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Merge pull request #161 from somehower/master
optimize the passed in parameters in the case of bilinear Former-commit-id: 5f37e8a6dc592563593210371cebd40f95788080
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c57180e90c
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@ -18,10 +18,10 @@ class UNet(nn.Module):
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self.down3 = Down(256, 512)
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factor = 2 if bilinear else 1
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self.down4 = Down(512, 1024 // factor)
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self.up1 = Up(1024, 512, bilinear)
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self.up2 = Up(512, 256, bilinear)
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self.up3 = Up(256, 128, bilinear)
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self.up4 = Up(128, 64 * factor, bilinear)
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self.up1 = Up(1024, 512 // factor, bilinear)
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self.up2 = Up(512, 256 // factor, bilinear)
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self.up3 = Up(256, 128 // factor, bilinear)
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self.up4 = Up(128, 64, bilinear)
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self.outc = OutConv(64, n_classes)
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def forward(self, x):
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@ -48,7 +48,7 @@ class Up(nn.Module):
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# if bilinear, use the normal convolutions to reduce the number of channels
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if bilinear:
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self.up = nn.Upsample(scale_factor=2, mode='bilinear', align_corners=True)
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self.conv = DoubleConv(in_channels, out_channels // 2, in_channels // 2)
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self.conv = DoubleConv(in_channels, out_channels, in_channels // 2)
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else:
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self.up = nn.ConvTranspose2d(in_channels , in_channels // 2, kernel_size=2, stride=2)
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self.conv = DoubleConv(in_channels, out_channels)
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