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github.com/HobbitLong/SupContrast
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Functions
47 in github.com/HobbitLong/SupContrast
⨍
Functions
47
◇
Types & classes
10
↓ 17 callers
Method
update
(self, val, n=1)
util.py:29
↓ 6 callers
Method
__init__
(self, block, num_blocks, in_channel=3, zero_init_residual=False)
networks/resnet_big.py:76
↓ 4 callers
Method
_make_layer
(self, block, planes, num_blocks, stride)
networks/resnet_big.py:107
↓ 4 callers
Function
accuracy
Computes the accuracy over the k top predictions for the specified values of k
util.py:36
↓ 4 callers
Function
save_model
(model, optimizer, opt, epoch, save_file)
util.py:86
↓ 3 callers
Function
adjust_learning_rate
(args, optimizer, epoch)
util.py:53
↓ 3 callers
Function
set_optimizer
(opt, model)
util.py:78
↓ 3 callers
Function
warmup_learning_rate
(args, epoch, batch_id, total_batches, optimizer)
util.py:68
↓ 2 callers
Function
set_loader
(opt)
main_ce.py:118
↓ 1 callers
Function
main
()
main_ce.py:280
↓ 1 callers
Function
main
()
main_supcon.py:255
↓ 1 callers
Function
main
()
main_linear.py:229
↓ 1 callers
Function
parse_option
()
main_ce.py:26
↓ 1 callers
Function
parse_option
()
main_supcon.py:27
↓ 1 callers
Function
parse_option
()
main_linear.py:24
↓ 1 callers
Method
reset
(self)
util.py:23
↓ 1 callers
Function
set_loader
(opt)
main_supcon.py:131
↓ 1 callers
Function
set_model
(opt)
main_ce.py:170
↓ 1 callers
Function
set_model
(opt)
main_supcon.py:179
↓ 1 callers
Function
set_model
(opt)
main_linear.py:103
↓ 1 callers
Function
train
one epoch training
main_ce.py:188
↓ 1 callers
Function
train
one epoch training
main_supcon.py:197
↓ 1 callers
Function
train
one epoch training
main_linear.py:133
↓ 1 callers
Function
validate
validation
main_ce.py:240
↓ 1 callers
Function
validate
validation
main_linear.py:188
Method
__call__
(self, x)
util.py:14
Method
__init__
(self, temperature=0.07, contrast_mode='all', base_temperature=0.07)
losses.py:14
Method
__init__
(self, transform)
util.py:11
Method
__init__
(self)
util.py:20
Method
__init__
(self, in_planes, planes, stride=1, is_last=False)
networks/resnet_big.py:15
Method
__init__
(self, in_planes, planes, stride=1, is_last=False)
networks/resnet_big.py:45
Method
__init__
(self, dim, affine=True)
networks/resnet_big.py:153
Method
__init__
(self, name='resnet50', head='mlp', feat_dim=128)
networks/resnet_big.py:167
Method
__init__
(self, name='resnet50', num_classes=10)
networks/resnet_big.py:191
Method
__init__
(self, name='resnet50', num_classes=10)
networks/resnet_big.py:203
Method
forward
Compute loss for model. If both `labels` and `mask` are None, it degenerates to SimCLR unsupervised loss: https://arxiv.org/pdf/2002.0
losses.py:21
Method
forward
(self, x)
networks/resnet_big.py:30
Method
forward
(self, x)
networks/resnet_big.py:62
Method
forward
(self, x, layer=100)
networks/resnet_big.py:116
Method
forward
(self, x)
networks/resnet_big.py:158
Method
forward
(self, x)
networks/resnet_big.py:183
Method
forward
(self, x)
networks/resnet_big.py:197
Method
forward
(self, features)
networks/resnet_big.py:208
Function
resnet101
(**kwargs)
networks/resnet_big.py:139
Function
resnet18
(**kwargs)
networks/resnet_big.py:127
Function
resnet34
(**kwargs)
networks/resnet_big.py:131
Function
resnet50
(**kwargs)
networks/resnet_big.py:135