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github.com/a1600012888/YOPO-You-Only-Propagate-Once
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Functions
230 in github.com/a1600012888/YOPO-You-Only-Propagate-Once
⨍
Functions
230
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Types & classes
65
Method
forward
(self, x)
experiments/CIFAR10/pre-res18.pgd10/network.py:133
Method
forward
(self, x, p)
experiments/CIFAR10/pre-res18.yopo-5-3/loss.py:15
Method
forward
(self, x)
experiments/CIFAR10/pre-res18.yopo-5-3/network.py:28
Method
forward
(self, x)
experiments/CIFAR10/pre-res18.yopo-5-3/network.py:68
Method
forward
(self, x)
experiments/CIFAR10/pre-res18.yopo-5-3/network.py:89
Method
forward
(self, x)
experiments/CIFAR10/pre-res18.yopo-5-3/network.py:122
Method
forward
(self, x, p)
experiments/CIFAR10/wide34.yopo-5-3/loss.py:15
Method
forward
(self, x, p)
experiments/MNIST/YOPO-5-10/loss.py:15
Method
forward
(self, input)
experiments/MNIST/YOPO-5-10/network.py:54
Method
lib_dir
(self)
lib/training/config.py:34
Method
log_dir
(self)
lib/training/config.py:19
Function
mkdir
(path)
lib/utils/misc.py:68
Method
model_dir
(self)
lib/training/config.py:25
Method
num_epochs
(self)
lib/training/config.py:39
Function
save_args
(args, save_dir = None)
lib/utils/misc.py:55
Function
test
()
lib/base_model/network.py:146
Function
test
()
lib/base_model/small_cnn.py:75
Function
test
()
lib/base_model/preact_resnet.py:140
Function
test
()
experiments/CIFAR10-TRADES/pre-res18.TRADES-YOPO-2-5/network.py:135
Function
test
()
experiments/CIFAR10-TRADES/baseline.res-pre18.TRADES.10step/network.py:10
Function
test
()
experiments/CIFAR10-TRADES/pre-res18.TRADES-YOPO-3-4/network.py:135
Function
test
()
experiments/CIFAR10/wide34.natural/network.py:8
Function
test
()
experiments/CIFAR10/pre-res18.pgd10/network.py:146
Function
test
()
experiments/CIFAR10/pre-res18.yopo-5-3/network.py:135
Function
test
()
experiments/CIFAR10/wide34.pgd10/network.py:8
Function
test
()
experiments/CIFAR10/wide34.yopo-5-3/network.py:8
Function
test
()
experiments/MNIST/YOPO-5-10/network.py:67
Function
test
()
experiments/MNIST/pgd40/network.py:9
Function
train_one_epoch
:param attack_freq: Frequencies of training with adversarial examples. -1 indicates natural training :param AttackMethod: the attack method
lib/training/train.py:12
Method
val_interval
Specify how many epochs between two validation steps Return <= 0 means no validation phase
lib/training/config.py:43
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