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Functions209 in github.com/LAMDA-CL/CVPR22-Fact

⨍ Functions 209◇ Types & classes 48
Method__getitem__
(self, index)
dataloader/cifar100/cifar.py:243
Method__getitem__
(self, i)
dataloader/miniimagenet/miniimagenet.py:129
Method__getitem__
(self, i)
dataloader/miniimagenet/miniimagenet.py:167
Method__getitem__
(self, i)
dataloader/cub200/cub200.py:147
Method__getitem__
(self, i)
dataloader/cub200/cub200.py:181
Method__getitem__
(self, i)
dataloader/imagenet100/ImageNet.py:132
Method__getitem__
(self, i)
dataloader/imagenet100/ImageNet.py:170
Method__init__
(self)
utils.py:49
Method__init__
(self)
utils.py:63
Method__init__
(self, label, n_batch, n_cls, n_per, )
dataloader/sampler.py:8
Method__init__
(self, label, n_batch, n_cls, n_per, )
dataloader/sampler.py:42
Method__init__
(self, label, n_batch, n_cls, n_per,)
dataloader/sampler.py:76
Method__init__
(self, root='/data/zhoudw/FSCIL', train=True, transform=None, index_path=Non
dataloader/imagenet1000/ImageNet.py:13
Method__init__
(self, train,x1,y1,x2,y2)
dataloader/imagenet1000/ImageNet.py:140
Method__init__
(self, fillcolor=(128, 128, 128))
dataloader/imagenet1000/autoaugment.py:13
Method__init__
(self, fillcolor=(128, 128, 128))
dataloader/imagenet1000/autoaugment.py:54
Method__init__
(self, fillcolor=(128, 128, 128))
dataloader/imagenet1000/autoaugment.py:96
Method__init__
(self, p1, operation1, magnitude_idx1, p2, operation2, magnitude_idx2, fillcolor=(128, 128, 128))
dataloader/imagenet1000/autoaugment.py:138
Method__init__
(self, root, train=True, transform=None, target_transform=None, download=False, index=None, b
dataloader/cifar100/cifar.py:52
Method__init__
(self, train,x1,y1,x2,y2)
dataloader/cifar100/cifar.py:222
Method__init__
(self, n_holes, length)
dataloader/cifar100/autoaugment.py:8
Method__init__
(self, fillcolor=(128, 128, 128))
dataloader/cifar100/autoaugment.py:48
Method__init__
(self, fillcolor=(128, 128, 128))
dataloader/cifar100/autoaugment.py:103
Method__init__
(self, fillcolor=(128, 128, 128))
dataloader/cifar100/autoaugment.py:158
Method__init__
(self, p1, operation1, magnitude_idx1, p2, operation2, magnitude_idx2, fillcolor=(128, 128, 128))
dataloader/cifar100/autoaugment.py:201
Method__init__
(self, root='/data/zhoudw/FSCIL', train=True, transform=None, index_path=Non
dataloader/miniimagenet/miniimagenet.py:13
Method__init__
(self, train,x1,y1,x2,y2)
dataloader/miniimagenet/miniimagenet.py:137
Method__init__
(self, fillcolor=(128, 128, 128))
dataloader/miniimagenet/autoaugment.py:13
Method__init__
(self, fillcolor=(128, 128, 128))
dataloader/miniimagenet/autoaugment.py:54
Method__init__
(self, fillcolor=(128, 128, 128))
dataloader/miniimagenet/autoaugment.py:96
Method__init__
(self, p1, operation1, magnitude_idx1, p2, operation2, magnitude_idx2, fillcolor=(128, 128, 128))
dataloader/miniimagenet/autoaugment.py:138
Method__init__
(self, root='/data/zhoudw/FSCIL', train=True, index_path=None, index=None, base_sess=None,aut
dataloader/cub200/cub200.py:13
Method__init__
(self, train,x1,y1,x2,y2)
dataloader/cub200/cub200.py:154
Method__init__
(self, fillcolor=(128, 128, 128))
dataloader/cub200/autoaugment.py:13
Method__init__
(self, fillcolor=(128, 128, 128))
dataloader/cub200/autoaugment.py:54
Method__init__
(self, fillcolor=(128, 128, 128))
dataloader/cub200/autoaugment.py:96
Method__init__
(self, p1, operation1, magnitude_idx1, p2, operation2, magnitude_idx2, fillcolor=(128, 128, 128))
dataloader/cub200/autoaugment.py:138
Method__init__
(self, root='/data/zhoudw/FSCIL', train=True, transform=None, index_path=Non
dataloader/imagenet100/ImageNet.py:13
Method__init__
(self, train,x1,y1,x2,y2)
dataloader/imagenet100/ImageNet.py:140
Method__init__
(self, fillcolor=(128, 128, 128))
dataloader/imagenet100/autoaugment.py:13
Method__init__
(self, fillcolor=(128, 128, 128))
dataloader/imagenet100/autoaugment.py:54
Method__init__
(self, fillcolor=(128, 128, 128))
dataloader/imagenet100/autoaugment.py:96
Method__init__
(self, p1, operation1, magnitude_idx1, p2, operation2, magnitude_idx2, fillcolor=(128, 128, 128))
dataloader/imagenet100/autoaugment.py:138
Method__init__
(self, inplanes, planes, stride=1, downsample=None, groups=1, base_width=64, dilation=1, norm
models/resnet18_encoder.py:160
Method__init__
(self, inplanes, planes, stride=1, downsample=None, groups=1, base_width=64, dilation=1, norm
models/resnet18_encoder.py:200
Method__init__
(self, inplanes, planes, stride=1, downsample=None, last=False)
models/resnet20_cifar.py:13
Method__init__
(self, args, mode=None)
models/fact/Network.py:12
Method__init__
(self, args)
models/fact/base.py:13
Method__init__
(self, args)
models/fact/fscil_trainer.py:12
Method__init__
(self, args, mode=None)
models/base/Network.py:12
Method__init__
(self, args)
models/base/base.py:13
Method__init__
(self, args)
models/base/fscil_trainer.py:12
Method__iter__
(self)
dataloader/sampler.py:23
Method__iter__
(self)
dataloader/sampler.py:57
Method__iter__
(self)
dataloader/sampler.py:94
Method__len__
(self)
dataloader/sampler.py:20
Method__len__
(self)
dataloader/sampler.py:54
Method__len__
(self)
dataloader/sampler.py:91
Method__len__
(self)
dataloader/imagenet1000/ImageNet.py:129
Method__len__
(self)
dataloader/imagenet1000/ImageNet.py:167
Method__len__
(self)
dataloader/cifar100/cifar.py:199
Method__len__
(self)
dataloader/cifar100/cifar.py:254
Method__len__
(self)
dataloader/miniimagenet/miniimagenet.py:126
Method__len__
(self)
dataloader/miniimagenet/miniimagenet.py:164
Method__len__
(self)
dataloader/cub200/cub200.py:178
Method__len__
(self)
dataloader/imagenet100/ImageNet.py:167
Method__repr__
(self)
dataloader/imagenet1000/autoaugment.py:49
Method__repr__
(self)
dataloader/imagenet1000/autoaugment.py:91
Method__repr__
(self)
dataloader/imagenet1000/autoaugment.py:133
Method__repr__
(self)
dataloader/cifar100/autoaugment.py:86
Method__repr__
(self)
dataloader/cifar100/autoaugment.py:141
Method__repr__
(self)
dataloader/cifar100/autoaugment.py:196
Method__repr__
(self)
dataloader/miniimagenet/autoaugment.py:49
Method__repr__
(self)
dataloader/miniimagenet/autoaugment.py:91
Method__repr__
(self)
dataloader/miniimagenet/autoaugment.py:133
Method__repr__
(self)
dataloader/cub200/autoaugment.py:49
Method__repr__
(self)
dataloader/cub200/autoaugment.py:91
Method__repr__
(self)
dataloader/cub200/autoaugment.py:133
Method__repr__
(self)
dataloader/imagenet100/autoaugment.py:49
Method__repr__
(self)
dataloader/imagenet100/autoaugment.py:91
Method__repr__
(self)
dataloader/imagenet100/autoaugment.py:133
Functioncount_acc_taskIL
(logits, label,args)
utils.py:91
Methodextra_repr
(self)
dataloader/cifar100/cifar.py:217
Methodforward
(self, x)
models/resnet18_encoder.py:178
Methodforward
(self, x)
models/resnet18_encoder.py:217
Methodforward
(self, x)
models/resnet18_encoder.py:317
Methodforward
(self, x)
models/resnet20_cifar.py:24
Methodforward
(self, x)
models/resnet20_cifar.py:86
Methodforward
(self, input)
models/fact/Network.py:119
Methodforward
(self, input)
models/base/Network.py:48
Functionget_base_dataloader_meta
(args)
dataloader/data_utils.py:121
Functionget_dataloader
(args,session)
dataloader/data_utils.py:80
Methodmeasure
(self, p=1)
utils.py:66
Functionresnet101
r"""ResNet-101 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ Args: pretrained (
models/resnet18_encoder.py:385
Functionresnet152
r"""ResNet-152 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ Args: pretrained (
models/resnet18_encoder.py:397
Functionresnet34
r"""ResNet-34 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ Args: pretrained (b
models/resnet18_encoder.py:361
Functionresnet50
r"""ResNet-50 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ Args: pretrained (b
models/resnet18_encoder.py:373
Functionresnext101_32x8d
r"""ResNeXt-101 32x8d model from `"Aggregated Residual Transformation for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ Args
models/resnet18_encoder.py:423
Functionresnext50_32x4d
r"""ResNeXt-50 32x4d model from `"Aggregated Residual Transformation for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ Args:
models/resnet18_encoder.py:409
Methodrotate_with_fill
(img, magnitude)
dataloader/imagenet1000/autoaugment.py:156
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