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From yxji...@apache.org
Subject svn commit: r1527266 - in /hama/trunk: ./ CHANGES.txt examples/src/main/java/org/apache/hama/examples/NeuralNetwork.java examples/src/test/java/org/apache/hama/examples/NeuralNetworkTest.java
Date Sun, 29 Sep 2013 03:04:05 GMT
Author: yxjiang
Date: Sun Sep 29 03:04:05 2013
New Revision: 1527266

URL: http://svn.apache.org/r1527266
Log:
HAMA-806: Make the description of NeuralNetwork example more clear

Modified:
    hama/trunk/   (props changed)
    hama/trunk/CHANGES.txt
    hama/trunk/examples/src/main/java/org/apache/hama/examples/NeuralNetwork.java
    hama/trunk/examples/src/test/java/org/apache/hama/examples/NeuralNetworkTest.java

Propchange: hama/trunk/
------------------------------------------------------------------------------
--- svn:ignore (original)
+++ svn:ignore Sun Sep 29 03:04:05 2013
@@ -6,10 +6,8 @@ src-gen
 **/docs
 logs
 .settings
-
 lib
 target
-
 *.ipr
-
 *.iml
+*.patch

Modified: hama/trunk/CHANGES.txt
URL: http://svn.apache.org/viewvc/hama/trunk/CHANGES.txt?rev=1527266&r1=1527265&r2=1527266&view=diff
==============================================================================
--- hama/trunk/CHANGES.txt (original)
+++ hama/trunk/CHANGES.txt Sun Sep 29 03:04:05 2013
@@ -3,6 +3,7 @@ Hama Change Log
 Release 0.6.3 (unreleased changes)
 
   NEW FEATURES
+  
    HAMA-804: Create NeuralNetwork Example (Yexi Jiang)
    HAMA-795: Implement Autoencoder based on NeuralNetwork (Yexi Jiang)
    HAMA-767: Add vertex addition/removal APIs (Anastasis Andronidis via edwardyoon)
@@ -24,6 +25,7 @@ Release 0.6.3 (unreleased changes)
 
   IMPROVEMENTS
 
+   HAMA-806: Make the description of NeuralNetwork example more clear (Yexi Jiang)
    HAMA-749: Build for C++ Pipes (Martin Illecker)
    HAMA-796: Add Vector multiply Matrix for DoubleVector as well as DenseDoubleVector. (Yexi
Jiang)
    HAMA-770: Use a unified model to represent linear regression, logistic regression, MLP,
autoencoder, and deepNets (Yexi Jiang)

Modified: hama/trunk/examples/src/main/java/org/apache/hama/examples/NeuralNetwork.java
URL: http://svn.apache.org/viewvc/hama/trunk/examples/src/main/java/org/apache/hama/examples/NeuralNetwork.java?rev=1527266&r1=1527265&r2=1527266&view=diff
==============================================================================
--- hama/trunk/examples/src/main/java/org/apache/hama/examples/NeuralNetwork.java (original)
+++ hama/trunk/examples/src/main/java/org/apache/hama/examples/NeuralNetwork.java Sun Sep
29 03:04:05 2013
@@ -34,7 +34,8 @@ import org.apache.hama.ml.math.DoubleVec
 import org.apache.hama.ml.math.FunctionFactory;
 
 /**
- * 
+ * The example of using {@link SmallLayeredNeuralNetwork}, including the
+ * training phase and labeling phase.
  */
 public class NeuralNetwork {
 
@@ -50,9 +51,9 @@ public class NeuralNetwork {
         return;
       }
 
-      String modelPath = args[1];
-      String featureDataPath = args[2];
-      String resultDataPath = args[3];
+      String featureDataPath = args[1];
+      String resultDataPath = args[2];
+      String modelPath = args[3];
 
       SmallLayeredNeuralNetwork ann = new SmallLayeredNeuralNetwork(modelPath);
 
@@ -187,14 +188,14 @@ public class NeuralNetwork {
     System.out
         .println("\tMODE\t- train: train the model with given training data.");
     System.out
-        .println("\t\t- evaluate: obtain the result by feeding the features to the neural
network.");
+        .println("\t\t- label: obtain the result by feeding the features to the neural network.");
     System.out
-        .println("\tINPUT_PATH\tin 'train' mode, it is the path of the training data; in
'evaluate' mode, it is the path of the to be evaluated data that lacks the label.");
+        .println("\tINPUT_PATH\tin 'train' mode, it is the path of the training data; in
'label' mode, it is the path of the to be evaluated data that lacks the label.");
     System.out
-        .println("\tOUTPUT_PATH\tin 'train' mode, it is where the trained model is stored;
in 'evaluate' mode, it is where the labeled data is stored.");
+        .println("\tOUTPUT_PATH\tin 'train' mode, it is where the trained model is stored;
in 'label' mode, it is where the labeled data is stored.");
     System.out.println("\n\tConditional Parameters:");
     System.out
-        .println("\tMODEL_PATH\tonly required in 'evaluate' mode. It specifies where to load
the trained neural network model.");
+        .println("\tMODEL_PATH\tonly required in 'label' mode. It specifies where to load
the trained neural network model.");
     System.out
         .println("\tMAX_ITERATION\tonly used in 'train' mode. It specifies how many iterations
for the neural network to run. Default is 0.01.");
     System.out
@@ -205,9 +206,9 @@ public class NeuralNetwork {
         .println("\tREGULARIZATION_WEIGHT\tonly required in 'train' model. It specifies the
weight of reqularization.");
     System.out.println("\nExample:");
     System.out
-        .println("Train a neural network with default setting:\n\tneuralnets train hdfs://localhost:30002/training_data
hdfs://localhost:30002/model 8 1");
+        .println("Train a neural network with with feature dimension 8, label dimension 1
and default setting:\n\tneuralnets train hdfs://localhost:30002/training_data hdfs://localhost:30002/model
8 1");
     System.out
-        .println("Train a neural network by specify learning rate as 0.1, momemtum rate as
0.2, and regularization weight as 0.01:\n\tneuralnets.train hdfs://localhost:30002/training_data
hdfs://localhost:30002/model 0.1 0.2 0.01");
+        .println("Train a neural network with with feature dimension 8, label dimension 1
and specify learning rate as 0.1, momemtum rate as 0.2, and regularization weight as 0.01:\n\tneuralnets.train
hdfs://localhost:30002/training_data hdfs://localhost:30002/model 8 1 0.1 0.2 0.01");
     System.out
         .println("Label the data with trained model:\n\tneuralnets evaluate hdfs://localhost:30002/unlabeled_data
hdfs://localhost:30002/result hdfs://localhost:30002/model");
   }

Modified: hama/trunk/examples/src/test/java/org/apache/hama/examples/NeuralNetworkTest.java
URL: http://svn.apache.org/viewvc/hama/trunk/examples/src/test/java/org/apache/hama/examples/NeuralNetworkTest.java?rev=1527266&r1=1527265&r2=1527266&view=diff
==============================================================================
--- hama/trunk/examples/src/test/java/org/apache/hama/examples/NeuralNetworkTest.java (original)
+++ hama/trunk/examples/src/test/java/org/apache/hama/examples/NeuralNetworkTest.java Sun
Sep 29 03:04:05 2013
@@ -58,7 +58,7 @@ public class NeuralNetworkTest extends T
     String mode = "label";
     try {
       NeuralNetwork
-          .main(new String[] { mode, MODEL_PATH, dataPath, RESULT_PATH });
+          .main(new String[] { mode, dataPath, RESULT_PATH, MODEL_PATH });
 
       // compare results with ground-truth
       BufferedReader groundTruthReader = new BufferedReader(new FileReader(



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