be65ce986a45bf2f35b5494db3fa6e993b905aeb,deepctr/models/dcn.py,,DCN,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,18

Before Change

    if len(dnn_hidden_units) == 0 and cross_num == 0:
        raise ValueError("Either hidden_layer or cross layer 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,
                                                                  seed,
                                                                  create_linear_weight=False)

    deep_input = tf.keras.layers.Flatten()(concat_fun(deep_emb_list))

    if len(dnn_hidden_units) > 0 and cross_num > 0:  // Deep & Cross

After Change

        raise ValueError("Either hidden_layer or cross layer must > 0")

    //check_feature_config_dict(feature_dim_dict)
    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)
    //todo not support dense?
    dnn_input = tf.keras.layers.Flatten()(concat_fun(sparse_embedding_list))

    if len(dnn_hidden_units) > 0 and cross_num > 0:  // Deep & Cross

Instances