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@ -4,3 +4,4 @@
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================ Training Loss (Sun Feb 23 16:02:40 2025) ================
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================ Training Loss (Sun Feb 23 16:05:19 2025) ================
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================ Training Loss (Sun Feb 23 16:06:44 2025) ================
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================ Training Loss (Sun Feb 23 16:09:38 2025) ================
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@ -984,7 +984,7 @@ class ResnetGenerator(nn.Module):
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else:
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# print("%d: skipping %s %d" % (layer_id, layer.__class__.__name__, feat.size(1)))
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pass
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if layer_id == layers[-1] and encode_only:
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if layer_id == len(list(self.model)) - 1 and encode_only:
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# print('encoder only return features')
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return feats # return intermediate features alone; stop in the last layers
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@ -405,7 +405,6 @@ class RomaUnsbModel(BaseModel):
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self.mutil_real_A0_tokens = self.netPreViT(real_A0, self.atten_layers, get_tokens=True)
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self.mutil_real_A1_tokens = self.netPreViT(real_A1, self.atten_layers, get_tokens=True)
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print(self.mutil_real_A0_tokens)
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self.mutil_real_A0_tokens = torch.cat(self.mutil_real_A0_tokens, dim=1).to(self.device)
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self.mutil_real_A1_tokens = torch.cat(self.mutil_real_A1_tokens, dim=1).to(self.device)
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