Author: tommaso
Date: Tue Dec 31 15:08:07 2013
New Revision: 1554532
URL: http://svn.apache.org/r1554532
Log:
HAMA-835 - findbugs fixes applied to ML
Modified:
hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/AbstractLayeredNeuralNetwork.java
hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/AutoEncoder.java
hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/NeuralNetwork.java
hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/SmallLayeredNeuralNetwork.java
hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/SmallLayeredNeuralNetworkTrainer.java
hama/trunk/ml/src/main/java/org/apache/hama/ml/kmeans/KMeansBSP.java
hama/trunk/ml/src/main/java/org/apache/hama/ml/perception/SmallMLPTrainer.java
hama/trunk/ml/src/main/java/org/apache/hama/ml/perception/SmallMultiLayerPerceptron.java
hama/trunk/ml/src/main/java/org/apache/hama/ml/regression/GradientDescentBSP.java
hama/trunk/ml/src/main/java/org/apache/hama/ml/regression/LinearRegression.java
hama/trunk/ml/src/main/java/org/apache/hama/ml/regression/LogisticRegression.java
hama/trunk/ml/src/main/java/org/apache/hama/ml/semiclustering/SemiClusterDetails.java
hama/trunk/ml/src/main/java/org/apache/hama/ml/semiclustering/SemiClusterMessage.java
hama/trunk/ml/src/main/java/org/apache/hama/ml/semiclustering/SemiClusteringVertex.java
Modified:
hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/AbstractLayeredNeuralNetwork.java
URL:
http://svn.apache.org/viewvc/hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/AbstractLayeredNeuralNetwork.java?rev=1554532&r1=1554531&r2=1554532&view=diff
==============================================================================
---
hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/AbstractLayeredNeuralNetwork.java
(original)
+++
hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/AbstractLayeredNeuralNetwork.java
Tue Dec 31 15:08:07 2013
@@ -20,7 +20,6 @@ package org.apache.hama.ml.ann;
import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
-import java.util.ArrayList;
import java.util.List;
import org.apache.hadoop.io.WritableUtils;
@@ -252,8 +251,8 @@ abstract class AbstractLayeredNeuralNetw
// write layer size list
output.writeInt(this.layerSizeList.size());
- for (int i = 0; i < this.layerSizeList.size(); ++i) {
- output.writeInt(this.layerSizeList.get(i));
+ for (Integer aLayerSizeList : this.layerSizeList) {
+ output.writeInt(aLayerSizeList);
}
WritableUtils.writeEnum(output, this.trainingMethod);
Modified: hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/AutoEncoder.java
URL:
http://svn.apache.org/viewvc/hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/AutoEncoder.java?rev=1554532&r1=1554531&r2=1554532&view=diff
==============================================================================
--- hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/AutoEncoder.java
(original)
+++ hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/AutoEncoder.java Tue Dec
31 15:08:07 2013
@@ -40,7 +40,7 @@ import com.google.common.base.Preconditi
*/
public class AutoEncoder {
- private SmallLayeredNeuralNetwork model;
+ private final SmallLayeredNeuralNetwork model;
/**
* Initialize the autoencoder.
Modified: hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/NeuralNetwork.java
URL:
http://svn.apache.org/viewvc/hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/NeuralNetwork.java?rev=1554532&r1=1554531&r2=1554532&view=diff
==============================================================================
--- hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/NeuralNetwork.java
(original)
+++ hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/NeuralNetwork.java Tue
Dec 31 15:08:07 2013
@@ -17,16 +17,8 @@
*/
package org.apache.hama.ml.ann;
-import java.io.DataInput;
-import java.io.DataOutput;
-import java.io.IOException;
-import java.lang.reflect.Constructor;
-import java.lang.reflect.InvocationTargetException;
-import java.lang.reflect.Method;
-import java.net.URI;
-import java.net.URISyntaxException;
-import java.util.Map;
-
+import com.google.common.base.Preconditions;
+import com.google.common.io.Closeables;
import org.apache.commons.lang.SerializationUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataInputStream;
@@ -38,8 +30,14 @@ import org.apache.hadoop.io.WritableUtil
import org.apache.hama.ml.util.DefaultFeatureTransformer;
import org.apache.hama.ml.util.FeatureTransformer;
-import com.google.common.base.Preconditions;
-import com.google.common.io.Closeables;
+import java.io.DataInput;
+import java.io.DataOutput;
+import java.io.IOException;
+import java.lang.reflect.Constructor;
+import java.lang.reflect.InvocationTargetException;
+import java.net.URI;
+import java.net.URISyntaxException;
+import java.util.Map;
/**
* NeuralNetwork defines the general operations for all the derivative models.
Modified:
hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/SmallLayeredNeuralNetwork.java
URL:
http://svn.apache.org/viewvc/hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/SmallLayeredNeuralNetwork.java?rev=1554532&r1=1554531&r2=1554532&view=diff
==============================================================================
---
hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/SmallLayeredNeuralNetwork.java
(original)
+++
hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/SmallLayeredNeuralNetwork.java
Tue Dec 31 15:08:07 2013
@@ -21,6 +21,7 @@ import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import java.util.ArrayList;
+import java.util.Collections;
import java.util.List;
import java.util.Map;
@@ -145,9 +146,7 @@ public class SmallLayeredNeuralNetwork e
*/
void setPrevWeightMatrices(DoubleMatrix[] prevUpdates) {
this.prevWeightUpdatesList.clear();
- for (DoubleMatrix prevUpdate : prevUpdates) {
- this.prevWeightUpdatesList.add(prevUpdate);
- }
+ Collections.addAll(this.prevWeightUpdatesList, prevUpdates);
}
/**
@@ -181,9 +180,7 @@ public class SmallLayeredNeuralNetwork e
*/
public void setWeightMatrices(DoubleMatrix[] matrices) {
this.weightMatrixList = new ArrayList<DoubleMatrix>();
- for (DoubleMatrix matrix : matrices) {
- this.weightMatrixList.add(matrix);
- }
+ Collections.addAll(this.weightMatrixList, matrices);
}
/**
@@ -239,15 +236,15 @@ public class SmallLayeredNeuralNetwork e
// write squashing functions
output.writeInt(this.squashingFunctionList.size());
- for (int i = 0; i < this.squashingFunctionList.size(); ++i) {
- WritableUtils.writeString(output, this.squashingFunctionList.get(i)
- .getFunctionName());
+ for (DoubleFunction aSquashingFunctionList : this.squashingFunctionList) {
+ WritableUtils.writeString(output, aSquashingFunctionList
+ .getFunctionName());
}
// write weight matrices
output.writeInt(this.weightMatrixList.size());
- for (int i = 0; i < this.weightMatrixList.size(); ++i) {
- MatrixWritable.write(this.weightMatrixList.get(i), output);
+ for (DoubleMatrix aWeightMatrixList : this.weightMatrixList) {
+ MatrixWritable.write(aWeightMatrixList, output);
}
// DO NOT WRITE WEIGHT UPDATE
Modified:
hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/SmallLayeredNeuralNetworkTrainer.java
URL:
http://svn.apache.org/viewvc/hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/SmallLayeredNeuralNetworkTrainer.java?rev=1554532&r1=1554531&r2=1554532&view=diff
==============================================================================
---
hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/SmallLayeredNeuralNetworkTrainer.java
(original)
+++
hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/SmallLayeredNeuralNetworkTrainer.java
Tue Dec 31 15:08:07 2013
@@ -153,7 +153,7 @@ public final class SmallLayeredNeuralNet
LongWritable key = new LongWritable();
VectorWritable value = new VectorWritable();
for (int recordsRead = 0; recordsRead < batchSize; ++recordsRead) {
- if (peer.readNext(key, value) == false) {
+ if (!peer.readNext(key, value)) {
peer.reopenInput();
peer.readNext(key, value);
}
Modified: hama/trunk/ml/src/main/java/org/apache/hama/ml/kmeans/KMeansBSP.java
URL:
http://svn.apache.org/viewvc/hama/trunk/ml/src/main/java/org/apache/hama/ml/kmeans/KMeansBSP.java?rev=1554532&r1=1554531&r2=1554532&view=diff
==============================================================================
--- hama/trunk/ml/src/main/java/org/apache/hama/ml/kmeans/KMeansBSP.java
(original)
+++ hama/trunk/ml/src/main/java/org/apache/hama/ml/kmeans/KMeansBSP.java Tue
Dec 31 15:08:07 2013
@@ -112,9 +112,7 @@ public final class KMeansBSP
try {
distanceMeasurer = ReflectionUtils.newInstance(distanceClass);
} catch (ClassNotFoundException e) {
- throw new RuntimeException(new StringBuilder(
- "Wrong DistanceMeasurer implementation ").append(distanceClass)
- .append(" provided").toString());
+ throw new RuntimeException("Wrong DistanceMeasurer implementation " +
distanceClass + " provided");
}
} else {
distanceMeasurer = new EuclidianDistance();
Modified:
hama/trunk/ml/src/main/java/org/apache/hama/ml/perception/SmallMLPTrainer.java
URL:
http://svn.apache.org/viewvc/hama/trunk/ml/src/main/java/org/apache/hama/ml/perception/SmallMLPTrainer.java?rev=1554532&r1=1554531&r2=1554532&view=diff
==============================================================================
---
hama/trunk/ml/src/main/java/org/apache/hama/ml/perception/SmallMLPTrainer.java
(original)
+++
hama/trunk/ml/src/main/java/org/apache/hama/ml/perception/SmallMLPTrainer.java
Tue Dec 31 15:08:07 2013
@@ -315,8 +315,8 @@ class SmallMLPTrainer extends NeuralNetw
for (int i = 0; i < mat.length; ++i) {
sb.append(String.format("Matrix [%d]\n", i));
double[][] values = mat[i].getValues();
- for (int d = 0; d < values.length; ++d) {
- sb.append(Arrays.toString(values[d]));
+ for (double[] value : values) {
+ sb.append(Arrays.toString(value));
sb.append('\n');
}
sb.append('\n');
Modified:
hama/trunk/ml/src/main/java/org/apache/hama/ml/perception/SmallMultiLayerPerceptron.java
URL:
http://svn.apache.org/viewvc/hama/trunk/ml/src/main/java/org/apache/hama/ml/perception/SmallMultiLayerPerceptron.java?rev=1554532&r1=1554531&r2=1554532&view=diff
==============================================================================
---
hama/trunk/ml/src/main/java/org/apache/hama/ml/perception/SmallMultiLayerPerceptron.java
(original)
+++
hama/trunk/ml/src/main/java/org/apache/hama/ml/perception/SmallMultiLayerPerceptron.java
Tue Dec 31 15:08:07 2013
@@ -115,7 +115,7 @@ public final class SmallMultiLayerPercep
this.weightMatrice[i].applyToElements(new DoubleFunction() {
- private Random rnd = new Random();
+ private final Random rnd = new Random();
@Override
public double apply(double value) {
@@ -556,8 +556,8 @@ public final class SmallMultiLayerPercep
for (int i = 0; i < mat.length; ++i) {
sb.append(String.format("Matrix [%d]\n", i));
double[][] values = mat[i].getValues();
- for (int d = 0; d < values.length; ++d) {
- sb.append(Arrays.toString(values[d]));
+ for (double[] value : values) {
+ sb.append(Arrays.toString(value));
sb.append('\n');
}
sb.append('\n');
Modified:
hama/trunk/ml/src/main/java/org/apache/hama/ml/regression/GradientDescentBSP.java
URL:
http://svn.apache.org/viewvc/hama/trunk/ml/src/main/java/org/apache/hama/ml/regression/GradientDescentBSP.java?rev=1554532&r1=1554531&r2=1554532&view=diff
==============================================================================
---
hama/trunk/ml/src/main/java/org/apache/hama/ml/regression/GradientDescentBSP.java
(original)
+++
hama/trunk/ml/src/main/java/org/apache/hama/ml/regression/GradientDescentBSP.java
Tue Dec 31 15:08:07 2013
@@ -17,10 +17,6 @@
*/
package org.apache.hama.ml.regression;
-import java.io.IOException;
-import java.math.BigDecimal;
-import java.util.Arrays;
-
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hama.bsp.BSP;
import org.apache.hama.bsp.BSPPeer;
@@ -32,6 +28,10 @@ import org.apache.hama.commons.util.KeyV
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
+import java.io.IOException;
+import java.math.BigDecimal;
+import java.util.Arrays;
+
/**
* A gradient descent (see
* <code>http://en.wikipedia.org/wiki/Gradient_descent</code>) BSP based
@@ -195,9 +195,7 @@ public class GradientDescentBSP
BSPPeer<VectorWritable, DoubleWritable, VectorWritable, DoubleWritable,
VectorWritable> peer,
int iterations, double totalCost) {
if (iterations > 0 && cost < totalCost) {
- throw new RuntimeException(new StringBuilder(
- "gradient descent failed to converge with alpha ").append(alpha)
- .toString());
+ throw new RuntimeException("gradient descent failed to converge with
alpha " + alpha);
} else if (totalCost == 0 || totalCost < costThreshold
|| iterations >= iterationsThreshold) {
cost = totalCost;
Modified:
hama/trunk/ml/src/main/java/org/apache/hama/ml/regression/LinearRegression.java
URL:
http://svn.apache.org/viewvc/hama/trunk/ml/src/main/java/org/apache/hama/ml/regression/LinearRegression.java?rev=1554532&r1=1554531&r2=1554532&view=diff
==============================================================================
---
hama/trunk/ml/src/main/java/org/apache/hama/ml/regression/LinearRegression.java
(original)
+++
hama/trunk/ml/src/main/java/org/apache/hama/ml/regression/LinearRegression.java
Tue Dec 31 15:08:07 2013
@@ -35,7 +35,7 @@ import org.apache.hama.ml.util.FeatureTr
public class LinearRegression {
/* Internal model */
- private SmallLayeredNeuralNetwork ann;
+ private final SmallLayeredNeuralNetwork ann;
public LinearRegression(int dimension) {
ann = new SmallLayeredNeuralNetwork();
Modified:
hama/trunk/ml/src/main/java/org/apache/hama/ml/regression/LogisticRegression.java
URL:
http://svn.apache.org/viewvc/hama/trunk/ml/src/main/java/org/apache/hama/ml/regression/LogisticRegression.java?rev=1554532&r1=1554531&r2=1554532&view=diff
==============================================================================
---
hama/trunk/ml/src/main/java/org/apache/hama/ml/regression/LogisticRegression.java
(original)
+++
hama/trunk/ml/src/main/java/org/apache/hama/ml/regression/LogisticRegression.java
Tue Dec 31 15:08:07 2013
@@ -18,15 +18,15 @@
package org.apache.hama.ml.regression;
-import java.io.IOException;
-import java.util.Map;
-
import org.apache.hadoop.fs.Path;
import org.apache.hama.commons.math.DoubleVector;
import org.apache.hama.commons.math.FunctionFactory;
import org.apache.hama.ml.ann.SmallLayeredNeuralNetwork;
import org.apache.hama.ml.util.FeatureTransformer;
+import java.io.IOException;
+import java.util.Map;
+
/**
* The logistic regression model. It can be used to conduct 2-class
* classification.
@@ -34,7 +34,7 @@ import org.apache.hama.ml.util.FeatureTr
*/
public class LogisticRegression {
- private SmallLayeredNeuralNetwork ann;
+ private final SmallLayeredNeuralNetwork ann;
public LogisticRegression(int dimension) {
this.ann = new SmallLayeredNeuralNetwork();
Modified:
hama/trunk/ml/src/main/java/org/apache/hama/ml/semiclustering/SemiClusterDetails.java
URL:
http://svn.apache.org/viewvc/hama/trunk/ml/src/main/java/org/apache/hama/ml/semiclustering/SemiClusterDetails.java?rev=1554532&r1=1554531&r2=1554532&view=diff
==============================================================================
---
hama/trunk/ml/src/main/java/org/apache/hama/ml/semiclustering/SemiClusterDetails.java
(original)
+++
hama/trunk/ml/src/main/java/org/apache/hama/ml/semiclustering/SemiClusterDetails.java
Tue Dec 31 15:08:07 2013
@@ -89,10 +89,8 @@ public class SemiClusterDetails implemen
return false;
} else if (!semiClusterId.equals(other.semiClusterId))
return false;
- if (Double.doubleToLongBits(semiClusterScore) != Double
- .doubleToLongBits(other.semiClusterScore))
- return false;
- return true;
+ return Double.doubleToLongBits(semiClusterScore) == Double
+ .doubleToLongBits(other.semiClusterScore);
}
@Override
Modified:
hama/trunk/ml/src/main/java/org/apache/hama/ml/semiclustering/SemiClusterMessage.java
URL:
http://svn.apache.org/viewvc/hama/trunk/ml/src/main/java/org/apache/hama/ml/semiclustering/SemiClusterMessage.java?rev=1554532&r1=1554531&r2=1554532&view=diff
==============================================================================
---
hama/trunk/ml/src/main/java/org/apache/hama/ml/semiclustering/SemiClusterMessage.java
(original)
+++
hama/trunk/ml/src/main/java/org/apache/hama/ml/semiclustering/SemiClusterMessage.java
Tue Dec 31 15:08:07 2013
@@ -138,9 +138,7 @@ public class SemiClusterMessage implemen
}
}
out.writeInt(semiClusterContainThis.size());
- Iterator<SemiClusterDetails> itr = semiClusterContainThis.iterator();
- while (itr.hasNext())
- itr.next().write(out);
+ for (SemiClusterDetails semiClusterContainThi : semiClusterContainThis)
semiClusterContainThi.write(out);
}
public Set<SemiClusterDetails> getSemiClusterContainThis() {
Modified:
hama/trunk/ml/src/main/java/org/apache/hama/ml/semiclustering/SemiClusteringVertex.java
URL:
http://svn.apache.org/viewvc/hama/trunk/ml/src/main/java/org/apache/hama/ml/semiclustering/SemiClusteringVertex.java?rev=1554532&r1=1554531&r2=1554532&view=diff
==============================================================================
---
hama/trunk/ml/src/main/java/org/apache/hama/ml/semiclustering/SemiClusteringVertex.java
(original)
+++
hama/trunk/ml/src/main/java/org/apache/hama/ml/semiclustering/SemiClusteringVertex.java
Tue Dec 31 15:08:07 2013
@@ -18,21 +18,15 @@
package org.apache.hama.ml.semiclustering;
-import java.io.IOException;
-import java.util.ArrayList;
-import java.util.Collections;
-import java.util.Comparator;
-import java.util.Iterator;
-import java.util.List;
-import java.util.Set;
-import java.util.TreeSet;
-
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.Text;
import org.apache.hama.HamaConfiguration;
import org.apache.hama.graph.Edge;
import org.apache.hama.graph.Vertex;
+import java.io.IOException;
+import java.util.*;
+
/**
* SemiClusteringVertex Class defines each vertex in a Graph job and the
* compute() method is the function which is applied on each Vertex in the
graph
@@ -207,11 +201,8 @@ public class SemiClusteringVertex extend
*/
public boolean isVertexInSc(SemiClusterMessage msg) {
List<String> vertexId = getSemiClusterVerticesIdList(msg.getVertexList());
- if (vertexId.contains(this.getVertexID().toString())
- && vertexId.size() < semiClusterMaximumVertexCount)
- return true;
- else
- return false;
+ return vertexId.contains(this.getVertexID().toString())
+ && vertexId.size() < semiClusterMaximumVertexCount;
}
/**
