Dependency version upgrades + small SameDiff fix (#405)

* #8861 Training evaluation on variables not required for loss fix

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

* Dependency version updates flagged by dependabot

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

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/autodiff/samediff/internal/AbstractSession.java

@@ -132,7 +132,7 @@ public abstract class AbstractSession<T, O> {
         Preconditions.checkState(!variables.isEmpty() || !requiredActivations.isEmpty(), "Variables to perform forward pass for must not be empty");
 
         if (requiredActivations == null)
-            requiredActivations = Collections.emptyList();
+            requiredActivations = Collections.emptySet();
 
         if (at == null)
             at = At.defaultAt();

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/autodiff/samediff/internal/TrainingSession.java

@@ -75,7 +75,7 @@ public class TrainingSession extends InferenceSession {
             this.listeners = filtered.isEmpty() ? null : filtered;
         }
 
-        List<String> requiredActivations = new ArrayList<>();
+        Set<String> requiredActivations = new HashSet<>();
         gradVarToVarMap = new HashMap<>();       //Key: gradient variable. Value: variable that the key is gradient for
         for (String s : paramsToTrain) {
             Preconditions.checkState(sameDiff.hasVariable(s), "SameDiff instance does not have a variable with name \"%s\"", s);
@@ -95,6 +95,12 @@ public class TrainingSession extends InferenceSession {
             gradVarToVarMap.put(grad.name(), s);
         }
 
+        //Also add evaluations - in case we want to evaluate something that isn't required to determine loss
+        // (hence wouldn't normally be calculated)
+        if(config.getTrainEvaluations() != null){
+            requiredActivations.addAll(config.getTrainEvaluations().keySet());
+        }
+
         //Set up losses
         lossVarsToLossIdx = new LinkedHashMap<>();
         List<String> lossVars;

nd4j/nd4j-backends/nd4j-tests/src/test/java/org/nd4j/autodiff/samediff/SameDiffTrainingTest.java

@@ -16,6 +16,7 @@
 
 package org.nd4j.autodiff.samediff;
 
+import static org.junit.Assert.assertEquals;
 import static org.junit.Assert.assertTrue;
 
 import java.util.Collections;
@@ -35,6 +36,7 @@ import org.nd4j.linalg.api.ndarray.INDArray;
 import org.nd4j.linalg.dataset.DataSet;
 import org.nd4j.linalg.dataset.IrisDataSetIterator;
 import org.nd4j.linalg.dataset.MultiDataSet;
+import org.nd4j.linalg.dataset.adapter.SingletonDataSetIterator;
 import org.nd4j.linalg.dataset.adapter.SingletonMultiDataSetIterator;
 import org.nd4j.linalg.dataset.api.iterator.DataSetIterator;
 import org.nd4j.linalg.dataset.api.preprocessor.NormalizerStandardize;
@@ -341,6 +343,39 @@ public class SameDiffTrainingTest extends BaseNd4jTest {
         History history = sd.fit(new SingletonMultiDataSetIterator(mds), 1);
     }
 
+    @Test
+    public void testTrainingEvalVarNotReqForLoss(){
+        //If a variable is not required for the loss - normally it won't be calculated
+        //But we want to make sure it IS calculated here - so we can perform evaluation on it
+
+        SameDiff sd = SameDiff.create();
+        SDVariable in = sd.placeHolder("in", DataType.FLOAT, -1, 4);
+        SDVariable label = sd.placeHolder("label", DataType.FLOAT, -1, 3);
+        SDVariable w = sd.var("w", Nd4j.rand(DataType.FLOAT, 4, 3));
+        SDVariable z = in.mmul(w);
+        SDVariable out = sd.nn.softmax("softmax", z);
+        SDVariable loss = sd.loss.logLoss("loss", label, out);
+        SDVariable notRequiredForLoss = sd.nn.softmax("notRequiredForLoss", z);
+
+        sd.setTrainingConfig(TrainingConfig.builder()
+                .updater(new Adam(0.001))
+                .dataSetFeatureMapping("in")
+                .dataSetLabelMapping("label")
+                .trainEvaluation("notRequiredForLoss", 0, new Evaluation())
+                .build());
+
+//        sd.setListeners(new ScoreListener(1));
+
+        DataSet ds = new DataSet(Nd4j.rand(DataType.FLOAT, 3, 4), Nd4j.createFromArray(new float[][]{{1,0,0}, {0,1,0}, {0,0,1}}));
+
+        History h = sd.fit()
+                .train(new SingletonDataSetIterator(ds), 4)
+                .exec();
+
+        List<Double> l = h.trainingEval(Evaluation.Metric.ACCURACY);
+        assertEquals(4, l.size());
+    }
+
 
     @Override
     public char ordering() {

nd4j/nd4j-jdbc/nd4j-jdbc-api/pom.xml

@@ -40,7 +40,7 @@
         <dependency>
             <groupId>com.mchange</groupId>
             <artifactId>c3p0</artifactId>
-            <version>0.9.5-pre5</version>
+            <version>0.9.5.4</version>
         </dependency>
         <dependency>
             <groupId>org.nd4j</groupId>

nd4j/nd4j-remote/nd4j-json-server/pom.xml

@@ -121,7 +121,7 @@
         <dependency>
             <groupId>javax.activation</groupId>
             <artifactId>activation</artifactId>
-            <version>1.1</version>
+            <version>1.1.1</version>
         </dependency>
 
         <dependency>

pom.xml

@@ -271,7 +271,7 @@
         <jodah.typetools.version>0.5.0</jodah.typetools.version>
         <freemarker.version>2.3.23</freemarker.version>
         <geoip2.version>2.8.1</geoip2.version>
-        <stream.analytics.version>2.7.0</stream.analytics.version>
+        <stream.analytics.version>2.9.8</stream.analytics.version>
         <opencsv.version>2.3</opencsv.version>
         <tdigest.version>3.2</tdigest.version>
         <jtransforms.version>3.1</jtransforms.version>
@@ -325,14 +325,14 @@
         <commons-collections.version>3.2.2</commons-collections.version>
         <commons-collections4.version>4.1</commons-collections4.version>
 
-        <spark.version>2.4.3</spark.version>
+        <spark.version>2.4.5</spark.version>
         <spark.major.version>2</spark.major.version>
         <args4j.version>2.0.29</args4j.version>
         <slf4j.version>1.7.21</slf4j.version>
         <junit.version>4.12</junit.version>
         <logback.version>1.2.3</logback.version>
         <jackson.version>2.10.1</jackson.version>
-        <jackson.databind.version>2.10.1</jackson.databind.version>
+        <jackson.databind.version>2.10.3</jackson.databind.version>
         <shaded.snakeyaml.version>1.24</shaded.snakeyaml.version>
         <geo.jackson.version>2.8.7</geo.jackson.version>
         <lombok.version>1.18.12</lombok.version>
@@ -353,7 +353,7 @@
         <gson.version>2.8.0</gson.version>
         <fbs.version>1.2.0-3f79e055</fbs.version>
         <threadly.version>4.10.0</threadly.version>
-        <vertx.version>3.8.3</vertx.version>
+        <vertx.version>3.9.0</vertx.version>
 
         <flatbuffers.version>1.10.0</flatbuffers.version>
         <grpc.version>1.14.0</grpc.version>
@@ -368,7 +368,7 @@
         <maven-compiler-plugin.version>3.7.0</maven-compiler-plugin.version>
         <maven-scala-plugin.version>3.3.1</maven-scala-plugin.version>
         <maven-resources-plugin.version>3.0.1</maven-resources-plugin.version>
-        <sbt-compiler-maven-plugin.version>1.0.0-beta8</sbt-compiler-maven-plugin.version>
+        <sbt-compiler-maven-plugin.version>1.0.0</sbt-compiler-maven-plugin.version>
         <maven-git-commit-plugin.version>2.2.2</maven-git-commit-plugin.version>
         <maven-git-commit-id-plugin.version>${maven-git-commit-plugin.version}
         </maven-git-commit-id-plugin.version>