dcf583f15d08415d4e1972d44c250a5f13f6b10c,examples/run_dsin.py,,get_xy_fd,#Any#,7

Before Change

                       SparseFeat("item_gender", 2 + 1, embedding_dim=4,use_hash=hash_flag),
                       DenseFeat("score", 1)]
    feature_columns += [VarLenSparseFeat("sess_0_item",maxlen=4,vocabulary_size=3+1,embedding_dim=4,use_hash=hash_flag,embedding_name="item"),VarLenSparseFeat("sess_0_item_gender",maxlen=4,vocabulary_size=2+1,embedding_dim=4,use_hash=hash_flag,embedding_name="item_gender")]
    feature_columns += [VarLenSparseFeat("sess_1_item", maxlen= 4,vocabulary_size=3 + 1,embedding_dim=4, use_hash=hash_flag, embedding_name="item"),VarLenSparseFeat("sess_1_item_gender", maxlen= 4,vocabulary_size=2 + 1, embedding_dim=4,use_hash=hash_flag,embedding_name="item_gender")]

    behavior_feature_list = ["item", "item_gender"]
    uid = np.array([0, 1, 2])

After Change

                       SparseFeat("item_gender", 2 + 1, embedding_dim=4,use_hash=hash_flag),
                       DenseFeat("score", 1)]
    feature_columns += [VarLenSparseFeat( SparseFeat("sess_0_item", 3 + 1, embedding_dim=4,use_hash=hash_flag,embedding_name="item"),maxlen=4),VarLenSparseFeat(SparseFeat("sess_0_item_gender", 2 + 1, embedding_dim=4,use_hash=hash_flag,embedding_name="item_gender"),maxlen=4)]
    feature_columns += [VarLenSparseFeat( SparseFeat("sess_1_item", 3 + 1, embedding_dim=4,use_hash=hash_flag,embedding_name="item"),maxlen=4),VarLenSparseFeat(SparseFeat("sess_1_item_gender", 2 + 1, embedding_dim=4,use_hash=hash_flag,embedding_name="item_gender"),maxlen=4)]

    behavior_feature_list = ["item", "item_gender"]
    uid = np.array([0, 1, 2])

Instances