Examples with VariationalAutoencoder org.deeplearning4j.nn.layers.variational.VariationalAutoencoder used on opensource projects

Example 6 with VariationalAutoencoder

use of org.deeplearning4j.nn.layers.variational.VariationalAutoencoder in project deeplearning4j by deeplearning4j.

the class TestMiscFunctions method testVaeReconstructionErrorWithKey.

@Test
public void testVaeReconstructionErrorWithKey() {
    //Simple test. We CAN do a direct comparison here vs. local, as reconstruction error is deterministic
    int nIn = 10;
    MultiLayerConfiguration mlc = new NeuralNetConfiguration.Builder().list().layer(0, new org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder.Builder().reconstructionDistribution(new LossFunctionWrapper(Activation.IDENTITY, new LossMSE())).nIn(nIn).nOut(5).encoderLayerSizes(12).decoderLayerSizes(13).build()).build();
    MultiLayerNetwork net = new MultiLayerNetwork(mlc);
    net.init();
    VariationalAutoencoder vae = (VariationalAutoencoder) net.getLayer(0);
    List<Tuple2<Integer, INDArray>> toScore = new ArrayList<>();
    for (int i = 0; i < 100; i++) {
        INDArray arr = Nd4j.rand(1, nIn);
        toScore.add(new Tuple2<Integer, INDArray>(i, arr));
    }
    JavaPairRDD<Integer, INDArray> rdd = sc.parallelizePairs(toScore);
    JavaPairRDD<Integer, Double> reconstrErrors = rdd.mapPartitionsToPair(new VaeReconstructionErrorWithKeyFunction<Integer>(sc.broadcast(net.params()), sc.broadcast(mlc.toJson()), 16));
    Map<Integer, Double> l = reconstrErrors.collectAsMap();
    assertEquals(100, l.size());
    for (int i = 0; i < 100; i++) {
        assertTrue(l.containsKey(i));
        INDArray localToScore = toScore.get(i)._2();
        double localScore = vae.reconstructionError(localToScore).data().asDouble()[0];
        assertEquals(localScore, l.get(i), 1e-6);
    }
}