performance improvement (#9055)

* performance improvement

Signed-off-by: Dariusz Zbyrad <dariusz.zbyrad@gmail.com>

* revert some changes

Signed-off-by: Dariusz Zbyrad <dariusz.zbyrad@gmail.com>

arbiter/arbiter-core/src/main/java/org/deeplearning4j/arbiter/optimize/api/CandidateGenerator.java

@@ -16,10 +16,7 @@
 
 package org.deeplearning4j.arbiter.optimize.api;
 
-import org.deeplearning4j.arbiter.optimize.generator.GridSearchCandidateGenerator;
-import org.deeplearning4j.arbiter.optimize.generator.RandomSearchGenerator;
 import org.nd4j.shade.jackson.annotation.JsonInclude;
-import org.nd4j.shade.jackson.annotation.JsonSubTypes;
 import org.nd4j.shade.jackson.annotation.JsonTypeInfo;
 
 /**

arbiter/arbiter-core/src/main/java/org/deeplearning4j/arbiter/optimize/config/OptimizationConfiguration.java

@@ -29,7 +29,6 @@ import org.nd4j.shade.jackson.core.JsonProcessingException;
 import org.nd4j.shade.jackson.databind.annotation.JsonSerialize;
 
 import java.io.IOException;
-import java.lang.reflect.Constructor;
 import java.util.Arrays;
 import java.util.List;
 import java.util.Properties;

arbiter/arbiter-core/src/main/java/org/deeplearning4j/arbiter/optimize/distribution/DegenerateIntegerDistribution.java

@@ -20,6 +20,8 @@ import org.apache.commons.math3.distribution.IntegerDistribution;
 import org.apache.commons.math3.exception.NumberIsTooLargeException;
 import org.apache.commons.math3.exception.OutOfRangeException;
 
+import java.util.Arrays;
+
 /**
  * Degenerate distribution: i.e., integer "distribution" that is just a fixed value
  */
@@ -89,8 +91,7 @@ public class DegenerateIntegerDistribution implements IntegerDistribution {
     @Override
     public int[] sample(int sampleSize) {
         int[] out = new int[sampleSize];
-        for (int i = 0; i < out.length; i++)
+        Arrays.fill(out, value);
-            out[i] = value;
         return out;
     }
 }

arbiter/arbiter-core/src/main/java/org/deeplearning4j/arbiter/optimize/parameter/continuous/ContinuousParameterSpace.java

@@ -22,7 +22,6 @@ import org.deeplearning4j.arbiter.optimize.api.ParameterSpace;
 import org.deeplearning4j.arbiter.optimize.distribution.DistributionUtils;
 import org.deeplearning4j.arbiter.optimize.serde.jackson.RealDistributionDeserializer;
 import org.deeplearning4j.arbiter.optimize.serde.jackson.RealDistributionSerializer;
-import org.nd4j.shade.jackson.annotation.JsonIgnoreProperties;
 import org.nd4j.shade.jackson.annotation.JsonProperty;
 import org.nd4j.shade.jackson.databind.annotation.JsonDeserialize;
 import org.nd4j.shade.jackson.databind.annotation.JsonSerialize;

arbiter/arbiter-core/src/main/java/org/deeplearning4j/arbiter/optimize/parameter/discrete/DiscreteParameterSpace.java

@@ -19,7 +19,6 @@ package org.deeplearning4j.arbiter.optimize.parameter.discrete;
 import lombok.EqualsAndHashCode;
 import org.deeplearning4j.arbiter.optimize.api.ParameterSpace;
 import org.deeplearning4j.arbiter.util.ObjectUtils;
-import org.nd4j.shade.jackson.annotation.JsonIgnoreProperties;
 import org.nd4j.shade.jackson.annotation.JsonProperty;
 import org.nd4j.shade.jackson.databind.annotation.JsonSerialize;
 

arbiter/arbiter-core/src/main/java/org/deeplearning4j/arbiter/optimize/runner/BaseOptimizationRunner.java

@@ -319,11 +319,9 @@ public abstract class BaseOptimizationRunner implements IOptimizationRunner {
     @Override
     public void removeListeners(StatusListener... listeners) {
         for (StatusListener l : listeners) {
-            if (statusListeners.contains(l)) {
             statusListeners.remove(l);
         }
     }
-    }
 
     @Override
     public void removeAllListeners() {
@@ -332,8 +330,7 @@ public abstract class BaseOptimizationRunner implements IOptimizationRunner {
 
     @Override
     public List<CandidateInfo> getCandidateStatus() {
-        List<CandidateInfo> list = new ArrayList<>();
+        List<CandidateInfo> list = new ArrayList<>(currentStatus.values());
-        list.addAll(currentStatus.values());
         return list;
     }
 

arbiter/arbiter-core/src/test/java/org/deeplearning4j/arbiter/optimize/genetic/mutation/RandomMutationOperatorTests.java

@@ -23,7 +23,6 @@ import org.junit.Assert;
 import org.junit.Test;
 
 import java.lang.reflect.Field;
-import java.util.Arrays;
 
 public class RandomMutationOperatorTests extends BaseDL4JTest {
     @Test

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/BaseNetworkSpace.java

@@ -187,19 +187,19 @@ public abstract class BaseNetworkSpace<T> extends AbstractParameterSpace<T> {
         if (allParamConstraints != null){
             List<LayerConstraint> c = allParamConstraints.getValue(values);
             if(c != null){
-                builder.constrainAllParameters(c.toArray(new LayerConstraint[c.size()]));
+                builder.constrainAllParameters(c.toArray(new LayerConstraint[0]));
             }
         }
         if (weightConstraints != null){
             List<LayerConstraint> c = weightConstraints.getValue(values);
             if(c != null){
-                builder.constrainWeights(c.toArray(new LayerConstraint[c.size()]));
+                builder.constrainWeights(c.toArray(new LayerConstraint[0]));
             }
         }
         if (biasConstraints != null){
             List<LayerConstraint> c = biasConstraints.getValue(values);
             if(c != null){
-                builder.constrainBias(c.toArray(new LayerConstraint[c.size()]));
+                builder.constrainBias(c.toArray(new LayerConstraint[0]));
             }
         }
 
@@ -226,7 +226,7 @@ public abstract class BaseNetworkSpace<T> extends AbstractParameterSpace<T> {
                 out.add(next);
             } else {
                 Map<String, ParameterSpace> m = next.getNestedSpaces();
-                ParameterSpace[] arr = m.values().toArray(new ParameterSpace[m.size()]);
+                ParameterSpace[] arr = m.values().toArray(new ParameterSpace[0]);
                 for (int i = arr.length - 1; i >= 0; i--) {
                     stack.add(arr[i]);
                 }

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/conf/updater/AdaGradSpace.java

@@ -18,18 +18,12 @@ package org.deeplearning4j.arbiter.conf.updater;
 
 import lombok.Data;
 import lombok.EqualsAndHashCode;
-import lombok.Getter;
-import lombok.Setter;
 import org.deeplearning4j.arbiter.optimize.api.ParameterSpace;
 import org.nd4j.linalg.learning.config.AdaGrad;
 import org.nd4j.linalg.learning.config.IUpdater;
 import org.nd4j.linalg.schedule.ISchedule;
 import org.nd4j.shade.jackson.annotation.JsonProperty;
 
-import java.util.Collections;
-import java.util.List;
-import java.util.Map;
-
 @Data
 @EqualsAndHashCode(callSuper = false)
 public class AdaGradSpace extends BaseUpdaterSpace {

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/conf/updater/BaseUpdaterSpace.java

@@ -17,8 +17,6 @@
 package org.deeplearning4j.arbiter.conf.updater;
 
 import lombok.Data;
-import lombok.Getter;
-import lombok.Setter;
 import org.deeplearning4j.arbiter.optimize.api.AbstractParameterSpace;
 import org.deeplearning4j.arbiter.optimize.api.ParameterSpace;
 import org.nd4j.linalg.learning.config.IUpdater;

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/conf/updater/schedule/InverseScheduleSpace.java

@@ -21,7 +21,6 @@ import lombok.NoArgsConstructor;
 import lombok.NonNull;
 import org.deeplearning4j.arbiter.optimize.api.ParameterSpace;
 import org.deeplearning4j.arbiter.optimize.parameter.FixedValue;
-import org.nd4j.linalg.schedule.ExponentialSchedule;
 import org.nd4j.linalg.schedule.ISchedule;
 import org.nd4j.linalg.schedule.InverseSchedule;
 import org.nd4j.linalg.schedule.ScheduleType;

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/conf/updater/schedule/PolyScheduleSpace.java

@@ -22,7 +22,6 @@ import lombok.NonNull;
 import org.deeplearning4j.arbiter.optimize.api.ParameterSpace;
 import org.deeplearning4j.arbiter.optimize.parameter.FixedValue;
 import org.nd4j.linalg.schedule.ISchedule;
-import org.nd4j.linalg.schedule.InverseSchedule;
 import org.nd4j.linalg.schedule.PolySchedule;
 import org.nd4j.linalg.schedule.ScheduleType;
 import org.nd4j.shade.jackson.annotation.JsonProperty;

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/conf/updater/schedule/SigmoidScheduleSpace.java

@@ -22,7 +22,6 @@ import lombok.NonNull;
 import org.deeplearning4j.arbiter.optimize.api.ParameterSpace;
 import org.deeplearning4j.arbiter.optimize.parameter.FixedValue;
 import org.nd4j.linalg.schedule.ISchedule;
-import org.nd4j.linalg.schedule.PolySchedule;
 import org.nd4j.linalg.schedule.ScheduleType;
 import org.nd4j.linalg.schedule.SigmoidSchedule;
 import org.nd4j.shade.jackson.annotation.JsonProperty;

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/conf/updater/schedule/StepScheduleSpace.java

@@ -22,7 +22,6 @@ import lombok.NonNull;
 import org.deeplearning4j.arbiter.optimize.api.ParameterSpace;
 import org.deeplearning4j.arbiter.optimize.parameter.FixedValue;
 import org.nd4j.linalg.schedule.ISchedule;
-import org.nd4j.linalg.schedule.InverseSchedule;
 import org.nd4j.linalg.schedule.ScheduleType;
 import org.nd4j.linalg.schedule.StepSchedule;
 import org.nd4j.shade.jackson.annotation.JsonProperty;

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/dropout/GaussianDropoutSpace.java

@@ -19,7 +19,6 @@ package org.deeplearning4j.arbiter.dropout;
 import lombok.AllArgsConstructor;
 import org.deeplearning4j.arbiter.optimize.api.ParameterSpace;
 import org.deeplearning4j.arbiter.optimize.parameter.FixedValue;
-import org.deeplearning4j.nn.conf.dropout.Dropout;
 import org.deeplearning4j.nn.conf.dropout.GaussianDropout;
 import org.deeplearning4j.nn.conf.dropout.IDropout;
 

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/layers/AbstractLSTMLayerSpace.java

@@ -25,7 +25,6 @@ import org.deeplearning4j.arbiter.optimize.api.ParameterSpace;
 import org.deeplearning4j.arbiter.optimize.parameter.FixedValue;
 import org.deeplearning4j.arbiter.util.LeafUtils;
 import org.deeplearning4j.nn.conf.layers.AbstractLSTM;
-import org.deeplearning4j.nn.conf.layers.GravesLSTM;
 import org.nd4j.linalg.activations.Activation;
 import org.nd4j.linalg.activations.IActivation;
 

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/layers/BaseLayerSpace.java

@@ -26,7 +26,6 @@ import org.deeplearning4j.arbiter.optimize.api.ParameterSpace;
 import org.deeplearning4j.arbiter.optimize.parameter.FixedValue;
 import org.deeplearning4j.arbiter.optimize.parameter.discrete.DiscreteParameterSpace;
 import org.deeplearning4j.nn.conf.GradientNormalization;
-import org.deeplearning4j.nn.conf.Updater;
 import org.deeplearning4j.nn.conf.distribution.Distribution;
 import org.deeplearning4j.nn.conf.layers.BaseLayer;
 import org.deeplearning4j.nn.conf.weightnoise.IWeightNoise;

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/layers/BatchNormalizationSpace.java

@@ -86,13 +86,13 @@ public class BatchNormalizationSpace extends FeedForwardLayerSpace<BatchNormaliz
         if (constrainBeta != null){
             List<LayerConstraint> c = constrainBeta.getValue(values);
             if(c != null){
-                builder.constrainBeta(c.toArray(new LayerConstraint[c.size()]));
+                builder.constrainBeta(c.toArray(new LayerConstraint[0]));
             }
         }
         if (constrainGamma != null){
             List<LayerConstraint> c = constrainGamma.getValue(values);
             if(c != null){
-                builder.constrainGamma(c.toArray(new LayerConstraint[c.size()]));
+                builder.constrainGamma(c.toArray(new LayerConstraint[0]));
             }
         }
     }

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/layers/DropoutLayerSpace.java

@@ -18,13 +18,11 @@ package org.deeplearning4j.arbiter.layers;
 
 import lombok.*;
 import org.deeplearning4j.arbiter.dropout.DropoutSpace;
-import org.deeplearning4j.arbiter.optimize.api.AbstractParameterSpace;
 import org.deeplearning4j.arbiter.optimize.api.ParameterSpace;
 import org.deeplearning4j.arbiter.optimize.parameter.FixedValue;
 import org.deeplearning4j.nn.conf.dropout.IDropout;
 import org.deeplearning4j.nn.conf.layers.DropoutLayer;
 
-import java.util.Collections;
 import java.util.List;
 
 @Data

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/layers/FeedForwardLayerSpace.java

@@ -56,19 +56,19 @@ public abstract class FeedForwardLayerSpace<L extends FeedForwardLayer> extends
         if (constrainWeights != null){
             List<LayerConstraint> c = constrainWeights.getValue(values);
             if(c != null){
-                builder.constrainWeights(c.toArray(new LayerConstraint[c.size()]));
+                builder.constrainWeights(c.toArray(new LayerConstraint[0]));
             }
         }
         if (constrainBias != null){
             List<LayerConstraint> c = constrainBias.getValue(values);
             if(c != null){
-                builder.constrainBias(c.toArray(new LayerConstraint[c.size()]));
+                builder.constrainBias(c.toArray(new LayerConstraint[0]));
             }
         }
         if (constrainAll != null){
             List<LayerConstraint> c = constrainAll.getValue(values);
             if(c != null){
-                builder.constrainAllParameters(c.toArray(new LayerConstraint[c.size()]));
+                builder.constrainAllParameters(c.toArray(new LayerConstraint[0]));
             }
         }
 

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/layers/GravesLSTMLayerSpace.java

@@ -20,8 +20,6 @@ import lombok.AccessLevel;
 import lombok.Data;
 import lombok.EqualsAndHashCode;
 import lombok.NoArgsConstructor;
-import org.deeplearning4j.arbiter.optimize.api.ParameterSpace;
-import org.deeplearning4j.arbiter.optimize.parameter.FixedValue;
 import org.deeplearning4j.arbiter.util.LeafUtils;
 import org.deeplearning4j.nn.conf.layers.GravesLSTM;
 
@@ -60,9 +58,7 @@ public class GravesLSTMLayerSpace extends AbstractLSTMLayerSpace<GravesLSTM> {
 
     @Override
     public String toString(String delim) {
-        StringBuilder sb = new StringBuilder("GravesLSTMLayerSpace(");
+        return "GravesLSTMLayerSpace(" + super.toString(delim) + ")";
-        sb.append(super.toString(delim)).append(")");
-        return sb.toString();
     }
 
     public static class Builder extends AbstractLSTMLayerSpace.Builder<Builder> {

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/layers/LSTMLayerSpace.java

@@ -20,10 +20,7 @@ import lombok.AccessLevel;
 import lombok.Data;
 import lombok.EqualsAndHashCode;
 import lombok.NoArgsConstructor;
-import org.deeplearning4j.arbiter.optimize.api.ParameterSpace;
-import org.deeplearning4j.arbiter.optimize.parameter.FixedValue;
 import org.deeplearning4j.arbiter.util.LeafUtils;
-import org.deeplearning4j.nn.conf.layers.GravesLSTM;
 import org.deeplearning4j.nn.conf.layers.LSTM;
 
 /**
@@ -61,9 +58,7 @@ public class LSTMLayerSpace extends AbstractLSTMLayerSpace<LSTM> {
 
     @Override
     public String toString(String delim) {
-        StringBuilder sb = new StringBuilder("LSTMLayerSpace(");
+        return "LSTMLayerSpace(" + super.toString(delim) + ")";
-        sb.append(super.toString(delim)).append(")");
-        return sb.toString();
     }
 
     public static class Builder extends AbstractLSTMLayerSpace.Builder<Builder> {

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/layers/LayerSpace.java

@@ -64,7 +64,7 @@ public abstract class LayerSpace<L extends Layer> extends AbstractParameterSpace
                 out.add(next);
             } else {
                 Map<String, ParameterSpace> m = next.getNestedSpaces();
-                ParameterSpace[] arr = m.values().toArray(new ParameterSpace[m.size()]);
+                ParameterSpace[] arr = m.values().toArray(new ParameterSpace[0]);
                 for (int i = arr.length - 1; i >= 0; i--) {
                     stack.add(arr[i]);
                 }

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/layers/SeparableConvolution2DLayerSpace.java

@@ -66,7 +66,7 @@ public class SeparableConvolution2DLayerSpace extends BaseConvolutionLayerSpace<
         if (pointWiseConstraints != null){
             List<LayerConstraint> c = pointWiseConstraints.getValue(values);
             if(c != null){
-                builder.constrainPointWise(c.toArray(new LayerConstraint[c.size()]));
+                builder.constrainPointWise(c.toArray(new LayerConstraint[0]));
             }
         }
     }

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/listener/DL4JArbiterStatusReportingListener.java

@@ -21,7 +21,6 @@ import org.deeplearning4j.arbiter.optimize.runner.CandidateInfo;
 import org.deeplearning4j.arbiter.optimize.runner.listener.StatusListener;
 import org.deeplearning4j.nn.api.Model;
 import org.deeplearning4j.optimize.api.BaseTrainingListener;
-import org.deeplearning4j.optimize.api.IterationListener;
 
 import java.util.List;
 

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/saver/local/FileModelSaver.java

@@ -94,7 +94,7 @@ public class FileModelSaver implements ResultSaver {
 
 
         Object additionalResults = result.getModelSpecificResults();
-        if (additionalResults != null && additionalResults instanceof Serializable) {
+        if (additionalResults instanceof Serializable) {
             try (ObjectOutputStream oos = new ObjectOutputStream(new FileOutputStream(additionalResultsFile))) {
                 oos.writeObject(additionalResults);
             }

arbiter/arbiter-deeplearning4j/src/main/java/org/deeplearning4j/arbiter/scoring/impl/BaseNetScoreFunction.java

@@ -26,7 +26,6 @@ import org.nd4j.linalg.dataset.api.iterator.DataSetIterator;
 import org.nd4j.linalg.dataset.api.iterator.DataSetIteratorFactory;
 import org.nd4j.linalg.dataset.api.iterator.MultiDataSetIterator;
 
-import java.io.IOException;
 import java.util.Arrays;
 import java.util.List;
 import java.util.Map;

arbiter/arbiter-deeplearning4j/src/test/java/org/deeplearning4j/arbiter/computationgraph/TestGraphLocalExecutionGenetic.java

@@ -69,7 +69,6 @@ import java.util.Map;
 import java.util.Properties;
 import java.util.concurrent.TimeUnit;
 
-import static org.junit.Assert.assertEquals;
 import static org.junit.Assert.assertTrue;
 
 @Slf4j

arbiter/arbiter-deeplearning4j/src/test/java/org/deeplearning4j/arbiter/json/TestJson.java

@@ -24,7 +24,6 @@ import org.deeplearning4j.arbiter.conf.updater.AdamSpace;
 import org.deeplearning4j.arbiter.conf.updater.SgdSpace;
 import org.deeplearning4j.arbiter.layers.DenseLayerSpace;
 import org.deeplearning4j.arbiter.layers.OutputLayerSpace;
-import org.deeplearning4j.arbiter.multilayernetwork.MnistDataSetIteratorFactory;
 import org.deeplearning4j.arbiter.optimize.api.CandidateGenerator;
 import org.deeplearning4j.arbiter.optimize.api.ParameterSpace;
 import org.deeplearning4j.arbiter.optimize.api.data.DataProvider;
@@ -47,12 +46,8 @@ import org.deeplearning4j.datasets.iterator.impl.IrisDataSetIterator;
 import org.deeplearning4j.datasets.iterator.impl.MnistDataSetIterator;
 import org.deeplearning4j.earlystopping.EarlyStoppingConfiguration;
 import org.deeplearning4j.earlystopping.saver.InMemoryModelSaver;
-import org.deeplearning4j.earlystopping.scorecalc.ClassificationScoreCalculator;
 import org.deeplearning4j.earlystopping.scorecalc.DataSetLossCalculatorCG;
-import org.deeplearning4j.earlystopping.scorecalc.base.BaseIEvaluationScoreCalculator;
 import org.deeplearning4j.earlystopping.termination.MaxEpochsTerminationCondition;
-import org.deeplearning4j.eval.Evaluation;
-import org.deeplearning4j.eval.IEvaluation;
 import org.deeplearning4j.nn.api.OptimizationAlgorithm;
 import org.deeplearning4j.nn.conf.inputs.InputType;
 import org.deeplearning4j.nn.graph.ComputationGraph;

arbiter/arbiter-deeplearning4j/src/test/java/org/deeplearning4j/arbiter/multilayernetwork/TestDL4JLocalExecution.java

@@ -72,7 +72,6 @@ import java.util.Map;
 import java.util.Properties;
 import java.util.concurrent.TimeUnit;
 
-import static org.junit.Assert.assertEquals;
 import static org.junit.Assert.assertTrue;
 
 @Slf4j

arbiter/arbiter-deeplearning4j/src/test/java/org/deeplearning4j/arbiter/multilayernetwork/TestMultiLayerSpace.java

@@ -384,8 +384,7 @@ public class TestMultiLayerSpace extends BaseDL4JTest {
 
 
         double[] ones = new double[numParams];
-        for (int i = 0; i < ones.length; i++)
+        Arrays.fill(ones, 1.0);
-            ones[i] = 1.0;
 
         configuration = mls.getValue(ones);
 

arbiter/arbiter-deeplearning4j/src/test/java/org/deeplearning4j/arbiter/util/TestDataFactoryProviderMnist.java

@@ -17,14 +17,11 @@
 package org.deeplearning4j.arbiter.util;
 
 import lombok.AllArgsConstructor;
-import org.deeplearning4j.arbiter.optimize.api.data.DataProvider;
 import org.deeplearning4j.datasets.iterator.EarlyTerminationDataSetIterator;
 import org.deeplearning4j.datasets.iterator.impl.MnistDataSetIterator;
 import org.nd4j.linalg.dataset.api.iterator.DataSetIterator;
 import org.nd4j.linalg.dataset.api.iterator.DataSetIteratorFactory;
 
-import java.util.Map;
-
 @AllArgsConstructor
 public class TestDataFactoryProviderMnist implements DataSetIteratorFactory {
 

arbiter/arbiter-server/src/test/java/org/deeplearning4j/arbiter/server/ArbiterCLIRunnerTest.java

@@ -38,7 +38,6 @@ import org.deeplearning4j.arbiter.scoring.impl.TestSetLossScoreFunction;
 import org.deeplearning4j.nn.api.OptimizationAlgorithm;
 import org.junit.Test;
 import org.nd4j.linalg.activations.Activation;
-import org.nd4j.linalg.learning.config.Sgd;
 import org.nd4j.linalg.lossfunctions.LossFunctions;
 
 import java.io.File;