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Merged
merged 7 commits into from
Apr 22, 2022
Merged

Restructuring metrics meta-data #5859

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41b14dc
Restructuring metrics meta-data for detection, segmentation and optic…
datumbox Apr 21, 2022
f207d84
Renaming acc to pixel_acc for segmentation
datumbox Apr 22, 2022
7b35b63
Restructure video meta-data.
datumbox Apr 22, 2022
45d552a
Restructure classification and quantization meta-data.
datumbox Apr 22, 2022
27b37ae
Fix tests.
datumbox Apr 22, 2022
4d1d69f
Fix documentation
datumbox Apr 22, 2022
5ec428f
Merge branch 'main' into models/meta_metrics
datumbox Apr 22, 2022
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4 changes: 2 additions & 2 deletions docs/source/conf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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"],
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Fixing documentation.

f"{w.meta['num_params']/1e6:.1f}M",
f"`link <{w.meta['recipe']}>`__",
)
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35 changes: 24 additions & 11 deletions test/test_extended_models.py
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Expand Up @@ -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:
Expand All @@ -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
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6 changes: 4 additions & 2 deletions torchvision/models/alexnet.py
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Expand Up @@ -61,8 +61,10 @@ class AlexNet_Weights(WeightsEnum):
"min_size": (63, 63),
"categories": _IMAGENET_CATEGORIES,
"recipe": "https://github.com/pytorch/vision/tree/main/references/classification#alexnet-and-vgg",
"acc@1": 56.522,
"acc@5": 79.066,
"metrics": {
"acc@1": 56.522,
"acc@5": 79.066,
},
},
)
DEFAULT = IMAGENET1K_V1
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24 changes: 16 additions & 8 deletions torchvision/models/convnext.py
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Expand Up @@ -217,8 +217,10 @@ class ConvNeXt_Tiny_Weights(WeightsEnum):
meta={
**_COMMON_META,
"num_params": 28589128,
"acc@1": 82.520,
"acc@5": 96.146,
"metrics": {
"acc@1": 82.520,
"acc@5": 96.146,
},
},
)
DEFAULT = IMAGENET1K_V1
Expand All @@ -231,8 +233,10 @@ class ConvNeXt_Small_Weights(WeightsEnum):
meta={
**_COMMON_META,
"num_params": 50223688,
"acc@1": 83.616,
"acc@5": 96.650,
"metrics": {
"acc@1": 83.616,
"acc@5": 96.650,
},
},
)
DEFAULT = IMAGENET1K_V1
Expand All @@ -245,8 +249,10 @@ class ConvNeXt_Base_Weights(WeightsEnum):
meta={
**_COMMON_META,
"num_params": 88591464,
"acc@1": 84.062,
"acc@5": 96.870,
"metrics": {
"acc@1": 84.062,
"acc@5": 96.870,
},
},
)
DEFAULT = IMAGENET1K_V1
Expand All @@ -259,8 +265,10 @@ class ConvNeXt_Large_Weights(WeightsEnum):
meta={
**_COMMON_META,
"num_params": 197767336,
"acc@1": 84.414,
"acc@5": 96.976,
"metrics": {
"acc@1": 84.414,
"acc@5": 96.976,
},
},
)
DEFAULT = IMAGENET1K_V1
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24 changes: 16 additions & 8 deletions torchvision/models/densenet.py
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Expand Up @@ -279,8 +279,10 @@ class DenseNet121_Weights(WeightsEnum):
meta={
**_COMMON_META,
"num_params": 7978856,
"acc@1": 74.434,
"acc@5": 91.972,
"metrics": {
"acc@1": 74.434,
"acc@5": 91.972,
},
},
)
DEFAULT = IMAGENET1K_V1
Expand All @@ -293,8 +295,10 @@ class DenseNet161_Weights(WeightsEnum):
meta={
**_COMMON_META,
"num_params": 28681000,
"acc@1": 77.138,
"acc@5": 93.560,
"metrics": {
"acc@1": 77.138,
"acc@5": 93.560,
},
},
)
DEFAULT = IMAGENET1K_V1
Expand All @@ -307,8 +311,10 @@ class DenseNet169_Weights(WeightsEnum):
meta={
**_COMMON_META,
"num_params": 14149480,
"acc@1": 75.600,
"acc@5": 92.806,
"metrics": {
"acc@1": 75.600,
"acc@5": 92.806,
},
},
)
DEFAULT = IMAGENET1K_V1
Expand All @@ -321,8 +327,10 @@ class DenseNet201_Weights(WeightsEnum):
meta={
**_COMMON_META,
"num_params": 20013928,
"acc@1": 76.896,
"acc@5": 93.370,
"metrics": {
"acc@1": 76.896,
"acc@5": 93.370,
},
},
)
DEFAULT = IMAGENET1K_V1
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16 changes: 12 additions & 4 deletions torchvision/models/detection/faster_rcnn.py
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Expand Up @@ -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
Expand All @@ -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
Expand All @@ -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
Expand All @@ -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
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4 changes: 3 additions & 1 deletion torchvision/models/detection/fcos.py
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Expand Up @@ -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
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12 changes: 8 additions & 4 deletions torchvision/models/detection/keypoint_rcnn.py
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Expand Up @@ -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(
Expand All @@ -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
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12 changes: 8 additions & 4 deletions torchvision/models/detection/mask_rcnn.py
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Expand Up @@ -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
Expand All @@ -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
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8 changes: 6 additions & 2 deletions torchvision/models/detection/retinanet.py
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Expand Up @@ -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
Expand All @@ -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
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4 changes: 3 additions & 1 deletion torchvision/models/detection/ssd.py
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Expand Up @@ -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
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4 changes: 3 additions & 1 deletion torchvision/models/detection/ssdlite.py
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Expand Up @@ -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
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