Method forward

core/unet_timeImage_cond.py:225–239

(self, x, xs, t_emb=None)

            self.upsample = nn.Conv2d(out_channels, out_channels, kernel_size=3, stride=1, padding=1)

    def forward(self, x, xs, t_emb=None):

        for attn, net in zip(self.attns, self.nets):
            res_x = xs[-1] 
            xs = xs[:-1]  
            x = torch.cat([x, res_x], dim=1)
            x = net(x, t_emb)
            if attn:
                x = attn(x)
            
        if self.upsample:
            x = F.interpolate(x, scale_factor=2.0, mode='nearest')
            x = self.upsample(x)

        return x

class UNet_timeimage_cond(nn.Module): 
    def __init__(