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package org.deeplearning4j.nn.modelimport.keras.layers.noise;

import org.deeplearning4j.nn.conf.dropout.GaussianNoise;
import org.deeplearning4j.nn.conf.layers.DropoutLayer;
import org.deeplearning4j.BaseDL4JTest;
import org.deeplearning4j.nn.modelimport.keras.config.Keras1LayerConfiguration;
import org.deeplearning4j.nn.modelimport.keras.config.Keras2LayerConfiguration;
import org.deeplearning4j.nn.modelimport.keras.config.KerasLayerConfiguration;
import org.junit.jupiter.api.Test;

import java.util.HashMap;
import java.util.Map;

import static org.junit.jupiter.api.Assertions.assertEquals;

/**
 * @author Max Pumperla
 */
public class KerasGaussianNoiseTest extends BaseDL4JTest {

    String LAYER_NAME = "gaussian_noise";
    private final double STDDEV = 0.3;

    private Integer keras1 = 1;
    private Integer keras2 = 2;
    private Keras1LayerConfiguration conf1 = new Keras1LayerConfiguration();
    private Keras2LayerConfiguration conf2 = new Keras2LayerConfiguration();


    @Test
    public void testGaussianNoiseLayer() throws Exception {
        buildGaussianNoiseLayer(conf1, keras1);
        buildGaussianNoiseLayer(conf2, keras2);
    }


    private void buildGaussianNoiseLayer(KerasLayerConfiguration conf, Integer kerasVersion) throws Exception {
        Map<String, Object> layerConfig = new HashMap<>();
        layerConfig.put(conf.getLAYER_FIELD_CLASS_NAME(), conf.getLAYER_CLASS_NAME_DROPOUT());
        Map<String, Object> config = new HashMap<>();
        config.put(conf.getLAYER_FIELD_NAME(), LAYER_NAME);
        config.put(conf.getLAYER_FIELD_GAUSSIAN_VARIANCE(), STDDEV);
        layerConfig.put(conf.getLAYER_FIELD_CONFIG(), config);
        layerConfig.put(conf.getLAYER_FIELD_KERAS_VERSION(), kerasVersion);

        DropoutLayer layer = new KerasGaussianNoise(layerConfig).getGaussianNoiseLayer();
        assertEquals(LAYER_NAME, layer.getLayerName());
        assertEquals(new GaussianNoise(STDDEV), layer.getIDropout());
    }

}
