Revert D36402214 for torchvision

Reviewed By: datumbox

Differential Revision: D36413349

fbshipit-source-id: 5fbcd7c993151b792d831e3591547e2e507cb0ed

Author: NicolasHug

hubconf.py

@@ -2,18 +2,8 @@
 dependencies = ["torch"]
 
 from torchvision.models.alexnet import alexnet
-from torchvision.models.convnext import (
-    convnext_base,
-    convnext_large,
-    convnext_small,
-    convnext_tiny,
-)
-from torchvision.models.densenet import (
-    densenet121,
-    densenet161,
-    densenet169,
-    densenet201,
-)
+from torchvision.models.convnext import convnext_tiny, convnext_small, convnext_base, convnext_large
+from torchvision.models.densenet import densenet121, densenet169, densenet201, densenet161
 from torchvision.models.efficientnet import (
     efficientnet_b0,
     efficientnet_b1,
@@ -23,9 +13,9 @@
     efficientnet_b5,
     efficientnet_b6,
     efficientnet_b7,
-    efficientnet_v2_l,
-    efficientnet_v2_m,
     efficientnet_v2_s,
+    efficientnet_v2_m,
+    efficientnet_v2_l,
 )
 from torchvision.models.googlenet import googlenet
 from torchvision.models.inception import inception_v3
@@ -34,39 +24,39 @@
 from torchvision.models.mobilenetv3 import mobilenet_v3_large, mobilenet_v3_small
 from torchvision.models.optical_flow import raft_large, raft_small
 from torchvision.models.regnet import (
-    regnet_x_16gf,
-    regnet_x_1_6gf,
-    regnet_x_32gf,
-    regnet_x_3_2gf,
-    regnet_x_400mf,
-    regnet_x_800mf,
-    regnet_x_8gf,
-    regnet_y_128gf,
-    regnet_y_16gf,
-    regnet_y_1_6gf,
-    regnet_y_32gf,
-    regnet_y_3_2gf,
     regnet_y_400mf,
     regnet_y_800mf,
+    regnet_y_1_6gf,
+    regnet_y_3_2gf,
     regnet_y_8gf,
+    regnet_y_16gf,
+    regnet_y_32gf,
+    regnet_y_128gf,
+    regnet_x_400mf,
+    regnet_x_800mf,
+    regnet_x_1_6gf,
+    regnet_x_3_2gf,
+    regnet_x_8gf,
+    regnet_x_16gf,
+    regnet_x_32gf,
 )
 from torchvision.models.resnet import (
-    resnet101,
-    resnet152,
     resnet18,
     resnet34,
     resnet50,
-    resnext101_32x8d,
+    resnet101,
+    resnet152,
     resnext50_32x4d,
-    wide_resnet101_2,
+    resnext101_32x8d,
     wide_resnet50_2,
+    wide_resnet101_2,
 )
 from torchvision.models.segmentation import (
-    deeplabv3_mobilenet_v3_large,
-    deeplabv3_resnet101,
-    deeplabv3_resnet50,
-    fcn_resnet101,
     fcn_resnet50,
+    fcn_resnet101,
+    deeplabv3_resnet50,
+    deeplabv3_resnet101,
+    deeplabv3_mobilenet_v3_large,
     lraspp_mobilenet_v3_large,
 )
 from torchvision.models.shufflenetv2 import (
@@ -76,20 +66,11 @@
     shufflenet_v2_x2_0,
 )
 from torchvision.models.squeezenet import squeezenet1_0, squeezenet1_1
-from torchvision.models.vgg import (
-    vgg11,
-    vgg11_bn,
-    vgg13,
-    vgg13_bn,
-    vgg16,
-    vgg16_bn,
-    vgg19,
-    vgg19_bn,
-)
+from torchvision.models.vgg import vgg11, vgg13, vgg16, vgg19, vgg11_bn, vgg13_bn, vgg16_bn, vgg19_bn
 from torchvision.models.vision_transformer import (
     vit_b_16,
     vit_b_32,
-    vit_h_14,
     vit_l_16,
     vit_l_32,
+    vit_h_14,
 )

references/classification/train_quantization.py

@@ -9,7 +9,7 @@
 import torchvision
 import utils
 from torch import nn
-from train import evaluate, load_data, train_one_epoch
+from train import train_one_epoch, evaluate, load_data
 
 
 def main(args):

references/detection/group_by_aspect_ratio.py

@@ -2,7 +2,7 @@
 import copy
 import math
 from collections import defaultdict
-from itertools import chain, repeat
+from itertools import repeat, chain
 
 import numpy as np
 import torch

references/detection/train.py

@@ -29,8 +29,8 @@
 import torchvision.models.detection.mask_rcnn
 import utils
 from coco_utils import get_coco, get_coco_kp
-from engine import evaluate, train_one_epoch
-from group_by_aspect_ratio import create_aspect_ratio_groups, GroupedBatchSampler
+from engine import train_one_epoch, evaluate
+from group_by_aspect_ratio import GroupedBatchSampler, create_aspect_ratio_groups
 
 
 def get_dataset(name, image_set, transform, data_path):

references/detection/transforms.py

@@ -1,9 +1,10 @@
-from typing import Dict, List, Optional, Tuple, Union
+from typing import List, Tuple, Dict, Optional, Union
 
 import torch
 import torchvision
 from torch import nn, Tensor
-from torchvision.transforms import functional as F, InterpolationMode, transforms as T
+from torchvision.transforms import functional as F
+from torchvision.transforms import transforms as T, InterpolationMode
 
 
 def _flip_coco_person_keypoints(kps, width):

references/optical_flow/train.py

@@ -6,8 +6,8 @@
 import torch
 import torchvision.models.optical_flow
 import utils
-from presets import OpticalFlowPresetEval, OpticalFlowPresetTrain
-from torchvision.datasets import FlyingChairs, FlyingThings3D, HD1K, KittiFlow, Sintel
+from presets import OpticalFlowPresetTrain, OpticalFlowPresetEval
+from torchvision.datasets import KittiFlow, FlyingChairs, FlyingThings3D, Sintel, HD1K
 
 
 def get_train_dataset(stage, dataset_root):

references/optical_flow/utils.py

@@ -1,7 +1,8 @@
 import datetime
 import os
 import time
-from collections import defaultdict, deque
+from collections import defaultdict
+from collections import deque
 
 import torch
 import torch.distributed as dist

references/video_classification/presets.py

@@ -1,6 +1,6 @@
 import torch
 from torchvision.transforms import transforms
-from transforms import ConvertBCHWtoCBHW, ConvertBHWCtoBCHW
+from transforms import ConvertBHWCtoBCHW, ConvertBCHWtoCBHW
 
 
 class VideoClassificationPresetTrain:

references/video_classification/train.py

@@ -11,11 +11,7 @@
 import utils
 from torch import nn
 from torch.utils.data.dataloader import default_collate
-from torchvision.datasets.samplers import (
-    DistributedSampler,
-    RandomClipSampler,
-    UniformClipSampler,
-)
+from torchvision.datasets.samplers import DistributedSampler, UniformClipSampler, RandomClipSampler
 
 
 def train_one_epoch(model, criterion, optimizer, lr_scheduler, data_loader, device, epoch, print_freq, scaler=None):

setup.py

@@ -7,14 +7,9 @@
 import sys
 
 import torch
-from pkg_resources import DistributionNotFound, get_distribution, parse_version
-from setuptools import find_packages, setup
-from torch.utils.cpp_extension import (
-    BuildExtension,
-    CppExtension,
-    CUDA_HOME,
-    CUDAExtension,
-)
+from pkg_resources import parse_version, get_distribution, DistributionNotFound
+from setuptools import setup, find_packages
+from torch.utils.cpp_extension import BuildExtension, CppExtension, CUDAExtension, CUDA_HOME
 
 
 def read(*names, **kwargs):

test/builtin_dataset_mocks.py

@@ -13,19 +13,13 @@
 import unittest.mock
 import warnings
 import xml.etree.ElementTree as ET
-from collections import Counter, defaultdict
+from collections import defaultdict, Counter
 
 import numpy as np
 import PIL.Image
 import pytest
 import torch
-from datasets_utils import (
-    combinations_grid,
-    create_image_file,
-    create_image_folder,
-    make_tar,
-    make_zip,
-)
+from datasets_utils import make_zip, make_tar, create_image_folder, create_image_file, combinations_grid
 from torch.nn.functional import one_hot
 from torch.testing import make_tensor as _make_tensor
 from torchvision._utils import sequence_to_str

test/conftest.py

@@ -3,13 +3,7 @@
 import numpy as np
 import pytest
 import torch
-from common_utils import (
-    CIRCLECI_GPU_NO_CUDA_MSG,
-    CUDA_NOT_AVAILABLE_MSG,
-    IN_CIRCLE_CI,
-    IN_FBCODE,
-    IN_RE_WORKER,
-)
+from common_utils import IN_CIRCLE_CI, CIRCLECI_GPU_NO_CUDA_MSG, IN_FBCODE, IN_RE_WORKER, CUDA_NOT_AVAILABLE_MSG
 
 
 def pytest_configure(config):

test/datasets_utils.py

@@ -22,7 +22,7 @@
 import torch
 import torchvision.datasets
 import torchvision.io
-from common_utils import disable_console_output, get_tmp_dir
+from common_utils import get_tmp_dir, disable_console_output
 
 
 __all__ = [

test/test_backbone_utils.py

@@ -7,15 +7,8 @@
 from common_utils import set_rng_seed
 from torchvision import models
 from torchvision.models._utils import IntermediateLayerGetter
-from torchvision.models.detection.backbone_utils import (
-    BackboneWithFPN,
-    mobilenet_backbone,
-    resnet_fpn_backbone,
-)
-from torchvision.models.feature_extraction import (
-    create_feature_extractor,
-    get_graph_node_names,
-)
+from torchvision.models.detection.backbone_utils import BackboneWithFPN, mobilenet_backbone, resnet_fpn_backbone
+from torchvision.models.feature_extraction import create_feature_extractor, get_graph_node_names
 
 
 def get_available_models():

test/test_datasets_download.py

@@ -9,15 +9,15 @@
 from os import path
 from urllib.error import HTTPError, URLError
 from urllib.parse import urlparse
-from urllib.request import Request, urlopen
+from urllib.request import urlopen, Request
 
 import pytest
 from torchvision import datasets
 from torchvision.datasets.utils import (
-    _get_redirect_url,
+    download_url,
     check_integrity,
     download_file_from_google_drive,
-    download_url,
+    _get_redirect_url,
     USER_AGENT,
 )
 

test/test_datasets_samplers.py

@@ -1,6 +1,6 @@
 import pytest
 import torch
-from common_utils import assert_equal, get_list_of_videos
+from common_utils import get_list_of_videos, assert_equal
 from torchvision import io
 from torchvision.datasets.samplers import (
     DistributedSampler,

test/test_datasets_video_utils.py

@@ -1,8 +1,8 @@
 import pytest
 import torch
-from common_utils import assert_equal, get_list_of_videos
+from common_utils import get_list_of_videos, assert_equal
 from torchvision import io
-from torchvision.datasets.video_utils import unfold, VideoClips
+from torchvision.datasets.video_utils import VideoClips, unfold
 
 
 class TestVideo:

test/test_extended_models.py

@@ -5,7 +5,7 @@
 import test_models as TM
 import torch
 from torchvision import models
-from torchvision.models._api import Weights, WeightsEnum
+from torchvision.models._api import WeightsEnum, Weights
 from torchvision.models._utils import handle_legacy_interface
 
 

test/test_functional_tensor.py

@@ -14,14 +14,14 @@
 import torchvision.transforms.functional_pil as F_pil
 import torchvision.transforms.functional_tensor as F_t
 from common_utils import (
-    _assert_approx_equal_tensor_to_pil,
-    _assert_equal_tensor_to_pil,
+    cpu_and_gpu,
+    needs_cuda,
     _create_data,
     _create_data_batch,
+    _assert_equal_tensor_to_pil,
+    _assert_approx_equal_tensor_to_pil,
     _test_fn_on_batch,
     assert_equal,
-    cpu_and_gpu,
-    needs_cuda,
 )
 from torchvision.transforms import InterpolationMode
 

test/test_image.py

@@ -8,21 +8,21 @@
 import pytest
 import torch
 import torchvision.transforms.functional as F
-from common_utils import assert_equal, needs_cuda
-from PIL import __version__ as PILLOW_VERSION, Image
+from common_utils import needs_cuda, assert_equal
+from PIL import Image, __version__ as PILLOW_VERSION
 from torchvision.io.image import (
-    _read_png_16,
-    decode_image,
-    decode_jpeg,
     decode_png,
+    decode_jpeg,
     encode_jpeg,
+    write_jpeg,
+    decode_image,
+    read_file,
     encode_png,
+    write_png,
+    write_file,
     ImageReadMode,
-    read_file,
     read_image,
-    write_file,
-    write_jpeg,
-    write_png,
+    _read_png_16,
 )
 
 IMAGE_ROOT = os.path.join(os.path.dirname(os.path.abspath(__file__)), "assets")

test/test_models.py

@@ -14,13 +14,7 @@
 import torch.fx
 import torch.nn as nn
 from _utils_internal import get_relative_path
-from common_utils import (
-    cpu_and_gpu,
-    freeze_rng_state,
-    map_nested_tensor_object,
-    needs_cuda,
-    set_rng_seed,
-)
+from common_utils import map_nested_tensor_object, freeze_rng_state, set_rng_seed, cpu_and_gpu, needs_cuda
 from torchvision import models
 
 ACCEPT = os.getenv("EXPECTTEST_ACCEPT", "0") == "1"