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< h1 > Source code for torchreid.models.shufflenet< / h1 > < div class = "highlight" > < pre >
< span > < / span > < span class = "kn" > from< / span > < span class = "nn" > __future__< / span > < span class = "k" > import< / span > < span class = "n" > absolute_import< / span >
< span class = "kn" > from< / span > < span class = "nn" > __future__< / span > < span class = "k" > import< / span > < span class = "n" > division< / span >
< span class = "n" > __all__< / span > < span class = "o" > =< / span > < span class = "p" > [< / span > < span class = "s1" > ' shufflenet' < / span > < span class = "p" > ]< / span >
< span class = "kn" > import< / span > < span class = "nn" > torch< / span >
< span class = "kn" > from< / span > < span class = "nn" > torch< / span > < span class = "k" > import< / span > < span class = "n" > nn< / span >
< span class = "kn" > from< / span > < span class = "nn" > torch.nn< / span > < span class = "k" > import< / span > < span class = "n" > functional< / span > < span class = "k" > as< / span > < span class = "n" > F< / span >
< span class = "kn" > import< / span > < span class = "nn" > torchvision< / span >
< span class = "kn" > import< / span > < span class = "nn" > torch.utils.model_zoo< / span > < span class = "k" > as< / span > < span class = "nn" > model_zoo< / span >
< span class = "n" > model_urls< / span > < span class = "o" > =< / span > < span class = "p" > {< / span >
< span class = "c1" > # training epoch = 90, top1 = 61.8< / span >
< span class = "s1" > ' imagenet' < / span > < span class = "p" > :< / span > < span class = "s1" > ' http://www.eecs.qmul.ac.uk/~kz303/deep-person-reid/model-zoo/imagenet-pretrained/shufflenet-bee1b265.pth.tar' < / span > < span class = "p" > ,< / span >
< span class = "p" > }< / span >
< span class = "k" > class< / span > < span class = "nc" > ChannelShuffle< / span > < span class = "p" > (< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > Module< / span > < span class = "p" > ):< / span >
< span class = "k" > def< / span > < span class = "nf" > __init__< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "n" > num_groups< / span > < span class = "p" > ):< / span >
< span class = "nb" > super< / span > < span class = "p" > (< / span > < span class = "n" > ChannelShuffle< / span > < span class = "p" > ,< / span > < span class = "bp" > self< / span > < span class = "p" > )< / span > < span class = "o" > .< / span > < span class = "fm" > __init__< / span > < span class = "p" > ()< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > g< / span > < span class = "o" > =< / span > < span class = "n" > num_groups< / span >
< span class = "k" > def< / span > < span class = "nf" > forward< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "n" > x< / span > < span class = "p" > ):< / span >
< span class = "n" > b< / span > < span class = "p" > ,< / span > < span class = "n" > c< / span > < span class = "p" > ,< / span > < span class = "n" > h< / span > < span class = "p" > ,< / span > < span class = "n" > w< / span > < span class = "o" > =< / span > < span class = "n" > x< / span > < span class = "o" > .< / span > < span class = "n" > size< / span > < span class = "p" > ()< / span >
< span class = "n" > n< / span > < span class = "o" > =< / span > < span class = "n" > c< / span > < span class = "o" > //< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > g< / span >
< span class = "c1" > # reshape< / span >
< span class = "n" > x< / span > < span class = "o" > =< / span > < span class = "n" > x< / span > < span class = "o" > .< / span > < span class = "n" > view< / span > < span class = "p" > (< / span > < span class = "n" > b< / span > < span class = "p" > ,< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > g< / span > < span class = "p" > ,< / span > < span class = "n" > n< / span > < span class = "p" > ,< / span > < span class = "n" > h< / span > < span class = "p" > ,< / span > < span class = "n" > w< / span > < span class = "p" > )< / span >
< span class = "c1" > # transpose< / span >
< span class = "n" > x< / span > < span class = "o" > =< / span > < span class = "n" > x< / span > < span class = "o" > .< / span > < span class = "n" > permute< / span > < span class = "p" > (< / span > < span class = "mi" > 0< / span > < span class = "p" > ,< / span > < span class = "mi" > 2< / span > < span class = "p" > ,< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "mi" > 3< / span > < span class = "p" > ,< / span > < span class = "mi" > 4< / span > < span class = "p" > )< / span > < span class = "o" > .< / span > < span class = "n" > contiguous< / span > < span class = "p" > ()< / span >
< span class = "c1" > # flatten< / span >
< span class = "n" > x< / span > < span class = "o" > =< / span > < span class = "n" > x< / span > < span class = "o" > .< / span > < span class = "n" > view< / span > < span class = "p" > (< / span > < span class = "n" > b< / span > < span class = "p" > ,< / span > < span class = "n" > c< / span > < span class = "p" > ,< / span > < span class = "n" > h< / span > < span class = "p" > ,< / span > < span class = "n" > w< / span > < span class = "p" > )< / span >
< span class = "k" > return< / span > < span class = "n" > x< / span >
< span class = "k" > class< / span > < span class = "nc" > Bottleneck< / span > < span class = "p" > (< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > Module< / span > < span class = "p" > ):< / span >
< span class = "k" > def< / span > < span class = "nf" > __init__< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "n" > in_channels< / span > < span class = "p" > ,< / span > < span class = "n" > out_channels< / span > < span class = "p" > ,< / span > < span class = "n" > stride< / span > < span class = "p" > ,< / span > < span class = "n" > num_groups< / span > < span class = "p" > ,< / span > < span class = "n" > group_conv1x1< / span > < span class = "o" > =< / span > < span class = "kc" > True< / span > < span class = "p" > ):< / span >
< span class = "nb" > super< / span > < span class = "p" > (< / span > < span class = "n" > Bottleneck< / span > < span class = "p" > ,< / span > < span class = "bp" > self< / span > < span class = "p" > )< / span > < span class = "o" > .< / span > < span class = "fm" > __init__< / span > < span class = "p" > ()< / span >
< span class = "k" > assert< / span > < span class = "n" > stride< / span > < span class = "ow" > in< / span > < span class = "p" > [< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "mi" > 2< / span > < span class = "p" > ],< / span > < span class = "s1" > ' Warning: stride must be either 1 or 2' < / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > stride< / span > < span class = "o" > =< / span > < span class = "n" > stride< / span >
< span class = "n" > mid_channels< / span > < span class = "o" > =< / span > < span class = "n" > out_channels< / span > < span class = "o" > //< / span > < span class = "mi" > 4< / span >
< span class = "k" > if< / span > < span class = "n" > stride< / span > < span class = "o" > ==< / span > < span class = "mi" > 2< / span > < span class = "p" > :< / span > < span class = "n" > out_channels< / span > < span class = "o" > -=< / span > < span class = "n" > in_channels< / span >
< span class = "c1" > # group conv is not applied to first conv1x1 at stage 2< / span >
< span class = "n" > num_groups_conv1x1< / span > < span class = "o" > =< / span > < span class = "n" > num_groups< / span > < span class = "k" > if< / span > < span class = "n" > group_conv1x1< / span > < span class = "k" > else< / span > < span class = "mi" > 1< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > conv1< / span > < span class = "o" > =< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > Conv2d< / span > < span class = "p" > (< / span > < span class = "n" > in_channels< / span > < span class = "p" > ,< / span > < span class = "n" > mid_channels< / span > < span class = "p" > ,< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > groups< / span > < span class = "o" > =< / span > < span class = "n" > num_groups_conv1x1< / span > < span class = "p" > ,< / span > < span class = "n" > bias< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > bn1< / span > < span class = "o" > =< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > BatchNorm2d< / span > < span class = "p" > (< / span > < span class = "n" > mid_channels< / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > shuffle1< / span > < span class = "o" > =< / span > < span class = "n" > ChannelShuffle< / span > < span class = "p" > (< / span > < span class = "n" > num_groups< / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > conv2< / span > < span class = "o" > =< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > Conv2d< / span > < span class = "p" > (< / span > < span class = "n" > mid_channels< / span > < span class = "p" > ,< / span > < span class = "n" > mid_channels< / span > < span class = "p" > ,< / span > < span class = "mi" > 3< / span > < span class = "p" > ,< / span > < span class = "n" > stride< / span > < span class = "o" > =< / span > < span class = "n" > stride< / span > < span class = "p" > ,< / span > < span class = "n" > padding< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > groups< / span > < span class = "o" > =< / span > < span class = "n" > mid_channels< / span > < span class = "p" > ,< / span > < span class = "n" > bias< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > bn2< / span > < span class = "o" > =< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > BatchNorm2d< / span > < span class = "p" > (< / span > < span class = "n" > mid_channels< / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > conv3< / span > < span class = "o" > =< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > Conv2d< / span > < span class = "p" > (< / span > < span class = "n" > mid_channels< / span > < span class = "p" > ,< / span > < span class = "n" > out_channels< / span > < span class = "p" > ,< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > groups< / span > < span class = "o" > =< / span > < span class = "n" > num_groups< / span > < span class = "p" > ,< / span > < span class = "n" > bias< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > bn3< / span > < span class = "o" > =< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > BatchNorm2d< / span > < span class = "p" > (< / span > < span class = "n" > out_channels< / span > < span class = "p" > )< / span >
< span class = "k" > if< / span > < span class = "n" > stride< / span > < span class = "o" > ==< / span > < span class = "mi" > 2< / span > < span class = "p" > :< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > shortcut< / span > < span class = "o" > =< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > AvgPool2d< / span > < span class = "p" > (< / span > < span class = "mi" > 3< / span > < span class = "p" > ,< / span > < span class = "n" > stride< / span > < span class = "o" > =< / span > < span class = "mi" > 2< / span > < span class = "p" > ,< / span > < span class = "n" > padding< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / span > < span class = "p" > )< / span >
< span class = "k" > def< / span > < span class = "nf" > forward< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "n" > x< / span > < span class = "p" > ):< / span >
< span class = "n" > out< / span > < span class = "o" > =< / span > < span class = "n" > F< / span > < span class = "o" > .< / span > < span class = "n" > relu< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > bn1< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > conv1< / span > < span class = "p" > (< / span > < span class = "n" > x< / span > < span class = "p" > )))< / span >
< span class = "n" > out< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > shuffle1< / span > < span class = "p" > (< / span > < span class = "n" > out< / span > < span class = "p" > )< / span >
< span class = "n" > out< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > bn2< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > conv2< / span > < span class = "p" > (< / span > < span class = "n" > out< / span > < span class = "p" > ))< / span >
< span class = "n" > out< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > bn3< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > conv3< / span > < span class = "p" > (< / span > < span class = "n" > out< / span > < span class = "p" > ))< / span >
< span class = "k" > if< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > stride< / span > < span class = "o" > ==< / span > < span class = "mi" > 2< / span > < span class = "p" > :< / span >
< span class = "n" > res< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > shortcut< / span > < span class = "p" > (< / span > < span class = "n" > x< / span > < span class = "p" > )< / span >
< span class = "n" > out< / span > < span class = "o" > =< / span > < span class = "n" > F< / span > < span class = "o" > .< / span > < span class = "n" > relu< / span > < span class = "p" > (< / span > < span class = "n" > torch< / span > < span class = "o" > .< / span > < span class = "n" > cat< / span > < span class = "p" > ([< / span > < span class = "n" > res< / span > < span class = "p" > ,< / span > < span class = "n" > out< / span > < span class = "p" > ],< / span > < span class = "mi" > 1< / span > < span class = "p" > ))< / span >
< span class = "k" > else< / span > < span class = "p" > :< / span >
< span class = "n" > out< / span > < span class = "o" > =< / span > < span class = "n" > F< / span > < span class = "o" > .< / span > < span class = "n" > relu< / span > < span class = "p" > (< / span > < span class = "n" > x< / span > < span class = "o" > +< / span > < span class = "n" > out< / span > < span class = "p" > )< / span >
< span class = "k" > return< / span > < span class = "n" > out< / span >
< span class = "c1" > # configuration of (num_groups: #out_channels) based on Table 1 in the paper< / span >
< span class = "n" > cfg< / span > < span class = "o" > =< / span > < span class = "p" > {< / span >
< span class = "mi" > 1< / span > < span class = "p" > :< / span > < span class = "p" > [< / span > < span class = "mi" > 144< / span > < span class = "p" > ,< / span > < span class = "mi" > 288< / span > < span class = "p" > ,< / span > < span class = "mi" > 576< / span > < span class = "p" > ],< / span >
< span class = "mi" > 2< / span > < span class = "p" > :< / span > < span class = "p" > [< / span > < span class = "mi" > 200< / span > < span class = "p" > ,< / span > < span class = "mi" > 400< / span > < span class = "p" > ,< / span > < span class = "mi" > 800< / span > < span class = "p" > ],< / span >
< span class = "mi" > 3< / span > < span class = "p" > :< / span > < span class = "p" > [< / span > < span class = "mi" > 240< / span > < span class = "p" > ,< / span > < span class = "mi" > 480< / span > < span class = "p" > ,< / span > < span class = "mi" > 960< / span > < span class = "p" > ],< / span >
< span class = "mi" > 4< / span > < span class = "p" > :< / span > < span class = "p" > [< / span > < span class = "mi" > 272< / span > < span class = "p" > ,< / span > < span class = "mi" > 544< / span > < span class = "p" > ,< / span > < span class = "mi" > 1088< / span > < span class = "p" > ],< / span >
< span class = "mi" > 8< / span > < span class = "p" > :< / span > < span class = "p" > [< / span > < span class = "mi" > 384< / span > < span class = "p" > ,< / span > < span class = "mi" > 768< / span > < span class = "p" > ,< / span > < span class = "mi" > 1536< / span > < span class = "p" > ],< / span >
< span class = "p" > }< / span >
< div class = "viewcode-block" id = "ShuffleNet" > < a class = "viewcode-back" href = "../../../pkg/models.html#torchreid.models.shufflenet.ShuffleNet" > [docs]< / a > < span class = "k" > class< / span > < span class = "nc" > ShuffleNet< / span > < span class = "p" > (< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > Module< / span > < span class = "p" > ):< / span >
< span class = "sd" > " " " ShuffleNet.< / span >
< span class = "sd" > Reference:< / span >
< span class = "sd" > Zhang et al. ShuffleNet: An Extremely Efficient Convolutional Neural< / span >
< span class = "sd" > Network for Mobile Devices. CVPR 2018.< / span >
< span class = "sd" > Public keys:< / span >
< span class = "sd" > - ``shufflenet``: ShuffleNet (groups=3).< / span >
< span class = "sd" > " " " < / span >
< span class = "k" > def< / span > < span class = "nf" > __init__< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "n" > num_classes< / span > < span class = "p" > ,< / span > < span class = "n" > loss< / span > < span class = "o" > =< / span > < span class = "s1" > ' softmax' < / span > < span class = "p" > ,< / span > < span class = "n" > num_groups< / span > < span class = "o" > =< / span > < span class = "mi" > 3< / span > < span class = "p" > ,< / span > < span class = "o" > **< / span > < span class = "n" > kwargs< / span > < span class = "p" > ):< / span >
< span class = "nb" > super< / span > < span class = "p" > (< / span > < span class = "n" > ShuffleNet< / span > < span class = "p" > ,< / span > < span class = "bp" > self< / span > < span class = "p" > )< / span > < span class = "o" > .< / span > < span class = "fm" > __init__< / span > < span class = "p" > ()< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > loss< / span > < span class = "o" > =< / span > < span class = "n" > loss< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > conv1< / span > < span class = "o" > =< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > Sequential< / span > < span class = "p" > (< / span >
< span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > Conv2d< / span > < span class = "p" > (< / span > < span class = "mi" > 3< / span > < span class = "p" > ,< / span > < span class = "mi" > 24< / span > < span class = "p" > ,< / span > < span class = "mi" > 3< / span > < span class = "p" > ,< / span > < span class = "n" > stride< / span > < span class = "o" > =< / span > < span class = "mi" > 2< / span > < span class = "p" > ,< / span > < span class = "n" > padding< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > bias< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > ),< / span >
< span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > BatchNorm2d< / span > < span class = "p" > (< / span > < span class = "mi" > 24< / span > < span class = "p" > ),< / span >
< span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > ReLU< / span > < span class = "p" > (),< / span >
< span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > MaxPool2d< / span > < span class = "p" > (< / span > < span class = "mi" > 3< / span > < span class = "p" > ,< / span > < span class = "n" > stride< / span > < span class = "o" > =< / span > < span class = "mi" > 2< / span > < span class = "p" > ,< / span > < span class = "n" > padding< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / span > < span class = "p" > ),< / span >
< span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > stage2< / span > < span class = "o" > =< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > Sequential< / span > < span class = "p" > (< / span >
< span class = "n" > Bottleneck< / span > < span class = "p" > (< / span > < span class = "mi" > 24< / span > < span class = "p" > ,< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 0< / span > < span class = "p" > ],< / span > < span class = "mi" > 2< / span > < span class = "p" > ,< / span > < span class = "n" > num_groups< / span > < span class = "p" > ,< / span > < span class = "n" > group_conv1x1< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > ),< / span >
< span class = "n" > Bottleneck< / span > < span class = "p" > (< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 0< / span > < span class = "p" > ],< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 0< / span > < span class = "p" > ],< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > num_groups< / span > < span class = "p" > ),< / span >
< span class = "n" > Bottleneck< / span > < span class = "p" > (< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 0< / span > < span class = "p" > ],< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 0< / span > < span class = "p" > ],< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > num_groups< / span > < span class = "p" > ),< / span >
< span class = "n" > Bottleneck< / span > < span class = "p" > (< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 0< / span > < span class = "p" > ],< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 0< / span > < span class = "p" > ],< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > num_groups< / span > < span class = "p" > ),< / span >
< span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > stage3< / span > < span class = "o" > =< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > Sequential< / span > < span class = "p" > (< / span >
< span class = "n" > Bottleneck< / span > < span class = "p" > (< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 0< / span > < span class = "p" > ],< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "mi" > 2< / span > < span class = "p" > ,< / span > < span class = "n" > num_groups< / span > < span class = "p" > ),< / span >
< span class = "n" > Bottleneck< / span > < span class = "p" > (< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > num_groups< / span > < span class = "p" > ),< / span >
< span class = "n" > Bottleneck< / span > < span class = "p" > (< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > num_groups< / span > < span class = "p" > ),< / span >
< span class = "n" > Bottleneck< / span > < span class = "p" > (< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > num_groups< / span > < span class = "p" > ),< / span >
< span class = "n" > Bottleneck< / span > < span class = "p" > (< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > num_groups< / span > < span class = "p" > ),< / span >
< span class = "n" > Bottleneck< / span > < span class = "p" > (< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > num_groups< / span > < span class = "p" > ),< / span >
< span class = "n" > Bottleneck< / span > < span class = "p" > (< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > num_groups< / span > < span class = "p" > ),< / span >
< span class = "n" > Bottleneck< / span > < span class = "p" > (< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > num_groups< / span > < span class = "p" > ),< / span >
< span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > stage4< / span > < span class = "o" > =< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > Sequential< / span > < span class = "p" > (< / span >
< span class = "n" > Bottleneck< / span > < span class = "p" > (< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 2< / span > < span class = "p" > ],< / span > < span class = "mi" > 2< / span > < span class = "p" > ,< / span > < span class = "n" > num_groups< / span > < span class = "p" > ),< / span >
< span class = "n" > Bottleneck< / span > < span class = "p" > (< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 2< / span > < span class = "p" > ],< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 2< / span > < span class = "p" > ],< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > num_groups< / span > < span class = "p" > ),< / span >
< span class = "n" > Bottleneck< / span > < span class = "p" > (< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 2< / span > < span class = "p" > ],< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 2< / span > < span class = "p" > ],< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > num_groups< / span > < span class = "p" > ),< / span >
< span class = "n" > Bottleneck< / span > < span class = "p" > (< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 2< / span > < span class = "p" > ],< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 2< / span > < span class = "p" > ],< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > num_groups< / span > < span class = "p" > ),< / span >
< span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > classifier< / span > < span class = "o" > =< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > Linear< / span > < span class = "p" > (< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 2< / span > < span class = "p" > ],< / span > < span class = "n" > num_classes< / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > feat_dim< / span > < span class = "o" > =< / span > < span class = "n" > cfg< / span > < span class = "p" > [< / span > < span class = "n" > num_groups< / span > < span class = "p" > ][< / span > < span class = "mi" > 2< / span > < span class = "p" > ]< / span >
< span class = "k" > def< / span > < span class = "nf" > forward< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "n" > x< / span > < span class = "p" > ):< / span >
< span class = "n" > x< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > conv1< / span > < span class = "p" > (< / span > < span class = "n" > x< / span > < span class = "p" > )< / span >
< span class = "n" > x< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > stage2< / span > < span class = "p" > (< / span > < span class = "n" > x< / span > < span class = "p" > )< / span >
< span class = "n" > x< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > stage3< / span > < span class = "p" > (< / span > < span class = "n" > x< / span > < span class = "p" > )< / span >
< span class = "n" > x< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > stage4< / span > < span class = "p" > (< / span > < span class = "n" > x< / span > < span class = "p" > )< / span >
< span class = "n" > x< / span > < span class = "o" > =< / span > < span class = "n" > F< / span > < span class = "o" > .< / span > < span class = "n" > avg_pool2d< / span > < span class = "p" > (< / span > < span class = "n" > x< / span > < span class = "p" > ,< / span > < span class = "n" > x< / span > < span class = "o" > .< / span > < span class = "n" > size< / span > < span class = "p" > ()[< / span > < span class = "mi" > 2< / span > < span class = "p" > :])< / span > < span class = "o" > .< / span > < span class = "n" > view< / span > < span class = "p" > (< / span > < span class = "n" > x< / span > < span class = "o" > .< / span > < span class = "n" > size< / span > < span class = "p" > (< / span > < span class = "mi" > 0< / span > < span class = "p" > ),< / span > < span class = "o" > -< / span > < span class = "mi" > 1< / span > < span class = "p" > )< / span >
< span class = "k" > if< / span > < span class = "ow" > not< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > training< / span > < span class = "p" > :< / span >
< span class = "k" > return< / span > < span class = "n" > x< / span >
< span class = "n" > y< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > classifier< / span > < span class = "p" > (< / span > < span class = "n" > x< / span > < span class = "p" > )< / span >
< span class = "k" > if< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > loss< / span > < span class = "o" > ==< / span > < span class = "s1" > ' softmax' < / span > < span class = "p" > :< / span >
< span class = "k" > return< / span > < span class = "n" > y< / span >
< span class = "k" > elif< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > loss< / span > < span class = "o" > ==< / span > < span class = "s1" > ' triplet' < / span > < span class = "p" > :< / span >
< span class = "k" > return< / span > < span class = "n" > y< / span > < span class = "p" > ,< / span > < span class = "n" > x< / span >
< span class = "k" > else< / span > < span class = "p" > :< / span >
< span class = "k" > raise< / span > < span class = "ne" > KeyError< / span > < span class = "p" > (< / span > < span class = "s1" > ' Unsupported loss: < / span > < span class = "si" > {}< / span > < span class = "s1" > ' < / span > < span class = "o" > .< / span > < span class = "n" > format< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > loss< / span > < span class = "p" > ))< / span > < / div >
< span class = "k" > def< / span > < span class = "nf" > init_pretrained_weights< / span > < span class = "p" > (< / span > < span class = "n" > model< / span > < span class = "p" > ,< / span > < span class = "n" > model_url< / span > < span class = "p" > ):< / span >
< span class = "sd" > " " " Initializes model with pretrained weights.< / span >
< span class = "sd" > < / span >
< span class = "sd" > Layers that don' t match with pretrained layers in name or size are kept unchanged.< / span >
< span class = "sd" > " " " < / span >
< span class = "n" > pretrain_dict< / span > < span class = "o" > =< / span > < span class = "n" > model_zoo< / span > < span class = "o" > .< / span > < span class = "n" > load_url< / span > < span class = "p" > (< / span > < span class = "n" > model_url< / span > < span class = "p" > )< / span >
< span class = "n" > model_dict< / span > < span class = "o" > =< / span > < span class = "n" > model< / span > < span class = "o" > .< / span > < span class = "n" > state_dict< / span > < span class = "p" > ()< / span >
< span class = "n" > pretrain_dict< / span > < span class = "o" > =< / span > < span class = "p" > {< / span > < span class = "n" > k< / span > < span class = "p" > :< / span > < span class = "n" > v< / span > < span class = "k" > for< / span > < span class = "n" > k< / span > < span class = "p" > ,< / span > < span class = "n" > v< / span > < span class = "ow" > in< / span > < span class = "n" > pretrain_dict< / span > < span class = "o" > .< / span > < span class = "n" > items< / span > < span class = "p" > ()< / span > < span class = "k" > if< / span > < span class = "n" > k< / span > < span class = "ow" > in< / span > < span class = "n" > model_dict< / span > < span class = "ow" > and< / span > < span class = "n" > model_dict< / span > < span class = "p" > [< / span > < span class = "n" > k< / span > < span class = "p" > ]< / span > < span class = "o" > .< / span > < span class = "n" > size< / span > < span class = "p" > ()< / span > < span class = "o" > ==< / span > < span class = "n" > v< / span > < span class = "o" > .< / span > < span class = "n" > size< / span > < span class = "p" > ()}< / span >
< span class = "n" > model_dict< / span > < span class = "o" > .< / span > < span class = "n" > update< / span > < span class = "p" > (< / span > < span class = "n" > pretrain_dict< / span > < span class = "p" > )< / span >
< span class = "n" > model< / span > < span class = "o" > .< / span > < span class = "n" > load_state_dict< / span > < span class = "p" > (< / span > < span class = "n" > model_dict< / span > < span class = "p" > )< / span >
< span class = "k" > def< / span > < span class = "nf" > shufflenet< / span > < span class = "p" > (< / span > < span class = "n" > num_classes< / span > < span class = "p" > ,< / span > < span class = "n" > loss< / span > < span class = "o" > =< / span > < span class = "s1" > ' softmax' < / span > < span class = "p" > ,< / span > < span class = "n" > pretrained< / span > < span class = "o" > =< / span > < span class = "kc" > True< / span > < span class = "p" > ,< / span > < span class = "o" > **< / span > < span class = "n" > kwargs< / span > < span class = "p" > ):< / span >
< span class = "n" > model< / span > < span class = "o" > =< / span > < span class = "n" > ShuffleNet< / span > < span class = "p" > (< / span > < span class = "n" > num_classes< / span > < span class = "p" > ,< / span > < span class = "n" > loss< / span > < span class = "p" > ,< / span > < span class = "o" > **< / span > < span class = "n" > kwargs< / span > < span class = "p" > )< / span >
< span class = "k" > if< / span > < span class = "n" > pretrained< / span > < span class = "p" > :< / span >
< span class = "n" > init_pretrained_weights< / span > < span class = "p" > (< / span > < span class = "n" > model< / span > < span class = "p" > ,< / span > < span class = "n" > model_urls< / span > < span class = "p" > [< / span > < span class = "s1" > ' imagenet' < / span > < span class = "p" > ])< / span >
< span class = "k" > return< / span > < span class = "n" > model< / span >
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© Copyright 2019, Kaiyang Zhou
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