Created
May 11, 2015 21:49
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| Nd4j.ENFORCE_NUMERICAL_STABILITY = true; | |
| LayerFactory layerFactory = LayerFactories.getFactory(ConvolutionDownSampleLayer.class); | |
| int batchSize = 1000; | |
| /** | |
| * | |
| */ | |
| Nd4j.MAX_ELEMENTS_PER_SLICE = Integer.MAX_VALUE; | |
| Nd4j.MAX_ELEMENTS_PER_SLICE = Integer.MAX_VALUE; | |
| MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder() | |
| .optimizationAlgo(OptimizationAlgorithm.LBFGS).momentum(0.9) | |
| .dist(Nd4j.getDistributions().createUniform(1e-5, 1e-1)).constrainGradientToUnitNorm(true) | |
| .iterations(10).iterationListener(new ScoreIterationListener(1)).convolutionType(ConvolutionDownSampleLayer.ConvolutionType.MAX) | |
| .activationFunction("relu").filterSize(5, 1, 2, 2) | |
| .nIn(numRows * numColumns).nOut(2).batchSize(batchSize) | |
| .layerFactory(layerFactory) | |
| .list(2) | |
| .inputPreProcessor(0, new ConvolutionInputPreProcessor(28, 28)) | |
| .preProcessor(0, new ConvolutionPostProcessor()) | |
| .hiddenLayerSizes(new int[]{841}) | |
| .override(0, new ConfOverride() { | |
| @Override | |
| public void overrideLayer(int i, NeuralNetConfiguration.Builder builder) { | |
| if (i == 0) | |
| builder.filterSize(5, 1, 2, 2); | |
| } | |
| }) | |
| .override(1, new ConfOverride() { | |
| @Override | |
| public void overrideLayer(int i, NeuralNetConfiguration.Builder builder) { | |
| if (i == 1) { | |
| builder.activationFunction("softmax"); | |
| builder.weightInit(WeightInit.ZERO); | |
| builder.layerFactory(LayerFactories.getFactory(OutputLayer.class)); | |
| builder.lossFunction(LossFunctions.LossFunction.MCXENT); | |
| } | |
| } | |
| }).build(); | |
| MultiLayerNetwork network = new MultiLayerNetwork(conf); | |
| while(iter.hasNext()) { | |
| DataSet next = iter.next(); | |
| next.normalizeZeroMeanZeroUnitVariance(); | |
| network.fit(next); | |
| } |
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