Fix resnet_fpn_backbone(pretrained=True) (#7172)

test/test_extended_models.py

@@ -9,6 +9,7 @@ from common_extended_utils import get_file_size_mb, get_ops
 from torchvision import models
 from torchvision.models import get_model_weights, Weights, WeightsEnum
 from torchvision.models._utils import handle_legacy_interface
+from torchvision.models.detection.backbone_utils import mobilenet_backbone, resnet_fpn_backbone
 
 run_if_test_with_extended = pytest.mark.skipif(
     os.getenv("PYTORCH_TEST_WITH_EXTENDED", "0") != "1",
@@ -425,7 +426,11 @@ class TestHandleLegacyInterface:
         + TM.list_model_fns(models.quantization)
         + TM.list_model_fns(models.segmentation)
         + TM.list_model_fns(models.video)
-        + TM.list_model_fns(models.optical_flow),
+        + TM.list_model_fns(models.optical_flow)
+        + [
+            lambda pretrained: resnet_fpn_backbone(backbone_name="resnet50", pretrained=pretrained),
+            lambda pretrained: mobilenet_backbone(backbone_name="mobilenet_v2", fpn=False, pretrained=pretrained),
+        ],
     )
     @run_if_test_with_extended
     def test_pretrained_deprecation(self, model_fn):

torchvision/models/_api.py

@@ -6,7 +6,7 @@ from enum import Enum
 from functools import partial
 from inspect import signature
 from types import ModuleType
-from typing import Any, Callable, cast, Dict, List, Mapping, Optional, TypeVar, Union
+from typing import Any, Callable, Dict, List, Mapping, Optional, Type, TypeVar, Union
 
 from torch import nn
 
@@ -138,7 +138,7 @@ def get_weight(name: str) -> WeightsEnum:
     return weights_enum[value_name]
 
 
-def get_model_weights(name: Union[Callable, str]) -> WeightsEnum:
+def get_model_weights(name: Union[Callable, str]) -> Type[WeightsEnum]:
     """
     Returns the weights enum class associated to the given model.
 
@@ -152,7 +152,7 @@ def get_model_weights(name: Union[Callable, str]) -> WeightsEnum:
     return _get_enum_from_fn(model)
 
 
-def _get_enum_from_fn(fn: Callable) -> WeightsEnum:
+def _get_enum_from_fn(fn: Callable) -> Type[WeightsEnum]:
     """
     Internal method that gets the weight enum of a specific model builder method.
 
@@ -182,7 +182,7 @@ def _get_enum_from_fn(fn: Callable) -> WeightsEnum:
             "The WeightsEnum class for the specific method couldn't be retrieved. Make sure the typing info is correct."
         )
 
-    return cast(WeightsEnum, weights_enum)
+    return weights_enum
 
 
 M = TypeVar("M", bound=nn.Module)

torchvision/models/detection/backbone_utils.py

@@ -62,7 +62,7 @@ class BackboneWithFPN(nn.Module):
 @handle_legacy_interface(
     weights=(
         "pretrained",
-        lambda kwargs: _get_enum_from_fn(resnet.__dict__[kwargs["backbone_name"]]).from_str("IMAGENET1K_V1"),
+        lambda kwargs: _get_enum_from_fn(resnet.__dict__[kwargs["backbone_name"]])["IMAGENET1K_V1"],
     ),
 )
 def resnet_fpn_backbone(
@@ -177,7 +177,7 @@ def _validate_trainable_layers(
 @handle_legacy_interface(
     weights=(
         "pretrained",
-        lambda kwargs: _get_enum_from_fn(mobilenet.__dict__[kwargs["backbone_name"]]).from_str("IMAGENET1K_V1"),
+        lambda kwargs: _get_enum_from_fn(mobilenet.__dict__[kwargs["backbone_name"]])["IMAGENET1K_V1"],
     ),
 )
 def mobilenet_backbone(