samediff/training.

Signed-off-by: Robert Altena <[email protected]>

Author: RobAltena

dl4j-examples/src/main/java/org/deeplearning4j/examples/samediff/training/SameDiffCustomListenerExample.java

@@ -1,33 +1,21 @@
 package org.deeplearning4j.examples.samediff.training;
 
-import static org.deeplearning4j.examples.samediff.training.SameDiffMNISTTrainingExample.makeMNISTNet;
-
-import java.util.Arrays;
-import java.util.List;
 import org.deeplearning4j.datasets.iterator.impl.MnistDataSetIterator;
 import org.deeplearning4j.examples.samediff.tfimport.SameDiffTransferLearningExample;
-import org.nd4j.autodiff.listeners.At;
-import org.nd4j.autodiff.listeners.BaseEvaluationListener;
-import org.nd4j.autodiff.listeners.BaseListener;
-import org.nd4j.autodiff.listeners.Listener;
-import org.nd4j.autodiff.listeners.ListenerVariables;
-import org.nd4j.autodiff.listeners.Operation;
-import org.nd4j.autodiff.listeners.impl.ScoreListener;
+import org.nd4j.autodiff.listeners.*;
 import org.nd4j.autodiff.listeners.records.History;
-import org.nd4j.autodiff.samediff.SDVariable;
 import org.nd4j.autodiff.samediff.SameDiff;
 import org.nd4j.autodiff.samediff.TrainingConfig;
 import org.nd4j.autodiff.samediff.internal.SameDiffOp;
-import org.nd4j.evaluation.classification.Evaluation;
 import org.nd4j.evaluation.classification.Evaluation.Metric;
-import org.nd4j.linalg.api.buffer.DataType;
 import org.nd4j.linalg.api.ndarray.INDArray;
-import org.nd4j.linalg.api.ops.impl.layers.convolution.config.Conv2DConfig;
-import org.nd4j.linalg.api.ops.impl.layers.convolution.config.Pooling2DConfig;
 import org.nd4j.linalg.dataset.api.MultiDataSet;
 import org.nd4j.linalg.dataset.api.iterator.DataSetIterator;
 import org.nd4j.linalg.learning.config.Adam;
-import org.nd4j.weightinit.impl.XavierInitScheme;
+
+import java.util.List;
+
+import static org.deeplearning4j.examples.samediff.training.SameDiffMNISTTrainingExample.makeMNISTNet;
 
 /**
  * This example shows how to use a custom listener, and is based on the {@link SameDiffMNISTTrainingExample}.<br><br>
@@ -40,6 +28,7 @@
  * If you want to use evaluations in your listener, look at {@link BaseEvaluationListener}.
  *
  */
+@SuppressWarnings("DuplicatedCode")
 public class SameDiffCustomListenerExample {
 
     public static void main(String[] args) throws Exception {
@@ -84,7 +73,7 @@ public static void main(String[] args) throws Exception {
      */
     public static class CustomListener extends BaseListener {
 
-        public INDArray z;
+        INDArray z;
         public INDArray out;
 
         // Specify that this listener is active during inference operations

dl4j-examples/src/main/java/org/deeplearning4j/examples/samediff/training/SameDiffMNISTTrainingExample.java

@@ -1,10 +1,6 @@
 package org.deeplearning4j.examples.samediff.training;
 
-import java.util.Arrays;
-import java.util.List;
 import org.deeplearning4j.datasets.iterator.impl.MnistDataSetIterator;
-import org.nd4j.autodiff.listeners.ListenerEvaluations;
-import org.nd4j.autodiff.listeners.impl.HistoryListener;
 import org.nd4j.autodiff.listeners.impl.ScoreListener;
 import org.nd4j.autodiff.listeners.records.History;
 import org.nd4j.autodiff.samediff.SDVariable;
@@ -17,15 +13,16 @@
 import org.nd4j.linalg.api.ops.impl.layers.convolution.config.Pooling2DConfig;
 import org.nd4j.linalg.dataset.api.iterator.DataSetIterator;
 import org.nd4j.linalg.learning.config.Adam;
-import org.nd4j.weightinit.impl.OneInitScheme;
 import org.nd4j.weightinit.impl.XavierInitScheme;
 
+import java.util.List;
+
 /**
  * This example shows the creation and training of a MNIST CNN network.
  */
 public class SameDiffMNISTTrainingExample {
 
-    public static SameDiff makeMNISTNet(){
+    static SameDiff makeMNISTNet(){
         SameDiff sd = SameDiff.create();
 
         //Properties for MNIST dataset:
@@ -75,6 +72,7 @@ public static SameDiff makeMNISTNet(){
         // softmax crossentropy loss function
         SDVariable loss = sd.loss().softmaxCrossEntropy("loss", label, z);
 
+        //noinspection unused
         SDVariable out = sd.nn().softmax("out", z, 1);
 
         sd.setLossVariables(loss);

dl4j-examples/src/main/java/org/deeplearning4j/examples/samediff/training/SameDiffTrainingExample.java

@@ -1,4 +1,4 @@
-/*******************************************************************************
+/* *****************************************************************************
  * Copyright (c) 2015-2019 Skymind, Inc.
  *
  * This program and the accompanying materials are made available under the
@@ -39,6 +39,7 @@
  *
  * @author Alex Black
  */
+@SuppressWarnings("DuplicatedCode")
 public class SameDiffTrainingExample {
 
     public static void main(String[] args) throws Exception {