AbstractTrainerTest.java

/*
 * Copyright [2012-2014] PayPal Software Foundation
 *
 * 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 ml.shifu.shifu.core;

import ml.shifu.shifu.container.obj.ModelConfig;
import ml.shifu.shifu.container.obj.RawSourceData.SourceType;
import ml.shifu.shifu.core.alg.NNTrainer;
import ml.shifu.shifu.util.CommonUtils;
import org.apache.commons.io.FileUtils;
import org.encog.ml.data.MLDataPair;
import org.encog.ml.data.MLDataSet;
import org.encog.ml.data.basic.BasicMLData;
import org.encog.ml.data.basic.BasicMLDataPair;
import org.encog.ml.data.basic.BasicMLDataSet;
import org.testng.Assert;
import org.testng.annotations.AfterClass;
import org.testng.annotations.BeforeClass;
import org.testng.annotations.Test;

import java.io.File;
import java.io.FilenameFilter;
import java.io.IOException;
import java.util.Date;
import java.util.Random;


public class AbstractTrainerTest {

    private Random random;

    @BeforeClass
    public void setUp() throws IOException {
        random = new Random(new Date().getTime());
    }

    @Test
    public void testLoad1() throws IOException {
        MLDataSet set = new BasicMLDataSet();
        ModelConfig modelConfig = CommonUtils.loadModelConfig(
                "src/test/resources/example/cancer-judgement/ModelStore/ModelSet1/ModelConfig.json",
                SourceType.LOCAL);

        double[] input = new double[modelConfig.getVarSelectFilterNum()];

        for (int j = 0; j < 1000; j++) {
            for (int i = 0; i < modelConfig.getVarSelectFilterNum(); i++) {
                input[i] = random.nextDouble();
            }

            double[] ideal = new double[1];
            ideal[0] = random.nextInt(2);
            MLDataPair pair = new BasicMLDataPair(new BasicMLData(input),
                    new BasicMLData(ideal));

            set.add(pair);
        }

        modelConfig.getTrain().setTrainOnDisk(false);
        AbstractTrainer trainer = new NNTrainer(modelConfig, 0, false);
        trainer.setDataSet(set);

        Assert.assertTrue(trainer.getTrainSet().getRecordCount() <= (1 - modelConfig
                .getValidSetRate())
                * modelConfig.getBaggingSampleRate()
                * set.getRecordCount() * 1.05);
        Assert.assertTrue(trainer.getTrainSet().getRecordCount() >= (1 - modelConfig
                .getValidSetRate())
                * modelConfig.getBaggingSampleRate()
                * set.getRecordCount() * 0.95);

        modelConfig.getTrain().setFixInitInput(true);
        trainer = new NNTrainer(modelConfig, 0, false);
        trainer.setDataSet(set);

        Assert.assertTrue(trainer.getTrainSet().getRecordCount() <= (1 - modelConfig
                .getValidSetRate())
                * modelConfig.getBaggingSampleRate()
                * set.getRecordCount() * 1.05);
        Assert.assertTrue(trainer.getTrainSet().getRecordCount() >= (1 - modelConfig
                .getValidSetRate())
                * modelConfig.getBaggingSampleRate()
                * set.getRecordCount() * 0.95);

        modelConfig.getTrain().setFixInitInput(false);
        modelConfig.getTrain().setBaggingWithReplacement(false);
        trainer = new NNTrainer(modelConfig, 0, false);
        trainer.setDataSet(set);

        Assert.assertTrue(trainer.getTrainSet().getRecordCount() <= (1 - modelConfig
                .getValidSetRate())
                * modelConfig.getBaggingSampleRate()
                * set.getRecordCount() * 1.05);
        Assert.assertTrue(trainer.getTrainSet().getRecordCount() >= (1 - modelConfig
                .getValidSetRate())
                * modelConfig.getBaggingSampleRate()
                * set.getRecordCount() * 0.95);

    }

    @AfterClass
    public void delete() throws IOException {
        File json = new File(".");
        File[] files = json.listFiles(filter);
        if (files != null) {
            for (File tmp : files) {
                FileUtils.deleteQuietly(tmp);
            }
        } else {
          throw new IOException(String.format("Failed to list files in %s", json.getAbsolutePath()));
        }
        FileUtils.deleteDirectory(new File("tmp"));
    }

    private FilenameFilter filter = new FilenameFilter() {
        @Override
        public boolean accept(File dir, String name) {

            return name.toLowerCase().startsWith("init") && name.toLowerCase().endsWith("json");
        }
    };
}