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Types & classes22 in github.com/SHI-Labs/Any-Precision-DNNs

⨍ Functions 66◇ Types & classes 22
↓ 7 callersClassActivate
models/svhn_quan.py:14
↓ 6 callersClassActivate
models/resnet_quan.py:10
↓ 6 callersClassAverageMeter
Adapted from https://github.com/pytorch/examples/blob/master/imagenet/main.py
utils.py:9
↓ 2 callersClassCrossEntropyLossSoft
inplace distillation for image classification. Refer to https://github.com/JiahuiYu/slimmable_networks/blob/master/utils/loss_ops.py
models/losses.py:4
↓ 2 callersClassactivation_quantize_fn
models/quan_ops.py:102
↓ 2 callersClassweight_quantize_fn
models/quan_ops.py:80
↓ 1 callersClassCIFAR10
`CIFAR10 <https://www.cs.toronto.edu/~kriz/cifar.html>`_ Dataset. Args: root (string): Root directory of dataset where directory
datasets/cifar10.py:20
↓ 1 callersClassPreActResNet
models/resnet_quan.py:72
↓ 1 callersClassPreActResNetBottleneck
models/resnet_quan.py:138
↓ 1 callersClassSVHNMIX
`SVHN <http://ufldl.stanford.edu/housenumbers/>`_ Dataset. Note: The SVHN dataset assigns the label `10` to the digit `0`. However, in this Datase
datasets/svhn.py:14
↓ 1 callersClassSVHNQ
models/svhn_quan.py:34
ClassConv2d_Q
models/quan_ops.py:117
ClassConv2d_Q_
models/quan_ops.py:123
ClassLinear_Q
models/quan_ops.py:139
ClassLinear_Q_
models/quan_ops.py:145
ClassPreActBasicBlockQ
Pre-activation version of the BasicBlock.
models/resnet_quan.py:30
ClassPreActBottleneckQ
models/resnet_quan.py:106
ClassSwitchBatchNorm1d
Adapted from https://github.com/JiahuiYu/slimmable_networks
models/quan_ops.py:39
ClassSwitchBatchNorm1d_
models/quan_ops.py:60
ClassSwitchBatchNorm2d
Adapted from https://github.com/JiahuiYu/slimmable_networks
models/quan_ops.py:11
ClassSwitchBatchNorm2d_
models/quan_ops.py:32
Classqfn
models/quan_ops.py:67