weights.IMAGENET1K_V1.url,
+        "regnet_y_3_2gf": RegNet_Y_3_2GF_Weights.IMAGENET1K_V1.url,
+        "regnet_y_8gf": RegNet_Y_8GF_Weights.IMAGENET1K_V1.url,
+        "regnet_y_16gf": RegNet_Y_16GF_Weights.IMAGENET1K_V1.url,
+        "regnet_y_32gf": RegNet_Y_32GF_Weights.IMAGENET1K_V1.url,
+        "regnet_x_400mf": RegNet_X_400MF_Weights.IMAGENET1K_V1.url,
+        "regnet_x_800mf": RegNet_X_800MF_Weights.IMAGENET1K_V1.url,
+        "regnet_x_1_6gf": RegNet_X_1_6GF_Weights.IMAGENET1K_V1.url,
+        "regnet_x_3_2gf": RegNet_X_3_2GF_Weights.IMAGENET1K_V1.url,
+        "regnet_x_8gf": RegNet_X_8GF_Weights.IMAGENET1K_V1.url,
+        "regnet_x_16gf": RegNet_X_16GF_Weights.IMAGENET1K_V1.url,
+        "regnet_x_32gf": RegNet_X_32GF_Weights.IMAGENET1K_V1.url,
+    }
+)

torchvision/models/resnet.py

@@ -853,3 +853,22 @@ def wide_resnet101_2(
 
     _ovewrite_named_param(kwargs, "width_per_group", 64 * 2)
     return _resnet(Bottleneck, [3, 4, 23, 3], weights, progress, **kwargs)
+
+
+# The dictionary below is internal implementation detail and will be removed in v0.15
+from ._utils import _ModelURLs
+
+
+model_urls = _ModelURLs(
+    {
+        "resnet18": ResNet18_Weights.IMAGENET1K_V1.url,
+        "resnet34": ResNet34_Weights.IMAGENET1K_V1.url,
+        "resnet50": ResNet50_Weights.IMAGENET1K_V1.url,
+        "resnet101": ResNet101_Weights.IMAGENET1K_V1.url,
+        "resnet152": ResNet152_Weights.IMAGENET1K_V1.url,
+        "resnext50_32x4d": ResNeXt50_32X4D_Weights.IMAGENET1K_V1.url,
+        "resnext101_32x8d": ResNeXt101_32X8D_Weights.IMAGENET1K_V1.url,
+        "wide_resnet50_2": Wide_ResNet50_2_Weights.IMAGENET1K_V1.url,
+        "wide_resnet101_2": Wide_ResNet101_2_Weights.IMAGENET1K_V1.url,
+    }
+)

torchvision/models/segmentation/deeplabv3.py

@@ -365,3 +365,16 @@ def deeplabv3_mobilenet_v3_large(
         model.load_state_dict(weights.get_state_dict(progress=progress))
 
     return model
+
+
+# The dictionary below is internal implementation detail and will be removed in v0.15
+from .._utils import _ModelURLs
+
+
+model_urls = _ModelURLs(
+    {
+        "deeplabv3_resnet50_coco": DeepLabV3_ResNet50_Weights.COCO_WITH_VOC_LABELS_V1.url,
+        "deeplabv3_resnet101_coco": DeepLabV3_ResNet101_Weights.COCO_WITH_VOC_LABELS_V1.url,
+        "deeplabv3_mobilenet_v3_large_coco": DeepLabV3_MobileNet_V3_Large_Weights.COCO_WITH_VOC_LABELS_V1.url,
+    }
+)

torchvision/models/segmentation/fcn.py

@@ -212,3 +212,15 @@ def fcn_resnet101(
         model.load_state_dict(weights.get_state_dict(progress=progress))
 
     return model
+
+
+# The dictionary below is internal implementation detail and will be removed in v0.15
+from .._utils import _ModelURLs
+
+
+model_urls = _ModelURLs(
+    {
+        "fcn_resnet50_coco": FCN_ResNet50_Weights.COCO_WITH_VOC_LABELS_V1.url,
+        "fcn_resnet101_coco": FCN_ResNet101_Weights.COCO_WITH_VOC_LABELS_V1.url,
+    }
+)

torchvision/models/segmentation/lraspp.py

@@ -165,3 +165,14 @@ def lraspp_mobilenet_v3_large(
         model.load_state_dict(weights.get_state_dict(progress=progress))
 
     return model
+
+
+# The dictionary below is internal implementation detail and will be removed in v0.15
+from .._utils import _ModelURLs
+
+
+model_urls = _ModelURLs(
+    {
+        "lraspp_mobilenet_v3_large_coco": LRASPP_MobileNet_V3_Large_Weights.COCO_WITH_VOC_LABELS_V1.url,
+    }
+)

torchvision/models/shufflenetv2.py

@@ -374,3 +374,17 @@ def shufflenet_v2_x2_0(
     weights = ShuffleNet_V2_X2_0_Weights.verify(weights)
 
     return _shufflenetv2(weights, progress, [4, 8, 4], [24, 244, 488, 976, 2048], **kwargs)
+
+
+# The dictionary below is internal implementation detail and will be removed in v0.15
+from ._utils import _ModelURLs
+
+
+model_urls = _ModelURLs(
+    {
+        "shufflenetv2_x0.5": ShuffleNet_V2_X0_5_Weights.IMAGENET1K_V1.url,
+        "shufflenetv2_x1.0": ShuffleNet_V2_X1_0_Weights.IMAGENET1K_V1.url,
+        "shufflenetv2_x1.5": None,
+        "shufflenetv2_x2.0": None,
+    }
+)

torchvision/models/squeezenet.py

@@ -213,3 +213,15 @@ def squeezenet1_1(
     """
     weights = SqueezeNet1_1_Weights.verify(weights)
     return _squeezenet("1_1", weights, progress, **kwargs)
+
+
+# The dictionary below is internal implementation detail and will be removed in v0.15
+from ._utils import _ModelURLs
+
+
+model_urls = _ModelURLs(
+    {
+        "squeezenet1_0": SqueezeNet1_0_Weights.IMAGENET1K_V1.url,
+        "squeezenet1_1": SqueezeNet1_1_Weights.IMAGENET1K_V1.url,
+    }
+)

torchvision/models/vgg.py

@@ -461,3 +461,21 @@ def vgg19_bn(*, weights: Optional[VGG19_BN_Weights] = None, progress: bool = Tru
     weights = VGG19_BN_Weights.verify(weights)
 
     return _vgg("E", True, weights, progress, **kwargs)
+
+
+# The dictionary below is internal implementation detail and will be removed in v0.15
+from ._utils import _ModelURLs
+
+
+model_urls = _ModelURLs(
+    {
+        "vgg11": VGG11_Weights.IMAGENET1K_V1.url,
+        "vgg13": VGG13_Weights.IMAGENET1K_V1.url,
+        "vgg16": VGG16_Weights.IMAGENET1K_V1.url,
+        "vgg19": VGG19_Weights.IMAGENET1K_V1.url,
+        "vgg11_bn": VGG11_BN_Weights.IMAGENET1K_V1.url,
+        "vgg13_bn": VGG13_BN_Weights.IMAGENET1K_V1.url,
+        "vgg16_bn": VGG16_BN_Weights.IMAGENET1K_V1.url,
+        "vgg19_bn": VGG19_BN_Weights.IMAGENET1K_V1.url,
+    }
+)

torchvision/models/video/resnet.py

@@ -463,3 +463,16 @@ def r2plus1d_18(*, weights: Optional[R2Plus1D_18_Weights] = None, progress: bool
         progress,
         **kwargs,
     )
+
+
+# The dictionary below is internal implementation detail and will be removed in v0.15
+from .._utils import _ModelURLs
+
+
+model_urls = _ModelURLs(
+    {
+        "r3d_18": R3D_18_Weights.KINETICS400_V1.url,
+        "mc3_18": MC3_18_Weights.KINETICS400_V1.url,
+        "r2plus1d_18": R2Plus1D_18_Weights.KINETICS400_V1.url,
+    }
+)

torchvision/models/vision_transformer.py

@@ -746,3 +746,17 @@ def interpolate_embeddings(
             model_state = model_state_copy
 
     return model_state
+
+
+# The dictionary below is internal implementation detail and will be removed in v0.15
+from ._utils import _ModelURLs
+
+
+model_urls = _ModelURLs(
+    {
+        "vit_b_16": ViT_B_16_Weights.IMAGENET1K_V1.url,
+        "vit_b_32": ViT_B_32_Weights.IMAGENET1K_V1.url,
+        "vit_l_16": ViT_L_16_Weights.IMAGENET1K_V1.url,
+        "vit_l_32": ViT_L_32_Weights.IMAGENET1K_V1.url,
+    }
+)