Adding Deeplearning4j UI to the sample

Author: fbrunacci

samples/DeepLearning4j-Cuda.ipynb

@@ -44,7 +44,7 @@
     "val outputNum = 10 // number of output classes\n",
     "val batchSize = 64 // batch size for each epoch\n",
     "val rngSeed = 123 // random number seed for reproducibility\n",
-    "val numEpochs = 15 // number of epochs to perform\n",
+    "val numEpochs = 5 // number of epochs to perform\n",
     "val rate = 0.0015 // learning rate"
    ]
   },
@@ -124,7 +124,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Train model"
+    "### Launching Deeplearning4j UI"
    ]
   },
   {
@@ -133,9 +133,39 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "import org.deeplearning4j.ui.api.UIServer\n",
     "import org.deeplearning4j.optimize.listeners.ScoreIterationListener\n",
+    "import org.deeplearning4j.api.storage.StatsStorageRouter\n",
+    "import org.deeplearning4j.api.storage.impl.RemoteUIStatsStorageRouter\n",
+    "import org.deeplearning4j.ui.stats.StatsListener\n",
     "\n",
-    "model.setListeners(ScoreIterationListener(100))\n",
+    "val uiServer: UIServer = UIServer.getInstance()\n",
+    "uiServer.enableRemoteListener()\n",
+    "//Create the remote stats storage router - this sends the results to the UI via HTTP, assuming the UI is at http://localhost:9000\n",
+    "val remoteUIRouter: StatsStorageRouter = RemoteUIStatsStorageRouter(\"http://localhost:9000\")\n",
+    "model.setListeners(ScoreIterationListener(100), StatsListener(remoteUIRouter))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "open a new tab in your browser and go to [http://localhost:9000](http://localhost:9000)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Train model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "model.fit(mnistTrain, numEpochs)"
    ]
   },
@@ -148,7 +178,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -159,26 +189,26 @@
       "\n",
       "========================Evaluation Metrics========================\n",
       " # of classes:    10\n",
-      " Accuracy:        0,9820\n",
-      " Precision:       0,9819\n",
-      " Recall:          0,9818\n",
-      " F1 Score:        0,9819\n",
+      " Accuracy:        0,9718\n",
+      " Precision:       0,9722\n",
+      " Recall:          0,9711\n",
+      " F1 Score:        0,9714\n",
       "Precision, recall & F1: macro-averaged (equally weighted avg. of 10 classes)\n",
       "\n",
       "\n",
       "=========================Confusion Matrix=========================\n",
       "    0    1    2    3    4    5    6    7    8    9\n",
       "---------------------------------------------------\n",
-      "  969    0    0    0    1    1    3    1    3    2 | 0 = 0\n",
-      "    0 1128    1    1    0    1    2    1    1    0 | 1 = 1\n",
-      "    2    1 1014    2    3    0    1    3    6    0 | 2 = 2\n",
-      "    1    0    4  992    0    2    0    2    3    6 | 3 = 3\n",
-      "    1    0    2    0  964    0    3    3    0    9 | 4 = 4\n",
-      "    2    0    0    7    1  872    4    1    3    2 | 5 = 5\n",
-      "    4    2    1    1    2    5  942    0    1    0 | 6 = 6\n",
-      "    0    6    7    2    0    0    0 1005    4    4 | 7 = 7\n",
-      "    4    0    1    5    2    3    3    2  952    2 | 8 = 8\n",
-      "    2    2    1    5    9    1    1    3    3  982 | 9 = 9\n",
+      "  967    0    0    1    1    0    4    2    2    3 | 0 = 0\n",
+      "    0 1123    2    1    0    0    5    1    3    0 | 1 = 1\n",
+      "    4    3  995    0    2    0    4   14   10    0 | 2 = 2\n",
+      "    0    1    2  988    0    1    0   10    6    2 | 3 = 3\n",
+      "    3    0    0    0  956    0    6    4    0   13 | 4 = 4\n",
+      "    7    1    0   19    2  825   20    1   11    6 | 5 = 5\n",
+      "    6    3    0    0    4    1  943    1    0    0 | 6 = 6\n",
+      "    0    8    5    2    0    0    0 1010    1    2 | 7 = 7\n",
+      "    5    0    2    6    4    1    8    7  937    4 | 8 = 8\n",
+      "    3    6    1    6   10    0    2    6    1  974 | 9 = 9\n",
       "\n",
       "Confusion matrix format: Actual (rowClass) predicted as (columnClass) N times\n",
       "==================================================================\n"
@@ -189,6 +219,22 @@
     "val eval: org.nd4j.evaluation.classification.Evaluation = model.evaluate(mnistTest)\n",
     "println(eval.stats())"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To stop the UI:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "uiServer.stop()"
+   ]
   }
  ],
  "metadata": {
@@ -203,7 +249,7 @@
    "mimetype": "text/x-kotlin",
    "name": "kotlin",
    "pygments_lexer": "kotlin",
-   "version": "1.3.70-eap-274"
+   "version": "1.4.0-dev-7568"
   }
  },
  "nbformat": 4,