train HR feature trainer
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@ -74,10 +74,10 @@ class FeatureModel(BaseModel):
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self.optimizer_G.zero_grad()
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self.optimizer_G.zero_grad()
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# grey out the LR image but keep 3 channels.
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# grey out the LR image but keep 3 channels.
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lr = torch.mean(self.var_L, dim=1, keepdim=True)
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lr = torch.mean(self.var_H, dim=1, keepdim=True)
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lr = lr.repeat(1, 3, 1, 1)
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lr = lr.repeat(1, 3, 1, 1)
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self.fake_H = self.fea_train(lr, interpolate_factor=2)
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self.fake_H = self.fea_train(lr, interpolate_factor=1)
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ref_H = self.net_ref(self.real_H)
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ref_H = self.net_ref(self.real_H)
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l_fea = self.cri_fea(self.fake_H, ref_H)
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l_fea = self.cri_fea(self.fake_H, ref_H)
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l_fea.backward()
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l_fea.backward()
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