把训练时l2正则化改成l1正则化

eda/esmm/Model_pipline/train.py

@@ -157,7 +157,7 @@ def model_fn(features, labels, mode, params):
 
 
         # x_concat = tf.reshape(embedding_id,shape=[-1, common_dims])  # None * (F * K)
-        x_concat = tf.concat([tf.reshape(embedding_id, shape=[-1, common_dims]), app_id, levetf.nn.l1, level3, tag1,
+        x_concat = tf.concat([tf.reshape(embedding_id, shape=[-1, common_dims]), app_id, level2, level3, tag1,
                               tag2, tag3, tag4, tag5, tag6, tag7,search_tag2,search_tag3], axis=1)
 
         uid = tf.sparse.to_dense(uid,default_value="")