remove unnecessary imports

Author: thucbx99

examples/domain_adaptation/image_classification/afn.py

@@ -5,7 +5,6 @@
 import random
 import time
 import warnings
-import sys
 import argparse
 import shutil
 import os.path as osp

examples/domain_adaptation/image_classification/bsp.py

@@ -5,7 +5,6 @@
 import random
 import time
 import warnings
-import sys
 import argparse
 import shutil
 import os.path as osp

examples/domain_adaptation/image_classification/cdan.py

@@ -5,7 +5,6 @@
 import random
 import time
 import warnings
-import sys
 import argparse
 import shutil
 import os.path as osp

examples/domain_adaptation/image_classification/dan.py

@@ -5,7 +5,6 @@
 import random
 import time
 import warnings
-import sys
 import argparse
 import shutil
 import os.path as osp

examples/domain_adaptation/image_classification/dann.py

@@ -5,7 +5,6 @@
 import random
 import time
 import warnings
-import sys
 import argparse
 import shutil
 import os.path as osp

examples/domain_adaptation/image_classification/jan.py

@@ -5,7 +5,6 @@
 import random
 import time
 import warnings
-import sys
 import argparse
 import shutil
 import os.path as osp

examples/domain_adaptation/image_classification/mcc.py

@@ -5,7 +5,6 @@
 import random
 import time
 import warnings
-import sys
 import argparse
 import shutil
 import os.path as osp

examples/domain_adaptation/image_classification/mcd.py

@@ -5,7 +5,6 @@
 import random
 import time
 import warnings
-import sys
 import argparse
 import shutil
 import os.path as osp

examples/domain_adaptation/image_classification/mdd.py

@@ -5,7 +5,6 @@
 import random
 import time
 import warnings
-import sys
 import argparse
 import os.path as osp
 import shutil

examples/semi_supervised_learning/image_classification/utils.py

@@ -12,9 +12,7 @@
 import torch.nn.functional as F
 from torch.optim.lr_scheduler import LambdaLR
 from torch.utils.data.dataset import Subset, ConcatDataset
-import torchvision
 import torchvision.transforms as T
-from torchvision.datasets.folder import default_loader
 import timm
 from timm.data.auto_augment import auto_augment_transform, rand_augment_transform