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github.com/Eric-mingjie/network-slimming
/ functions
Functions
49 in github.com/Eric-mingjie/network-slimming
⨍
Functions
49
◇
Types & classes
13
↓ 3 callers
Method
_make_denseblock
(self, block, blocks, cfg)
mask-impl/models/densenet.py:101
↓ 3 callers
Method
_make_denseblock
(self, block, blocks, cfg)
models/densenet.py:107
↓ 3 callers
Method
_make_layer
(self, block, planes, blocks, cfg, stride=1)
mask-impl/models/preresnet.py:87
↓ 3 callers
Method
_make_layer
(self, block, planes, blocks, cfg, stride=1)
models/preresnet.py:91
↓ 2 callers
Method
__init__
(self, depth=40, dropRate=0, dataset='cifar10', growthRate=12, compressionRate=1, cfg = None)
mask-impl/models/densenet.py:52
↓ 2 callers
Method
__init__
(self, depth=40, dropRate=0, dataset='cifar10', growthRate=12, compressionRate=1, cfg = None)
models/densenet.py:57
↓ 2 callers
Method
_make_transition
(self, compressionRate, cfg)
mask-impl/models/densenet.py:111
↓ 2 callers
Method
_make_transition
(self, compressionRate, cfg)
models/densenet.py:117
↓ 2 callers
Function
test
(model)
vggprune.py:89
↓ 2 callers
Function
test
(model)
resprune.py:91
↓ 2 callers
Function
test
(model)
denseprune.py:89
↓ 1 callers
Function
BN_grad_zero
()
mask-impl/main_mask.py:131
↓ 1 callers
Method
__init__
(self, depth=164, dataset='cifar10', cfg=None)
mask-impl/models/preresnet.py:51
↓ 1 callers
Method
__init__
(self, depth=164, dataset='cifar10', cfg=None)
models/preresnet.py:54
↓ 1 callers
Method
_initialize_weights
(self)
mask-impl/models/vgg.py:54
↓ 1 callers
Method
_initialize_weights
(self)
models/vgg.py:54
↓ 1 callers
Method
make_layers
(self, cfg, batch_norm=False)
mask-impl/models/vgg.py:32
↓ 1 callers
Method
make_layers
(self, cfg, batch_norm=False)
models/vgg.py:32
↓ 1 callers
Function
save_checkpoint
(state, is_best, filepath)
main.py:169
↓ 1 callers
Function
save_checkpoint
(state, is_best, filepath)
mask-impl/main_mask.py:179
↓ 1 callers
Function
test
()
main.py:150
↓ 1 callers
Function
test
()
mask-impl/prune_mask.py:92
↓ 1 callers
Function
test
()
mask-impl/main_mask.py:159
↓ 1 callers
Function
train
(epoch)
main.py:131
↓ 1 callers
Function
train
(epoch)
mask-impl/main_mask.py:139
↓ 1 callers
Function
updateBN
()
main.py:126
↓ 1 callers
Function
updateBN
()
mask-impl/main_mask.py:126
Method
__init__
(self, inplanes, cfg, expansion=1, growthRate=12, dropRate=0)
mask-impl/models/densenet.py:15
Method
__init__
(self, inplanes, outplanes, cfg)
mask-impl/models/densenet.py:36
Method
__init__
(self, dataset='cifar10', depth=19, init_weights=True, cfg=None)
mask-impl/models/vgg.py:17
Method
__init__
(self, inplanes, planes, cfg, stride=1, downsample=None)
mask-impl/models/preresnet.py:15
Method
__init__
(self, inplanes, cfg, expansion=1, growthRate=12, dropRate=0)
models/densenet.py:16
Method
__init__
(self, inplanes, outplanes, cfg)
models/densenet.py:39
Method
__init__
Initialize the `indexes` with all one vector with the length same as the number of channels. During pruning, the places in `indexes`
models/channel_selection.py:11
Method
__init__
(self, dataset='cifar10', depth=19, init_weights=True, cfg=None)
models/vgg.py:17
Method
__init__
(self, inplanes, planes, cfg, stride=1, downsample=None)
models/preresnet.py:16
Method
forward
(self, x)
mask-impl/models/densenet.py:24
Method
forward
(self, x)
mask-impl/models/densenet.py:43
Method
forward
(self, x)
mask-impl/models/densenet.py:118
Method
forward
(self, x)
mask-impl/models/vgg.py:47
Method
forward
(self, x)
mask-impl/models/preresnet.py:28
Method
forward
(self, x)
mask-impl/models/preresnet.py:103
Method
forward
(self, x)
models/densenet.py:26
Method
forward
(self, x)
models/densenet.py:47
Method
forward
(self, x)
models/densenet.py:124
Method
forward
Parameter --------- input_tensor: (N,C,H,W). It should be the output of BatchNorm2d layer.
models/channel_selection.py:19
Method
forward
(self, x)
models/vgg.py:47
Method
forward
(self, x)
models/preresnet.py:30
Method
forward
(self, x)
models/preresnet.py:107