Merge branch 'update_cnntrainer' into 'master'

Set default optimizer, updated cnntrainer to replace unsupported optimizer by...

See merge request !25

src/main/java/de/monticore/lang/monticar/cnnarch/caffe2generator/CNNTrain2Caffe2.java

@@ -8,6 +8,7 @@ import de.monticore.lang.monticar.cnntrain._cocos.CNNTrainCocos;
 import de.monticore.lang.monticar.cnntrain._symboltable.CNNTrainCompilationUnitSymbol;
 import de.monticore.lang.monticar.cnntrain._symboltable.CNNTrainLanguage;
 import de.monticore.lang.monticar.cnntrain._symboltable.ConfigurationSymbol;
+import de.monticore.lang.monticar.cnntrain._symboltable.OptimizerSymbol;
 import de.monticore.lang.monticar.generator.FileContent;
 import de.monticore.lang.monticar.generator.cpp.GeneratorCPP;
 import de.monticore.symboltable.GlobalScope;
@@ -49,7 +50,8 @@ public class CNNTrain2Caffe2 implements CNNTrainGenerator {
             ASTOptimizerEntry astOptimizer = (ASTOptimizerEntry) configuration.getOptimizer().getAstNode().get();
             astOptimizer.accept(funcChecker);
             if (funcChecker.getUnsupportedElemList().contains(funcChecker.unsupportedOptFlag)) {
-                configuration.setOptimizer(null);
+                OptimizerSymbol adamOptimizer = new OptimizerSymbol("adam");
+                configuration.setOptimizer(adamOptimizer); //Set default as adam optimizer
             }else {
                 Iterator it = configuration.getOptimizer().getOptimizerParamMap().keySet().iterator();
                 while (it.hasNext()) {

src/main/resources/templates/caffe2/CNNTrainer.ftl

@@ -33,9 +33,9 @@ if __name__ == "__main__":
         loss='${config.loss}',
 </#if>
 <#if (config.configuration.optimizer)??>
-        opt_type='${config.optimizerName}',
+        opt_type='${config.optimizerName}'<#if config.optimizerParams?has_content>,
 <#list config.optimizerParams?keys as param>
-    <#--To adapt parameter names since parameter names in Caffe2 are different than in CNNTrainLang-->
+    <#--To adapt parameter names to Caffe2 since they are different than in CNNTrainLang-->
     <#assign paramName = param>
     <#if param == "learning_rate">
         <#assign paramName = "base_learning_rate">
@@ -50,6 +50,7 @@ if __name__ == "__main__":
     </#if>
         ${paramName}=${config.optimizerParams[param]}<#sep>,
 </#list>
+</#if>
 </#if>
 
     )

src/test/java/de/monticore/lang/monticar/cnnarch/caffe2generator/GenerationTest.java

@@ -169,6 +169,20 @@ public class GenerationTest extends AbstractSymtabTest{
                         "CNNTrainer_emptyConfig.py"));
     }
 
+    @Test
+    public void testUnsupportedTrainParameters() throws IOException {
+        Log.getFindings().clear();
+        Path modelPath = Paths.get("src/test/resources/valid_tests");
+        CNNTrain2Caffe2 trainGenerator = new CNNTrain2Caffe2();
+        trainGenerator.generate(modelPath, "UnsupportedConfig");
+
+        assertTrue(Log.getFindings().size() == 6);
+        checkFilesAreEqual(
+                Paths.get("./target/generated-sources-cnnarch"),
+                Paths.get("./src/test/resources/target_code"),
+                Arrays.asList(
+                        "CNNTrainer_unsupportedConfig.py"));
+    }
 
     @Test
     public void testCMakeGeneration() {

src/test/resources/target_code/CNNTrainer_unsupportedConfig.py

+from caffe2.python import workspace, core, model_helper, brew, optimizer
+from caffe2.python.predictor import mobile_exporter
+from caffe2.proto import caffe2_pb2
+
+import numpy as np
+import logging
+import CNNCreator_unsupportedConfig
+
+if __name__ == "__main__":
+    logging.basicConfig(level=logging.DEBUG)
+    logger = logging.getLogger()
+    handler = logging.FileHandler("train.log", "w", encoding=None, delay="true")
+    logger.addHandler(handler)
+
+    unsupportedConfig = CNNCreator_unsupportedConfig.CNNCreator_unsupportedConfig()
+    unsupportedConfig.train(
+        num_epoch=5,
+        batch_size=100,
+        context='gpu',
+        opt_type='adam'
+    )

src/test/resources/valid_tests/UnsupportedConfig.cnnt

+configuration UnsupportedConfig{
+     num_epoch : 5
+     batch_size : 100
+     context : gpu
+     load_checkpoint : true
+     normalize : true
+     optimizer : nag{
+         learning_rate_minimum : 0.00001
+         rescale_grad : 1.1
+         clip_gradient : 10
+     }
+}
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