Fixes (#213)

* Increase timeouts for 2 tests occasionally failing on CI

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* Explicitly set character encoding via argline for maven surefire tests

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* CUDA gradient check timeout fix + simple rnn masking fix

Signed-off-by: AlexDBlack <blacka101@gmail.com>

arbiter/pom.xml

@@ -192,7 +192,7 @@
                     <artifactId>maven-surefire-plugin</artifactId>
                     <version>${maven-surefire-plugin.version}</version>
                     <configuration>
-                        <argLine>-Ddtype=double -Xmx3024m -Xms3024m</argLine>
+                        <argLine>-Ddtype=double -Dfile.encoding=UTF-8 -Xmx3024m -Xms3024m</argLine>
                         <!--
                          By default: Surefire will set the classpath based on the manifest. Because tests are not included
                          in the JAR, any tests that rely on class path scanning for resources in the tests directory will not

datavec/pom.xml

@@ -148,7 +148,7 @@
                     <artifactId>maven-surefire-plugin</artifactId>
                     <version>${maven-surefire-plugin.version}</version>
                     <configuration>
-                        <argLine>-Ddtype=float</argLine>
+                        <argLine>-Ddtype=float -Dfile.encoding=UTF-8</argLine>
                         <!--
                         By default: Surefire will set the classpath based on the manifest. Because tests are not included
                         in the JAR, any tests that rely on class path scanning for resources in the tests directory will not

deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/gradientcheck/GradientCheckTestsMasking.java

@@ -56,6 +56,11 @@ public class GradientCheckTestsMasking extends BaseDL4JTest {
         Nd4j.setDataType(DataType.DOUBLE);
     }
 
+    @Override
+    public long getTimeoutMilliseconds() {
+        return 90000L;
+    }
+
     private static class GradientCheckSimpleScenario {
         private final ILossFunction lf;
         private final Activation act;
@@ -159,9 +164,8 @@ public class GradientCheckTestsMasking extends BaseDL4JTest {
                             .updater(new NoOp())
                             .dataType(DataType.DOUBLE)
                             .dist(new NormalDistribution(0, 1.0)).seed(12345L).list()
-                            .layer(0, new GravesBidirectionalLSTM.Builder().nIn(nIn).nOut(layerSize)
+                            .layer(0, new SimpleRnn.Builder().nIn(nIn).nOut(2).activation(Activation.TANH).build())
-                                            .activation(Activation.TANH).build())
+                            .layer(1, new GravesBidirectionalLSTM.Builder().nIn(2).nOut(layerSize)
-                            .layer(1, new GravesBidirectionalLSTM.Builder().nIn(layerSize).nOut(layerSize)
                                             .activation(Activation.TANH).build())
                             .layer(2, new RnnOutputLayer.Builder(LossFunctions.LossFunction.MCXENT)
                                             .activation(Activation.SOFTMAX).nIn(layerSize).nOut(nOut).build())
@@ -390,24 +394,24 @@ public class GradientCheckTestsMasking extends BaseDL4JTest {
         Nd4j.getRandom().setSeed(12345);
         //Idea: RNN input, global pooling, OutputLayer - with "per example" mask arrays
 
-        int mb = 10;
+        int mb = 4;
         int tsLength = 5;
         MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder()
                 .dataType(DataType.DOUBLE)
                 .weightInit(new NormalDistribution(0,2))
                 .updater(new NoOp())
                 .list()
-                .layer(new LSTM.Builder().nIn(10).nOut(10).build())
+                .layer(new LSTM.Builder().nIn(3).nOut(3).build())
                 .layer(new GlobalPoolingLayer.Builder().poolingType(PoolingType.AVG).build())
-                .layer(new OutputLayer.Builder().nIn(10).nOut(10).activation(Activation.SOFTMAX).build())
+                .layer(new OutputLayer.Builder().nIn(3).nOut(3).activation(Activation.SOFTMAX).build())
-                .setInputType(InputType.recurrent(10))
+                .setInputType(InputType.recurrent(3))
                 .build();
 
         MultiLayerNetwork net = new MultiLayerNetwork(conf);
         net.init();
 
-        INDArray f = Nd4j.rand(new int[]{mb, 10, tsLength});
+        INDArray f = Nd4j.rand(new int[]{mb, 3, tsLength});
-        INDArray l = TestUtils.randomOneHot(mb, 10);
+        INDArray l = TestUtils.randomOneHot(mb, 3);
         INDArray lm = TestUtils.randomBernoulli(mb, 1);
 
         assertTrue(lm.sumNumber().intValue() > 0);
@@ -449,18 +453,18 @@ public class GradientCheckTestsMasking extends BaseDL4JTest {
                 .updater(new NoOp())
                 .graphBuilder()
                 .addInputs("in")
-                .layer("0", new LSTM.Builder().nIn(10).nOut(10).build(), "in")
+                .layer("0", new LSTM.Builder().nIn(3).nOut(3).build(), "in")
                 .layer("1", new GlobalPoolingLayer.Builder().poolingType(PoolingType.AVG).build(), "0")
-                .layer("out", new OutputLayer.Builder().nIn(10).nOut(10).activation(Activation.SOFTMAX).build(), "1")
+                .layer("out", new OutputLayer.Builder().nIn(3).nOut(3).activation(Activation.SOFTMAX).build(), "1")
                 .setOutputs("out")
-                .setInputTypes(InputType.recurrent(10))
+                .setInputTypes(InputType.recurrent(3))
                 .build();
 
         ComputationGraph net = new ComputationGraph(conf);
         net.init();
 
-        INDArray f = Nd4j.rand(new int[]{mb, 10, tsLength});
+        INDArray f = Nd4j.rand(new int[]{mb, 3, tsLength});
-        INDArray l = TestUtils.randomOneHot(mb, 10);
+        INDArray l = TestUtils.randomOneHot(mb, 3);
         INDArray lm = TestUtils.randomBernoulli(mb, 1);
 
         assertTrue(lm.sumNumber().intValue() > 0);

deeplearning4j/deeplearning4j-dataimport-solrj/pom.xml

@@ -37,7 +37,7 @@
                     <groupId>org.apache.maven.plugins</groupId>
                     <artifactId>maven-surefire-plugin</artifactId>
                     <configuration>
-                        <argLine>-Ddtype=float -Xmx8g -Dtest.solr.allowed.securerandom=NativePRNG</argLine>
+                        <argLine>-Ddtype=float -Dfile.encoding=UTF-8 -Xmx8g -Dtest.solr.allowed.securerandom=NativePRNG</argLine>
                         <includes>
                             <!-- Default setting only runs tests that start/end with "Test" -->
                             <include>*.java</include>

deeplearning4j/deeplearning4j-modelexport-solr/pom.xml

@@ -33,7 +33,7 @@
                     <groupId>org.apache.maven.plugins</groupId>
                     <artifactId>maven-surefire-plugin</artifactId>
                     <configuration>
-                        <argLine>-Ddtype=float -Xmx8g -Dtest.solr.allowed.securerandom=NativePRNG</argLine>
+                        <argLine>-Ddtype=float -Dfile.encoding=UTF-8 -Xmx8g -Dtest.solr.allowed.securerandom=NativePRNG</argLine>
                         <includes>
                             <!-- Default setting only runs tests that start/end with "Test" -->
                             <include>*.java</include>

deeplearning4j/deeplearning4j-nearestneighbors-parent/deeplearning4j-nearestneighbor-server/pom.xml

@@ -36,7 +36,7 @@
                     <groupId>org.apache.maven.plugins</groupId>
                     <artifactId>maven-surefire-plugin</artifactId>
                     <configuration>
-                        <argLine>-Ddtype=float -Xmx8g</argLine>
+                        <argLine>-Ddtype=float -Dfile.encoding=UTF-8 -Xmx8g</argLine>
                         <includes>
                             <!-- Default setting only runs tests that start/end with "Test" -->
                             <include>*.java</include>

deeplearning4j/deeplearning4j-nearestneighbors-parent/nearestneighbor-core/src/test/java/org/deeplearning4j/clustering/kmeans/KMeansTest.java

@@ -38,6 +38,11 @@ public class KMeansTest extends BaseDL4JTest {
 
     private boolean[] useKMeansPlusPlus = {true, false};
 
+    @Override
+    public long getTimeoutMilliseconds() {
+        return 60000L;
+    }
+
     @Test
     public void testKMeans() {
         Nd4j.getRandom().setSeed(7);

deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/layers/recurrent/SimpleRnn.java

@@ -282,6 +282,12 @@ public class SimpleRnn extends BaseRecurrentLayer<org.deeplearning4j.nn.conf.lay
 
             a.getActivation(currOut, training);
 
+            if( maskArray != null){
+                //If mask array is present: Also need to zero out errors to avoid sending anything but 0s to layer below for masked steps
+                INDArray maskCol = maskArray.getColumn(i, true).castTo(dataType);
+                currOut.muliColumnVector(maskCol);
+            }
+
             prevStepOut = currOut;
         }
 

deeplearning4j/pom.xml

@@ -380,7 +380,7 @@
                          -->
                         <useSystemClassLoader>true</useSystemClassLoader>
                         <useManifestOnlyJar>false</useManifestOnlyJar>
-                        <argLine>-Ddtype=float -Xmx8g</argLine>
+                        <argLine>-Ddtype=float -Dfile.encoding=UTF-8 -Xmx8g</argLine>
                         <includes>
                             <!-- Default setting only runs tests that start/end with "Test" -->
                             <include>*.java</include>

nd4j/nd4j-backends/nd4j-backend-impls/nd4j-cuda/pom.xml

@@ -60,7 +60,7 @@
                         Maximum heap size was set to 6g, as a minimum required value for tests run.
                         Depending on a build machine, default value is not always enough.
                     -->
-                    <argLine>-Ddtype=float -Xmx8g</argLine>
+                    <argLine>-Ddtype=float -Dfile.encoding=UTF-8 -Xmx8g</argLine>
                 </configuration>
             </plugin>
             <plugin>

nd4j/nd4j-backends/nd4j-backend-impls/pom.xml

@@ -117,7 +117,7 @@
                             Maximum heap size was set to 8g, as a minimum required value for tests run.
                             Depending on a build machine, default value is not always enough.
                         -->
-                        <argLine>-Ddtype=float -Xmx8g</argLine>
+                        <argLine>-Ddtype=float -Dfile.encoding=UTF-8 -Xmx8g</argLine>
                     </configuration>
                 </plugin>
                 <plugin>

nd4j/nd4j-backends/nd4j-tests-tensorflow/pom.xml

@@ -224,7 +224,7 @@
                                 Depending on a build machine, default value is not always enough.
                             -->
                             <skip>false</skip>
-                            <argLine>-Xmx6g</argLine>
+                            <argLine>-Xmx6g -Dfile.encoding=UTF-8</argLine>
                         </configuration>
                     </plugin>
                 </plugins>
@@ -296,7 +296,7 @@
                                 Maximum heap size was set to 6g, as a minimum required value for tests run.
                                 Depending on a build machine, default value is not always enough.
                             -->
-                            <argLine>-Xmx6g</argLine>
+                            <argLine>-Xmx6g -Dfile.encoding=UTF-8</argLine>
                             <skipTests>false</skipTests>
                             <skip>false</skip>
                         </configuration>

nd4j/nd4j-backends/nd4j-tests/pom.xml

@@ -252,7 +252,7 @@
                                 Maximum heap size was set to 6g, as a minimum required value for tests run.
                                 Depending on a build machine, default value is not always enough.
                             -->
-                            <argLine>-Ddtype=float -Xmx6g</argLine>
+                            <argLine>-Ddtype=float -Dfile.encoding=UTF-8 -Xmx6g</argLine>
                         </configuration>
                     </plugin>
                 </plugins>

nd4j/nd4j-backends/nd4j-tests/src/test/java/org/nd4j/autodiff/TestOpMapping.java

@@ -44,6 +44,11 @@ public class TestOpMapping extends BaseNd4jTest {
         return 'c';
     }
 
+    @Override
+    public long getTimeoutMilliseconds() {
+        return 60000L;
+    }
+
     @Test
     public void testOpMappingCoverage() throws Exception {
         Reflections reflections = new Reflections("org.nd4j");

nd4j/nd4j-serde/nd4j-aeron/pom.xml

@@ -91,7 +91,7 @@
 
                   For testing large zoo models, this may not be enough (so comment it out).
               -->
-              <argLine>-Ddtype=float -Xmx8g</argLine>
+              <argLine>-Ddtype=float -Dfile.encoding=UTF-8 -Xmx8g</argLine>
             </configuration>
           </plugin>
         </plugins>

nd4j/nd4j-serde/nd4j-arrow/pom.xml

@@ -109,7 +109,7 @@
 
                                 For testing large zoo models, this may not be enough (so comment it out).
                             -->
-                            <argLine>-Ddtype=float -Xmx8g</argLine>
+                            <argLine>-Ddtype=float -Dfile.encoding=UTF-8 -Xmx8g</argLine>
                         </configuration>
                     </plugin>
                 </plugins>

nd4j/nd4j-serde/nd4j-gson/pom.xml

@@ -100,7 +100,7 @@
 
                                 For testing large zoo models, this may not be enough (so comment it out).
                             -->
-                            <argLine>-Ddtype=float -Xmx8g</argLine>
+                            <argLine>-Ddtype=float -Dfile.encoding=UTF-8 -Xmx8g</argLine>
                         </configuration>
                     </plugin>
                 </plugins>

nd4j/nd4j-serde/nd4j-kryo/pom.xml

@@ -220,7 +220,7 @@
                                 Maximum heap size was set to 6g, as a minimum required value for tests run.
                                 Depending on a build machine, default value is not always enough.
                             -->
-                            <argLine>-Ddtype=float -Xmx6g</argLine>
+                            <argLine>-Ddtype=float -Dfile.encoding=UTF-8 -Xmx6g</argLine>
                         </configuration>
                     </plugin>
                 </plugins>