Restructuring metrics meta-data (#5859)

* Restructuring metrics meta-data for detection, segmentation and optical flow.

* Renaming acc to pixel_acc for segmentation

* Restructure video meta-data.

* Restructure classification and quantization meta-data.

* Fix tests.

* Fix documentation

docs/source/conf.py

@@ -347,8 +347,8 @@ def generate_classification_table():
     content = [
         (
             f":class:`{w} <{type(w).__name__}>`",
-            w.meta["acc@1"],
-            w.meta["acc@5"],
+            w.meta["metrics"]["acc@1"],
+            w.meta["metrics"]["acc@5"],
             f"{w.meta['num_params']/1e6:.1f}M",
             f"`link <{w.meta['recipe']}>`__",
         )

test/test_extended_models.py

@@ -79,20 +79,32 @@ def test_naming_conventions(model_fn):
 )
 @run_if_test_with_extended
 def test_schema_meta_validation(model_fn):
-    # TODO: add list of permitted fields
-    classification_fields = ["categories", "acc@1", "acc@5"]
+    # list of all possible supported high-level fields for weights meta-data
+    permitted_fields = {
+        "backend",
+        "categories",
+        "keypoint_names",
+        "license",
+        "metrics",
+        "min_size",
+        "num_params",
+        "recipe",
+        "unquantized",
+    }
+    # mandatory fields for each computer vision task
+    classification_fields = {"categories", ("metrics", "acc@1"), ("metrics", "acc@5")}
     defaults = {
-        "all": ["recipe", "num_params", "min_size"],
+        "all": {"metrics", "min_size", "num_params", "recipe"},
         "models": classification_fields,
-        "detection": ["categories", "map"],
-        "quantization": classification_fields + ["backend", "unquantized"],
-        "segmentation": ["categories", "mIoU", "acc"],
+        "detection": {"categories", ("metrics", "box_map")},
+        "quantization": classification_fields | {"backend", "unquantized"},
+        "segmentation": {"categories", ("metrics", "miou"), ("metrics", "pixel_acc")},
         "video": classification_fields,
-        "optical_flow": [],
+        "optical_flow": set(),
     }
     model_name = model_fn.__name__
     module_name = model_fn.__module__.split(".")[-2]
-    fields = set(defaults["all"] + defaults[module_name])
+    fields = defaults["all"] | defaults[module_name]
 
     weights_enum = _get_model_weights(model_fn)
     if len(weights_enum) == 0:
@@ -102,9 +114,10 @@ def test_schema_meta_validation(model_fn):
     incorrect_params = []
     bad_names = []
     for w in weights_enum:
-        missing_fields = fields - set(w.meta.keys())
-        if missing_fields:
-            problematic_weights[w] = missing_fields
+        missing_fields = fields - (set(w.meta.keys()) | set(("metrics", x) for x in w.meta.get("metrics", {}).keys()))
+        unsupported_fields = set(w.meta.keys()) - permitted_fields
+        if missing_fields or unsupported_fields:
+            problematic_weights[w] = {"missing": missing_fields, "unsupported": unsupported_fields}
         if w == weights_enum.DEFAULT:
             if module_name == "quantization":
                 # parameters() count doesn't work well with quantization, so we check against the non-quantized

torchvision/models/alexnet.py

@@ -61,9 +61,11 @@ class AlexNet_Weights(WeightsEnum):
             "min_size": (63, 63),
             "categories": _IMAGENET_CATEGORIES,
             "recipe": "https://github.com/pytorch/vision/tree/main/references/classification#alexnet-and-vgg",
+            "metrics": {
                 "acc@1": 56.522,
                 "acc@5": 79.066,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 

torchvision/models/convnext.py

@@ -217,9 +217,11 @@ class ConvNeXt_Tiny_Weights(WeightsEnum):
         meta={
             **_COMMON_META,
             "num_params": 28589128,
+            "metrics": {
                 "acc@1": 82.520,
                 "acc@5": 96.146,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 
@@ -231,9 +233,11 @@ class ConvNeXt_Small_Weights(WeightsEnum):
         meta={
             **_COMMON_META,
             "num_params": 50223688,
+            "metrics": {
                 "acc@1": 83.616,
                 "acc@5": 96.650,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 
@@ -245,9 +249,11 @@ class ConvNeXt_Base_Weights(WeightsEnum):
         meta={
             **_COMMON_META,
             "num_params": 88591464,
+            "metrics": {
                 "acc@1": 84.062,
                 "acc@5": 96.870,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 
@@ -259,9 +265,11 @@ class ConvNeXt_Large_Weights(WeightsEnum):
         meta={
             **_COMMON_META,
             "num_params": 197767336,
+            "metrics": {
                 "acc@1": 84.414,
                 "acc@5": 96.976,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 

torchvision/models/densenet.py

@@ -279,9 +279,11 @@ class DenseNet121_Weights(WeightsEnum):
         meta={
             **_COMMON_META,
             "num_params": 7978856,
+            "metrics": {
                 "acc@1": 74.434,
                 "acc@5": 91.972,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 
@@ -293,9 +295,11 @@ class DenseNet161_Weights(WeightsEnum):
         meta={
             **_COMMON_META,
             "num_params": 28681000,
+            "metrics": {
                 "acc@1": 77.138,
                 "acc@5": 93.560,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 
@@ -307,9 +311,11 @@ class DenseNet169_Weights(WeightsEnum):
         meta={
             **_COMMON_META,
             "num_params": 14149480,
+            "metrics": {
                 "acc@1": 75.600,
                 "acc@5": 92.806,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 
@@ -321,9 +327,11 @@ class DenseNet201_Weights(WeightsEnum):
         meta={
             **_COMMON_META,
             "num_params": 20013928,
+            "metrics": {
                 "acc@1": 76.896,
                 "acc@5": 93.370,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 

torchvision/models/detection/faster_rcnn.py

@@ -383,7 +383,9 @@ class FasterRCNN_ResNet50_FPN_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 41755286,
             "recipe": "https://github.com/pytorch/vision/tree/main/references/detection#faster-r-cnn-resnet-50-fpn",
-            "map": 37.0,
+            "metrics": {
+                "box_map": 37.0,
+            },
         },
     )
     DEFAULT = COCO_V1
@@ -397,7 +399,9 @@ class FasterRCNN_ResNet50_FPN_V2_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 43712278,
             "recipe": "https://github.com/pytorch/vision/pull/5763",
-            "map": 46.7,
+            "metrics": {
+                "box_map": 46.7,
+            },
         },
     )
     DEFAULT = COCO_V1
@@ -411,7 +415,9 @@ class FasterRCNN_MobileNet_V3_Large_FPN_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 19386354,
             "recipe": "https://github.com/pytorch/vision/tree/main/references/detection#faster-r-cnn-mobilenetv3-large-fpn",
-            "map": 32.8,
+            "metrics": {
+                "box_map": 32.8,
+            },
         },
     )
     DEFAULT = COCO_V1
@@ -425,7 +431,9 @@ class FasterRCNN_MobileNet_V3_Large_320_FPN_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 19386354,
             "recipe": "https://github.com/pytorch/vision/tree/main/references/detection#faster-r-cnn-mobilenetv3-large-320-fpn",
-            "map": 22.8,
+            "metrics": {
+                "box_map": 22.8,
+            },
         },
     )
     DEFAULT = COCO_V1

torchvision/models/detection/fcos.py

@@ -655,7 +655,9 @@ class FCOS_ResNet50_FPN_Weights(WeightsEnum):
             "categories": _COCO_CATEGORIES,
             "min_size": (1, 1),
             "recipe": "https://github.com/pytorch/vision/tree/main/references/detection#fcos-resnet-50-fpn",
-            "map": 39.2,
+            "metrics": {
+                "box_map": 39.2,
+            },
         },
     )
     DEFAULT = COCO_V1

torchvision/models/detection/keypoint_rcnn.py

@@ -322,8 +322,10 @@ class KeypointRCNN_ResNet50_FPN_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 59137258,
             "recipe": "https://github.com/pytorch/vision/issues/1606",
-            "map": 50.6,
-            "map_kp": 61.1,
+            "metrics": {
+                "box_map": 50.6,
+                "kp_map": 61.1,
+            },
         },
     )
     COCO_V1 = Weights(
@@ -333,8 +335,10 @@ class KeypointRCNN_ResNet50_FPN_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 59137258,
             "recipe": "https://github.com/pytorch/vision/tree/main/references/detection#keypoint-r-cnn",
-            "map": 54.6,
-            "map_kp": 65.0,
+            "metrics": {
+                "box_map": 54.6,
+                "kp_map": 65.0,
+            },
         },
     )
     DEFAULT = COCO_V1

torchvision/models/detection/mask_rcnn.py

@@ -364,8 +364,10 @@ class MaskRCNN_ResNet50_FPN_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 44401393,
             "recipe": "https://github.com/pytorch/vision/tree/main/references/detection#mask-r-cnn",
-            "map": 37.9,
-            "map_mask": 34.6,
+            "metrics": {
+                "box_map": 37.9,
+                "mask_map": 34.6,
+            },
         },
     )
     DEFAULT = COCO_V1
@@ -379,8 +381,10 @@ class MaskRCNN_ResNet50_FPN_V2_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 46359409,
             "recipe": "https://github.com/pytorch/vision/pull/5773",
-            "map": 47.4,
-            "map_mask": 41.8,
+            "metrics": {
+                "box_map": 47.4,
+                "mask_map": 41.8,
+            },
         },
     )
     DEFAULT = COCO_V1

torchvision/models/detection/retinanet.py

@@ -687,7 +687,9 @@ class RetinaNet_ResNet50_FPN_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 34014999,
             "recipe": "https://github.com/pytorch/vision/tree/main/references/detection#retinanet",
-            "map": 36.4,
+            "metrics": {
+                "box_map": 36.4,
+            },
         },
     )
     DEFAULT = COCO_V1
@@ -701,7 +703,9 @@ class RetinaNet_ResNet50_FPN_V2_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 38198935,
             "recipe": "https://github.com/pytorch/vision/pull/5756",
-            "map": 41.5,
+            "metrics": {
+                "box_map": 41.5,
+            },
         },
     )
     DEFAULT = COCO_V1

torchvision/models/detection/ssd.py

@@ -34,7 +34,9 @@ class SSD300_VGG16_Weights(WeightsEnum):
             "categories": _COCO_CATEGORIES,
             "min_size": (1, 1),
             "recipe": "https://github.com/pytorch/vision/tree/main/references/detection#ssd300-vgg16",
-            "map": 25.1,
+            "metrics": {
+                "box_map": 25.1,
+            },
         },
     )
     DEFAULT = COCO_V1

torchvision/models/detection/ssdlite.py

@@ -193,7 +193,9 @@ class SSDLite320_MobileNet_V3_Large_Weights(WeightsEnum):
             "categories": _COCO_CATEGORIES,
             "min_size": (1, 1),
             "recipe": "https://github.com/pytorch/vision/tree/main/references/detection#ssdlite320-mobilenetv3-large",
-            "map": 21.3,
+            "metrics": {
+                "box_map": 21.3,
+            },
         },
     )
     DEFAULT = COCO_V1

torchvision/models/efficientnet.py

@@ -456,9 +456,11 @@ class EfficientNet_B0_Weights(WeightsEnum):
         meta={
             **_COMMON_META_V1,
             "num_params": 5288548,
+            "metrics": {
                 "acc@1": 77.692,
                 "acc@5": 93.532,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 
@@ -472,9 +474,11 @@ class EfficientNet_B1_Weights(WeightsEnum):
         meta={
             **_COMMON_META_V1,
             "num_params": 7794184,
+            "metrics": {
                 "acc@1": 78.642,
                 "acc@5": 94.186,
             },
+        },
     )
     IMAGENET1K_V2 = Weights(
         url="https://download.pytorch.org/models/efficientnet_b1-c27df63c.pth",
@@ -485,9 +489,11 @@ class EfficientNet_B1_Weights(WeightsEnum):
             **_COMMON_META_V1,
             "num_params": 7794184,
             "recipe": "https://github.com/pytorch/vision/issues/3995#new-recipe-with-lr-wd-crop-tuning",
+            "metrics": {
                 "acc@1": 79.838,
                 "acc@5": 94.934,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V2
 
@@ -501,9 +507,11 @@ class EfficientNet_B2_Weights(WeightsEnum):
         meta={
             **_COMMON_META_V1,
             "num_params": 9109994,
+            "metrics": {
                 "acc@1": 80.608,
                 "acc@5": 95.310,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 
@@ -517,9 +525,11 @@ class EfficientNet_B3_Weights(WeightsEnum):
         meta={
             **_COMMON_META_V1,
             "num_params": 12233232,
+            "metrics": {
                 "acc@1": 82.008,
                 "acc@5": 96.054,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 
@@ -533,9 +543,11 @@ class EfficientNet_B4_Weights(WeightsEnum):
         meta={
             **_COMMON_META_V1,
             "num_params": 19341616,
+            "metrics": {
                 "acc@1": 83.384,
                 "acc@5": 96.594,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 
@@ -549,9 +561,11 @@ class EfficientNet_B5_Weights(WeightsEnum):
         meta={
             **_COMMON_META_V1,
             "num_params": 30389784,
+            "metrics": {
                 "acc@1": 83.444,
                 "acc@5": 96.628,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 
@@ -565,9 +579,11 @@ class EfficientNet_B6_Weights(WeightsEnum):
         meta={
             **_COMMON_META_V1,
             "num_params": 43040704,
+            "metrics": {
                 "acc@1": 84.008,
                 "acc@5": 96.916,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 
@@ -581,9 +597,11 @@ class EfficientNet_B7_Weights(WeightsEnum):
         meta={
             **_COMMON_META_V1,
             "num_params": 66347960,
+            "metrics": {
                 "acc@1": 84.122,
                 "acc@5": 96.908,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 
@@ -600,9 +618,11 @@ class EfficientNet_V2_S_Weights(WeightsEnum):
         meta={
             **_COMMON_META_V2,
             "num_params": 21458488,
+            "metrics": {
                 "acc@1": 84.228,
                 "acc@5": 96.878,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 
@@ -619,9 +639,11 @@ class EfficientNet_V2_M_Weights(WeightsEnum):
         meta={
             **_COMMON_META_V2,
             "num_params": 54139356,
+            "metrics": {
                 "acc@1": 85.112,
                 "acc@5": 97.156,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 
@@ -640,9 +662,11 @@ class EfficientNet_V2_L_Weights(WeightsEnum):
         meta={
             **_COMMON_META_V2,
             "num_params": 118515272,
+            "metrics": {
                 "acc@1": 85.808,
                 "acc@5": 97.788,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 

torchvision/models/googlenet.py

@@ -284,9 +284,11 @@ class GoogLeNet_Weights(WeightsEnum):
             "min_size": (15, 15),
             "categories": _IMAGENET_CATEGORIES,
             "recipe": "https://github.com/pytorch/vision/tree/main/references/classification#googlenet",
+            "metrics": {
                 "acc@1": 69.778,
                 "acc@5": 89.530,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 

torchvision/models/inception.py

@@ -416,9 +416,11 @@ class Inception_V3_Weights(WeightsEnum):
             "min_size": (75, 75),
             "categories": _IMAGENET_CATEGORIES,
             "recipe": "https://github.com/pytorch/vision/tree/main/references/classification#inception-v3",
+            "metrics": {
                 "acc@1": 77.294,
                 "acc@5": 93.450,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 

torchvision/models/mnasnet.py

@@ -225,9 +225,11 @@ class MNASNet0_5_Weights(WeightsEnum):
         meta={
             **_COMMON_META,
             "num_params": 2218512,
+            "metrics": {
                 "acc@1": 67.734,
                 "acc@5": 87.490,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 
@@ -244,9 +246,11 @@ class MNASNet1_0_Weights(WeightsEnum):
         meta={
             **_COMMON_META,
             "num_params": 4383312,
+            "metrics": {
                 "acc@1": 73.456,
                 "acc@5": 91.510,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 

torchvision/models/mobilenetv2.py

@@ -208,9 +208,11 @@ class MobileNet_V2_Weights(WeightsEnum):
         meta={
             **_COMMON_META,
             "recipe": "https://github.com/pytorch/vision/tree/main/references/classification#mobilenetv2",
+            "metrics": {
                 "acc@1": 71.878,
                 "acc@5": 90.286,
             },
+        },
     )
     IMAGENET1K_V2 = Weights(
         url="https://download.pytorch.org/models/mobilenet_v2-7ebf99e0.pth",
@@ -218,9 +220,11 @@ class MobileNet_V2_Weights(WeightsEnum):
         meta={
             **_COMMON_META,
             "recipe": "https://github.com/pytorch/vision/issues/3995#new-recipe-with-reg-tuning",
+            "metrics": {
                 "acc@1": 72.154,
                 "acc@5": 90.822,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V2
 

torchvision/models/mobilenetv3.py

@@ -317,9 +317,11 @@ class MobileNet_V3_Large_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 5483032,
             "recipe": "https://github.com/pytorch/vision/tree/main/references/classification#mobilenetv3-large--small",
+            "metrics": {
                 "acc@1": 74.042,
                 "acc@5": 91.340,
             },
+        },
     )
     IMAGENET1K_V2 = Weights(
         url="https://download.pytorch.org/models/mobilenet_v3_large-5c1a4163.pth",
@@ -328,9 +330,11 @@ class MobileNet_V3_Large_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 5483032,
             "recipe": "https://github.com/pytorch/vision/issues/3995#new-recipe-with-reg-tuning",
+            "metrics": {
                 "acc@1": 75.274,
                 "acc@5": 92.566,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V2
 
@@ -343,9 +347,11 @@ class MobileNet_V3_Small_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 2542856,
             "recipe": "https://github.com/pytorch/vision/tree/main/references/classification#mobilenetv3-large--small",
+            "metrics": {
                 "acc@1": 67.668,
                 "acc@5": 87.402,
             },
+        },
     )
     DEFAULT = IMAGENET1K_V1
 

torchvision/models/optical_flow/raft.py

@@ -525,10 +525,12 @@ class Raft_Large_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 5257536,
             "recipe": "https://github.com/princeton-vl/RAFT",
+            "metrics": {
                 "sintel_train_cleanpass_epe": 1.4411,
                 "sintel_train_finalpass_epe": 2.7894,
                 "kitti_train_per_image_epe": 5.0172,
-            "kitti_train_f1-all": 17.4506,
+                "kitti_train_fl_all": 17.4506,
+            },
         },
     )
 
@@ -540,10 +542,12 @@ class Raft_Large_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 5257536,
             "recipe": "https://github.com/pytorch/vision/tree/main/references/optical_flow",
+            "metrics": {
                 "sintel_train_cleanpass_epe": 1.3822,
                 "sintel_train_finalpass_epe": 2.7161,
                 "kitti_train_per_image_epe": 4.5118,
-            "kitti_train_f1-all": 16.0679,
+                "kitti_train_fl_all": 16.0679,
+            },
         },
     )
 
@@ -555,9 +559,11 @@ class Raft_Large_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 5257536,
             "recipe": "https://github.com/princeton-vl/RAFT",
+            "metrics": {
                 "sintel_test_cleanpass_epe": 1.94,
                 "sintel_test_finalpass_epe": 3.18,
             },
+        },
     )
 
     C_T_SKHT_V2 = Weights(
@@ -570,9 +576,11 @@ class Raft_Large_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 5257536,
             "recipe": "https://github.com/pytorch/vision/tree/main/references/optical_flow",
+            "metrics": {
                 "sintel_test_cleanpass_epe": 1.819,
                 "sintel_test_finalpass_epe": 3.067,
             },
+        },
     )
 
     C_T_SKHT_K_V1 = Weights(
@@ -583,7 +591,9 @@ class Raft_Large_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 5257536,
             "recipe": "https://github.com/princeton-vl/RAFT",
-            "kitti_test_f1-all": 5.10,
+            "metrics": {
+                "kitti_test_fl_all": 5.10,
+            },
         },
     )
 
@@ -598,7 +608,9 @@ class Raft_Large_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 5257536,
             "recipe": "https://github.com/pytorch/vision/tree/main/references/optical_flow",
-            "kitti_test_f1-all": 5.19,
+            "metrics": {
+                "kitti_test_fl_all": 5.19,
+            },
         },
     )
 
@@ -614,10 +626,12 @@ class Raft_Small_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 990162,
             "recipe": "https://github.com/princeton-vl/RAFT",
+            "metrics": {
                 "sintel_train_cleanpass_epe": 2.1231,
                 "sintel_train_finalpass_epe": 3.2790,
                 "kitti_train_per_image_epe": 7.6557,
-            "kitti_train_f1-all": 25.2801,
+                "kitti_train_fl_all": 25.2801,
+            },
         },
     )
     C_T_V2 = Weights(
@@ -628,10 +642,12 @@ class Raft_Small_Weights(WeightsEnum):
             **_COMMON_META,
             "num_params": 990162,
             "recipe": "https://github.com/pytorch/vision/tree/main/references/optical_flow",
+            "metrics": {
                 "sintel_train_cleanpass_epe": 1.9901,
                 "sintel_train_finalpass_epe": 3.2831,
                 "kitti_train_per_image_epe": 7.5978,
-            "kitti_train_f1-all": 25.2369,
+                "kitti_train_fl_all": 25.2369,
+            },
         },
     )
 

torchvision/models/quantization/googlenet.py

@@ -117,9 +117,11 @@ class GoogLeNet_QuantizedWeights(WeightsEnum):
             "backend": "fbgemm",
             "recipe": "https://github.com/pytorch/vision/tree/main/references/classification#post-training-quantized-models",
             "unquantized": GoogLeNet_Weights.IMAGENET1K_V1,
+            "metrics": {
                 "acc@1": 69.826,
                 "acc@5": 89.404,
             },
+        },
     )
     DEFAULT = IMAGENET1K_FBGEMM_V1