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2019-03-26 02:49:57 +08:00
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< h1 > Source code for torchreid.models.pcb< / 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" > ' pcb_p6' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' pcb_p4' < / 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 = "s1" > ' resnet18' < / span > < span class = "p" > :< / span > < span class = "s1" > ' https://download.pytorch.org/models/resnet18-5c106cde.pth' < / span > < span class = "p" > ,< / span >
< span class = "s1" > ' resnet34' < / span > < span class = "p" > :< / span > < span class = "s1" > ' https://download.pytorch.org/models/resnet34-333f7ec4.pth' < / span > < span class = "p" > ,< / span >
< span class = "s1" > ' resnet50' < / span > < span class = "p" > :< / span > < span class = "s1" > ' https://download.pytorch.org/models/resnet50-19c8e357.pth' < / span > < span class = "p" > ,< / span >
< span class = "s1" > ' resnet101' < / span > < span class = "p" > :< / span > < span class = "s1" > ' https://download.pytorch.org/models/resnet101-5d3b4d8f.pth' < / span > < span class = "p" > ,< / span >
< span class = "s1" > ' resnet152' < / span > < span class = "p" > :< / span > < span class = "s1" > ' https://download.pytorch.org/models/resnet152-b121ed2d.pth' < / span > < span class = "p" > ,< / span >
< span class = "p" > }< / span >
< span class = "k" > def< / span > < span class = "nf" > conv3x3< / span > < span class = "p" > (< / span > < span class = "n" > in_planes< / span > < span class = "p" > ,< / span > < span class = "n" > out_planes< / span > < span class = "p" > ,< / span > < span class = "n" > stride< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / span > < span class = "p" > ):< / span >
< span class = "sd" > " " " 3x3 convolution with padding" " " < / span >
< span class = "k" > return< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > Conv2d< / span > < span class = "p" > (< / span > < span class = "n" > in_planes< / span > < span class = "p" > ,< / span > < span class = "n" > out_planes< / span > < span class = "p" > ,< / span > < span class = "n" > kernel_size< / span > < span class = "o" > =< / 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" > bias< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > )< / span >
< span class = "k" > class< / span > < span class = "nc" > BasicBlock< / 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 = "n" > expansion< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / 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" > inplanes< / span > < span class = "p" > ,< / span > < span class = "n" > planes< / span > < span class = "p" > ,< / span > < span class = "n" > stride< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > downsample< / span > < span class = "o" > =< / span > < span class = "kc" > None< / span > < span class = "p" > ):< / span >
< span class = "nb" > super< / span > < span class = "p" > (< / span > < span class = "n" > BasicBlock< / 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" > conv1< / span > < span class = "o" > =< / span > < span class = "n" > conv3x3< / span > < span class = "p" > (< / span > < span class = "n" > inplanes< / span > < span class = "p" > ,< / span > < span class = "n" > planes< / span > < span class = "p" > ,< / span > < span class = "n" > stride< / 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" > planes< / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > relu< / span > < span class = "o" > =< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > ReLU< / span > < span class = "p" > (< / span > < span class = "n" > inplace< / span > < span class = "o" > =< / span > < span class = "kc" > True< / 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" > conv3x3< / span > < span class = "p" > (< / span > < span class = "n" > planes< / span > < span class = "p" > ,< / span > < span class = "n" > planes< / 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" > planes< / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > downsample< / span > < span class = "o" > =< / span > < span class = "n" > downsample< / 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 = "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" > residual< / span > < span class = "o" > =< / span > < span class = "n" > x< / span >
< span class = "n" > out< / 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" > out< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > bn1< / 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" > relu< / 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" > 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" > bn2< / 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" > downsample< / span > < span class = "ow" > is< / span > < span class = "ow" > not< / span > < span class = "kc" > None< / span > < span class = "p" > :< / span >
< span class = "n" > residual< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > downsample< / 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" > residual< / span >
< span class = "n" > out< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > relu< / span > < span class = "p" > (< / span > < span class = "n" > out< / span > < span class = "p" > )< / span >
< span class = "k" > return< / span > < span class = "n" > out< / 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 = "n" > expansion< / span > < span class = "o" > =< / span > < span class = "mi" > 4< / 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" > inplanes< / span > < span class = "p" > ,< / span > < span class = "n" > planes< / span > < span class = "p" > ,< / span > < span class = "n" > stride< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > downsample< / span > < span class = "o" > =< / span > < span class = "kc" > None< / 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 = "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" > inplanes< / span > < span class = "p" > ,< / span > < span class = "n" > planes< / span > < span class = "p" > ,< / span > < span class = "n" > kernel_size< / 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 = "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" > planes< / 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" > planes< / span > < span class = "p" > ,< / span > < span class = "n" > planes< / span > < span class = "p" > ,< / span > < span class = "n" > kernel_size< / span > < span class = "o" > =< / 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" > 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" > planes< / 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" > planes< / span > < span class = "p" > ,< / span > < span class = "n" > planes< / span > < span class = "o" > *< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > expansion< / span > < span class = "p" > ,< / span > < span class = "n" > kernel_size< / 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 = "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" > planes< / span > < span class = "o" > *< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > expansion< / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > relu< / span > < span class = "o" > =< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > ReLU< / span > < span class = "p" > (< / span > < span class = "n" > inplace< / span > < span class = "o" > =< / span > < span class = "kc" > True< / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > downsample< / span > < span class = "o" > =< / span > < span class = "n" > downsample< / 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 = "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" > residual< / span > < span class = "o" > =< / span > < span class = "n" > x< / span >
< span class = "n" > out< / 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" > out< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > bn1< / 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" > relu< / 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" > 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" > bn2< / 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" > relu< / 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" > conv3< / 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 = "n" > out< / span > < span class = "p" > )< / span >
< span class = "k" > if< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > downsample< / span > < span class = "ow" > is< / span > < span class = "ow" > not< / span > < span class = "kc" > None< / span > < span class = "p" > :< / span >
< span class = "n" > residual< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > downsample< / 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" > residual< / span >
< span class = "n" > out< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > relu< / span > < span class = "p" > (< / span > < span class = "n" > out< / span > < span class = "p" > )< / span >
< span class = "k" > return< / span > < span class = "n" > out< / span >
< span class = "k" > class< / span > < span class = "nc" > DimReduceLayer< / 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" > nonlinear< / span > < span class = "p" > ):< / span >
< span class = "nb" > super< / span > < span class = "p" > (< / span > < span class = "n" > DimReduceLayer< / 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 = "n" > layers< / span > < span class = "o" > =< / span > < span class = "p" > []< / span >
< span class = "n" > layers< / span > < span class = "o" > .< / span > < span class = "n" > append< / 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 = "n" > in_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" > stride< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > padding< / span > < span class = "o" > =< / span > < span class = "mi" > 0< / 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" > layers< / span > < span class = "o" > .< / span > < span class = "n" > append< / 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 = "n" > out_channels< / span > < span class = "p" > ))< / span >
< span class = "k" > if< / span > < span class = "n" > nonlinear< / span > < span class = "o" > ==< / span > < span class = "s1" > ' relu' < / span > < span class = "p" > :< / span >
< span class = "n" > layers< / span > < span class = "o" > .< / span > < span class = "n" > append< / 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" > inplace< / span > < span class = "o" > =< / span > < span class = "kc" > True< / span > < span class = "p" > ))< / span >
< span class = "k" > elif< / span > < span class = "n" > nonlinear< / span > < span class = "o" > ==< / span > < span class = "s1" > ' leakyrelu' < / span > < span class = "p" > :< / span >
< span class = "n" > layers< / span > < span class = "o" > .< / span > < span class = "n" > append< / span > < span class = "p" > (< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > LeakyReLU< / span > < span class = "p" > (< / span > < span class = "mf" > 0.1< / span > < span class = "p" > ))< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > layers< / 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 = "o" > *< / span > < span class = "n" > layers< / 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 = "k" > return< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > layers< / span > < span class = "p" > (< / span > < span class = "n" > x< / span > < span class = "p" > )< / span >
< div class = "viewcode-block" id = "PCB" > < a class = "viewcode-back" href = "../../../pkg/models.html#torchreid.models.pcb.PCB" > [docs]< / a > < span class = "k" > class< / span > < span class = "nc" > PCB< / 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" > " " " Part-based Convolutional Baseline.< / span >
< span class = "sd" > Reference:< / span >
< span class = "sd" > Sun et al. Beyond Part Models: Person Retrieval with Refined< / span >
< span class = "sd" > Part Pooling (and A Strong Convolutional Baseline). ECCV 2018.< / span >
< span class = "sd" > Public keys:< / span >
< span class = "sd" > - ``pcb_p4``: PCB with 4-part strips.< / span >
< span class = "sd" > - ``pcb_p6``: PCB with 6-part strips.< / 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 = "p" > ,< / span > < span class = "n" > block< / span > < span class = "p" > ,< / span > < span class = "n" > layers< / span > < span class = "p" > ,< / span >
< span class = "n" > parts< / span > < span class = "o" > =< / span > < span class = "mi" > 6< / span > < span class = "p" > ,< / span >
< span class = "n" > reduced_dim< / span > < span class = "o" > =< / span > < span class = "mi" > 256< / span > < span class = "p" > ,< / span >
< span class = "n" > nonlinear< / span > < span class = "o" > =< / span > < span class = "s1" > ' relu' < / span > < span class = "p" > ,< / span >
< span class = "o" > **< / span > < span class = "n" > kwargs< / span > < span class = "p" > ):< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > inplanes< / span > < span class = "o" > =< / span > < span class = "mi" > 64< / span >
< span class = "nb" > super< / span > < span class = "p" > (< / span > < span class = "n" > PCB< / 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" > parts< / span > < span class = "o" > =< / span > < span class = "n" > parts< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > feature_dim< / span > < span class = "o" > =< / span > < span class = "mi" > 512< / span > < span class = "o" > *< / span > < span class = "n" > block< / span > < span class = "o" > .< / span > < span class = "n" > expansion< / span >
< span class = "c1" > # backbone network< / 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 = "mi" > 3< / span > < span class = "p" > ,< / span > < span class = "mi" > 64< / span > < span class = "p" > ,< / span > < span class = "n" > kernel_size< / span > < span class = "o" > =< / span > < span class = "mi" > 7< / 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" > 3< / 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 = "mi" > 64< / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > relu< / span > < span class = "o" > =< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > ReLU< / span > < span class = "p" > (< / span > < span class = "n" > inplace< / span > < span class = "o" > =< / span > < span class = "kc" > True< / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > maxpool< / span > < span class = "o" > =< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > MaxPool2d< / span > < span class = "p" > (< / span > < span class = "n" > kernel_size< / span > < span class = "o" > =< / 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 = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > layer1< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _make_layer< / span > < span class = "p" > (< / span > < span class = "n" > block< / span > < span class = "p" > ,< / span > < span class = "mi" > 64< / span > < span class = "p" > ,< / span > < span class = "n" > layers< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ])< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > layer2< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _make_layer< / span > < span class = "p" > (< / span > < span class = "n" > block< / span > < span class = "p" > ,< / span > < span class = "mi" > 128< / span > < span class = "p" > ,< / span > < span class = "n" > layers< / span > < span class = "p" > [< / span > < span class = "mi" > 1< / 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 = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > layer3< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _make_layer< / span > < span class = "p" > (< / span > < span class = "n" > block< / span > < span class = "p" > ,< / span > < span class = "mi" > 256< / span > < span class = "p" > ,< / span > < span class = "n" > layers< / span > < span class = "p" > [< / span > < span class = "mi" > 2< / 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 = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > layer4< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _make_layer< / span > < span class = "p" > (< / span > < span class = "n" > block< / span > < span class = "p" > ,< / span > < span class = "mi" > 512< / span > < span class = "p" > ,< / span > < span class = "n" > layers< / 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" > 1< / span > < span class = "p" > )< / span >
< span class = "c1" > # pcb layers< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > parts_avgpool< / span > < span class = "o" > =< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > AdaptiveAvgPool2d< / span > < span class = "p" > ((< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > parts< / span > < span class = "p" > ,< / span > < span class = "mi" > 1< / span > < span class = "p" > ))< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > dropout< / span > < span class = "o" > =< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > Dropout< / span > < span class = "p" > (< / span > < span class = "n" > p< / span > < span class = "o" > =< / span > < span class = "mf" > 0.5< / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > conv5< / span > < span class = "o" > =< / span > < span class = "n" > DimReduceLayer< / span > < span class = "p" > (< / span > < span class = "mi" > 512< / span > < span class = "o" > *< / span > < span class = "n" > block< / span > < span class = "o" > .< / span > < span class = "n" > expansion< / span > < span class = "p" > ,< / span > < span class = "n" > reduced_dim< / span > < span class = "p" > ,< / span > < span class = "n" > nonlinear< / span > < span class = "o" > =< / span > < span class = "n" > nonlinear< / span > < span class = "p" > )< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > feature_dim< / span > < span class = "o" > =< / span > < span class = "n" > reduced_dim< / 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" > ModuleList< / span > < span class = "p" > ([< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > Linear< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > feature_dim< / span > < span class = "p" > ,< / span > < span class = "n" > num_classes< / span > < span class = "p" > )< / span > < span class = "k" > for< / span > < span class = "n" > _< / span > < span class = "ow" > in< / span > < span class = "nb" > range< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > parts< / span > < span class = "p" > )])< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _init_params< / span > < span class = "p" > ()< / span >
< span class = "k" > def< / span > < span class = "nf" > _make_layer< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "n" > block< / span > < span class = "p" > ,< / span > < span class = "n" > planes< / span > < span class = "p" > ,< / span > < span class = "n" > blocks< / span > < span class = "p" > ,< / span > < span class = "n" > stride< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / span > < span class = "p" > ):< / span >
< span class = "n" > downsample< / span > < span class = "o" > =< / span > < span class = "kc" > None< / span >
< span class = "k" > if< / span > < span class = "n" > stride< / span > < span class = "o" > !=< / span > < span class = "mi" > 1< / span > < span class = "ow" > or< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > inplanes< / span > < span class = "o" > !=< / span > < span class = "n" > planes< / span > < span class = "o" > *< / span > < span class = "n" > block< / span > < span class = "o" > .< / span > < span class = "n" > expansion< / span > < span class = "p" > :< / span >
< span class = "n" > downsample< / 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 = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > inplanes< / span > < span class = "p" > ,< / span > < span class = "n" > planes< / span > < span class = "o" > *< / span > < span class = "n" > block< / span > < span class = "o" > .< / span > < span class = "n" > expansion< / span > < span class = "p" > ,< / span >
< span class = "n" > kernel_size< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / 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" > 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 = "n" > planes< / span > < span class = "o" > *< / span > < span class = "n" > block< / span > < span class = "o" > .< / span > < span class = "n" > expansion< / span > < span class = "p" > ),< / span >
< span class = "p" > )< / span >
< span class = "n" > layers< / span > < span class = "o" > =< / span > < span class = "p" > []< / span >
< span class = "n" > layers< / span > < span class = "o" > .< / span > < span class = "n" > append< / span > < span class = "p" > (< / span > < span class = "n" > block< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > inplanes< / span > < span class = "p" > ,< / span > < span class = "n" > planes< / span > < span class = "p" > ,< / span > < span class = "n" > stride< / span > < span class = "p" > ,< / span > < span class = "n" > downsample< / span > < span class = "p" > ))< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > inplanes< / span > < span class = "o" > =< / span > < span class = "n" > planes< / span > < span class = "o" > *< / span > < span class = "n" > block< / span > < span class = "o" > .< / span > < span class = "n" > expansion< / span >
< span class = "k" > for< / span > < span class = "n" > i< / span > < span class = "ow" > in< / span > < span class = "nb" > range< / span > < span class = "p" > (< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > blocks< / span > < span class = "p" > ):< / span >
< span class = "n" > layers< / span > < span class = "o" > .< / span > < span class = "n" > append< / span > < span class = "p" > (< / span > < span class = "n" > block< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > inplanes< / span > < span class = "p" > ,< / span > < span class = "n" > planes< / span > < span class = "p" > ))< / span >
< span class = "k" > return< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > Sequential< / span > < span class = "p" > (< / span > < span class = "o" > *< / span > < span class = "n" > layers< / span > < span class = "p" > )< / span >
< span class = "k" > def< / span > < span class = "nf" > _init_params< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ):< / span >
< span class = "k" > for< / span > < span class = "n" > m< / span > < span class = "ow" > in< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > modules< / span > < span class = "p" > ():< / span >
< span class = "k" > if< / span > < span class = "nb" > isinstance< / span > < span class = "p" > (< / span > < span class = "n" > m< / 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 = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > init< / span > < span class = "o" > .< / span > < span class = "n" > kaiming_normal_< / span > < span class = "p" > (< / span > < span class = "n" > m< / span > < span class = "o" > .< / span > < span class = "n" > weight< / span > < span class = "p" > ,< / span > < span class = "n" > mode< / span > < span class = "o" > =< / span > < span class = "s1" > ' fan_out' < / span > < span class = "p" > ,< / span > < span class = "n" > nonlinearity< / span > < span class = "o" > =< / span > < span class = "s1" > ' relu' < / span > < span class = "p" > )< / span >
< span class = "k" > if< / span > < span class = "n" > m< / span > < span class = "o" > .< / span > < span class = "n" > bias< / span > < span class = "ow" > is< / span > < span class = "ow" > not< / span > < span class = "kc" > None< / span > < span class = "p" > :< / span >
< span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > init< / span > < span class = "o" > .< / span > < span class = "n" > constant_< / span > < span class = "p" > (< / span > < span class = "n" > m< / span > < span class = "o" > .< / span > < span class = "n" > bias< / span > < span class = "p" > ,< / span > < span class = "mi" > 0< / span > < span class = "p" > )< / span >
< span class = "k" > elif< / span > < span class = "nb" > isinstance< / span > < span class = "p" > (< / span > < span class = "n" > m< / 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 = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > init< / span > < span class = "o" > .< / span > < span class = "n" > constant_< / span > < span class = "p" > (< / span > < span class = "n" > m< / span > < span class = "o" > .< / span > < span class = "n" > weight< / span > < span class = "p" > ,< / span > < span class = "mi" > 1< / span > < span class = "p" > )< / span >
< span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > init< / span > < span class = "o" > .< / span > < span class = "n" > constant_< / span > < span class = "p" > (< / span > < span class = "n" > m< / span > < span class = "o" > .< / span > < span class = "n" > bias< / span > < span class = "p" > ,< / span > < span class = "mi" > 0< / span > < span class = "p" > )< / span >
< span class = "k" > elif< / span > < span class = "nb" > isinstance< / span > < span class = "p" > (< / span > < span class = "n" > m< / span > < span class = "p" > ,< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > BatchNorm1d< / span > < span class = "p" > ):< / span >
< span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > init< / span > < span class = "o" > .< / span > < span class = "n" > constant_< / span > < span class = "p" > (< / span > < span class = "n" > m< / span > < span class = "o" > .< / span > < span class = "n" > weight< / span > < span class = "p" > ,< / span > < span class = "mi" > 1< / span > < span class = "p" > )< / span >
< span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > init< / span > < span class = "o" > .< / span > < span class = "n" > constant_< / span > < span class = "p" > (< / span > < span class = "n" > m< / span > < span class = "o" > .< / span > < span class = "n" > bias< / span > < span class = "p" > ,< / span > < span class = "mi" > 0< / span > < span class = "p" > )< / span >
< span class = "k" > elif< / span > < span class = "nb" > isinstance< / span > < span class = "p" > (< / span > < span class = "n" > m< / span > < span class = "p" > ,< / span > < span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > Linear< / span > < span class = "p" > ):< / span >
< span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > init< / span > < span class = "o" > .< / span > < span class = "n" > normal_< / span > < span class = "p" > (< / span > < span class = "n" > m< / span > < span class = "o" > .< / span > < span class = "n" > weight< / span > < span class = "p" > ,< / span > < span class = "mi" > 0< / span > < span class = "p" > ,< / span > < span class = "mf" > 0.01< / span > < span class = "p" > )< / span >
< span class = "k" > if< / span > < span class = "n" > m< / span > < span class = "o" > .< / span > < span class = "n" > bias< / span > < span class = "ow" > is< / span > < span class = "ow" > not< / span > < span class = "kc" > None< / span > < span class = "p" > :< / span >
< span class = "n" > nn< / span > < span class = "o" > .< / span > < span class = "n" > init< / span > < span class = "o" > .< / span > < span class = "n" > constant_< / span > < span class = "p" > (< / span > < span class = "n" > m< / span > < span class = "o" > .< / span > < span class = "n" > bias< / span > < span class = "p" > ,< / span > < span class = "mi" > 0< / span > < span class = "p" > )< / span >
< span class = "k" > def< / span > < span class = "nf" > featuremaps< / 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" > bn1< / 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" > relu< / 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" > maxpool< / 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" > layer1< / 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" > layer2< / 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" > layer3< / 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" > layer4< / span > < span class = "p" > (< / span > < span class = "n" > x< / span > < span class = "p" > )< / span >
< span class = "k" > return< / span > < span class = "n" > x< / 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" > f< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > featuremaps< / span > < span class = "p" > (< / span > < span class = "n" > x< / span > < span class = "p" > )< / span >
< span class = "n" > v_g< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > parts_avgpool< / span > < span class = "p" > (< / span > < span class = "n" > f< / 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 = "n" > v_g< / span > < span class = "o" > =< / span > < span class = "n" > F< / span > < span class = "o" > .< / span > < span class = "n" > normalize< / span > < span class = "p" > (< / span > < span class = "n" > v_g< / span > < span class = "p" > ,< / span > < span class = "n" > p< / span > < span class = "o" > =< / span > < span class = "mi" > 2< / span > < span class = "p" > ,< / span > < span class = "n" > dim< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / span > < span class = "p" > )< / span >
< span class = "k" > return< / span > < span class = "n" > v_g< / span > < span class = "o" > .< / span > < span class = "n" > view< / span > < span class = "p" > (< / span > < span class = "n" > v_g< / 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 = "n" > v_g< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > dropout< / span > < span class = "p" > (< / span > < span class = "n" > v_g< / span > < span class = "p" > )< / span >
< span class = "n" > v_h< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > conv5< / span > < span class = "p" > (< / span > < span class = "n" > v_g< / span > < span class = "p" > )< / span >
< span class = "n" > y< / span > < span class = "o" > =< / span > < span class = "p" > []< / span >
< span class = "k" > for< / span > < span class = "n" > i< / span > < span class = "ow" > in< / span > < span class = "nb" > range< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > parts< / span > < span class = "p" > ):< / span >
< span class = "n" > v_h_i< / span > < span class = "o" > =< / span > < span class = "n" > v_h< / span > < span class = "p" > [:,< / span > < span class = "p" > :,< / span > < span class = "n" > i< / span > < span class = "p" > ,< / span > < span class = "p" > :]< / span >
< span class = "n" > v_h_i< / span > < span class = "o" > =< / span > < span class = "n" > v_h_i< / span > < span class = "o" > .< / span > < span class = "n" > view< / span > < span class = "p" > (< / span > < span class = "n" > v_h_i< / 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 = "n" > y_i< / 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" > i< / span > < span class = "p" > ](< / span > < span class = "n" > v_h_i< / span > < span class = "p" > )< / span >
< span class = "n" > y< / span > < span class = "o" > .< / span > < span class = "n" > append< / span > < span class = "p" > (< / span > < span class = "n" > y_i< / 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 = "n" > v_g< / span > < span class = "o" > =< / span > < span class = "n" > F< / span > < span class = "o" > .< / span > < span class = "n" > normalize< / span > < span class = "p" > (< / span > < span class = "n" > v_g< / span > < span class = "p" > ,< / span > < span class = "n" > p< / span > < span class = "o" > =< / span > < span class = "mi" > 2< / span > < span class = "p" > ,< / span > < span class = "n" > dim< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / span > < span class = "p" > )< / span >
< span class = "k" > return< / span > < span class = "n" > y< / span > < span class = "p" > ,< / span > < span class = "n" > v_g< / span > < span class = "o" > .< / span > < span class = "n" > view< / span > < span class = "p" > (< / span > < span class = "n" > v_g< / 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" > 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 = "nb" > print< / span > < span class = "p" > (< / span > < span class = "s1" > ' Initialized model with pretrained weights from < / span > < span class = "si" > {}< / span > < span class = "s1" > ' < / span > < span class = "o" > .< / span > < span class = "n" > format< / span > < span class = "p" > (< / span > < span class = "n" > model_url< / span > < span class = "p" > ))< / span >
< span class = "k" > def< / span > < span class = "nf" > pcb_p6< / 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" > PCB< / span > < span class = "p" > (< / span >
< span class = "n" > num_classes< / span > < span class = "o" > =< / span > < span class = "n" > num_classes< / span > < span class = "p" > ,< / span >
< span class = "n" > loss< / span > < span class = "o" > =< / span > < span class = "n" > loss< / span > < span class = "p" > ,< / span >
< span class = "n" > block< / span > < span class = "o" > =< / span > < span class = "n" > Bottleneck< / span > < span class = "p" > ,< / span >
< span class = "n" > layers< / span > < span class = "o" > =< / 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 = "mi" > 6< / span > < span class = "p" > ,< / span > < span class = "mi" > 3< / span > < span class = "p" > ],< / span >
< span class = "n" > last_stride< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span >
< span class = "n" > parts< / span > < span class = "o" > =< / span > < span class = "mi" > 6< / span > < span class = "p" > ,< / span >
< span class = "n" > reduced_dim< / span > < span class = "o" > =< / span > < span class = "mi" > 256< / span > < span class = "p" > ,< / span >
< span class = "n" > nonlinear< / span > < span class = "o" > =< / span > < span class = "s1" > ' relu' < / 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" > ' resnet50' < / span > < span class = "p" > ])< / span >
< span class = "k" > return< / span > < span class = "n" > model< / span >
< span class = "k" > def< / span > < span class = "nf" > pcb_p4< / 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" > PCB< / span > < span class = "p" > (< / span >
< span class = "n" > num_classes< / span > < span class = "o" > =< / span > < span class = "n" > num_classes< / span > < span class = "p" > ,< / span >
< span class = "n" > loss< / span > < span class = "o" > =< / span > < span class = "n" > loss< / span > < span class = "p" > ,< / span >
< span class = "n" > block< / span > < span class = "o" > =< / span > < span class = "n" > Bottleneck< / span > < span class = "p" > ,< / span >
< span class = "n" > layers< / span > < span class = "o" > =< / 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 = "mi" > 6< / span > < span class = "p" > ,< / span > < span class = "mi" > 3< / span > < span class = "p" > ],< / span >
< span class = "n" > last_stride< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span >
< span class = "n" > parts< / span > < span class = "o" > =< / span > < span class = "mi" > 4< / span > < span class = "p" > ,< / span >
< span class = "n" > reduced_dim< / span > < span class = "o" > =< / span > < span class = "mi" > 256< / span > < span class = "p" > ,< / span >
< span class = "n" > nonlinear< / span > < span class = "o" > =< / span > < span class = "s1" > ' relu' < / 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" > ' resnet50' < / 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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