Merge branch 'move-to-gluon' into 'master'

Move to gluon

Closes #1

See merge request !1

pom.xml

@@ -7,8 +7,8 @@
   <!-- == PROJECT COORDINATES ============================================= -->
 
   <groupId>de.monticore.lang.monticar</groupId>
-  <artifactId>cnnarch-mxnet-generator</artifactId>
-  <version>0.2.8</version>
+  <artifactId>cnnarch-gluon-generator</artifactId>
+  <version>0.1.0-SNAPSHOT</version>
 
   <!-- == PROJECT DEPENDENCIES ============================================= -->
 
@@ -172,7 +172,7 @@
             <configuration>
               <archive>
                 <manifest>
-                  <mainClass>de.monticore.lang.monticar.cnnarch.mxnetgenerator.CNNArch2MxNetCli</mainClass>
+                  <mainClass>de.monticore.lang.monticar.cnnarch.gluongenerator.CNNArch2GluonCli</mainClass>
                 </manifest>
               </archive>
               <descriptorRefs>
@@ -229,7 +229,8 @@
                     <maxmem>256m</maxmem>
                     <!-- aggregated reports for multi-module projects -->
                     <aggregate>true</aggregate>
-                </configuration>
+                    <check/>
+            </configuration>
 </plugin>
     </plugins>
   </build>

src/main/java/de/monticore/lang/monticar/cnnarch/mxnetgenerator/ArchitectureElementData.java → src/main/java/de/monticore/lang/monticar/cnnarch/gluongenerator/ArchitectureElementData.java

@@ -18,7 +18,7 @@
  *  License along with this project. If not, see <http://www.gnu.org/licenses/>.
  * *******************************************************************************
  */
-package de.monticore.lang.monticar.cnnarch.mxnetgenerator;
+package de.monticore.lang.monticar.cnnarch.gluongenerator;
 
 import de.monticore.lang.monticar.cnnarch._symboltable.ArchTypeSymbol;
 import de.monticore.lang.monticar.cnnarch._symboltable.ArchitectureElementSymbol;

src/main/java/de/monticore/lang/monticar/cnnarch/mxnetgenerator/CNNArch2MxNet.java → src/main/java/de/monticore/lang/monticar/cnnarch/gluongenerator/CNNArch2Gluon.java

@@ -18,7 +18,7 @@
  *  License along with this project. If not, see <http://www.gnu.org/licenses/>.
  * *******************************************************************************
  */
-package de.monticore.lang.monticar.cnnarch.mxnetgenerator;
+package de.monticore.lang.monticar.cnnarch.gluongenerator;
 
 import de.monticore.io.paths.ModelPath;
 import de.monticore.lang.monticar.cnnarch.CNNArchGenerator;
@@ -40,11 +40,11 @@ import java.util.HashMap;
 import java.util.Map;
 import java.util.Optional;
 
-public class CNNArch2MxNet implements CNNArchGenerator {
+public class CNNArch2Gluon implements CNNArchGenerator {
 
     private String generationTargetPath;
 
-    public CNNArch2MxNet() {
+    public CNNArch2Gluon() {
         setGenerationTargetPath("./target/generated-sources-cnnarch/");
     }
 
@@ -96,6 +96,9 @@ public class CNNArch2MxNet implements CNNArchGenerator {
         temp = archTc.process("CNNPredictor", Target.CPP);
         fileContentMap.put(temp.getKey(), temp.getValue());
 
+        temp = archTc.process("CNNNet", Target.PYTHON);
+        fileContentMap.put(temp.getKey(), temp.getValue());
+
         temp = archTc.process("CNNCreator", Target.PYTHON);
         fileContentMap.put(temp.getKey(), temp.getValue());
 

src/main/java/de/monticore/lang/monticar/cnnarch/mxnetgenerator/CNNArch2MxNetCli.java → src/main/java/de/monticore/lang/monticar/cnnarch/gluongenerator/CNNArch2GluonCli.java

@@ -18,14 +18,14 @@
  *  License along with this project. If not, see <http://www.gnu.org/licenses/>.
  * *******************************************************************************
  */
-package de.monticore.lang.monticar.cnnarch.mxnetgenerator;
+package de.monticore.lang.monticar.cnnarch.gluongenerator;
 
 import org.apache.commons.cli.*;
 
 import java.nio.file.Path;
 import java.nio.file.Paths;
 
-public class CNNArch2MxNetCli {
+public class CNNArch2GluonCli {
 
     public static final Option OPTION_MODELS_PATH = Option.builder("m")
             .longOpt("models-dir")
@@ -48,7 +48,7 @@ public class CNNArch2MxNetCli {
             .required(false)
             .build();
 
-    private CNNArch2MxNetCli() {
+    private CNNArch2GluonCli() {
     }
 
     public static void main(String[] args) {
@@ -84,7 +84,7 @@ public class CNNArch2MxNetCli {
         Path modelsDirPath = Paths.get(cliArgs.getOptionValue(OPTION_MODELS_PATH.getOpt()));
         String rootModelName = cliArgs.getOptionValue(OPTION_ROOT_MODEL.getOpt());
         String outputPath = cliArgs.getOptionValue(OPTION_OUTPUT_PATH.getOpt());
-        CNNArch2MxNet generator = new CNNArch2MxNet();
+        CNNArch2Gluon generator = new CNNArch2Gluon();
         if (outputPath != null){
             generator.setGenerationTargetPath(outputPath);
         }

src/main/java/de/monticore/lang/monticar/cnnarch/mxnetgenerator/CNNArchTemplateController.java → src/main/java/de/monticore/lang/monticar/cnnarch/gluongenerator/CNNArchTemplateController.java

@@ -18,7 +18,7 @@
  *  License along with this project. If not, see <http://www.gnu.org/licenses/>.
  * *******************************************************************************
  */
-package de.monticore.lang.monticar.cnnarch.mxnetgenerator;
+package de.monticore.lang.monticar.cnnarch.gluongenerator;
 
 import de.monticore.lang.monticar.cnnarch._symboltable.*;
 import de.monticore.lang.monticar.cnnarch.predefined.Sigmoid;
@@ -34,6 +34,7 @@ public class CNNArchTemplateController {
     public static final String TEMPLATE_ELEMENTS_DIR_PATH = "elements/";
     public static final String TEMPLATE_CONTROLLER_KEY = "tc";
     public static final String ELEMENT_DATA_KEY = "element";
+    public static final String NET_DEFINITION_MODE_KEY = "definition_mode";
 
     private LayerNameCreator nameManager;
     private ArchitectureSymbol architecture;
@@ -123,34 +124,43 @@ public class CNNArchTemplateController {
         return list;
     }
 
-    public void include(String relativePath, String templateWithoutFileEnding, Writer writer){
+    public void include(String relativePath, String templateWithoutFileEnding, Writer writer, NetDefinitionMode netDefinitionMode){
         String templatePath = relativePath + templateWithoutFileEnding + FTL_FILE_ENDING;
         Map<String, Object> ftlContext = new HashMap<>();
         ftlContext.put(TEMPLATE_CONTROLLER_KEY, this);
         ftlContext.put(ELEMENT_DATA_KEY, getCurrentElement());
+        ftlContext.put(NET_DEFINITION_MODE_KEY, netDefinitionMode);
         TemplateConfiguration.processTemplate(ftlContext, templatePath, writer);
     }
 
-    public void include(IOSymbol ioElement, Writer writer){
+    public void include(String relativePath, String templateWithoutFileEnding, Writer writer) {
+        String templatePath = relativePath + templateWithoutFileEnding + FTL_FILE_ENDING;
+        Map<String, Object> ftlContext = new HashMap<>();
+        ftlContext.put(TEMPLATE_CONTROLLER_KEY, this);
+        ftlContext.put(ELEMENT_DATA_KEY, getCurrentElement());
+        TemplateConfiguration.processTemplate(ftlContext, templatePath, writer);
+    }
+
+    public void include(IOSymbol ioElement, Writer writer, NetDefinitionMode netDefinitionMode){
         ArchitectureElementData previousElement = getCurrentElement();
         setCurrentElement(ioElement);
 
         if (ioElement.isAtomic()){
             if (ioElement.isInput()){
-                include(TEMPLATE_ELEMENTS_DIR_PATH, "Input", writer);
+                include(TEMPLATE_ELEMENTS_DIR_PATH, "Input", writer, netDefinitionMode);
             }
             else {
-                include(TEMPLATE_ELEMENTS_DIR_PATH, "Output", writer);
+                include(TEMPLATE_ELEMENTS_DIR_PATH, "Output", writer, netDefinitionMode);
             }
         }
         else {
-            include(ioElement.getResolvedThis().get(), writer);
+            include(ioElement.getResolvedThis().get(), writer, netDefinitionMode);
         }
 
         setCurrentElement(previousElement);
     }
 
-    public void include(LayerSymbol layer, Writer writer){
+    public void include(LayerSymbol layer, Writer writer, NetDefinitionMode netDefinitionMode){
         ArchitectureElementData previousElement = getCurrentElement();
         setCurrentElement(layer);
 
@@ -158,44 +168,48 @@ public class CNNArchTemplateController {
             ArchitectureElementSymbol nextElement = layer.getOutputElement().get();
             if (!isSoftmaxOutput(nextElement) && !isLogisticRegressionOutput(nextElement)){
                 String templateName = layer.getDeclaration().getName();
-                include(TEMPLATE_ELEMENTS_DIR_PATH, templateName, writer);
+                include(TEMPLATE_ELEMENTS_DIR_PATH, templateName, writer, netDefinitionMode);
             }
         }
         else {
-            include(layer.getResolvedThis().get(), writer);
+            include(layer.getResolvedThis().get(), writer, netDefinitionMode);
         }
 
         setCurrentElement(previousElement);
     }
 
-    public void include(CompositeElementSymbol compositeElement, Writer writer){
+    public void include(CompositeElementSymbol compositeElement, Writer writer, NetDefinitionMode netDefinitionMode){
         ArchitectureElementData previousElement = getCurrentElement();
         setCurrentElement(compositeElement);
 
         for (ArchitectureElementSymbol element : compositeElement.getElements()){
-            include(element, writer);
+            include(element, writer, netDefinitionMode);
         }
 
         setCurrentElement(previousElement);
     }
 
-    public void include(ArchitectureElementSymbol architectureElement, Writer writer){
+    public void include(ArchitectureElementSymbol architectureElement, Writer writer, NetDefinitionMode netDefinitionMode){
         if (architectureElement instanceof CompositeElementSymbol){
-            include((CompositeElementSymbol) architectureElement, writer);
+            include((CompositeElementSymbol) architectureElement, writer, netDefinitionMode);
         }
         else if (architectureElement instanceof LayerSymbol){
-            include((LayerSymbol) architectureElement, writer);
+            include((LayerSymbol) architectureElement, writer, netDefinitionMode);
         }
         else {
-            include((IOSymbol) architectureElement, writer);
+            include((IOSymbol) architectureElement, writer, netDefinitionMode);
         }
     }
 
-    public void include(ArchitectureElementSymbol architectureElement){
+    public void include(ArchitectureElementSymbol architectureElementSymbol, String netDefinitionMode) {
+        include(architectureElementSymbol, NetDefinitionMode.fromString(netDefinitionMode));
+    }
+
+    public void include(ArchitectureElementSymbol architectureElement, NetDefinitionMode netDefinitionMode){
         if (writer == null){
             throw new IllegalStateException("missing writer");
         }
-        include(architectureElement, writer);
+        include(architectureElement, writer, netDefinitionMode);
     }
 
     public Map.Entry<String,String> process(String templateNameWithoutEnding, Target targetLanguage){

src/main/java/de/monticore/lang/monticar/cnnarch/mxnetgenerator/CNNTrain2MxNet.java → src/main/java/de/monticore/lang/monticar/cnnarch/gluongenerator/CNNTrain2Gluon.java

-package de.monticore.lang.monticar.cnnarch.mxnetgenerator;
+package de.monticore.lang.monticar.cnnarch.gluongenerator;
 
 import de.monticore.io.paths.ModelPath;
 import de.monticore.lang.monticar.cnntrain.CNNTrainGenerator;
@@ -17,7 +17,7 @@ import java.io.IOException;
 import java.nio.file.Path;
 import java.util.*;
 
-public class CNNTrain2MxNet implements CNNTrainGenerator {
+public class CNNTrain2Gluon implements CNNTrainGenerator {
     private String generationTargetPath;
     private String instanceName;
 
@@ -58,7 +58,7 @@ public class CNNTrain2MxNet implements CNNTrainGenerator {
         }
     }
 
-    public CNNTrain2MxNet() {
+    public CNNTrain2Gluon() {
         setGenerationTargetPath("./target/generated-sources-cnnarch/");
     }
 

src/main/java/de/monticore/lang/monticar/cnnarch/mxnetgenerator/ConfigurationData.java → src/main/java/de/monticore/lang/monticar/cnnarch/gluongenerator/ConfigurationData.java

-package de.monticore.lang.monticar.cnnarch.mxnetgenerator;
+package de.monticore.lang.monticar.cnnarch.gluongenerator;
 
 import de.monticore.lang.monticar.cnntrain._symboltable.*;
 

src/main/java/de/monticore/lang/monticar/cnnarch/mxnetgenerator/LayerNameCreator.java → src/main/java/de/monticore/lang/monticar/cnnarch/gluongenerator/LayerNameCreator.java

@@ -18,7 +18,7 @@
  *  License along with this project. If not, see <http://www.gnu.org/licenses/>.
  * *******************************************************************************
  */
-package de.monticore.lang.monticar.cnnarch.mxnetgenerator;
+package de.monticore.lang.monticar.cnnarch.gluongenerator;
 
 import de.monticore.lang.monticar.cnnarch._symboltable.*;
 import de.monticore.lang.monticar.cnnarch.predefined.Convolution;

src/main/java/de/monticore/lang/monticar/cnnarch/gluongenerator/NetDefinitionMode.java

+package de.monticore.lang.monticar.cnnarch.gluongenerator;
+
+/**
+ *
+ */
+public enum NetDefinitionMode {
+    ARCHITECTURE_DEFINITION,
+    FORWARD_FUNCTION;
+
+    public static NetDefinitionMode fromString(final String netDefinitionMode) {
+        switch(netDefinitionMode) {
+            case "ARCHITECTURE_DEFINITION":
+                return ARCHITECTURE_DEFINITION;
+            case "FORWARD_FUNCTION":
+                return FORWARD_FUNCTION;
+            default:
+                throw new IllegalArgumentException("Unknown Net Definition Mode");
+        }
+    }
+}

src/main/java/de/monticore/lang/monticar/cnnarch/mxnetgenerator/Target.java → src/main/java/de/monticore/lang/monticar/cnnarch/gluongenerator/Target.java

@@ -18,7 +18,7 @@
  *  License along with this project. If not, see <http://www.gnu.org/licenses/>.
  * *******************************************************************************
  */
-package de.monticore.lang.monticar.cnnarch.mxnetgenerator;
+package de.monticore.lang.monticar.cnnarch.gluongenerator;
 
 //can be removed
 public enum Target {

src/main/java/de/monticore/lang/monticar/cnnarch/mxnetgenerator/TemplateConfiguration.java → src/main/java/de/monticore/lang/monticar/cnnarch/gluongenerator/TemplateConfiguration.java

@@ -18,7 +18,7 @@
  *  License along with this project. If not, see <http://www.gnu.org/licenses/>.
  * *******************************************************************************
  */
-package de.monticore.lang.monticar.cnnarch.mxnetgenerator;
+package de.monticore.lang.monticar.cnnarch.gluongenerator;
 
 import de.se_rwth.commons.logging.Log;
 import freemarker.template.Configuration;
@@ -38,7 +38,7 @@ public class TemplateConfiguration {
 
     private TemplateConfiguration() {
         configuration = new Configuration(Configuration.VERSION_2_3_23);
-        configuration.setClassForTemplateLoading(TemplateConfiguration.class, "/templates/mxnet/");
+        configuration.setClassForTemplateLoading(TemplateConfiguration.class, "/templates/gluon/");
         configuration.setDefaultEncoding("UTF-8");
         configuration.setTemplateExceptionHandler(TemplateExceptionHandler.RETHROW_HANDLER);
     }

src/main/java/de/monticore/lang/monticar/cnnarch/mxnetgenerator/TrainParamSupportChecker.java → src/main/java/de/monticore/lang/monticar/cnnarch/gluongenerator/TrainParamSupportChecker.java

-package de.monticore.lang.monticar.cnnarch.mxnetgenerator;
+package de.monticore.lang.monticar.cnnarch.gluongenerator;
 
 import de.monticore.lang.monticar.cnntrain._ast.*;
 import de.monticore.lang.monticar.cnntrain._visitor.CNNTrainVisitor;

src/main/resources/templates/mxnet/CNNCreator.ftl → src/main/resources/templates/gluon/CNNCreator.ftl

@@ -6,6 +6,9 @@ import shutil
 import h5py
 import sys
 import numpy as np
+import time
+from mxnet import gluon, autograd, nd
+from CNNNet_${tc.fullArchitectureName} import Net
 
 @mx.init.register
 class MyConstant(mx.init.Initializer):
@@ -17,7 +20,6 @@ class MyConstant(mx.init.Initializer):
 
 class ${tc.fileNameWithoutEnding}:
 
-    module = None
     _data_dir_ = "data/${tc.fullArchitectureName}/"
     _model_dir_ = "model/${tc.fullArchitectureName}/"
     _model_prefix_ = "${tc.architectureName}"
@@ -25,6 +27,9 @@ class ${tc.fileNameWithoutEnding}:
     _input_shapes_ = [<#list tc.architecture.inputs as input>(${tc.join(input.definition.type.dimensions, ",")})</#list>]
     _output_names_ = [${tc.join(tc.architectureOutputs, ",", "'", "_label'")}]
 
+    def __init__(self):
+        self.weight_initializer = mx.init.Normal()
+        self.net = None
 
     def load(self, context):
         lastEpoch = 0
@@ -51,11 +56,7 @@ class ${tc.fileNameWithoutEnding}:
             return 0
         else:
             logging.info("Loading checkpoint: " + param_file)
-            self.module.load(prefix=self._model_dir_ + self._model_prefix_,
-                              epoch=lastEpoch,
-                              data_names=self._input_names_,
-                              label_names=self._output_names_,
-                              context=context)
+            self.net.load_parameters(param_file)
             return lastEpoch
 
 
@@ -138,11 +139,11 @@ class ${tc.fileNameWithoutEnding}:
 
 
         train_iter, test_iter, data_mean, data_std = self.load_data(batch_size)
-        if self.module == None:
+        if self.net == None:
             if normalize:
-                self.construct(mx_context, data_mean, data_std)
+                self.construct(context=mx_context, data_mean=nd.array(data_mean), data_std=nd.array(data_std))
             else:
-                self.construct(mx_context)
+                self.construct(context=mx_context)
 
         begin_epoch = 0
         if load_checkpoint:
@@ -157,23 +158,79 @@ class ${tc.fileNameWithoutEnding}:
             if not os.path.isdir(self._model_dir_):
                 raise
 
-        self.module.fit(
-            train_data=train_iter,
-            eval_metric=eval_metric,
-            eval_data=test_iter,
-            optimizer=optimizer,
-            optimizer_params=optimizer_params,
-            batch_end_callback=mx.callback.Speedometer(batch_size),
-            epoch_end_callback=mx.callback.do_checkpoint(prefix=self._model_dir_ + self._model_prefix_, period=checkpoint_period),
-            begin_epoch=begin_epoch,
-            num_epoch=num_epoch + begin_epoch)
-        self.module.save_checkpoint(self._model_dir_ + self._model_prefix_, num_epoch + begin_epoch)
-        self.module.save_checkpoint(self._model_dir_ + self._model_prefix_ + '_newest', 0)
+        trainer = mx.gluon.Trainer(self.net.collect_params(), optimizer, optimizer_params)
+
+        if self.net.last_layer == 'softmax':
+            loss_function = mx.gluon.loss.SoftmaxCrossEntropyLoss()
+        elif self.net.last_layer == 'sigmoid':
+            loss_function = mx.gluon.loss.SigmoidBinaryCrossEntropyLoss()
+        elif self.net.last_layer == 'linear':
+            loss_function = mx.gluon.loss.L2Loss()
+        else: # TODO: Change default?
+            loss_function = mx.gluon.loss.L2Loss()
+            logging.warning("Invalid last_layer, defaulting to L2 loss")
+
+        speed_period = 50
+        tic = None
+
+        for epoch in range(begin_epoch, begin_epoch + num_epoch):
+            train_iter.reset()
+            for batch_i, batch in enumerate(train_iter):
+                data = batch.data[0].as_in_context(mx_context)
+                label = batch.label[0].as_in_context(mx_context)
+                with autograd.record():
+                    output = self.net(data)
+                    loss = loss_function(output, label)
+
+                loss.backward()
+                trainer.step(batch_size)
+
+                if tic is None:
+                    tic = time.time()
+                else:
+                    if batch_i % speed_period == 0:
+                        try:
+                            speed = speed_period * batch_size / (time.time() - tic)
+                        except ZeroDivisionError:
+                            speed = float("inf")
+
+                        logging.info("Epoch[%d] Batch[%d] Speed: %.2f samples/sec" % (epoch, batch_i, speed))
+
+                        tic = time.time()
+
+            tic = None
+
+            train_iter.reset()
+            metric = mx.metric.create(eval_metric)
+            for batch_i, batch in enumerate(train_iter):
+                data = batch.data[0].as_in_context(mx_context)
+                label = batch.label[0].as_in_context(mx_context)
+                output = self.net(data)
+                predictions = mx.nd.argmax(output, axis=1)
+                metric.update(preds=predictions, labels=label)
+            train_metric_score = metric.get()[1]
+
+            test_iter.reset()
+            metric = mx.metric.create(eval_metric)
+            for batch_i, batch in enumerate(test_iter):
+                data = batch.data[0].as_in_context(mx_context)
+                label = batch.label[0].as_in_context(mx_context)
+                output = self.net(data)
+                predictions = mx.nd.argmax(output, axis=1)
+                metric.update(preds=predictions, labels=label)
+            test_metric_score = metric.get()[1]
+
+            logging.info("Epoch[%d] Train: %f, Test: %f" % (epoch, train_metric_score, test_metric_score))
+
+            if (epoch - begin_epoch) % checkpoint_period == 0:
+                self.net.export(self._model_dir_ + self._model_prefix_, epoch)
+
+        self.net.export(self._model_dir_ + self._model_prefix_, num_epoch + begin_epoch)
+        self.net.export(self._model_dir_ + self._model_prefix_ + '_newest', 0)
 
 
     def construct(self, context, data_mean=None, data_std=None):
-${tc.include(tc.architecture.body)}
-        self.module = mx.mod.Module(symbol=mx.symbol.Group([${tc.join(tc.architectureOutputs, ",")}]),
-                                         data_names=self._input_names_,
-                                         label_names=self._output_names_,
-                                         context=context)
+        self.net = Net(data_mean=data_mean, data_std=data_std)
+        self.net.collect_params().initialize(self.weight_initializer, ctx=context)
+        self.net.hybridize()
+        self.net(mx.nd.zeros((1,)+self._input_shapes_[0], ctx=context))

src/main/resources/templates/gluon/CNNNet.ftl

+import mxnet as mx
+import numpy as np
+from mxnet import gluon
+
+class Softmax(gluon.HybridBlock):
+    def __init__(self, **kwargs):
+        super(Softmax, self).__init__(**kwargs)
+
+    def hybrid_forward(self, F, x):
+        return F.softmax(x)
+
+
+class Split(gluon.HybridBlock):
+    def __init__(self, num_outputs, axis=1, **kwargs):
+        super(Split, self).__init__(**kwargs)
+        with self.name_scope():
+            self.axis = axis
+            self.num_outputs = num_outputs
+
+    def hybrid_forward(self, F, x):
+        return F.split(data=x, axis=self.axis, num_outputs=self.num_outputs)
+
+
+class Concatenate(gluon.HybridBlock):
+    def __init__(self, dim=1, **kwargs):
+        super(Concatenate, self).__init__(**kwargs)
+        with self.name_scope():
+            self.dim = dim
+
+    def hybrid_forward(self, F, *x):
+        return F.concat(*x, dim=self.dim)
+
+
+class ZScoreNormalization(gluon.HybridBlock):
+    def __init__(self, data_mean, data_std, **kwargs):
+        super(ZScoreNormalization, self).__init__(**kwargs)
+        with self.name_scope():
+            self.data_mean = self.params.get('data_mean', shape=data_mean.shape,
+                init=mx.init.Constant(data_mean.asnumpy().tolist()), differentiable=False)
+            self.data_std = self.params.get('data_std', shape=data_mean.shape,
+                init=mx.init.Constant(data_std.asnumpy().tolist()), differentiable=False)
+
+    def hybrid_forward(self, F, x, data_mean, data_std):
+        x = F.broadcast_sub(x, data_mean)
+        x = F.broadcast_div(x, data_std)
+        return x
+
+
+class Padding(gluon.HybridBlock):
+    def __init__(self, padding, **kwargs):
+        super(Padding, self).__init__(**kwargs)
+        with self.name_scope():
+            self.pad_width = padding
+
+    def hybrid_forward(self, F, x):
+        x = F.pad(data=x,
+            mode='constant',
+            pad_width=self.pad_width,
+            constant_value=0)
+        return x
+
+
+class NoNormalization(gluon.HybridBlock):
+    def __init__(self, **kwargs):
+        super(NoNormalization, self).__init__(**kwargs)
+
+    def hybrid_forward(self, F, x):
+        return x
+
+
+class Net(gluon.HybridBlock):
+    def __init__(self, data_mean=None, data_std=None, **kwargs):
+        super(Net, self).__init__(**kwargs)
+        with self.name_scope():
+${tc.include(tc.architecture.body, "ARCHITECTURE_DEFINITION")}
+
+    def hybrid_forward(self, F, x):
+${tc.include(tc.architecture.body, "FORWARD_FUNCTION")}
\ No newline at end of file

src/main/resources/templates/mxnet/elements/Add.ftl → src/main/resources/templates/gluon/elements/Add.ftl

+<#-- TODO: May put this in an extra HybridBlock -->
+<#assign mode = definition_mode.toString()>
+<#if mode == "FORWARD_FUNCTION">
         ${element.name} = ${tc.join(element.inputs, " + ")}
-<#include "OutputShape.ftl">
\ No newline at end of file
+</#if>
\ No newline at end of file

src/main/resources/templates/gluon/elements/BatchNorm.ftl

+<#assign mode = definition_mode.toString()>
+<#assign input = element.inputs[0]>
+<#-- TODO: Find solution for the CNNArch fix_gamma parameter of BatchNorm. Gluon does not provide this parameter-->
+<#if mode == "ARCHITECTURE_DEFINITION">
+            self.${element.name} = gluon.nn.BatchNorm()
+            <#include "OutputShape.ftl">
+</#if>
+<#if mode == "FORWARD_FUNCTION">
+        ${element.name} = self.${element.name}(${input})
+</#if>
\ No newline at end of file