Examples with LocalResponseNormalization org.deeplearning4j.nn.conf.layers.LocalResponseNormalization used on opensource projects

Example 1 with LocalResponseNormalization

use of org.deeplearning4j.nn.conf.layers.LocalResponseNormalization in project deeplearning4j by deeplearning4j.

the class LocalResponseTest method testLrnManual.

@Test
public void testLrnManual() {
    int wh = 5;
    int depth = 6;
    int minibatch = 3;
    int n = 4;
    double k = 2.0;
    double alpha = 1e-4;
    double beta = 0.75;
    INDArray in = Nd4j.rand(new int[] { minibatch, depth, wh, wh });
    INDArray outExp = Nd4j.zeros(minibatch, depth, wh, wh);
    for (int m = 0; m < minibatch; m++) {
        for (int x = 0; x < wh; x++) {
            for (int y = 0; y < wh; y++) {
                for (int i = 0; i < depth; i++) {
                    int jFrom = Math.max(0, i - n / 2);
                    int jTo = Math.min(depth - 1, i + n / 2);
                    double sum = 0.0;
                    for (int j = jFrom; j <= jTo; j++) {
                        double d = in.getDouble(m, j, x, y);
                        sum += d * d;
                    }
                    double out = in.getDouble(m, i, x, y) / Math.pow(k + alpha * sum, beta);
                    outExp.putScalar(m, i, x, y, out);
                }
            }
        }
    }
    LocalResponseNormalization lrn = new LocalResponseNormalization.Builder().build();
    NeuralNetConfiguration nnc = new NeuralNetConfiguration.Builder().layer(lrn).build();
    org.deeplearning4j.nn.layers.normalization.LocalResponseNormalization layer = (org.deeplearning4j.nn.layers.normalization.LocalResponseNormalization) lrn.instantiate(nnc, null, 0, null, false);
    INDArray outAct = layer.activate(in, true);
    assertEquals(outExp, outAct);
}

Example 2 with LocalResponseNormalization

use of org.deeplearning4j.nn.conf.layers.LocalResponseNormalization in project deeplearning4j by deeplearning4j.

the class LocalResponseTest method doBefore.

@Before
public void doBefore() {
    NeuralNetConfiguration conf = new NeuralNetConfiguration.Builder().gradientNormalization(GradientNormalization.RenormalizeL2PerLayer).seed(123).layer(new LocalResponseNormalization.Builder().k(2).n(5).alpha(1e-4).beta(0.75).build()).build();
    layer = new LocalResponseNormalization().instantiate(conf, null, 0, null, false);
    activationsActual = layer.activate(x);
}