diff --git a/deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/nn/graph/TestComputationGraphNetwork.java b/deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/nn/graph/TestComputationGraphNetwork.java
index 743e16710..b0cc17376 100644
--- a/deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/nn/graph/TestComputationGraphNetwork.java
+++ b/deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/nn/graph/TestComputationGraphNetwork.java
@@ -57,10 +57,8 @@ import org.deeplearning4j.nn.weights.WeightInit;
 import org.deeplearning4j.nn.workspace.LayerWorkspaceMgr;
 import org.deeplearning4j.optimize.listeners.ScoreIterationListener;
 import org.deeplearning4j.util.ModelSerializer;
-import org.junit.AfterClass;
-import org.junit.Before;
-import org.junit.BeforeClass;
-import org.junit.Test;
+import org.junit.*;
+import org.junit.rules.TemporaryFolder;
 import org.nd4j.linalg.activations.Activation;
 import org.nd4j.linalg.activations.impl.ActivationIdentity;
 import org.nd4j.linalg.api.buffer.DataType;
@@ -82,6 +80,7 @@ import org.nd4j.common.resources.Resources;
 
 import java.io.ByteArrayInputStream;
 import java.io.ByteArrayOutputStream;
+import java.io.File;
 import java.io.IOException;
 import java.util.*;
 
@@ -91,6 +90,9 @@ import static org.junit.Assert.*;
 @Slf4j
 public class TestComputationGraphNetwork extends BaseDL4JTest {
 
+    @Rule
+    public TemporaryFolder testDir = new TemporaryFolder();
+
     private static ComputationGraphConfiguration getIrisGraphConfiguration() {
         return new NeuralNetConfiguration.Builder().seed(12345)
                 .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT).graphBuilder()
@@ -2177,4 +2179,40 @@ public class TestComputationGraphNetwork extends BaseDL4JTest {
         INDArray label = Nd4j.createFromArray(1, 0).reshape(1, 2);
         cg.fit(new DataSet(in, label));
     }
+
+    @Test
+    public void testMergeNchw() throws Exception {
+        ComputationGraphConfiguration conf = new NeuralNetConfiguration.Builder()
+                .convolutionMode(ConvolutionMode.Same)
+                .graphBuilder()
+                .addInputs("in")
+                .layer("l0", new ConvolutionLayer.Builder()
+                        .nOut(16)
+                        .kernelSize(2,2).stride(1,1)
+                        .build(), "in")
+                .layer("l1", new ConvolutionLayer.Builder()
+                        .nOut(8)
+                        .kernelSize(2,2).stride(1,1)
+                        .build(), "in")
+                .addVertex("merge", new MergeVertex(), "l0", "l1")
+                .layer("out", new CnnLossLayer.Builder().activation(Activation.TANH).lossFunction(LossFunctions.LossFunction.MSE).build(), "merge")
+                .setOutputs("out")
+                .setInputTypes(InputType.convolutional(32, 32, 3, CNN2DFormat.NHWC))
+                .build();
+
+        ComputationGraph cg = new ComputationGraph(conf);
+        cg.init();
+
+        INDArray[] in = new INDArray[]{Nd4j.rand(DataType.FLOAT, 1, 32, 32, 3)};
+        INDArray out = cg.outputSingle(in);
+
+        File dir = testDir.newFolder();
+        File f = new File(dir, "net.zip");
+        cg.save(f);
+
+        ComputationGraph c2 = ComputationGraph.load(f, true);
+        INDArray out2 = c2.outputSingle(in);
+
+        assertEquals(out, out2);
+    }
 }
diff --git a/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/conf/dropout/Dropout.java b/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/conf/dropout/Dropout.java
index 46a872fd8..acb6afa2c 100644
--- a/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/conf/dropout/Dropout.java
+++ b/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/conf/dropout/Dropout.java
@@ -66,8 +66,8 @@ import org.nd4j.shade.jackson.annotation.JsonProperty;
  * @author Alex Black
  */
 @Data
-@JsonIgnoreProperties({"mask", "helper", "helperCountFail"})
-@EqualsAndHashCode(exclude = {"mask", "helper", "helperCountFail"})
+@JsonIgnoreProperties({"mask", "helper", "helperCountFail", "initializedHelper"})
+@EqualsAndHashCode(exclude = {"mask", "helper", "helperCountFail", "initializedHelper"})
 @Slf4j
 public class Dropout implements IDropout {
 
diff --git a/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/conf/graph/MergeVertex.java b/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/conf/graph/MergeVertex.java
index 726a68403..c7a4fec63 100644
--- a/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/conf/graph/MergeVertex.java
+++ b/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/conf/graph/MergeVertex.java
@@ -17,6 +17,7 @@
 package org.deeplearning4j.nn.conf.graph;
 
 
+import lombok.Data;
 import lombok.val;
 import org.deeplearning4j.nn.conf.CNN2DFormat;
 import org.deeplearning4j.nn.conf.RNNFormat;
@@ -38,6 +39,7 @@ import org.nd4j.linalg.api.ndarray.INDArray;
  *      -> [numExamples,depth1 + depth2,width,height]}<br>
  * @author Alex Black
  */
+@Data
 public class MergeVertex extends GraphVertex {
 
     protected int mergeAxis = 1;       //default value for backward compatibility (deserialization of old version JSON) - NCHW and NCW format