Hi everyone,
I am quite new in pyTorch and I noticed that in version 0.4.1 of Pytorch the nn.Upsample is being replaced by nn.functional.interpolate
I’m trying to change the code which I am working on it but I got an error. any help to replace Upsampling to interpolate will be appreciated.
This is part of my model which I need to replace Upsampling to Interpolate:
class GeneratorUNet(nn.Module):
def __init__(self, in_channels=3, out_channels=3, dropout = 0.0):
super(GeneratorUNet, self).__init__()
self.down1 = UNetDown(in_channels, 64, normalize=False)
self.down2 = UNetDown(64, 128)
self.down3 = UNetDown(128, 256)
self.down4 = UNetDown(256, 512, dropout=dropout)
self.down5 = UNetDown(512, 512, dropout=dropout)
self.down6 = UNetDown(512, 512, dropout=dropout)
self.down7 = UNetDown(512, 512, dropout=dropout)
self.down8 = UNetDown(512, 512, normalize=False, dropout=dropout)
self.up1 = UNetUp(512, 512, dropout=dropout)
self.up2 = UNetUp(1024, 512, dropout=dropout)
self.up3 = UNetUp(1024, 512, dropout=dropout)
self.up4 = UNetUp(1024, 512, dropout=dropout)
self.up5 = UNetUp(1024, 256)
self.up6 = UNetUp(512, 128)
self.up7 = UNetUp(256, 64)
self.final = nn.Sequential(
nn.Upsample(scale_factor=2), # Here is the Upsampling needs to replace with interpolate
nn.ZeroPad2d((1, 0, 1, 0)),
nn.Conv2d(128, out_channels, 4, padding=1),
nn.Tanh()
)
def forward(self, x):
d1 = self.down1(x)
d2 = self.down2(d1)
d3 = self.down3(d2)
d4 = self.down4(d3)
d5 = self.down5(d4)
d6 = self.down6(d5)
d7 = self.down7(d6)
d8 = self.down8(d7)
u1 = self.up1(d8, d7)
u2 = self.up2(u1, d6)
u3 = self.up3(u2, d5)
u4 = self.up4(u3, d4)
u5 = self.up5(u4, d3)
u6 = self.up6(u5, d2)
u7 = self.up7(u6, d1)
return self.final(u7)