often 5 mēneši atpakaļ
vecāks
revīzija
94b8135327

+ 15 - 0
recommend-model-produce/src/main/python/models/dssm/data/train/train.txt

@@ -3,3 +3,18 @@ agsse-19290414-08429345-1709989892    1    1,3,5,2,4    2,16,5,5,8
 sdfsg-192980914-300345-1789969892    1    1,1,1,1,1    1,1,2,2,1
 gasrew-803414-139429345-1789989892    0    1,3,5,2,4    2,16,5,5,8
 gewt-9293414-429345-1789989852    0    12,3,12,2,4    8,16,9,5,8
+djise-19293414-39429345-1789989891    0    1,3,5,2,4    2,16,5,5,8
+agsse-19290414-08429345-17099898921    1    1,3,5,2,4    2,16,5,5,8
+sdfsg-192980914-300345-17899698921    1    1,1,1,1,1    1,1,2,2,1
+gasrew-803414-139429345-17899898921    0    1,3,5,2,4    2,16,5,5,8
+gewt-9293414-429345-17899898521    0    12,3,12,2,4    8,16,9,5,8
+djise-19293414-39429345-1789989891    0    1,3,5,2,4    2,16,5,5,8
+agsse-19290414-08429345-17099898921    1    1,3,5,2,4    2,16,5,5,8
+sdfsg-192980914-300345-17899698921    1    1,1,1,1,1    1,1,2,2,1
+gasrew-803414-139429345-17899898921    0    1,3,5,2,4    2,16,5,5,8
+gewt-9293414-429345-17899898521    0    12,3,12,2,4    8,16,9,5,8
+djise-19293414-39429345-1789989891    0    1,3,5,2,4    2,16,5,5,8
+agsse-19290414-08429345-17099898921    1    1,3,5,2,4    2,16,5,5,8
+sdfsg-192980914-300345-17899698921    1    1,1,1,1,1    1,1,2,2,1
+gasrew-803414-139429345-17899898921    0    1,3,5,2,4    2,16,5,5,8
+gewt-9293414-429345-17899898521    0    12,3,12,2,4    8,16,9,5,8

+ 9 - 2
recommend-model-produce/src/main/python/models/dssm/net.py

@@ -117,15 +117,22 @@ class DSSMLayer(nn.Layer):
         
         left_embedded = self._process_features(left_features, self.left_embeddings)
         paddle.static.Print(left_embedded, message="lqc left_embedded shape:")
-        left_vec = left_embedded
+        # left_vec = left_embedded
+        left_vec = paddle.reshape(left_embedded, [-1, self.feature_num * self.embedding_dim])
+              
+        
         paddle.static.Print(left_vec, message=f"lqc lqc left_vec:")
+        
+        
+        
         for i, layer in enumerate(self._left_tower):
             left_vec = layer(left_vec)
             paddle.static.Print(left_vec, message=f"After layer {i}:")
         
         # 处理右视频特征
         right_embedded = self._process_features(right_features, self.right_embeddings)
-        right_vec = right_embedded
+        # right_vec = right_embedded
+        right_vec = paddle.reshape(right_embedded, [-1, self.feature_num * self.embedding_dim])  
         for layer in self._right_tower:
             right_vec = layer(right_vec)