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The implementation of the decoder is different than the architecture posted here. #19

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hsu-z2 opened this issue Jul 11, 2018 · 0 comments

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@hsu-z2
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hsu-z2 commented Jul 11, 2018

In the architecture defined by the code is different than the architecture posed in the webpage:
Why is this different? Which one works better? Thank you!

class UpTransition(nn.Module):
def init(self, inChans, outChans, nConvs, elu, dropout=False):
super(UpTransition, self).init()
self.up_conv = nn.ConvTranspose3d(inChans, outChans // 2, kernel_size=2, stride=2)
self.bn1 = ContBatchNorm3d(outChans // 2)
self.do1 = passthrough
self.do2 = nn.Dropout3d()
self.relu1 = ELUCons(elu, outChans // 2)
self.relu2 = ELUCons(elu, outChans)
if dropout:
self.do1 = nn.Dropout3d()
self.ops = _make_nConv(outChans, nConvs, elu)
def forward(self, x, skipx):
out = self.do1(x)
skipxdo = self.do2(skipx)
out = self.relu1(self.bn1(self.up_conv(out)))
xcat = torch.cat((out, skipxdo), 1)
out = self.ops(xcat)
out = self.relu2(torch.add(out, xcat))
return out

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