/** * * Copyright (c) 2017 ytk-learn https://github.com/yuantiku * * Permission is hereby granted, free of charge, to any person obtaining a copy * of this software and associated documentation files (the "Software"), to deal * in the Software without restriction, including without limitation the rights * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell * copies of the Software, and to permit persons to whom the Software is * furnished to do so, subject to the following conditions: * The above copyright notice and this permission notice shall be included in all * copies or substantial portions of the Software. * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ package com.fenbi.ytklearn.param; import com.fenbi.ytklearn.eval.EvaluatorFactory; import com.fenbi.ytklearn.utils.CheckUtils; import com.typesafe.config.Config; import com.typesafe.config.ConfigFactory; import lombok.Data; import java.io.File; import java.io.Serializable; import java.util.List; /** * @author xialong */ @Data public class LossParams implements Serializable { public static final String KEY = "loss."; public String loss_function; public List<String> evaluate_metric; public boolean just_evaluate; public Regularization regularization; @Data public static class Regularization implements Serializable { public static final String KEY = "regularization."; public double l1[]; public double l2[]; public Regularization(Config config, String prefix) { List<Double> l1List = config.getDoubleList(prefix + KEY + "l1"); l1 = new double[l1List.size()]; for (int i = 0; i < l1List.size(); i++) { l1[i] = l1List.get(i); } List<Double> l2List = config.getDoubleList(prefix + KEY + "l2"); l2 = new double[l2List.size()]; for (int i = 0; i < l2List.size(); i++) { l2[i] = l2List.get(i); } CheckUtils.check(l1.length == l2.length, "%sl1 lenght must be equal to %sl2 lenght", prefix + KEY, prefix + KEY); } } public LossParams(Config config, String prefix) { loss_function = config.getString(prefix + KEY + "loss_function"); regularization = new Regularization(config, prefix + KEY); evaluate_metric = config.getStringList(prefix + KEY + "evaluate_metric"); just_evaluate = config.getBoolean(prefix + KEY + "just_evaluate"); for (String metric : evaluate_metric) { if (!EvaluatorFactory.EvalNameSet.contains(metric)) { boolean hit = false; for (String eval : EvaluatorFactory.EvalNameSet) { if (metric.startsWith(eval)) { hit = true; } } CheckUtils.check(hit, "%sevaluate_metric:%s, only support:%s", prefix + KEY, metric, EvaluatorFactory.EvalNameSet); } } } public static void main(String []args) { Config config = ConfigFactory.parseFile(new File("config/model/linear.conf")); LossParams params = new LossParams(config, ""); System.out.println(params.toString()); } }