/*
 * Copyright 2021 Tianmian Tech. All Rights Reserved.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.welab.wefe.serving.sdk.algorithm.lr.batch;

import com.welab.wefe.common.util.JObject;
import com.welab.wefe.serving.sdk.dto.BatchPredictParams;
import com.welab.wefe.serving.sdk.model.lr.BaseLrModel;
import com.welab.wefe.serving.sdk.model.lr.LrPredictResultModel;

import java.util.List;

/**
 * Bulk vertical federation(provider)
 *
 * @author hunter.zhao
 */
public class LrVertProviderBatchAlgorithm extends AbstractLrBatchAlgorithm<BaseLrModel, List<LrPredictResultModel>> {

    @Override
    protected List<LrPredictResultModel> handle(BatchPredictParams batchPredictParams, List<JObject> federatedResult) {
        List<LrPredictResultModel> resultModels = batchLocalCompute(batchPredictParams);

        maskSensitiveData(resultModels);

        return resultModels;
    }


    private void maskSensitiveData(List<LrPredictResultModel> resultModels) {
        resultModels
                .stream()
                .forEach(x -> x.setScoreCard(null));
    }
}
