Fix PlayUIServer.detach() to allow sequential attach-detach of StatsS…

…torage (#6950) * Fix PlayUIServer.detach(), add test for sequentially attaching and detaching StatsStorage * fix missing ND4J backend for TestPlayUI * remove unused imports
deeplearning4j · Jan 8, 2019 · fdc5f7e · fdc5f7e
1 parent b34bba2
commit fdc5f7e
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Showing 4 changed files with 63 additions and 5 deletions.
diff --git a/deeplearning4j/deeplearning4j-ui-parent/deeplearning4j-play/pom.xml b/deeplearning4j/deeplearning4j-ui-parent/deeplearning4j-play/pom.xml
@@ -299,6 +299,13 @@
             <artifactId>logback-classic</artifactId>    <!-- Version set by deeplearning4j-parent dependency management -->
             <scope>test</scope>
         </dependency>
+
+        <dependency>
+            <groupId>org.nd4j</groupId>
+            <artifactId>nd4j-native</artifactId>
+            <version>${project.version}</version>
+            <scope>test</scope>
+        </dependency>
     </dependencies>
 
 

diff --git a/...ent/deeplearning4j-play/src/main/java/org/deeplearning4j/ui/module/train/TrainModule.java b/...ent/deeplearning4j-play/src/main/java/org/deeplearning4j/ui/module/train/TrainModule.java
@@ -184,6 +184,10 @@ public void onDetach(StatsStorage statsStorage) {
         for (String s : knownSessionIDs.keySet()) {
             if (knownSessionIDs.get(s) == statsStorage) {
                 knownSessionIDs.remove(s);
+                workerIdxCount.remove(s);
+                workerIdxToName.remove(s);
+                currentSessionID = null;
+                getDefaultSession();
             }
         }
     }

diff --git a/...-ui-parent/deeplearning4j-play/src/main/java/org/deeplearning4j/ui/play/PlayUIServer.java b/...-ui-parent/deeplearning4j-play/src/main/java/org/deeplearning4j/ui/play/PlayUIServer.java
@@ -326,6 +326,7 @@ public synchronized void detach(StatsStorage statsStorage) {
             Pair<StatsStorage, StatsStorageListener> p = iterator.next();
             if (p.getFirst() == statsStorage) { //Same object, not equality
                 statsStorage.deregisterStatsStorageListener(p.getSecond());
+                listeners.remove(p);
                 found = true;
             }
         }

diff --git a/...4j-ui-parent/deeplearning4j-play/src/test/java/org/deeplearning4j/ui/play/TestPlayUI.java b/...4j-ui-parent/deeplearning4j-play/src/test/java/org/deeplearning4j/ui/play/TestPlayUI.java
@@ -148,11 +148,11 @@ public void testUIMultipleSessions() throws Exception {
             uiServer.attach(ss);
 
             MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder()
-                            .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT).list()
-                            .layer(0, new DenseLayer.Builder().activation(Activation.TANH).nIn(4).nOut(4).build())
-                            .layer(1, new OutputLayer.Builder().lossFunction(LossFunctions.LossFunction.MCXENT)
-                                            .activation(Activation.SOFTMAX).nIn(4).nOut(3).build())
-                            .build();
+                    .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT).list()
+                    .layer(0, new DenseLayer.Builder().activation(Activation.TANH).nIn(4).nOut(4).build())
+                    .layer(1, new OutputLayer.Builder().lossFunction(LossFunctions.LossFunction.MCXENT)
+                            .activation(Activation.SOFTMAX).nIn(4).nOut(3).build())
+                    .build();
 
             MultiLayerNetwork net = new MultiLayerNetwork(conf);
             net.init();
@@ -167,6 +167,52 @@ public void testUIMultipleSessions() throws Exception {
         }
 
 
+        Thread.sleep(1000000);
+    }
+
+    @Test
+    @Ignore
+    public void testUISequentialSessions() throws Exception {
+        UIServer uiServer = UIServer.getInstance();
+        StatsStorage ss = null;
+        for (int session = 0; session < 3; session++) {
+
+            if (ss != null) {
+                uiServer.detach(ss);
+            }
+            ss = new InMemoryStatsStorage();
+            uiServer.attach(ss);
+
+            int numInputs = 4;
+            int outputNum = 3;
+            MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder()
+                .activation(Activation.TANH)
+                .weightInit(WeightInit.XAVIER)
+                .updater(new Sgd(0.03))
+                .l2(1e-4)
+                .list()
+                .layer(0, new DenseLayer.Builder().nIn(numInputs).nOut(3)
+                        .build())
+                .layer(1, new DenseLayer.Builder().nIn(3).nOut(3)
+                        .build())
+                .layer(2, new OutputLayer.Builder(LossFunctions.LossFunction.NEGATIVELOGLIKELIHOOD)
+                        .activation(Activation.SOFTMAX)
+                        .nIn(3).nOut(outputNum).build())
+                .build();
+
+            MultiLayerNetwork net = new MultiLayerNetwork(conf);
+            net.init();
+            net.setListeners(new StatsListener(ss), new ScoreIterationListener(1));
+
+            DataSetIterator iter = new IrisDataSetIterator(150, 150);
+
+            for (int i = 0; i < 1000; i++) {
+                net.fit(iter);
+            }
+            Thread.sleep(5000);
+        }
+
+
         Thread.sleep(1000000);
     }