Adding new Quantized models.

Author: datumbox

torchvision/prototype/models/quantization/mobilenetv3.py

@@ -56,22 +56,37 @@ def _mobilenet_v3_model(
     return model
 
 
+_COMMON_META = {
+    "size": (224, 224),
+    "categories": _IMAGENET_CATEGORIES,
+    "interpolation": InterpolationMode.BILINEAR,
+    "backend": "qnnpack",
+    "quantization": "qat",
+    "recipe": "https://github.com/pytorch/vision/tree/main/references/classification#qat-mobilenetv3",
+}
+
+
 class QuantizedMobileNetV3LargeWeights(Weights):
     ImageNet1K_QNNPACK_RefV1 = WeightEntry(
         url="https://download.pytorch.org/models/quantized/mobilenet_v3_large_qnnpack-5bcacf28.pth",
         transforms=partial(ImageNetEval, crop_size=224),
         meta={
-            "size": (224, 224),
-            "categories": _IMAGENET_CATEGORIES,
-            "interpolation": InterpolationMode.BILINEAR,
-            "backend": "qnnpack",
-            "quantization": "qat",
-            "recipe": "https://github.com/pytorch/vision/tree/main/references/classification#qat-mobilenetv3",
+            **_COMMON_META,
             "unquantized": MobileNetV3LargeWeights.ImageNet1K_RefV1,
             "acc@1": 73.004,
             "acc@5": 90.858,
         },
     )
+    ImageNet1K_QNNPACK_RefV2 = WeightEntry(
+        url="https://download.pytorch.org/models/quantized/mobilenet_v3_large_qnnpack-a5ce659d.pth",
+        transforms=partial(ImageNetEval, crop_size=224, resize_size=232),
+        meta={
+            **_COMMON_META,
+            "unquantized": MobileNetV3LargeWeights.ImageNet1K_RefV2,
+            "acc@1": 74.140,
+            "acc@5": 91.982,
+        },
+    )
 
 
 def mobilenet_v3_large(

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(