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Java example source code file (MultiLayerWorkPerformerTests.java)
The MultiLayerWorkPerformerTests.java Java example source code/* * * * Copyright 2015 Skymind,Inc. * * * * Licensed under the Apache License, Version 2.0 (the "License"); * * you may not use this file except in compliance with the License. * * You may obtain a copy of the License at * * * * http://www.apache.org/licenses/LICENSE-2.0 * * * * Unless required by applicable law or agreed to in writing, software * * distributed under the License is distributed on an "AS IS" BASIS, * * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * * See the License for the specific language governing permissions and * * limitations under the License. * */ package org.deeplearning4j.scaleout.perform; import org.canova.api.conf.Configuration; import org.deeplearning4j.datasets.fetchers.IrisDataFetcher; import org.deeplearning4j.nn.conf.DeepLearningConfigurable; import org.deeplearning4j.nn.conf.MultiLayerConfiguration; import org.deeplearning4j.nn.conf.NeuralNetConfiguration; import org.deeplearning4j.nn.conf.distribution.NormalDistribution; import org.deeplearning4j.nn.weights.WeightInit; import org.deeplearning4j.scaleout.job.Job; import org.junit.Test; import org.nd4j.linalg.dataset.DataSet; import org.nd4j.linalg.lossfunctions.LossFunctions; /** * Created by agibsonccc on 11/27/14. */ public class MultiLayerWorkPerformerTests extends NeuralNetWorkPerformerTest { @Test public void testDbn() { MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder() .momentum(9e-1f) .iterations(10) .learningRate(1e-1f) .list() .layer(0, new org.deeplearning4j.nn.conf.layers.RBM.Builder() .nIn(4).nOut(3) .weightInit(WeightInit.DISTRIBUTION).dist(new NormalDistribution(1e-1, 1)) .lossFunction(LossFunctions.LossFunction.RECONSTRUCTION_CROSSENTROPY).build()) .layer(1, new org.deeplearning4j.nn.conf.layers.OutputLayer.Builder(LossFunctions.LossFunction.MCXENT) .nIn(3).nOut(3) .activation("softmax") .weightInit(WeightInit.ZERO).build()) .build(); String json = conf.toJson(); Configuration conf2 = new Configuration(); conf2.set(DeepLearningConfigurable.MULTI_LAYER_CONF,json); WorkerPerformer performer = new BaseMultiLayerNetworkWorkPerformer(); performer.setup(conf2); IrisDataFetcher fetcher = new IrisDataFetcher(); fetcher.fetch(10); DataSet d = fetcher.next(); Job j = new Job(d,"1"); assumeJobResultNotNull(performer,j); performer.update(j.getResult()); } } Other Java examples (source code examples)Here is a short list of links related to this Java MultiLayerWorkPerformerTests.java source code file: |
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