Merge branch 'main' into prabhat00155/update_wide_resnet101_weights

Author: prabhat00155

torchvision/models/quantization/mobilenetv3.py

@@ -43,7 +43,7 @@ def _load_from_state_dict(
     ):
         version = local_metadata.get("version", None)
 
-        if version is None or version < 2:
+        if hasattr(self, "qconfig") and (version is None or version < 2):
             default_state_dict = {
                 "scale_activation.activation_post_process.scale": torch.tensor([1.0]),
                 "scale_activation.activation_post_process.zero_point": torch.tensor([0], dtype=torch.int32),

torchvision/prototype/models/quantization/resnet.py

@@ -87,6 +87,16 @@ class QuantizedResNet50Weights(Weights):
             "acc@5": 92.814,
         },
     )
+    ImageNet1K_FBGEMM_RefV2 = WeightEntry(
+        url="https://download.pytorch.org/models/quantized/resnet50_fbgemm-23753f79.pth",
+        transforms=partial(ImageNetEval, crop_size=224, resize_size=232),
+        meta={
+            **_COMMON_META,
+            "unquantized": ResNet50Weights.ImageNet1K_RefV2,
+            "acc@1": 80.282,
+            "acc@5": 94.976,
+        },
+    )
 
 
 class QuantizedResNeXt101_32x8dWeights(Weights):
@@ -100,6 +110,16 @@ class QuantizedResNeXt101_32x8dWeights(Weights):
             "acc@5": 94.480,
         },
     )
+    ImageNet1K_FBGEMM_RefV2 = WeightEntry(
+        url="https://download.pytorch.org/models/quantized/resnext101_32x8_fbgemm-ee16d00c.pth",
+        transforms=partial(ImageNetEval, crop_size=224, resize_size=232),
+        meta={
+            **_COMMON_META,
+            "unquantized": ResNeXt101_32x8dWeights.ImageNet1K_RefV2,
+            "acc@1": 82.574,
+            "acc@5": 96.132,
+        },
+    )
 
 
 def resnet18(