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Functions45 in github.com/BangguWu/ECANet

⨍ Functions 45◇ Types & classes 10
↓ 9 callersMethodupdate
(self, val, n=1)
light_main.py:373
↓ 9 callersMethodupdate
(self, val, n=1)
main.py:364
↓ 5 callersFunctiondata_save
(root, file)
light_main.py:406
↓ 5 callersFunctiondata_save
(root, file)
main.py:395
↓ 4 callersMethod_make_layer
(self, block, planes, blocks, k_size, stride=1)
models/eca_resnet.py:112
↓ 2 callersMethod__init__
(self, block, layers, num_classes=1000, k_size=[3, 3, 3, 3])
models/eca_resnet.py:89
↓ 2 callersMethod__init__
(self, in_planes, out_planes, kernel_size=3, stride=1, groups=1)
models/eca_mobilenetv2.py:13
↓ 2 callersFunctionaccuracy
Computes the precision@k for the specified values of k
light_main.py:389
↓ 2 callersFunctionaccuracy
Computes the precision@k for the specified values of k
main.py:378
↓ 2 callersFunctionconv3x3
3x3 convolution with padding
models/eca_resnet.py:7
↓ 2 callersFunctionvalidate
(val_loader, model, criterion)
light_main.py:308
↓ 2 callersFunctionvalidate
(val_loader, model, criterion)
main.py:299
↓ 1 callersFunctionadjust_learning_rate
Sets the learning rate to the initial LR decayed by 10 every 30 epochs
light_main.py:380
↓ 1 callersFunctionadjust_learning_rate
Sets the learning rate to the initial LR decayed by 10 every 30 epochs
main.py:371
↓ 1 callersFunctionclever_format
(nums, format="%.2f")
paras_flops.py:34
↓ 1 callersFunctionmain
()
light_main.py:74
↓ 1 callersFunctionmain
()
paras_flops.py:19
↓ 1 callersFunctionmain
()
main.py:74
↓ 1 callersMethodreset
(self)
light_main.py:367
↓ 1 callersMethodreset
(self)
main.py:358
↓ 1 callersFunctionsave_checkpoint
(state, is_best, filename='checkpoint.pth.tar')
light_main.py:353
↓ 1 callersFunctionsave_checkpoint
(state, is_best, filename='checkpoint.pth.tar')
main.py:344
↓ 1 callersFunctiontrain
(train_loader, model, criterion, optimizer, epoch)
light_main.py:251
↓ 1 callersFunctiontrain
(train_loader, model, criterion, optimizer, epoch)
main.py:247
Method__init__
(self)
light_main.py:364
Method__init__
(self)
main.py:355
Method__init__
(self, inplanes, planes, stride=1, downsample=None, k_size=3)
models/eca_resnet.py:16
Method__init__
(self, inplanes, planes, stride=1, downsample=None, k_size=3)
models/eca_resnet.py:49
Method__init__
(self, inp, oup, stride, expand_ratio, k_size)
models/eca_mobilenetv2.py:23
Method__init__
(self, num_classes=1000, width_mult=1.0)
models/eca_mobilenetv2.py:53
Method__init__
(self, channel, k_size=3)
models/eca_module.py:12
Method__init__
(self, channel, k_size)
models/eca_ns.py:7
Functioneca_mobilenet_v2
Constructs a ECA_MobileNetV2 architecture from Args: pretrained (bool): If True, returns a model pre-trained on ImageNet pro
models/eca_mobilenetv2.py:116
Functioneca_resnet101
Constructs a ResNet-101 model. Args: k_size: Adaptive selection of kernel size num_classes:The classes of classification
models/eca_resnet.py:187
Functioneca_resnet152
Constructs a ResNet-152 model. Args: k_size: Adaptive selection of kernel size num_classes:The classes of classification
models/eca_resnet.py:200
Functioneca_resnet18
Constructs a ResNet-18 model. Args: k_size: Adaptive selection of kernel size pretrained (bool): If True, returns a model pre
models/eca_resnet.py:147
Functioneca_resnet34
Constructs a ResNet-34 model. Args: k_size: Adaptive selection of kernel size pretrained (bool): If True, returns a model pre
models/eca_resnet.py:160
Functioneca_resnet50
Constructs a ResNet-50 model. Args: k_size: Adaptive selection of kernel size num_classes:The classes of classification
models/eca_resnet.py:173
Methodforward
(self, x)
models/eca_resnet.py:27
Methodforward
(self, x)
models/eca_resnet.py:63
Methodforward
(self, x)
models/eca_resnet.py:129
Methodforward
(self, x)
models/eca_mobilenetv2.py:45
Methodforward
(self, x)
models/eca_mobilenetv2.py:109
Methodforward
(self, x)
models/eca_module.py:18
Methodforward
(self, x)
models/eca_ns.py:15