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Java example source code file (TestSetGetParameters.java)

This example Java source code file (TestSetGetParameters.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

computationgraph, computationgraphconfiguration, different, indarray, map, same, string, test, testsetgetparameters, util

The TestSetGetParameters.java Java example source code

package org.deeplearning4j.nn.graph;

import org.deeplearning4j.nn.conf.ComputationGraphConfiguration;
import org.deeplearning4j.nn.conf.NeuralNetConfiguration;
import org.deeplearning4j.nn.conf.layers.*;
import org.junit.Test;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.factory.Nd4j;
import org.nd4j.linalg.lossfunctions.LossFunctions.LossFunction;

import java.util.Map;

import static org.junit.Assert.*;

public class TestSetGetParameters {

    @Test
    public void testInitWithParamsCG() {

        Nd4j.getRandom().setSeed(12345);

        //Create configuration. Doesn't matter if this doesn't actually work for forward/backward pass here
        ComputationGraphConfiguration conf = new NeuralNetConfiguration.Builder()
                .seed(12345)
                .graphBuilder()
                .addInputs("in")
                .addLayer("0", new DenseLayer.Builder().nIn(10).nOut(10).build(),"in")
                .addLayer("1", new GravesLSTM.Builder().nIn(10).nOut(10).build(),"in")
                .addLayer("2", new GravesBidirectionalLSTM.Builder().nIn(10).nOut(10).build(),"in")
                .addLayer("3", new ConvolutionLayer.Builder().nIn(10).nOut(10).kernelSize(2, 2).stride(2, 2).padding(2, 2).build(), "in")
                .addLayer("4", new OutputLayer.Builder(LossFunction.MCXENT).nIn(10).nOut(10).build(),"3")
                .addLayer("5", new OutputLayer.Builder(LossFunction.MCXENT).nIn(10).nOut(10).build(),"0")
                .addLayer("6", new RnnOutputLayer.Builder(LossFunction.MCXENT).nIn(10).nOut(10).build(), "1","2")
                .setOutputs("4","5","6")
                .pretrain(false).backprop(true).build();

        ComputationGraph net = new ComputationGraph(conf);
        net.init();
        INDArray params = net.params();


        ComputationGraph net2 = new ComputationGraph(conf);
        net2.init(params, true);

        ComputationGraph net3 = new ComputationGraph(conf);
        net3.init(params, false);

        assertEquals(params, net2.params());
        assertEquals(params, net3.params());

        assertFalse(params == net2.params());    //Different objects due to clone
        assertTrue(params == net3.params());    //Same object due to clone


        Map<String, INDArray> paramsMap = net.paramTable();
        Map<String, INDArray> paramsMap2 = net2.paramTable();
        Map<String, INDArray> paramsMap3 = net3.paramTable();
        for (String s : paramsMap.keySet()) {
            assertEquals(paramsMap.get(s), paramsMap2.get(s));
            assertEquals(paramsMap.get(s), paramsMap3.get(s));
        }
    }
}

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