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@tastyminerals
Created January 30, 2018 13:51
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demo
class NetworkInit(vocabSize: Int) {
private val embeddingWidth = 100
private val hiddenSize = 200
private val numberOfFeats = 9
private val numberOfClasses = 1
val config: ComputationGraphConfiguration = new NeuralNetConfiguration.Builder()
.learningRate(DatasetTools.getTomlConfTable("romain").getDouble("minlr"))
.graphBuilder()
.addInputs("wordIndeces")
.addInputs("features")
.addLayer("wordVectorizer",
new EmbeddingLayer.Builder()
.nIn(vocabSize)
.nOut(embeddingWidth)
.build(),
"wordIndeces")
.addLayer("linear1",
new DenseLayer.Builder()
.nIn(numberOfFeats)
.nOut(embeddingWidth)
.build(),
"features")
.addVertex("sum", new ElementWiseVertex(ElementWiseVertex.Op.Add), "wordVectorizer", "linear1")
.addLayer("hidden",
new GravesLSTM.Builder()
.activation(Activation.TANH)
.nIn(hiddenSize)
.nOut(hiddenSize)
.build(),
"sum")
.addLayer("linear2",
new DenseLayer.Builder()
.activation(Activation.SIGMOID)
.nIn(hiddenSize)
.nOut(numberOfClasses)
.build(),
"hidden")
.setOutputs("linear2")
.build()
}
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