Functions — github.com/HobbitLong/RepDistiller

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Functions213 in github.com/HobbitLong/RepDistiller

⨍ Functions 213◇ Types & classes 58

Method__init__

(self, in_planes, planes, stride=1, is_last=False)

models/resnetv2.py:45

Method__init__

(self, groups=2)

models/ShuffleNetv2.py:10

Method__init__

(self, ratio)

models/ShuffleNetv2.py:22

Method__init__

(self, in_channels, split_ratio=0.5, is_last=False)

models/ShuffleNetv2.py:32

Method__init__

(self, net_size, num_classes=10)

models/ShuffleNetv2.py:103

Method__init__

(self, dim_in, n_label=10, p=0.1)

models/classifier.py:23

Method__init__

(self, nb_layers, in_planes, out_planes, block, stride, dropRate=0.0)

models/wrn.py:42

Method__init__

(self, depth, num_classes, widen_factor=1, dropRate=0.0)

models/wrn.py:57

Method__init__

(self, t_shape, k=0.5, use_bn=False)

models/util.py:9

Method__init__

(self, s_shape, t_shape, k=0.5, use_bn=True)

models/util.py:45

Method__init__

(self, s_shapes, t_shapes)

models/util.py:67

Method__init__

(self, s_shapes, t_shapes)

models/util.py:95

Method__init__

(self, s_shape, t_shape, use_relu=True)

models/util.py:133

Method__init__

(self, dim_in=1024, dim_out=1024)

models/util.py:159

Method__init__

(self, dim_in=1024, dim_out=128)

models/util.py:187

Method__init__

(self, dim_in=1024, dim_out=128)

(self, layer=0, dim_out=128, pool_type='avg')

models/util.py:236

Method__init__

(self, cfg, batch_norm=False, num_classes=1000)

models/vgg.py:25

Method__init__

(self, inp, oup, stride, expand_ratio)

models/mobilenetv2.py:32

Method__init__

(self, inplanes, planes, stride=1, downsample=None, is_last=False)

models/resnet.py:27

Method__init__

(self, inplanes, planes, stride=1, downsample=None, is_last=False)

models/resnet.py:63

Method__init__

(self, groups)

models/ShuffleNetv1.py:10

Method__init__

(self, cfg, num_classes=10)

models/ShuffleNetv1.py:57

Functionadjust_learning_rate_new

new learning rate schedule according to RotNet

helper/util.py:7

Methodconv1x1

(in_channels, out_channels, stride=1)

distiller_zoo/VID.py:20

Methodforward

(self, f_s, f_t)

distiller_zoo/RKD.py:15

Methodforward

(self, g_s, g_t)

distiller_zoo/FSP.py:19

Methodforward

(self, g_s, g_t)

distiller_zoo/KDSVD.py:17

Methodforward

(self, f_s, f_t)

distiller_zoo/FT.py:14

Methodforward

(self, f_s, f_t)

distiller_zoo/PKT.py:13

Methodforward

(self, g_s, g_t)

distiller_zoo/NST.py:13

Methodforward

(self, f_s, f_t)

distiller_zoo/CC.py:14

Methodforward

(self, g_s, g_t)

distiller_zoo/AT.py:15

Methodforward

(self, g_s, g_t)

distiller_zoo/AB.py:16

Methodforward

(self, input, target)

distiller_zoo/VID.py:38

Methodforward

(self, f_s, f_t)

distiller_zoo/FitNet.py:12

Methodforward

(self, y_s, y_t)

distiller_zoo/KD.py:13

Methodforward

(self, g_s, g_t)

distiller_zoo/SP.py:13

Methodforward

(self, v1, v2, y, idx=None)

crd/memory.py:23

Methodforward

Args: f_s: the feature of student network, size [batch_size, s_dim] f_t: the feature of teacher network, size [batch_

models/resnetv2.py:30

Methodforward

(self, x)

models/resnetv2.py:62

Methodforward

(self, x, is_feat=False, preact=False)

models/resnetv2.py:141

Methodforward

Channel shuffle: [N,C,H,W] -> [N,g,C/g,H,W] -> [N,C/g,g,H,w] -> [N,C,H,W]

models/ShuffleNetv2.py:14

Methodforward

(self, x)

models/ShuffleNetv2.py:26

Methodforward

(self, x)

models/ShuffleNetv2.py:48

Methodforward

(self, x)

models/ShuffleNetv2.py:88

Methodforward

(self, x, is_feat=False, preact=False)

models/ShuffleNetv2.py:140

Methodforward

(self, x)

models/classifier.py:17

Methodforward

(self, x)

models/classifier.py:34

(self, x, is_feat=False, preact=False)

models/wrn.py:103

Methodforward

(self, f_s, is_factor=False)

(self, x, is_feat=False, preact=False)

models/vgg.py:64

Methodforward

(self, x)

models/mobilenetv2.py:56

Methodforward

(self, x, is_feat=False, preact=False)

models/mobilenetv2.py:132

(self, x, is_feat=False, preact=False)

models/resnet.py:178

Methodforward

Channel shuffle: [N,C,H,W] -> [N,g,C/g,H,W] -> [N,C/g,g,H,w] -> [N,C,H,W]

models/ShuffleNetv1.py:14

Methodforward

(self, x)

models/ShuffleNetv1.py:41

Methodforward

(self, x, is_feat=False, preact=False)

models/ShuffleNetv1.py:95

Methodget_bn_before_relu

(self)

models/ShuffleNetv2.py:137

Methodget_bn_before_relu

(self)

models/ShuffleNetv1.py:92

Functionget_dataloader_sample

Data Loader for ImageNet

dataset/imagenet.py:134

Methodget_feat_modules

(self)

models/resnetv2.py:106

Methodget_feat_modules

(self)

models/ShuffleNetv2.py:128

Methodget_feat_modules

(self)

models/wrn.py:88

Methodget_feat_modules

(self)

models/mobilenetv2.py:126

Methodget_feat_modules

(self)

models/resnet.py:154

Methodget_feat_modules

(self)

models/ShuffleNetv1.py:83

Functionget_imagenet_dataloader

Data Loader for imagenet

dataset/imagenet.py:180

Functionget_test_loader

get the test data loader

dataset/imagenet.py:106

Functiontrain_distill

One epoch distillation

helper/loops.py:68

Functiontrain_vanilla

vanilla training

helper/loops.py:10

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