Undo push
diff --git a/CHANGES.txt b/CHANGES.txt
deleted file mode 100644
index 0826b90..0000000
--- a/CHANGES.txt
+++ /dev/null
@@ -1,11 +0,0 @@
-Horn Change Log
-
-Release 0.1.0 (unreleased changes)
-
- NEW FEATURES
-
- HORN-1: Website for Apache Horn (Incubating) (Elmurod Talipov via edwardyoon)
-
- BUG FIXES
-
- IMPROVEMENTS
diff --git a/src/main/java/org/apache/horn/distbelief/DistBeliefModelTrainer.java b/src/main/java/org/apache/horn/distbelief/DistBeliefModelTrainer.java
deleted file mode 100644
index c7326ab..0000000
--- a/src/main/java/org/apache/horn/distbelief/DistBeliefModelTrainer.java
+++ /dev/null
@@ -1,87 +0,0 @@
-package org.apache.horn.distbelief;
-
-import java.io.IOException;
-
-import org.apache.hama.bsp.BSP;
-import org.apache.hama.bsp.BSPPeer;
-import org.apache.hama.bsp.sync.SyncException;
-
-/**
- * This DistBeliefModelTrainer performs each SGD.
- */
-public class DistBeliefModelTrainer extends BSP {
-
- private boolean isConverge = false;
- private int iterations;
- private int maxIterations;
-
- @Override
- public final void setup(BSPPeer peer) {
- // loads subset of neural network model replica into memory
- }
-
- @Override
- public void bsp(BSPPeer peer) throws IOException, SyncException,
- InterruptedException {
-
- // Iterate until reach max iteration or convergence
- while (this.iterations++ < maxIterations) {
-
- // Fetch latest parameters
- fetchParameters(peer);
-
- // Perform mini-batch
- doMinibatch(peer);
-
- // Push parameters
- pushParameters(peer);
-
- if (this.isConverge) {
- break;
- }
- }
-
- }
-
- /**
- * Performs the mini-batch
- * @param peer
- */
- private void doMinibatch(BSPPeer peer) {
- double avgTrainingError = 0.0;
- // 1. loads a next set of mini-batch instances from assigned splits into memory
-
- // 2. train incrementally from a mini-batch of instances
- /*
- for (Instance trainingInstance : MiniBatchSet) {
-
- // 2.1 upward propagation (start from the input layer)
- for (Neuron neuron : neurons) {
- neuron.upward(msg);
- sync();
- }
-
- // 2.2 calculate total error
- sync();
-
- // 2.3 downward propagation (start from the total error)
- for (Neuron neuron : neurons) {
- neuron.downward(msg);
- sync();
- }
-
- }
- // calculate the the average training error
- */
-
- }
-
- private void fetchParameters(BSPPeer peer) {
- // TODO fetch latest weights from the parameter server
- }
-
- private void pushParameters(BSPPeer peer) {
- // TODO push updated weights
- }
-
-}
diff --git a/src/main/java/org/apache/horn/distbelief/Neuron.java b/src/main/java/org/apache/horn/distbelief/Neuron.java
deleted file mode 100644
index fadb522..0000000
--- a/src/main/java/org/apache/horn/distbelief/Neuron.java
+++ /dev/null
@@ -1,47 +0,0 @@
-/**
- * Licensed to the Apache Software Foundation (ASF) under one
- * or more contributor license agreements. See the NOTICE file
- * distributed with this work for additional information
- * regarding copyright ownership. The ASF licenses this file
- * to you under the Apache License, Version 2.0 (the
- * "License"); you may not use this file except in compliance
- * with the License. You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-package org.apache.horn.distbelief;
-
-import org.apache.hadoop.io.Writable;
-
-public abstract class Neuron<M extends Writable> implements NeuronInterface<M> {
- double output;
- double weight;
-
- public void propagate(double gradient) {
- // TODO Auto-generated method stub
- }
-
- public void setOutput(double output) {
- this.output = output;
- }
-
- public double getOutput() {
- return output;
- }
-
- public void push(double weight) {
- // TODO Auto-generated method stub
- this.weight = weight;
- }
-
- public double getUpdate() {
- return weight;
- }
-
-}
diff --git a/src/main/java/org/apache/horn/distbelief/NeuronInterface.java b/src/main/java/org/apache/horn/distbelief/NeuronInterface.java
deleted file mode 100644
index 8093b07..0000000
--- a/src/main/java/org/apache/horn/distbelief/NeuronInterface.java
+++ /dev/null
@@ -1,45 +0,0 @@
-/**
- * Licensed to the Apache Software Foundation (ASF) under one
- * or more contributor license agreements. See the NOTICE file
- * distributed with this work for additional information
- * regarding copyright ownership. The ASF licenses this file
- * to you under the Apache License, Version 2.0 (the
- * "License"); you may not use this file except in compliance
- * with the License. You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-package org.apache.horn.distbelief;
-
-import java.io.IOException;
-
-import org.apache.hadoop.io.Writable;
-
-public interface NeuronInterface<M extends Writable> {
-
- /**
- * This method is called when the messages are propagated from the lower
- * layer. It can be used to determine if the neuron would activate, or fire.
- *
- * @param messages
- * @throws IOException
- */
- public void upward(Iterable<M> messages) throws IOException;
-
- /**
- * This method is called when the errors are propagated from the upper layer.
- * It can be used to calculate the error of each neuron and change the
- * weights.
- *
- * @param messages
- * @throws IOException
- */
- public void downward(Iterable<M> messages) throws IOException;
-
-}
diff --git a/src/main/java/org/apache/horn/distbelief/PropMessage.java b/src/main/java/org/apache/horn/distbelief/PropMessage.java
deleted file mode 100644
index 029cd6a..0000000
--- a/src/main/java/org/apache/horn/distbelief/PropMessage.java
+++ /dev/null
@@ -1,63 +0,0 @@
-/**
- * Licensed to the Apache Software Foundation (ASF) under one
- * or more contributor license agreements. See the NOTICE file
- * distributed with this work for additional information
- * regarding copyright ownership. The ASF licenses this file
- * to you under the Apache License, Version 2.0 (the
- * "License"); you may not use this file except in compliance
- * with the License. You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-package org.apache.horn.distbelief;
-
-import java.io.DataInput;
-import java.io.DataOutput;
-import java.io.IOException;
-
-import org.apache.hadoop.io.Writable;
-
-/**
- * Message wrapper for a propagating message
- */
-public class PropMessage<M extends Writable, W extends Writable> implements
- Writable {
-
- M message;
- W weight;
-
- public PropMessage(M message, W weight) {
- this.message = message;
- this.weight = weight;
- }
-
- /**
- * @return the activation or error message
- */
- public M getMessage() {
- return message;
- }
-
- public W getWeight() {
- return weight;
- }
-
- @Override
- public void readFields(DataInput in) throws IOException {
- message.readFields(in);
- weight.readFields(in);
- }
-
- @Override
- public void write(DataOutput out) throws IOException {
- message.write(out);
- weight.write(out);
- }
-
-}
diff --git a/src/test/java/org/apache/horn/distbelief/TestDistBeliefModelTrainer.java b/src/test/java/org/apache/horn/distbelief/TestDistBeliefModelTrainer.java
deleted file mode 100644
index 5bbd90c..0000000
--- a/src/test/java/org/apache/horn/distbelief/TestDistBeliefModelTrainer.java
+++ /dev/null
@@ -1,5 +0,0 @@
-package org.apache.horn.distbelief;
-
-public class TestDistBeliefModelTrainer {
-
-}
diff --git a/src/test/java/org/apache/horn/distbelief/TestNeuron.java b/src/test/java/org/apache/horn/distbelief/TestNeuron.java
deleted file mode 100644
index 9af1315..0000000
--- a/src/test/java/org/apache/horn/distbelief/TestNeuron.java
+++ /dev/null
@@ -1,90 +0,0 @@
-/**
- * Licensed to the Apache Software Foundation (ASF) under one
- * or more contributor license agreements. See the NOTICE file
- * distributed with this work for additional information
- * regarding copyright ownership. The ASF licenses this file
- * to you under the Apache License, Version 2.0 (the
- * "License"); you may not use this file except in compliance
- * with the License. You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-package org.apache.horn.distbelief;
-
-import java.io.IOException;
-import java.util.ArrayList;
-import java.util.List;
-
-import junit.framework.TestCase;
-
-import org.apache.hadoop.io.DoubleWritable;
-import org.apache.hama.commons.math.Sigmoid;
-
-public class TestNeuron extends TestCase {
- private static double learningRate = 0.1;
- private static double bias = -1;
- private static double theta = 0.8;
-
- public static class MyNeuron extends
- Neuron<PropMessage<DoubleWritable, DoubleWritable>> {
-
- @Override
- public void upward(
- Iterable<PropMessage<DoubleWritable, DoubleWritable>> messages)
- throws IOException {
- double sum = 0;
- for (PropMessage<DoubleWritable, DoubleWritable> m : messages) {
- sum += m.getMessage().get() * m.getWeight().get();
- }
- sum += (bias * theta);
-
- double output = new Sigmoid().apply(sum);
- this.setOutput(output);
- this.propagate(output);
- }
-
- @Override
- public void downward(
- Iterable<PropMessage<DoubleWritable, DoubleWritable>> messages)
- throws IOException {
- for (PropMessage<DoubleWritable, DoubleWritable> m : messages) {
- // Calculates error gradient for each neuron
- double gradient = this.getOutput() * (1 - this.getOutput())
- * m.getMessage().get() * m.getWeight().get();
-
- // Propagates to lower layer
- this.propagate(gradient);
-
- // Weight corrections
- double weight = learningRate * this.getOutput() * m.getMessage().get();
- this.push(weight);
- }
- }
-
- }
-
- public void testProp() throws IOException {
- List<PropMessage<DoubleWritable, DoubleWritable>> x = new ArrayList<PropMessage<DoubleWritable, DoubleWritable>>();
- x.add(new PropMessage<DoubleWritable, DoubleWritable>(new DoubleWritable(
- 1.0), new DoubleWritable(0.5)));
- x.add(new PropMessage<DoubleWritable, DoubleWritable>(new DoubleWritable(
- 1.0), new DoubleWritable(0.4)));
-
- MyNeuron n = new MyNeuron();
- n.upward(x);
- assertEquals(0.5249791874789399, n.getOutput());
-
- x.clear();
- x.add(new PropMessage<DoubleWritable, DoubleWritable>(new DoubleWritable(
- -0.1274), new DoubleWritable(-1.2)));
- n.downward(x);
- assertEquals(-0.006688234848481696, n.getUpdate());
- }
-
-}
