Merge branch 'ba-baumann' into 'master'

GNN and DGL support, merge after CNNArchLang

See merge request !28

src/main/java/de/monticore/lang/monticar/cnnarch/generator/ArchitectureElementData.java

@@ -314,7 +314,11 @@ public class ArchitectureElementData {
     public int getValuesDim(){
         return getLayerSymbol().getIntValue(AllPredefinedLayers.VALUES_DIM_NAME).get();
     }
-    
+
+    public int getNodes(){
+        return getLayerSymbol().getIntValue(AllPredefinedLayers.NODES_NAME).get();
+    }
+
     @Nullable
     public List<Integer> getPadding(){
 

src/main/java/de/monticore/lang/monticar/cnnarch/generator/CNNArchTemplateController.java

@@ -106,6 +106,7 @@ public abstract class CNNArchTemplateController {
     public boolean containsAdaNet(){
         return this.architecture.containsAdaNet();
     }
+
     public String getName(ArchitectureElementSymbol layer){
         return nameManager.getName(layer);
     }

src/main/java/de/monticore/lang/monticar/cnnarch/generator/ConfigurationData.java

@@ -6,6 +6,7 @@ import com.google.common.collect.Maps;
 import de.monticore.lang.monticar.cnnarch.generator.annotations.ArchitectureAdapter;
 import de.monticore.lang.monticar.cnnarch.generator.annotations.Range;
 import de.monticore.lang.monticar.cnnarch.generator.training.RlAlgorithm;
+import de.monticore.lang.monticar.cnnarch.generator.training.NetworkType;
 import de.monticore.lang.monticar.cnnarch.generator.training.TrainingComponentsContainer;
 import de.monticore.lang.monticar.cnnarch.generator.training.TrainingConfiguration;
 
@@ -98,6 +99,21 @@ public abstract class ConfigurationData {
         return normalizeOpt.orElse(null);
     }
 
+    public Boolean getMultiGraph() {
+        Optional<Boolean> multiGraphOpt = trainingConfiguration.getMultiGraph();
+        return multiGraphOpt.orElse(null);
+    }
+
+    public List<Integer> getTrainMask() {
+        Optional<List<Integer>> trainMaskOpt = trainingConfiguration.getTrainMask();
+        return trainMaskOpt.orElse(null);
+    }
+
+    public List<Integer> getTestMask() {
+        Optional<List<Integer>> testMaskOpt = trainingConfiguration.getTestMask();
+        return testMaskOpt.orElse(null);
+    }
+
     public Boolean getShuffleData() {
         Optional<Boolean> shuffleDataOpt = trainingConfiguration.getShuffleData();
         return shuffleDataOpt.orElse(null);
@@ -379,6 +395,16 @@ public abstract class ConfigurationData {
         return DQN;
     }
 
+    public String getNetworkType() {
+        Optional<NetworkType> networkTypeOpt = trainingConfiguration.getNetworkType();
+
+        NetworkType networkType = networkTypeOpt.get();
+        if (networkType.equals(NetworkType.GNN)) {
+            return GNN;
+        }
+        return null;
+    }
+
 //    protected Object getDefaultValueOrElse(String parameterKey, Object elseValue) {
 //        if (schema == null) {
 //            return elseValue;

src/main/java/de/monticore/lang/monticar/cnnarch/generator/training/NetworkType.java

+package de.monticore.lang.monticar.cnnarch.generator.training;
+
+public enum NetworkType {
+
+    GNN("gnn");
+
+    String type;
+
+    NetworkType(String type) {
+        this.type = type;
+    }
+
+    public static NetworkType networkType(String type) {
+        for (NetworkType nt : values()) {
+            if (nt.type.equals(type)) {
+                return nt;
+            }
+        }
+        throw new IllegalArgumentException(String.valueOf(type));
+    }
+
+    public String getType() {
+        return type;
+    }
+}
\ No newline at end of file

src/main/java/de/monticore/lang/monticar/cnnarch/generator/training/TrainingConfiguration.java

@@ -107,6 +107,15 @@ public class TrainingConfiguration {
         return Optional.of(RlAlgorithm.rlAlgorithm(rlAlgorithm));
     }
 
+    public Optional<NetworkType> getNetworkType() {
+        Optional<ConfigurationEntry> networkTypeOpt = configurationSymbol.getConfigurationEntry(NETWORK_TYPE);
+        if (!networkTypeOpt.isPresent()) {
+            return Optional.empty();
+        }
+        String networkType = (String) networkTypeOpt.get().getValue();
+        return Optional.of(NetworkType.networkType(networkType));
+    }
+
     public Optional<Integer> getBatchSize() {
         return getParameterValue(BATCH_SIZE);
     }
@@ -143,6 +152,18 @@ public class TrainingConfiguration {
         return getParameterValue(SHUFFLE_DATA);
     }
 
+    public Optional<Boolean> getMultiGraph() {
+        return getParameterValue(MULTI_GRAPH);
+    }
+
+    public Optional<List<Integer>> getTrainMask() {
+        return getParameterValue(TRAIN_MASK);
+    }
+
+    public Optional<List<Integer>> getTestMask() {
+        return getParameterValue(TEST_MASK);
+    }
+
     public Optional<Double> getClipGlobalGradNorm() {
         return getParameterValue(CLIP_GLOBAL_GRAD_NORM);
     }

src/main/java/de/monticore/lang/monticar/cnnarch/generator/training/TrainingParameterConstants.java

@@ -42,6 +42,7 @@ public class TrainingParameterConstants {
     public static final String NORMALIZE = "normalize";
     public static final String CONTEXT = "context";
     public static final String SHUFFLE_DATA = "shuffle_data";
+
     public static final String CLIP_GLOBAL_GRAD_NORM = "clip_global_grad_norm";
     public static final String USE_TEACHER_FORCING = "use_teacher_forcing";
     public static final String SAVE_ATTENTION_IMAGE = "save_attention_image";
@@ -57,6 +58,12 @@ public class TrainingParameterConstants {
     public static final String DDPG = "ddpg";
     public static final String TD3 = "td3";
 
+    public static final String MULTI_GRAPH = "multi_graph";
+    public static final String TRAIN_MASK = "train_mask";
+    public static final String TEST_MASK = "test_mask";
+    public static final String GNN = "gnn";
+    public static final String NETWORK_TYPE = "network_type";
+
     public static final String LEARNING_METHOD = "learning_method";
     public static final String EVAL_METRIC = "eval_metric";
     public static final String NUM_EPISODES = "num_episodes";

src/main/resources/schemas/GNN.scm

+/* (c) https://github.com/MontiCore/monticore */
+
+schema GNN extends Supervised {
+    train_mask: Z*
+    test_mask: Z*
+    multi_graph: B
+}

src/main/resources/schemas/Supervised.scm

@@ -4,6 +4,10 @@ import Loss;
 
 schema Supervised extends General {
 
+    network_type: schema {
+        gnn;
+    }
+
     batch_size: N1
     num_epoch: N1
     normalize: B