be65ce986a45bf2f35b5494db3fa6e993b905aeb,deepctr/models/autoint.py,,AutoInt,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,21

Before Change

        raise ValueError("Either hidden_layer or att_layer_num must > 0")
    check_feature_config_dict(feature_dim_dict)

    deep_emb_list, _, _, inputs_list = preprocess_input_embedding(feature_dim_dict,
                                                                  embedding_size,
                                                                  l2_reg_embedding,
                                                                  0, init_std,

After Change

        raise ValueError("Either hidden_layer or att_layer_num must > 0")
    //check_feature_config_dict(dnn_feature_columns)

    features = build_input_features(dnn_feature_columns)
    inputs_list = list(features.values())

    sparse_embedding_list, dense_value_list = input_from_feature_columns(features,dnn_feature_columns,embedding_size,
                                                                                               l2_reg_embedding,
                                                                                                init_std,
                                                                                               seed)


    att_input = concat_fun(sparse_embedding_list, axis=1)

Instances