Update examples for building

Author: agibsonccc

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

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

dl4j-distributed-training-examples/pom.xml

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

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

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

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

@@ -38,6 +38,8 @@
         <logback.version>1.1.7</logback.version>
         <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
         <junit.version>5.8.0-M1</junit.version>
+        <maven-surefire-plugin.version>3.0.0-M5</maven-surefire-plugin.version>
+        <maven-surefire.version>${maven-surefire-plugin.version}</maven-surefire.version>
 
     </properties>
 
@@ -78,6 +80,36 @@
     <!-- Maven Enforcer: Ensures user has an up to date version of Maven before building -->
     <build>
         <plugins>
+            <plugin>
+                <artifactId>maven-surefire-plugin</artifactId>
+                <version>${maven-surefire-plugin.version}</version>
+                <inherited>true</inherited>
+                <dependencies>
+                    <dependency>
+                        <groupId>org.apache.maven.surefire</groupId>
+                        <artifactId>surefire-junit-platform</artifactId>
+                        <version>${maven-surefire-plugin.version}</version>
+                    </dependency>
+                </dependencies>
+                <configuration>
+                    <trimStackTrace>false</trimStackTrace>
+                    <forkNode implementation="org.apache.maven.plugin.surefire.extensions.SurefireForkNodeFactory"/>
+                    <reuseForks>false</reuseForks>
+                    <environmentVariables>
+                        <OMP_NUM_THREADS>1</OMP_NUM_THREADS>
+                    </environmentVariables>
+                    <classpathDependencyExcludes>
+                        <classpathDependencyExclude>org.junit:junit</classpathDependencyExclude>
+                        <classpathDependencyExclude>com.google.android:android
+                        </classpathDependencyExclude>
+                    </classpathDependencyExcludes>
+                    <useSystemClassLoader>true</useSystemClassLoader>
+                    <useManifestOnlyJar>false</useManifestOnlyJar>
+                    <forkCount>0</forkCount>
+                    <threadCount>1</threadCount>
+                    <perCoreThreadCount>false</perCoreThreadCount>
+                </configuration>
+            </plugin>
             <plugin>
                 <artifactId>maven-enforcer-plugin</artifactId>
                 <version>1.0.1</version>

nd4j-ndarray-examples/pom.xml

@@ -18,8 +18,6 @@
 package org.nd4j.examples.quickstart;
 
 import org.nd4j.linalg.api.ndarray.INDArray;
-import org.nd4j.linalg.api.ops.impl.indexaccum.IAMax;
-import org.nd4j.linalg.api.ops.impl.indexaccum.IMin;
 import org.nd4j.linalg.factory.Nd4j;
 
 import java.util.Arrays;
@@ -71,20 +69,13 @@ public static void main(String[] args){
         INDArray avgAlong0 = originalArray.mean(0);
         INDArray stdevAlong0 = originalArray.std(0);
 
-        // Index Accumulation operations
-        // IAMax returns index of max value along specified dimension
-        INDArray idxOfMaxInEachColumn = Nd4j.getExecutioner().exec(new IAMax(originalArray, 0));
-        INDArray idxOfMaxInEachRow = Nd4j.getExecutioner().exec(new IAMax(originalArray, 1));
-
 
         System.out.println("\n\n\n");
         System.out.println("min along dimension 0:  " + minAlong0);
         System.out.println("max along dimension 0:  " + maxAlong0);
         System.out.println("sum along dimension 0:  " + sumAlong0);
         System.out.println("avg along dimension 0:  " + avgAlong0);
         System.out.println("stddev along dimension 0:  " + stdevAlong0);
-        System.out.println("Index of max dimension 0:  " + idxOfMaxInEachColumn);
-        System.out.println("Index of max dimension 1:  " + idxOfMaxInEachRow);
 
 
         //If we had instead performed these along dimension 1, we would instead get a [3,1] array out
@@ -99,11 +90,6 @@ public static void main(String[] args){
         //Index accumulations return an integer value.
         INDArray argMaxAlongDim0 = Nd4j.argMax(originalArray,0);                            //Index of the max value, along dimension 0
         System.out.println("\n\nargmax along dimension 0:   " + argMaxAlongDim0);
-        INDArray argMinAlongDim0 = Nd4j.getExecutioner().exec(new IMin(originalArray, 0));   //Index of the min value, along dimension 0
-        System.out.println("argmin along dimension 0:   " + argMinAlongDim0);
-
-
-
 
     }
 

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

@@ -14,7 +14,7 @@
         <java.version>1.8</java.version>
         <maven-compiler-plugin.version>3.8.1</maven-compiler-plugin.version>
         <maven.minimum.version>3.3.1</maven.minimum.version>
-        <nd4j.backend>nd4j-native-platform</nd4j.backend>
+        <nd4j.backend>nd4j-native</nd4j.backend>
         <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
     </properties>