/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You 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 opennlp.tools.ml;
import static org.junit.Assert.assertFalse;
import static org.junit.Assert.assertTrue;
import opennlp.tools.ml.maxent.GIS;
import opennlp.tools.ml.perceptron.SimplePerceptronSequenceTrainer;
import opennlp.tools.util.TrainingParameters;
import org.junit.Before;
import org.junit.Test;
public class TrainerFactoryTest {
private TrainingParameters mlParams;
@Before
public void setup() {
mlParams = new TrainingParameters();
mlParams.put(TrainingParameters.ALGORITHM_PARAM, GIS.MAXENT_VALUE);
mlParams.put(TrainingParameters.ITERATIONS_PARAM, Integer.toString(10));
mlParams.put(TrainingParameters.CUTOFF_PARAM, Integer.toString(5));
}
@Test
public void testBuiltInValid() {
assertTrue(TrainerFactory.isValid(mlParams.getSettings()));
}
@Test
public void testSequenceTrainerValid() {
mlParams.put(TrainingParameters.ALGORITHM_PARAM, MockSequenceTrainer.class.getCanonicalName());
assertTrue(TrainerFactory.isValid(mlParams.getSettings()));
}
@Test
public void testEventTrainerValid() {
mlParams.put(TrainingParameters.ALGORITHM_PARAM, MockEventTrainer.class.getCanonicalName());
assertTrue(TrainerFactory.isValid(mlParams.getSettings()));
}
@Test
public void testInvalidTrainer() {
mlParams.put(TrainingParameters.ALGORITHM_PARAM, "xyz");
assertFalse(TrainerFactory.isValid(mlParams.getSettings()));
}
@Test
public void testIsSequenceTrainerTrue() {
mlParams.put(AbstractTrainer.ALGORITHM_PARAM,
SimplePerceptronSequenceTrainer.PERCEPTRON_SEQUENCE_VALUE);
assertTrue(TrainerFactory.isSequenceTraining(mlParams.getSettings()));
}
@Test
public void testIsSequenceTrainerFalse() {
mlParams.put(AbstractTrainer.ALGORITHM_PARAM,
GIS.MAXENT_VALUE);
assertFalse(TrainerFactory.isSequenceTraining(mlParams.getSettings()));
}
}