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															@@ -100,18 +100,18 @@ class DSSMLayer(nn.Layer): 
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															     def forward(self, left_features, right_features): 
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															     def forward(self, left_features, right_features): 
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															         # 获取两个视频的特征表示 
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															         # 获取两个视频的特征表示 
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															-        #paddle.static.Print(left_features, message="lqc left model input shape:") 
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															-        #paddle.static.Print(right_features, message="lqc right model input shape:")         
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															+        paddle.static.Print(left_features, message="lqc left model input shape:") 
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															+        paddle.static.Print(right_features, message="lqc right model input shape:")         
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															         left_vec, right_vec = self.get_vectors(left_features, right_features) 
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															         left_vec, right_vec = self.get_vectors(left_features, right_features) 
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															-        #paddle.static.Print(left_vec, message="lqc left model output shape:") 
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															-        #paddle.static.Print(right_vec, message="lqc right model output shape:") 
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															+        paddle.static.Print(left_vec, message="lqc left model output shape:") 
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															+        paddle.static.Print(right_vec, message="lqc right model output shape:") 
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															         # 计算相似度 
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															         # 计算相似度 
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															         sim_score = F.cosine_similarity( 
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															         sim_score = F.cosine_similarity( 
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															             left_vec,  
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															             left_vec,  
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															             right_vec,  
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															             right_vec,  
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															             axis=1 
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															             axis=1 
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															         ).reshape([-1, 1]) 
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															         ).reshape([-1, 1]) 
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															+        paddle.static.Print(sim_score, message="lqc sim_score shape:") 
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															         return sim_score, left_vec, right_vec 
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															         return sim_score, left_vec, right_vec 
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															     def get_vectors(self, left_features, right_features): 
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															     def get_vectors(self, left_features, right_features): 
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