NN fixes and todos

Author: cypof

.gitignore

@@ -31,3 +31,4 @@ h2o-samples/h2o-samples.iml
 src/main/java/water/BuildVersion.java
 hadoop/build.log
 .DS_Store
+/.idea

h2o-samples/src/main/java/samples/CloudRemote.java

@@ -14,7 +14,8 @@
  */
 public class CloudRemote {
   public static void main(String[] args) throws Exception {
-    launchEC2(null);
+    // launchEC2(null);
+    launchIPs(null);
   }
 
   /**

h2o-samples/src/main/java/samples/NeuralNetMnist.java

@@ -45,7 +45,7 @@ Layer[] build(Vec[] data, Vec labels, VecsInput inputStats, VecSoftmax outputSta
     ls[2].rate = .02f;
     for( int i = 0; i < ls.length; i++ ) {
       ls[i].l2 = .0001f;
-      ls[i].rateAnnealing = 1 / 2e6f;
+      ls[i].rate_annealing = 1 / 2e6f;
       ls[i].init(ls, i);
     }
     return ls;
@@ -86,12 +86,12 @@ Trainer startTraining(Layer[] ls) {
 
       // Build separate nets for scoring purposes, use same normalization stats as for training
       Layer[] temp = build(train, trainLabels, (VecsInput) ls[0], (VecSoftmax) ls[ls.length - 1]);
-      Layer.copyWeights(ls, temp);
+      Layer.shareWeights(ls, temp);
       Error error = NeuralNet.eval(temp, NeuralNet.EVAL_ROW_COUNT, null);
       text += "train: " + error;
 
       temp = build(test, testLabels, (VecsInput) ls[0], (VecSoftmax) ls[ls.length - 1]);
-      Layer.copyWeights(ls, temp);
+      Layer.shareWeights(ls, temp);
       error = NeuralNet.eval(temp, NeuralNet.EVAL_ROW_COUNT, null);
       text += ", test: " + error;
       text += ", rates: ";

h2o-samples/src/main/java/samples/NeuralNetMnistDeep.java

@@ -12,10 +12,10 @@
  */
 public class NeuralNetMnistDeep extends NeuralNetMnist {
   public static void main(String[] args) throws Exception {
-    // CloudLocal.launch(1, NeuralNetMnistDeep.class);
+    CloudLocal.launch(1, NeuralNetMnistDeep.class);
     // CloudProcess.launch(4, NeuralNetMnistDeep.class);
     // CloudConnect.launch("localhost:54321", NeuralNetMnistDeep.class);
-    CloudRemote.launchIPs(NeuralNetMnistDeep.class);
+    // CloudRemote.launchIPs(NeuralNetMnistDeep.class);
   }
 
   @Override public Layer[] build(Vec[] data, Vec labels, VecsInput inputStats, VecSoftmax outputStats) {
@@ -29,7 +29,7 @@ public static void main(String[] args) throws Exception {
     ls[ls.length - 1].rate = .02f;
     for( int i = 0; i < ls.length; i++ ) {
       ls[i].l2 = .0001f;
-      ls[i].rateAnnealing = 1 / 1e5f;
+      ls[i].rate_annealing = 1 / 1e5f;
       ls[i].init(ls, i);
     }
     return ls;

h2o-samples/src/main/java/samples/WebAPI.java

@@ -1,19 +1,37 @@
 package samples;
 
-import java.io.InputStreamReader;
+import java.io.*;
 
 import org.apache.commons.httpclient.HttpClient;
 import org.apache.commons.httpclient.methods.GetMethod;
+import org.apache.commons.httpclient.methods.PostMethod;
+import org.apache.commons.httpclient.methods.multipart.*;
 
-import com.google.gson.Gson;
+import water.util.Utils;
+
+import com.google.gson.*;
+import com.google.gson.internal.Streams;
+import com.google.gson.stream.JsonWriter;
 
 /**
- * Invokes an H2O functionality through the Web API.
+ * Invokes H2O functionality through the Web API.
  */
 public class WebAPI {
+  static final String URL = "http://127.0.0.1:54321";
+  static final File JSON_FILE = new File(Utils.tmp(), "model.json");
+
   public static void main(String[] args) throws Exception {
+    listJobs();
+    exportModel();
+    importModel();
+  }
+
+  /**
+   * Lists jobs currently running.
+   */
+  static void listJobs() throws Exception {
     HttpClient client = new HttpClient();
-    GetMethod get = new GetMethod("http://127.0.0.1:54321/Jobs.json");
+    GetMethod get = new GetMethod(URL + "/Jobs.json");
     int status = client.executeMethod(get);
     if( status != 200 )
       throw new Exception(get.getStatusText());
@@ -36,4 +54,46 @@ public static class Job {
     String end_time;
     String exception;
   }
+
+  /**
+   * Exports a model to a JSON file.
+   */
+  static void exportModel() throws Exception {
+    HttpClient client = new HttpClient();
+    GetMethod get = new GetMethod(URL + "/2/ExportModel.json?model=MyInitialNeuralNet");
+    int status = client.executeMethod(get);
+    if( status != 200 )
+      throw new Exception(get.getStatusText());
+    JsonObject response = (JsonObject) new JsonParser().parse(new InputStreamReader(get.getResponseBodyAsStream()));
+    JsonElement model = response.get("model");
+    JsonWriter writer = new JsonWriter(new FileWriter(JSON_FILE));
+    writer.setLenient(true);
+    writer.setIndent("  ");
+    Streams.write(model, writer);
+    writer.close();
+    get.releaseConnection();
+  }
+
+  /**
+   * Imports a model from a JSON file.
+   */
+  public static void importModel() throws Exception {
+    // Upload file to H2O
+    HttpClient client = new HttpClient();
+    PostMethod post = new PostMethod(URL + "/Upload.json?key=" + JSON_FILE.getName());
+    Part[] parts = { new FilePart(JSON_FILE.getName(), JSON_FILE) };
+    post.setRequestEntity(new MultipartRequestEntity(parts, post.getParams()));
+    if( 200 != client.executeMethod(post) )
+      throw new RuntimeException("Request failed: " + post.getStatusLine());
+    post.releaseConnection();
+
+    // Parse the key into a model
+    GetMethod get = new GetMethod(URL + "/2/ImportModel.json?" //
+        + "destination_key=MyImportedNeuralNet&" //
+        + "type=NeuralNetModel&" //
+        + "json=" + JSON_FILE.getName());
+    if( 200 != client.executeMethod(get) )
+      throw new RuntimeException("Request failed: " + get.getStatusLine());
+    get.releaseConnection();
+  }
 }

src/main/java/hex/KMeans2.java

@@ -146,7 +146,7 @@ public static class KMeans2Progress extends Progress2 {
     static public DocGen.FieldDoc[] DOC_FIELDS;
 
     @Override protected Response jobDone(Job job, Key dst) {
-      return new Response(Response.Status.redirect, this, 0, 0, new KMeans2ModelView().href(), "model", destination_key);
+      return new Response(Response.Status.redirect, this, 0, 0, new KMeans2ModelView().href(), "destination_key", destination_key);
     }
   }