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Update examples for building
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‎data-pipeline-examples/src/main/java/org/deeplearning4j/datapipelineexamples/formats/hdfs/conversion/CSVtoMapFileConversion.java

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‎dl4j-distributed-training-examples/pom.xml

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@@ -88,7 +88,7 @@
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<dependency>
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<groupId>org.datavec</groupId>
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<artifactId>datavec-spark_${scala.binary.version}</artifactId>
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<version>1.0.0-beta7_spark_2</version>
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<version>${dl4j-master.version}</version>
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</dependency>
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<dependency>
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<groupId>org.deeplearning4j</groupId>

‎dl4j-examples/src/main/java/org/deeplearning4j/examples/quickstart/modeling/recurrent/MemorizeSequence.java

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@@ -20,14 +20,15 @@
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import org.deeplearning4j.nn.conf.MultiLayerConfiguration;
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import org.deeplearning4j.nn.conf.NeuralNetConfiguration;
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import org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder;
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import org.deeplearning4j.nn.conf.Updater;
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import org.deeplearning4j.nn.conf.layers.LSTM;
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import org.deeplearning4j.nn.conf.layers.RnnOutputLayer;
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import org.deeplearning4j.nn.multilayer.MultiLayerNetwork;
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import org.deeplearning4j.nn.weights.WeightInit;
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import org.deeplearning4j.optimize.listeners.ScoreIterationListener;
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import org.nd4j.linalg.activations.Activation;
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import org.nd4j.linalg.api.ndarray.INDArray;
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import org.nd4j.linalg.api.ops.impl.indexaccum.IMax;
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import org.nd4j.linalg.api.ops.impl.indexaccum.custom.ArgMax;
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import org.nd4j.linalg.dataset.DataSet;
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import org.nd4j.linalg.factory.Nd4j;
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import org.nd4j.linalg.learning.config.RmsProp;
@@ -147,7 +148,7 @@ public static void main(String[] args) {
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// first process the last output of the network to a concrete
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// neuron, the neuron with the highest output has the highest
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// chance to get chosen
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int sampledCharacterIdx = Nd4j.getExecutioner().exec(new IMax(output, 1)).getInt(0);
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int sampledCharacterIdx = Nd4j.getExecutioner().exec(new ArgMax(output, 1))[0].getInt(0);
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// print the chosen output
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System.out.print(LEARNSTRING_CHARS_LIST.get(sampledCharacterIdx));

‎dl4j-examples/src/main/java/org/deeplearning4j/examples/utils/PlotUtil.java

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@@ -36,7 +36,7 @@
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import org.jfree.ui.RectangleEdge;
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import org.jfree.ui.RectangleInsets;
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import org.nd4j.linalg.api.ndarray.INDArray;
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import org.nd4j.linalg.api.ops.impl.indexaccum.IMax;
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import org.nd4j.linalg.api.ops.impl.indexaccum.custom.ArgMax;
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import org.nd4j.linalg.dataset.DataSet;
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import org.nd4j.linalg.dataset.api.iterator.DataSetIterator;
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import org.nd4j.linalg.factory.Nd4j;
@@ -142,7 +142,7 @@ private static XYDataset createDataSetTrain(INDArray features, INDArray labels)
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XYSeries[] series = new XYSeries[nClasses];
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for (int i = 0; i < series.length; i++) series[i] = new XYSeries("Class " + i);
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INDArray argMax = Nd4j.getExecutioner().exec(new IMax(labels, 1));
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INDArray argMax = Nd4j.getExecutioner().exec(new ArgMax(labels, 1))[0];
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for (int i = 0; i < nRows; i++) {
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int classIdx = (int) argMax.getDouble(i);
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series[classIdx].add(features.getDouble(i, 0), features.getDouble(i, 1));

‎nd4j-ndarray-examples/pom.xml

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@@ -38,6 +38,8 @@
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<logback.version>1.1.7</logback.version>
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<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
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<junit.version>5.8.0-M1</junit.version>
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<maven-surefire-plugin.version>3.0.0-M5</maven-surefire-plugin.version>
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<maven-surefire.version>${maven-surefire-plugin.version}</maven-surefire.version>
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</properties>
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<!-- Maven Enforcer: Ensures user has an up to date version of Maven before building -->
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<build>
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<plugins>
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<plugin>
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<artifactId>maven-surefire-plugin</artifactId>
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<version>${maven-surefire-plugin.version}</version>
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<inherited>true</inherited>
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<dependencies>
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<dependency>
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<groupId>org.apache.maven.surefire</groupId>
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<artifactId>surefire-junit-platform</artifactId>
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<version>${maven-surefire-plugin.version}</version>
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</dependency>
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</dependencies>
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<configuration>
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<trimStackTrace>false</trimStackTrace>
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<forkNode implementation="org.apache.maven.plugin.surefire.extensions.SurefireForkNodeFactory"/>
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<reuseForks>false</reuseForks>
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<environmentVariables>
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<OMP_NUM_THREADS>1</OMP_NUM_THREADS>
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</environmentVariables>
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<classpathDependencyExcludes>
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<classpathDependencyExclude>org.junit:junit</classpathDependencyExclude>
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<classpathDependencyExclude>com.google.android:android
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</classpathDependencyExclude>
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</classpathDependencyExcludes>
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<useSystemClassLoader>true</useSystemClassLoader>
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<useManifestOnlyJar>false</useManifestOnlyJar>
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<forkCount>0</forkCount>
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<threadCount>1</threadCount>
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<perCoreThreadCount>false</perCoreThreadCount>
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</configuration>
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</plugin>
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<plugin>
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<artifactId>maven-enforcer-plugin</artifactId>
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<version>1.0.1</version>

‎nd4j-ndarray-examples/src/main/java/org/nd4j/examples/quickstart/Nd4jEx5_Accumulations.java

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package org.nd4j.examples.quickstart;
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import org.nd4j.linalg.api.ndarray.INDArray;
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import org.nd4j.linalg.api.ops.impl.indexaccum.IAMax;
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import org.nd4j.linalg.api.ops.impl.indexaccum.IMin;
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import org.nd4j.linalg.factory.Nd4j;
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import java.util.Arrays;
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INDArray avgAlong0 = originalArray.mean(0);
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INDArray stdevAlong0 = originalArray.std(0);
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// Index Accumulation operations
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// IAMax returns index of max value along specified dimension
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INDArray idxOfMaxInEachColumn = Nd4j.getExecutioner().exec(new IAMax(originalArray, 0));
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INDArray idxOfMaxInEachRow = Nd4j.getExecutioner().exec(new IAMax(originalArray, 1));
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System.out.println("\n\n\n");
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System.out.println("min along dimension 0: " + minAlong0);
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System.out.println("max along dimension 0: " + maxAlong0);
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System.out.println("sum along dimension 0: " + sumAlong0);
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System.out.println("avg along dimension 0: " + avgAlong0);
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System.out.println("stddev along dimension 0: " + stdevAlong0);
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System.out.println("Index of max dimension 0: " + idxOfMaxInEachColumn);
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System.out.println("Index of max dimension 1: " + idxOfMaxInEachRow);
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//If we had instead performed these along dimension 1, we would instead get a [3,1] array out
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//Index accumulations return an integer value.
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INDArray argMaxAlongDim0 = Nd4j.argMax(originalArray,0); //Index of the max value, along dimension 0
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System.out.println("\n\nargmax along dimension 0: " + argMaxAlongDim0);
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INDArray argMinAlongDim0 = Nd4j.getExecutioner().exec(new IMin(originalArray, 0)); //Index of the min value, along dimension 0
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System.out.println("argmin along dimension 0: " + argMinAlongDim0);
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}
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‎rl4j-examples/pom.xml

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<java.version>1.8</java.version>
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<maven-compiler-plugin.version>3.8.1</maven-compiler-plugin.version>
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<maven.minimum.version>3.3.1</maven.minimum.version>
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<nd4j.backend>nd4j-native-platform</nd4j.backend>
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<nd4j.backend>nd4j-native</nd4j.backend>
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<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
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</properties>
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