Examples with Layer hex.Layer used on opensource projects

Example 6 with Layer

use of hex.Layer in project h2o-2 by h2oai.

the class NeuralNetMnistDrednet method build.

@Override
protected Layer[] build(Vec[] data, Vec labels, VecsInput inputStats, VecSoftmax outputStats) {
    NeuralNet p = new NeuralNet();
    Layer[] ls = new Layer[5];
    p.hidden = new int[] { 1024, 1024, 2048 };
    //    p.hidden = new int[]{128,128,256};
    ls[0] = new VecsInput(data, inputStats);
    for (int i = 1; i < ls.length - 1; i++) ls[i] = new Layer.RectifierDropout(p.hidden[i - 1]);
    ls[4] = new VecSoftmax(labels, outputStats);
    p.rate = 0.01f;
    p.rate_annealing = 1e-6f;
    p.epochs = 1000;
    p.activation = NeuralNet.Activation.RectifierWithDropout;
    p.input_dropout_ratio = 0.2;
    p.loss = NeuralNet.Loss.CrossEntropy;
    p.max_w2 = 15;
    p.momentum_start = 0.5f;
    p.momentum_ramp = 1800000;
    p.momentum_stable = 0.99f;
    p.score_training = 1000;
    p.score_validation = 10000;
    p.l1 = .00001f;
    p.l2 = .00f;
    p.initial_weight_distribution = NeuralNet.InitialWeightDistribution.UniformAdaptive;
    p.score_interval = 30;
    for (int i = 0; i < ls.length; i++) {
        ls[i].init(ls, i, p);
    }
    return ls;
}

Example 7 with Layer

use of hex.Layer in project h2o-2 by h2oai.

the class NeuralNet method correct.

// classification scoring
static boolean correct(Layer[] ls, Errors e, long[][] confusion) {
    Softmax output = (Softmax) ls[ls.length - 1];
    if (output.target() == -1)
        return false;
    for (Layer l : ls) l.fprop(-1, false);
    float[] out = ls[ls.length - 1]._a;
    int target = output.target();
    for (int o = 0; o < out.length; o++) {
        final boolean hitpos = (o == target);
        final double t = hitpos ? 1 : 0;
        final double d = t - out[o];
        e.mean_square += d * d;
        e.cross_entropy += hitpos ? -Math.log(out[o]) : 0;
    }
    float[] preds = new float[out.length + 1];
    for (int i = 0; i < out.length; ++i) preds[i + 1] = out[i];
    double[] data = new double[ls[0]._a.length];
    preds[0] = ModelUtils.getPrediction(preds, data);
    if (confusion != null) {
        if (output.target() != Layer.missing_int_value)
            confusion[output.target()][(int) preds[0]]++;
    }
    return preds[0] == output.target();
}

Example 8 with Layer

use of hex.Layer in project h2o-2 by h2oai.

the class NeuralNet method error.

// regression scoring
static void error(Layer[] ls, Errors e) {
    Linear linear = (Linear) ls[ls.length - 1];
    for (Layer l : ls) l.fprop(-1, false);
    float[] output = ls[ls.length - 1]._a;
    float[] target = linear.target();
    e.mean_square = 0;
    for (int o = 0; o < output.length; o++) {
        final double d = target[o] - output[o];
        e.mean_square += d * d;
    }
}