Update shaded Jackson version to 2.10.1 (#82)

* Update shaded Jackson version to 2.10.1

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* Remove no longer needed scala compiler plugin from UI

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* Fix op name for BitwiseAnd op

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* TimeDistributedLayer mask array fix + test

Signed-off-by: AlexDBlack <blacka101@gmail.com>

deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/gradientcheck/RnnGradientChecks.java

@@ -21,12 +21,14 @@ import org.deeplearning4j.TestUtils;
 import org.deeplearning4j.nn.conf.MultiLayerConfiguration;
 import org.deeplearning4j.nn.conf.NeuralNetConfiguration;
 import org.deeplearning4j.nn.conf.inputs.InputType;
+import org.deeplearning4j.nn.conf.layers.DenseLayer;
 import org.deeplearning4j.nn.conf.layers.LSTM;
 import org.deeplearning4j.nn.conf.layers.OutputLayer;
 import org.deeplearning4j.nn.conf.layers.RnnOutputLayer;
 import org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional;
 import org.deeplearning4j.nn.conf.layers.recurrent.LastTimeStep;
 import org.deeplearning4j.nn.conf.layers.recurrent.SimpleRnn;
+import org.deeplearning4j.nn.conf.layers.recurrent.TimeDistributed;
 import org.deeplearning4j.nn.multilayer.MultiLayerNetwork;
 import org.deeplearning4j.nn.weights.WeightInit;
 import org.junit.Ignore;
@@ -289,4 +291,66 @@ public class RnnGradientChecks extends BaseDL4JTest {
             }
         }
     }
+
+
+
+
+    @Test
+    public void testTimeDistributedDense() {
+        int nIn = 3;
+        int nOut = 5;
+        int tsLength = 4;
+        int layerSize = 8;
+
+        Random r = new Random(12345);
+        for (int mb : new int[]{1, 3}) {
+            for (boolean inputMask : new boolean[]{false, true}) {
+
+
+                INDArray in = Nd4j.rand(new int[]{mb, nIn, tsLength});
+                INDArray labels = TestUtils.randomOneHotTimeSeries(mb, nOut, tsLength);
+                String maskType = (inputMask ? "inputMask" : "none");
+
+                INDArray inMask = null;
+                if (inputMask) {
+                    inMask = Nd4j.ones(mb, tsLength);
+                    for (int i = 0; i < mb; i++) {
+                        int firstMaskedStep = tsLength - 1 - i;
+                        if (firstMaskedStep == 0) {
+                            firstMaskedStep = tsLength;
+                        }
+                        for (int j = firstMaskedStep; j < tsLength; j++) {
+                            inMask.putScalar(i, j, 0.0);
+                        }
+                    }
+                }
+
+                String name = "testLastTimeStepLayer() - mb=" + mb + ", tsLength = " + tsLength + ", maskType=" + maskType;
+                if (PRINT_RESULTS) {
+                    System.out.println("Starting test: " + name);
+                }
+
+                MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder()
+                        .dataType(DataType.DOUBLE)
+                        .activation(Activation.TANH)
+                        .updater(new NoOp())
+                        .weightInit(WeightInit.XAVIER)
+                        .list()
+                        .layer(new LSTM.Builder().nOut(layerSize).build())
+                        .layer(new TimeDistributed(new DenseLayer.Builder().nOut(layerSize).activation(Activation.SOFTMAX).build(), 2))
+                        .layer(new RnnOutputLayer.Builder().nOut(nOut).activation(Activation.SOFTMAX)
+                                .lossFunction(LossFunctions.LossFunction.MCXENT).build())
+                        .setInputType(InputType.recurrent(nIn))
+                        .build();
+
+                MultiLayerNetwork net = new MultiLayerNetwork(conf);
+                net.init();
+
+                boolean gradOK = GradientCheckUtil.checkGradients(net, DEFAULT_EPS, DEFAULT_MAX_REL_ERROR,
+                        DEFAULT_MIN_ABS_ERROR, PRINT_RESULTS, RETURN_ON_FIRST_FAILURE, in, labels, inMask, null, true, 16);
+                assertTrue(name, gradOK);
+                TestUtils.testModelSerialization(net);
+            }
+        }
+    }
 }

deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/nn/dtypes/DTypeTests.java

@@ -16,6 +16,7 @@
 
 package org.deeplearning4j.nn.dtypes;
 
+import org.deeplearning4j.nn.conf.layers.recurrent.TimeDistributed;
 import org.nd4j.shade.guava.collect.ImmutableSet;
 import org.nd4j.shade.guava.reflect.ClassPath;
 import lombok.extern.slf4j.Slf4j;
@@ -811,7 +812,8 @@ public class DTypeTests extends BaseDL4JTest {
                             .layer(new DenseLayer.Builder().nOut(5).build())
                             .layer(new GravesBidirectionalLSTM.Builder().nIn(5).nOut(5).activation(Activation.TANH).build())
                             .layer(new Bidirectional(new LSTM.Builder().nIn(5).nOut(5).activation(Activation.TANH).build()))
-                            .layer(new SimpleRnn.Builder().nIn(10).nOut(5).build())
+                            .layer(new TimeDistributed(new DenseLayer.Builder().nIn(10).nOut(5).activation(Activation.TANH).build(), 2))
+                            .layer(new SimpleRnn.Builder().nIn(5).nOut(5).build())
                             .layer(new MaskZeroLayer.Builder().underlying(new SimpleRnn.Builder().nIn(5).nOut(5).build()).maskValue(0.0).build())
                             .layer(secondLast)
                             .layer(ol)

deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/layers/recurrent/TimeDistributedLayer.java

@@ -1,10 +1,12 @@
 package org.deeplearning4j.nn.layers.recurrent;
 
 import org.deeplearning4j.nn.api.Layer;
+import org.deeplearning4j.nn.api.MaskState;
 import org.deeplearning4j.nn.gradient.Gradient;
 import org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer;
 import org.deeplearning4j.nn.workspace.ArrayType;
 import org.deeplearning4j.nn.workspace.LayerWorkspaceMgr;
+import org.deeplearning4j.util.TimeSeriesUtils;
 import org.nd4j.linalg.api.ndarray.INDArray;
 import org.nd4j.linalg.primitives.Pair;
 import org.nd4j.linalg.util.ArrayUtil;
@@ -107,4 +109,30 @@ public class TimeDistributedLayer extends BaseWrapperLayer {
         INDArray permuted = reshaped.permute(permute);
         return permuted;
     }
+
+    @Override
+    public void setMaskArray(INDArray maskArray) {
+        if(maskArray == null){
+            underlying.setMaskArray(null);
+        } else {
+            INDArray reshaped = TimeSeriesUtils.reshapeTimeSeriesMaskToVector(maskArray, LayerWorkspaceMgr.noWorkspaces(), ArrayType.ACTIVATIONS);
+            underlying.setMaskArray(reshaped);
+        }
+    }
+
+    @Override
+    public Pair<INDArray, MaskState> feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize) {
+        if(maskArray == null){
+            return underlying.feedForwardMaskArray(null, currentMaskState, minibatchSize);
+        } else {
+            INDArray reshaped = TimeSeriesUtils.reshapeTimeSeriesMaskToVector(maskArray, LayerWorkspaceMgr.noWorkspaces(), ArrayType.ACTIVATIONS);
+            Pair<INDArray, MaskState> p = underlying.feedForwardMaskArray(reshaped, currentMaskState, minibatchSize);
+            if(p == null || p.getFirst() == null){
+                return p;
+            }
+            INDArray reshaped2 = TimeSeriesUtils.reshapeVectorToTimeSeriesMask(p.getFirst(), (int)maskArray.size(0));
+            p.setFirst(reshaped2);
+            return p;
+        }
+    }
 }

deeplearning4j/deeplearning4j-ui-parent/pom.xml

@@ -34,36 +34,6 @@
                 <groupId>org.apache.maven.plugins</groupId>
                 <artifactId>maven-compiler-plugin</artifactId>
             </plugin>
-            <plugin>
-                <groupId>net.alchim31.maven</groupId>
-                <artifactId>scala-maven-plugin</artifactId>
-                <version>${maven-scala-plugin.version}</version>
-                <configuration>
-                    <args>
-                        <arg>-deprecation</arg>
-                        <arg>-explaintypes</arg>
-                        <arg>-nobootcp</arg>
-                    </args>
-                </configuration>
-                <executions>
-                    <execution>
-                        <id>scala-compile-first</id>
-                        <phase>process-resources</phase>
-                        <goals>
-                            <goal>add-source</goal>
-                            <goal>compile</goal>
-                        </goals>
-                    </execution>
-                    <execution>
-                        <id>scala-test-compile</id>
-                        <phase>process-test-resources</phase>
-                        <goals>
-                            <goal>add-source</goal>
-                            <goal>testCompile</goal>
-                        </goals>
-                    </execution>
-                </executions>
-            </plugin>
         </plugins>
     </build>
     <modules>

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/transforms/custom/BitwiseAnd.java

@@ -1,5 +1,6 @@
-/*******************************************************************************
+/* ******************************************************************************
  * Copyright (c) 2015-2018 Skymind, Inc.
+ * Copyright (c) 2019 Konduit K.K.
  *
  * This program and the accompanying materials are made available under the
  * terms of the Apache License, Version 2.0 which is available at
@@ -50,7 +51,7 @@ public class BitwiseAnd extends BaseDynamicTransformOp {
 
     @Override
     public String opName() {
-        return "BitwiseAnd";
+        return "bitwise_and";
     }
 
 

pom.xml

@@ -328,9 +328,9 @@
         <slf4j.version>1.7.21</slf4j.version>
         <junit.version>4.12</junit.version>
         <logback.version>1.2.3</logback.version>
-        <jackson.version>2.9.9</jackson.version>
+        <jackson.version>2.10.1</jackson.version>
-        <jackson.databind.version>2.9.9.3</jackson.databind.version>
+        <jackson.databind.version>2.10.1</jackson.databind.version>
-        <shaded.snakeyaml.version>1.23</shaded.snakeyaml.version>
+        <shaded.snakeyaml.version>1.24</shaded.snakeyaml.version>
         <geo.jackson.version>2.8.7</geo.jackson.version>
         <lombok.version>1.18.2</lombok.version>
         <cleartk.version>2.0.0</cleartk.version>