Upgrade usort to `1.0.2` and black to 22.3.0 (#5106)

* upgrade usort to

* Also update black

* Actually use 1.0.2

* Apply pre-commit
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

torchvision/models/quantization/googlenet.py

@@ -8,10 +8,10 @@ from torch import Tensor
 from torch.nn import functional as F
 
 from ...transforms._presets import ImageClassification
-from .._api import WeightsEnum, Weights
+from .._api import Weights, WeightsEnum
 from .._meta import _IMAGENET_CATEGORIES
-from .._utils import handle_legacy_interface, _ovewrite_named_param
-from ..googlenet import GoogLeNetOutputs, BasicConv2d, Inception, InceptionAux, GoogLeNet, GoogLeNet_Weights
+from .._utils import _ovewrite_named_param, handle_legacy_interface
+from ..googlenet import BasicConv2d, GoogLeNet, GoogLeNet_Weights, GoogLeNetOutputs, Inception, InceptionAux
 from .utils import _fuse_modules, _replace_relu, quantize_model
 
 

torchvision/models/quantization/inception.py

@@ -7,12 +7,12 @@ import torch.nn as nn
 import torch.nn.functional as F
 from torch import Tensor
 from torchvision.models import inception as inception_module
-from torchvision.models.inception import InceptionOutputs, Inception_V3_Weights
+from torchvision.models.inception import Inception_V3_Weights, InceptionOutputs
 
 from ...transforms._presets import ImageClassification
-from .._api import WeightsEnum, Weights
+from .._api import Weights, WeightsEnum
 from .._meta import _IMAGENET_CATEGORIES
-from .._utils import handle_legacy_interface, _ovewrite_named_param
+from .._utils import _ovewrite_named_param, handle_legacy_interface
 from .utils import _fuse_modules, _replace_relu, quantize_model
 
 

torchvision/models/quantization/mobilenetv2.py

 from functools import partial
 from typing import Any, Optional, Union
 
-from torch import Tensor
-from torch import nn
-from torch.ao.quantization import QuantStub, DeQuantStub
-from torchvision.models.mobilenetv2 import InvertedResidual, MobileNetV2, MobileNet_V2_Weights
+from torch import nn, Tensor
+from torch.ao.quantization import DeQuantStub, QuantStub
+from torchvision.models.mobilenetv2 import InvertedResidual, MobileNet_V2_Weights, MobileNetV2
 
 from ...ops.misc import Conv2dNormActivation
 from ...transforms._presets import ImageClassification
-from .._api import WeightsEnum, Weights
+from .._api import Weights, WeightsEnum
 from .._meta import _IMAGENET_CATEGORIES
-from .._utils import handle_legacy_interface, _ovewrite_named_param
+from .._utils import _ovewrite_named_param, handle_legacy_interface
 from .utils import _fuse_modules, _replace_relu, quantize_model
 
 

torchvision/models/quantization/mobilenetv3.py

@@ -3,19 +3,19 @@ from typing import Any, List, Optional, Union
 
 import torch
 from torch import nn, Tensor
-from torch.ao.quantization import QuantStub, DeQuantStub
+from torch.ao.quantization import DeQuantStub, QuantStub
 
 from ...ops.misc import Conv2dNormActivation, SqueezeExcitation
 from ...transforms._presets import ImageClassification
-from .._api import WeightsEnum, Weights
+from .._api import Weights, WeightsEnum
 from .._meta import _IMAGENET_CATEGORIES
-from .._utils import handle_legacy_interface, _ovewrite_named_param
+from .._utils import _ovewrite_named_param, handle_legacy_interface
 from ..mobilenetv3 import (
+    _mobilenet_v3_conf,
     InvertedResidual,
     InvertedResidualConfig,
-    MobileNetV3,
-    _mobilenet_v3_conf,
     MobileNet_V3_Large_Weights,
+    MobileNetV3,
 )
 from .utils import _fuse_modules, _replace_relu
 

torchvision/models/quantization/resnet.py

 from functools import partial
-from typing import Any, Type, Union, List, Optional
+from typing import Any, List, Optional, Type, Union
 
 import torch
 import torch.nn as nn
 from torch import Tensor
 from torchvision.models.resnet import (
-    Bottleneck,
     BasicBlock,
+    Bottleneck,
     ResNet,
     ResNet18_Weights,
     ResNet50_Weights,
@@ -15,9 +15,9 @@ from torchvision.models.resnet import (
 )
 
 from ...transforms._presets import ImageClassification
-from .._api import WeightsEnum, Weights
+from .._api import Weights, WeightsEnum
 from .._meta import _IMAGENET_CATEGORIES
-from .._utils import handle_legacy_interface, _ovewrite_named_param
+from .._utils import _ovewrite_named_param, handle_legacy_interface
 from .utils import _fuse_modules, _replace_relu, quantize_model
 
 

torchvision/models/quantization/shufflenetv2.py

@@ -7,9 +7,9 @@ from torch import Tensor
 from torchvision.models import shufflenetv2
 
 from ...transforms._presets import ImageClassification
-from .._api import WeightsEnum, Weights
+from .._api import Weights, WeightsEnum
 from .._meta import _IMAGENET_CATEGORIES
-from .._utils import handle_legacy_interface, _ovewrite_named_param
+from .._utils import _ovewrite_named_param, handle_legacy_interface
 from ..shufflenetv2 import (
     ShuffleNet_V2_X0_5_Weights,
     ShuffleNet_V2_X1_0_Weights,

torchvision/models/regnet.py

@@ -9,9 +9,9 @@ from torch import nn, Tensor
 from ..ops.misc import Conv2dNormActivation, SqueezeExcitation
 from ..transforms._presets import ImageClassification, InterpolationMode
 from ..utils import _log_api_usage_once
-from ._api import WeightsEnum, Weights
+from ._api import Weights, WeightsEnum
 from ._meta import _IMAGENET_CATEGORIES
-from ._utils import handle_legacy_interface, _ovewrite_named_param, _make_divisible
+from ._utils import _make_divisible, _ovewrite_named_param, handle_legacy_interface
 
 
 __all__ = [

torchvision/models/resnet.py

 from functools import partial
-from typing import Type, Any, Callable, Union, List, Optional
+from typing import Any, Callable, List, Optional, Type, Union
 
 import torch
 import torch.nn as nn
@@ -7,9 +7,9 @@ from torch import Tensor
 
 from ..transforms._presets import ImageClassification
 from ..utils import _log_api_usage_once
-from ._api import WeightsEnum, Weights
+from ._api import Weights, WeightsEnum
 from ._meta import _IMAGENET_CATEGORIES
-from ._utils import handle_legacy_interface, _ovewrite_named_param
+from ._utils import _ovewrite_named_param, handle_legacy_interface
 
 
 __all__ = [

torchvision/models/segmentation/_utils.py

 from collections import OrderedDict
-from typing import Optional, Dict
+from typing import Dict, Optional
 
 from torch import nn, Tensor
 from torch.nn import functional as F

torchvision/models/segmentation/deeplabv3.py

@@ -6,11 +6,11 @@ from torch import nn
 from torch.nn import functional as F
 
 from ...transforms._presets import SemanticSegmentation
-from .._api import WeightsEnum, Weights
+from .._api import Weights, WeightsEnum
 from .._meta import _VOC_CATEGORIES
-from .._utils import IntermediateLayerGetter, handle_legacy_interface, _ovewrite_value_param
-from ..mobilenetv3 import MobileNetV3, MobileNet_V3_Large_Weights, mobilenet_v3_large
-from ..resnet import ResNet, resnet50, resnet101, ResNet50_Weights, ResNet101_Weights
+from .._utils import _ovewrite_value_param, handle_legacy_interface, IntermediateLayerGetter
+from ..mobilenetv3 import mobilenet_v3_large, MobileNet_V3_Large_Weights, MobileNetV3
+from ..resnet import ResNet, resnet101, ResNet101_Weights, resnet50, ResNet50_Weights
 from ._utils import _SimpleSegmentationModel
 from .fcn import FCNHead
 

torchvision/models/segmentation/fcn.py

@@ -4,10 +4,10 @@ from typing import Any, Optional
 from torch import nn
 
 from ...transforms._presets import SemanticSegmentation
-from .._api import WeightsEnum, Weights
+from .._api import Weights, WeightsEnum
 from .._meta import _VOC_CATEGORIES
-from .._utils import IntermediateLayerGetter, handle_legacy_interface, _ovewrite_value_param
-from ..resnet import ResNet, ResNet50_Weights, ResNet101_Weights, resnet50, resnet101
+from .._utils import _ovewrite_value_param, handle_legacy_interface, IntermediateLayerGetter
+from ..resnet import ResNet, resnet101, ResNet101_Weights, resnet50, ResNet50_Weights
 from ._utils import _SimpleSegmentationModel
 
 

torchvision/models/segmentation/lraspp.py

@@ -7,10 +7,10 @@ from torch.nn import functional as F
 
 from ...transforms._presets import SemanticSegmentation
 from ...utils import _log_api_usage_once
-from .._api import WeightsEnum, Weights
+from .._api import Weights, WeightsEnum
 from .._meta import _VOC_CATEGORIES
-from .._utils import IntermediateLayerGetter, handle_legacy_interface, _ovewrite_value_param
-from ..mobilenetv3 import MobileNetV3, MobileNet_V3_Large_Weights, mobilenet_v3_large
+from .._utils import _ovewrite_value_param, handle_legacy_interface, IntermediateLayerGetter
+from ..mobilenetv3 import mobilenet_v3_large, MobileNet_V3_Large_Weights, MobileNetV3
 
 
 __all__ = ["LRASPP", "LRASPP_MobileNet_V3_Large_Weights", "lraspp_mobilenet_v3_large"]

torchvision/models/shufflenetv2.py

 from functools import partial
-from typing import Callable, Any, List, Optional
+from typing import Any, Callable, List, Optional
 
 import torch
 import torch.nn as nn
@@ -7,9 +7,9 @@ from torch import Tensor
 
 from ..transforms._presets import ImageClassification
 from ..utils import _log_api_usage_once
-from ._api import WeightsEnum, Weights
+from ._api import Weights, WeightsEnum
 from ._meta import _IMAGENET_CATEGORIES
-from ._utils import handle_legacy_interface, _ovewrite_named_param
+from ._utils import _ovewrite_named_param, handle_legacy_interface
 
 
 __all__ = [

torchvision/models/squeezenet.py

@@ -7,9 +7,9 @@ import torch.nn.init as init
 
 from ..transforms._presets import ImageClassification
 from ..utils import _log_api_usage_once
-from ._api import WeightsEnum, Weights
+from ._api import Weights, WeightsEnum
 from ._meta import _IMAGENET_CATEGORIES
-from ._utils import handle_legacy_interface, _ovewrite_named_param
+from ._utils import _ovewrite_named_param, handle_legacy_interface
 
 
 __all__ = ["SqueezeNet", "SqueezeNet1_0_Weights", "SqueezeNet1_1_Weights", "squeezenet1_0", "squeezenet1_1"]

torchvision/models/swin_transformer.py

 from functools import partial
-from typing import Optional, Callable, List, Any
+from typing import Any, Callable, List, Optional
 
 import torch
 import torch.nn.functional as F
@@ -9,7 +9,7 @@ from ..ops.misc import MLP, Permute
 from ..ops.stochastic_depth import StochasticDepth
 from ..transforms._presets import ImageClassification, InterpolationMode
 from ..utils import _log_api_usage_once
-from ._api import WeightsEnum, Weights
+from ._api import Weights, WeightsEnum
 from ._meta import _IMAGENET_CATEGORIES
 from ._utils import _ovewrite_named_param
 
@@ -366,7 +366,7 @@ class SwinTransformer(nn.Module):
         # build SwinTransformer blocks
         for i_stage in range(len(depths)):
             stage: List[nn.Module] = []
-            dim = embed_dim * 2 ** i_stage
+            dim = embed_dim * 2**i_stage
             for i_layer in range(depths[i_stage]):
                 # adjust stochastic depth probability based on the depth of the stage block
                 sd_prob = stochastic_depth_prob * float(stage_block_id) / (total_stage_blocks - 1)

torchvision/models/vgg.py

 from functools import partial
-from typing import Union, List, Dict, Any, Optional, cast
+from typing import Any, cast, Dict, List, Optional, Union
 
 import torch
 import torch.nn as nn
 
 from ..transforms._presets import ImageClassification
 from ..utils import _log_api_usage_once
-from ._api import WeightsEnum, Weights
+from ._api import Weights, WeightsEnum
 from ._meta import _IMAGENET_CATEGORIES
-from ._utils import handle_legacy_interface, _ovewrite_named_param
+from ._utils import _ovewrite_named_param, handle_legacy_interface
 
 
 __all__ = [

torchvision/models/video/mvit.py

@@ -7,10 +7,10 @@ import torch
 import torch.fx
 import torch.nn as nn
 
-from ...ops import StochasticDepth, MLP
+from ...ops import MLP, StochasticDepth
 from ...transforms._presets import VideoClassification
 from ...utils import _log_api_usage_once
-from .._api import WeightsEnum, Weights
+from .._api import Weights, WeightsEnum
 from .._meta import _KINETICS400_CATEGORIES
 from .._utils import _ovewrite_named_param
 

torchvision/models/video/resnet.py

 from functools import partial
-from typing import Tuple, Optional, Callable, List, Sequence, Type, Any, Union
+from typing import Any, Callable, List, Optional, Sequence, Tuple, Type, Union
 
 import torch.nn as nn
 from torch import Tensor
 
 from ...transforms._presets import VideoClassification
 from ...utils import _log_api_usage_once
-from .._api import WeightsEnum, Weights
+from .._api import Weights, WeightsEnum
 from .._meta import _KINETICS400_CATEGORIES
-from .._utils import handle_legacy_interface, _ovewrite_named_param
+from .._utils import _ovewrite_named_param, handle_legacy_interface
 
 
 __all__ = [

torchvision/models/vision_transformer.py

 import math
 from collections import OrderedDict
 from functools import partial
-from typing import Any, Callable, List, NamedTuple, Optional, Dict
+from typing import Any, Callable, Dict, List, NamedTuple, Optional
 
 import torch
 import torch.nn as nn
@@ -9,9 +9,9 @@ import torch.nn as nn
 from ..ops.misc import Conv2dNormActivation, MLP
 from ..transforms._presets import ImageClassification, InterpolationMode
 from ..utils import _log_api_usage_once
-from ._api import WeightsEnum, Weights
+from ._api import Weights, WeightsEnum
 from ._meta import _IMAGENET_CATEGORIES
-from ._utils import handle_legacy_interface, _ovewrite_named_param
+from ._utils import _ovewrite_named_param, handle_legacy_interface
 
 
 __all__ = [

torchvision/ops/__init__.py

 from ._register_onnx_ops import _register_custom_op
 from .boxes import (
-    nms,
     batched_nms,
-    remove_small_boxes,
-    clip_boxes_to_image,
     box_area,
     box_convert,
     box_iou,
-    generalized_box_iou,
-    distance_box_iou,
+    clip_boxes_to_image,
     complete_box_iou,
+    distance_box_iou,
+    generalized_box_iou,
     masks_to_boxes,
+    nms,
+    remove_small_boxes,
 )
 from .ciou_loss import complete_box_iou_loss
 from .deform_conv import deform_conv2d, DeformConv2d
 from .diou_loss import distance_box_iou_loss
-from .drop_block import drop_block2d, DropBlock2d, drop_block3d, DropBlock3d
+from .drop_block import drop_block2d, drop_block3d, DropBlock2d, DropBlock3d
 from .feature_pyramid_network import FeaturePyramidNetwork
 from .focal_loss import sigmoid_focal_loss
 from .giou_loss import generalized_box_iou_loss
-from .misc import FrozenBatchNorm2d, Conv2dNormActivation, Conv3dNormActivation, SqueezeExcitation, MLP, Permute
+from .misc import Conv2dNormActivation, Conv3dNormActivation, FrozenBatchNorm2d, MLP, Permute, SqueezeExcitation
 from .poolers import MultiScaleRoIAlign
 from .ps_roi_align import ps_roi_align, PSRoIAlign
 from .ps_roi_pool import ps_roi_pool, PSRoIPool