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Merged
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Apr 21, 2022
Merged

Remove publication_year and interpolation meta #5848

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5b6886e
Remove publication_year and interpolation meta
YosuaMichael Apr 21, 2022
2df2684
Add type to _COMMON_META and _COMMON_SWAG_META to prevent error from …
YosuaMichael Apr 21, 2022
fd1deaa
Remove test to check interpolation and publication_year meta
YosuaMichael Apr 21, 2022
c02778f
Merge branch 'main' into models/cleanup-meta
datumbox Apr 21, 2022
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2 changes: 1 addition & 1 deletion test/test_extended_models.py
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Expand Up @@ -81,7 +81,7 @@ def test_naming_conventions(model_fn):
def test_schema_meta_validation(model_fn):
classification_fields = ["size", "categories", "acc@1", "acc@5", "min_size"]
defaults = {
"all": ["task", "architecture", "publication_year", "interpolation", "recipe", "num_params"],
"all": ["task", "architecture", "recipe", "num_params"],
"models": classification_fields,
"detection": ["categories", "map"],
"quantization": classification_fields + ["backend", "quantization", "unquantized"],
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4 changes: 1 addition & 3 deletions torchvision/models/alexnet.py
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Expand Up @@ -4,7 +4,7 @@
import torch
import torch.nn as nn

from ..transforms._presets import ImageClassification, InterpolationMode
from ..transforms._presets import ImageClassification
from ..utils import _log_api_usage_once
from ._api import WeightsEnum, Weights
from ._meta import _IMAGENET_CATEGORIES
Expand Down Expand Up @@ -59,12 +59,10 @@ class AlexNet_Weights(WeightsEnum):
meta={
"task": "image_classification",
"architecture": "AlexNet",
"publication_year": 2012,
"num_params": 61100840,
"size": (224, 224),
"min_size": (63, 63),
"categories": _IMAGENET_CATEGORIES,
"interpolation": InterpolationMode.BILINEAR,
"recipe": "https://github.com/pytorch/vision/tree/main/references/classification#alexnet-and-vgg",
"acc@1": 56.522,
"acc@5": 79.066,
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4 changes: 1 addition & 3 deletions torchvision/models/convnext.py
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Expand Up @@ -7,7 +7,7 @@

from ..ops.misc import Conv2dNormActivation
from ..ops.stochastic_depth import StochasticDepth
from ..transforms._presets import ImageClassification, InterpolationMode
from ..transforms._presets import ImageClassification
from ..utils import _log_api_usage_once
from ._api import WeightsEnum, Weights
from ._meta import _IMAGENET_CATEGORIES
Expand Down Expand Up @@ -206,11 +206,9 @@ def _convnext(
_COMMON_META = {
"task": "image_classification",
"architecture": "ConvNeXt",
"publication_year": 2022,
"size": (224, 224),
"min_size": (32, 32),
"categories": _IMAGENET_CATEGORIES,
"interpolation": InterpolationMode.BILINEAR,
"recipe": "https://github.com/pytorch/vision/tree/main/references/classification#convnext",
}

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4 changes: 1 addition & 3 deletions torchvision/models/densenet.py
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Expand Up @@ -9,7 +9,7 @@
import torch.utils.checkpoint as cp
from torch import Tensor

from ..transforms._presets import ImageClassification, InterpolationMode
from ..transforms._presets import ImageClassification
from ..utils import _log_api_usage_once
from ._api import WeightsEnum, Weights
from ._meta import _IMAGENET_CATEGORIES
Expand Down Expand Up @@ -268,11 +268,9 @@ def _densenet(
_COMMON_META = {
"task": "image_classification",
"architecture": "DenseNet",
"publication_year": 2016,
"size": (224, 224),
"min_size": (29, 29),
"categories": _IMAGENET_CATEGORIES,
"interpolation": InterpolationMode.BILINEAR,
"recipe": "https://github.com/pytorch/vision/pull/116",
}

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5 changes: 1 addition & 4 deletions torchvision/models/detection/faster_rcnn.py
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Expand Up @@ -6,7 +6,7 @@
from torchvision.ops import MultiScaleRoIAlign

from ...ops import misc as misc_nn_ops
from ...transforms._presets import ObjectDetection, InterpolationMode
from ...transforms._presets import ObjectDetection
from .._api import WeightsEnum, Weights
from .._meta import _COCO_CATEGORIES
from .._utils import handle_legacy_interface, _ovewrite_value_param
Expand Down Expand Up @@ -372,9 +372,7 @@ def forward(self, x):
_COMMON_META = {
"task": "image_object_detection",
"architecture": "FasterRCNN",
"publication_year": 2015,
"categories": _COCO_CATEGORIES,
"interpolation": InterpolationMode.BILINEAR,
}


Expand All @@ -398,7 +396,6 @@ class FasterRCNN_ResNet50_FPN_V2_Weights(WeightsEnum):
transforms=ObjectDetection,
meta={
**_COMMON_META,
"publication_year": 2021,
"num_params": 43712278,
"recipe": "https://github.com/pytorch/vision/pull/5763",
"map": 46.7,
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4 changes: 1 addition & 3 deletions torchvision/models/detection/fcos.py
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Expand Up @@ -11,7 +11,7 @@
from ...ops import boxes as box_ops
from ...ops import misc as misc_nn_ops
from ...ops.feature_pyramid_network import LastLevelP6P7
from ...transforms._presets import ObjectDetection, InterpolationMode
from ...transforms._presets import ObjectDetection
from ...utils import _log_api_usage_once
from .._api import WeightsEnum, Weights
from .._meta import _COCO_CATEGORIES
Expand Down Expand Up @@ -653,10 +653,8 @@ class FCOS_ResNet50_FPN_Weights(WeightsEnum):
meta={
"task": "image_object_detection",
"architecture": "FCOS",
"publication_year": 2019,
"num_params": 32269600,
"categories": _COCO_CATEGORIES,
"interpolation": InterpolationMode.BILINEAR,
"recipe": "https://github.com/pytorch/vision/tree/main/references/detection#fcos-resnet-50-fpn",
"map": 39.2,
},
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4 changes: 1 addition & 3 deletions torchvision/models/detection/keypoint_rcnn.py
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Expand Up @@ -5,7 +5,7 @@
from torchvision.ops import MultiScaleRoIAlign

from ...ops import misc as misc_nn_ops
from ...transforms._presets import ObjectDetection, InterpolationMode
from ...transforms._presets import ObjectDetection
from .._api import WeightsEnum, Weights
from .._meta import _COCO_PERSON_CATEGORIES, _COCO_PERSON_KEYPOINT_NAMES
from .._utils import handle_legacy_interface, _ovewrite_value_param
Expand Down Expand Up @@ -310,10 +310,8 @@ def forward(self, x):
_COMMON_META = {
"task": "image_object_detection",
"architecture": "KeypointRCNN",
"publication_year": 2017,
"categories": _COCO_PERSON_CATEGORIES,
"keypoint_names": _COCO_PERSON_KEYPOINT_NAMES,
"interpolation": InterpolationMode.BILINEAR,
}


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5 changes: 1 addition & 4 deletions torchvision/models/detection/mask_rcnn.py
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Expand Up @@ -5,7 +5,7 @@
from torchvision.ops import MultiScaleRoIAlign

from ...ops import misc as misc_nn_ops
from ...transforms._presets import ObjectDetection, InterpolationMode
from ...transforms._presets import ObjectDetection
from .._api import WeightsEnum, Weights
from .._meta import _COCO_CATEGORIES
from .._utils import handle_legacy_interface, _ovewrite_value_param
Expand Down Expand Up @@ -354,7 +354,6 @@ def __init__(self, in_channels, dim_reduced, num_classes):
"task": "image_object_detection",
"architecture": "MaskRCNN",
"categories": _COCO_CATEGORIES,
"interpolation": InterpolationMode.BILINEAR,
}


Expand All @@ -364,7 +363,6 @@ class MaskRCNN_ResNet50_FPN_Weights(WeightsEnum):
transforms=ObjectDetection,
meta={
**_COMMON_META,
"publication_year": 2017,
"num_params": 44401393,
"recipe": "https://github.com/pytorch/vision/tree/main/references/detection#mask-r-cnn",
"map": 37.9,
Expand All @@ -380,7 +378,6 @@ class MaskRCNN_ResNet50_FPN_V2_Weights(WeightsEnum):
transforms=ObjectDetection,
meta={
**_COMMON_META,
"publication_year": 2021,
"num_params": 46359409,
"recipe": "https://github.com/pytorch/vision/pull/5773",
"map": 47.4,
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5 changes: 1 addition & 4 deletions torchvision/models/detection/retinanet.py
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Expand Up @@ -11,7 +11,7 @@
from ...ops import boxes as box_ops
from ...ops import misc as misc_nn_ops
from ...ops.feature_pyramid_network import LastLevelP6P7
from ...transforms._presets import ObjectDetection, InterpolationMode
from ...transforms._presets import ObjectDetection
from ...utils import _log_api_usage_once
from .._api import WeightsEnum, Weights
from .._meta import _COCO_CATEGORIES
Expand Down Expand Up @@ -677,7 +677,6 @@ def forward(self, images, targets=None):
"task": "image_object_detection",
"architecture": "RetinaNet",
"categories": _COCO_CATEGORIES,
"interpolation": InterpolationMode.BILINEAR,
}


Expand All @@ -687,7 +686,6 @@ class RetinaNet_ResNet50_FPN_Weights(WeightsEnum):
transforms=ObjectDetection,
meta={
**_COMMON_META,
"publication_year": 2017,
"num_params": 34014999,
"recipe": "https://github.com/pytorch/vision/tree/main/references/detection#retinanet",
"map": 36.4,
Expand All @@ -702,7 +700,6 @@ class RetinaNet_ResNet50_FPN_V2_Weights(WeightsEnum):
transforms=ObjectDetection,
meta={
**_COMMON_META,
"publication_year": 2019,
"num_params": 38198935,
"recipe": "https://github.com/pytorch/vision/pull/5756",
"map": 41.5,
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4 changes: 1 addition & 3 deletions torchvision/models/detection/ssd.py
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Expand Up @@ -7,7 +7,7 @@
from torch import nn, Tensor

from ...ops import boxes as box_ops
from ...transforms._presets import ObjectDetection, InterpolationMode
from ...transforms._presets import ObjectDetection
from ...utils import _log_api_usage_once
from .._api import WeightsEnum, Weights
from .._meta import _COCO_CATEGORIES
Expand All @@ -32,11 +32,9 @@ class SSD300_VGG16_Weights(WeightsEnum):
meta={
"task": "image_object_detection",
"architecture": "SSD",
"publication_year": 2015,
"num_params": 35641826,
"size": (300, 300),
"categories": _COCO_CATEGORIES,
"interpolation": InterpolationMode.BILINEAR,
"recipe": "https://github.com/pytorch/vision/tree/main/references/detection#ssd300-vgg16",
"map": 25.1,
},
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4 changes: 1 addition & 3 deletions torchvision/models/detection/ssdlite.py
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Expand Up @@ -7,7 +7,7 @@
from torch import nn, Tensor

from ...ops.misc import Conv2dNormActivation
from ...transforms._presets import ObjectDetection, InterpolationMode
from ...transforms._presets import ObjectDetection
from ...utils import _log_api_usage_once
from .. import mobilenet
from .._api import WeightsEnum, Weights
Expand Down Expand Up @@ -191,11 +191,9 @@ class SSDLite320_MobileNet_V3_Large_Weights(WeightsEnum):
meta={
"task": "image_object_detection",
"architecture": "SSDLite",
"publication_year": 2018,
"num_params": 3440060,
"size": (320, 320),
"categories": _COCO_CATEGORIES,
"interpolation": InterpolationMode.BILINEAR,
"recipe": "https://github.com/pytorch/vision/tree/main/references/detection#ssdlite320-mobilenetv3-large",
"map": 21.3,
},
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5 changes: 0 additions & 5 deletions torchvision/models/efficientnet.py
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Expand Up @@ -439,17 +439,13 @@ def _efficientnet_conf(
_COMMON_META_V1 = {
**_COMMON_META,
"architecture": "EfficientNet",
"publication_year": 2019,
"interpolation": InterpolationMode.BICUBIC,
"min_size": (1, 1),
}


_COMMON_META_V2 = {
**_COMMON_META,
"architecture": "EfficientNetV2",
"publication_year": 2021,
"interpolation": InterpolationMode.BILINEAR,
"min_size": (33, 33),
}

Expand Down Expand Up @@ -494,7 +490,6 @@ 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",
"interpolation": InterpolationMode.BILINEAR,
"size": (240, 240),
"acc@1": 79.838,
"acc@5": 94.934,
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4 changes: 1 addition & 3 deletions torchvision/models/googlenet.py
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Expand Up @@ -8,7 +8,7 @@
import torch.nn.functional as F
from torch import Tensor

from ..transforms._presets import ImageClassification, InterpolationMode
from ..transforms._presets import ImageClassification
from ..utils import _log_api_usage_once
from ._api import WeightsEnum, Weights
from ._meta import _IMAGENET_CATEGORIES
Expand Down Expand Up @@ -282,12 +282,10 @@ class GoogLeNet_Weights(WeightsEnum):
meta={
"task": "image_classification",
"architecture": "GoogLeNet",
"publication_year": 2014,
"num_params": 6624904,
"size": (224, 224),
"min_size": (15, 15),
"categories": _IMAGENET_CATEGORIES,
"interpolation": InterpolationMode.BILINEAR,
"recipe": "https://github.com/pytorch/vision/tree/main/references/classification#googlenet",
"acc@1": 69.778,
"acc@5": 89.530,
Expand Down
4 changes: 1 addition & 3 deletions torchvision/models/inception.py
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Expand Up @@ -7,7 +7,7 @@
import torch.nn.functional as F
from torch import nn, Tensor

from ..transforms._presets import ImageClassification, InterpolationMode
from ..transforms._presets import ImageClassification
from ..utils import _log_api_usage_once
from ._api import WeightsEnum, Weights
from ._meta import _IMAGENET_CATEGORIES
Expand Down Expand Up @@ -414,12 +414,10 @@ class Inception_V3_Weights(WeightsEnum):
meta={
"task": "image_classification",
"architecture": "InceptionV3",
"publication_year": 2015,
"num_params": 27161264,
"size": (299, 299),
"min_size": (75, 75),
"categories": _IMAGENET_CATEGORIES,
"interpolation": InterpolationMode.BILINEAR,
"recipe": "https://github.com/pytorch/vision/tree/main/references/classification#inception-v3",
"acc@1": 77.294,
"acc@5": 93.450,
Expand Down
4 changes: 1 addition & 3 deletions torchvision/models/mnasnet.py
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Expand Up @@ -6,7 +6,7 @@
import torch.nn as nn
from torch import Tensor

from ..transforms._presets import ImageClassification, InterpolationMode
from ..transforms._presets import ImageClassification
from ..utils import _log_api_usage_once
from ._api import WeightsEnum, Weights
from ._meta import _IMAGENET_CATEGORIES
Expand Down Expand Up @@ -214,11 +214,9 @@ def _load_from_state_dict(
_COMMON_META = {
"task": "image_classification",
"architecture": "MNASNet",
"publication_year": 2018,
"size": (224, 224),
"min_size": (1, 1),
"categories": _IMAGENET_CATEGORIES,
"interpolation": InterpolationMode.BILINEAR,
"recipe": "https://github.com/1e100/mnasnet_trainer",
}

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4 changes: 1 addition & 3 deletions torchvision/models/mobilenetv2.py
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Expand Up @@ -7,7 +7,7 @@
from torch import nn

from ..ops.misc import Conv2dNormActivation
from ..transforms._presets import ImageClassification, InterpolationMode
from ..transforms._presets import ImageClassification
from ..utils import _log_api_usage_once
from ._api import WeightsEnum, Weights
from ._meta import _IMAGENET_CATEGORIES
Expand Down Expand Up @@ -197,12 +197,10 @@ def forward(self, x: Tensor) -> Tensor:
_COMMON_META = {
"task": "image_classification",
"architecture": "MobileNetV2",
"publication_year": 2018,
"num_params": 3504872,
"size": (224, 224),
"min_size": (1, 1),
"categories": _IMAGENET_CATEGORIES,
"interpolation": InterpolationMode.BILINEAR,
}


Expand Down
4 changes: 1 addition & 3 deletions torchvision/models/mobilenetv3.py
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Expand Up @@ -6,7 +6,7 @@
from torch import nn, Tensor

from ..ops.misc import Conv2dNormActivation, SqueezeExcitation as SElayer
from ..transforms._presets import ImageClassification, InterpolationMode
from ..transforms._presets import ImageClassification
from ..utils import _log_api_usage_once
from ._api import WeightsEnum, Weights
from ._meta import _IMAGENET_CATEGORIES
Expand Down Expand Up @@ -306,11 +306,9 @@ def _mobilenet_v3(
_COMMON_META = {
"task": "image_classification",
"architecture": "MobileNetV3",
"publication_year": 2019,
"size": (224, 224),
"min_size": (1, 1),
"categories": _IMAGENET_CATEGORIES,
"interpolation": InterpolationMode.BILINEAR,
}


Expand Down
4 changes: 1 addition & 3 deletions torchvision/models/optical_flow/raft.py
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Expand Up @@ -8,7 +8,7 @@
from torch.nn.modules.instancenorm import InstanceNorm2d
from torchvision.ops import Conv2dNormActivation

from ...transforms._presets import OpticalFlow, InterpolationMode
from ...transforms._presets import OpticalFlow
from ...utils import _log_api_usage_once
from .._api import Weights, WeightsEnum
from .._utils import handle_legacy_interface
Expand Down Expand Up @@ -514,8 +514,6 @@ def forward(self, image1, image2, num_flow_updates: int = 12):
_COMMON_META = {
"task": "optical_flow",
"architecture": "RAFT",
"publication_year": 2020,
"interpolation": InterpolationMode.BILINEAR,
}


Expand Down
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