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import torch.nn as nn
from torch.autograd import Variable
from .layers.SE_Resnet import SEResnet
from .layers.DUC import DUC
from opt import opt
def createModel():
return FastPose()
class FastPose(nn.Module):
DIM = 128
def __init__(self):
super(FastPose, self).__init__()
self.preact = SEResnet('resnet101')
self.suffle1 = nn.PixelShuffle(2)
self.duc1 = DUC(512, 1024, upscale_factor=2)
self.duc2 = DUC(256, 512, upscale_factor=2)
self.conv_out = nn.Conv2d(
self.DIM, opt.nClasses, kernel_size=3, stride=1, padding=1)
def forward(self, x: Variable):
out = self.preact(x)
out = self.suffle1(out)
out = self.duc1(out)
out = self.duc2(out)
out = self.conv_out(out)
return out