EMADL component and config to train a direct perception network as described in DeepDriving paper

CNNModelTraining/src/main/java/de/monticore/lang/monticar/torcs_dl/CNNCodeGenerator.java

 package de.monticore.lang.monticar.torcs_dl;
 
-import de.monticore.lang.monticar.emadl.generator.Generator;
+import de.monticore.lang.monticar.emadl.generator.EMADLGenerator;
 import freemarker.template.TemplateException;
 
 import java.io.IOException;
@@ -17,10 +17,10 @@ public class CNNCodeGenerator {
     public static void main(String[] args) {
         System.out.println("Starting code generation...");
 
-        Generator gen =  new Generator();
+        EMADLGenerator gen =  new EMADLGenerator();
         gen.setGenerationTargetPath(TARGET_PATH_GENERATED);
         try {
-            gen.generate(MODELS_PATH, "Alexnet");
+            gen.generate(MODELS_PATH, "Dpnet");
         } catch (IOException | TemplateException e) {
             e.printStackTrace();
         }

CNNModelTraining/src/main/models/Alexnet.emadl

-component Alexnet{
-    ports in Z(0:255)^{3, 224, 224} image,
-         out Q(0:1)^{10,1,1} predictions;
-
-    implementation CNN {
-
-        def split1(i){
-            [i] ->
-            Convolution(kernel=(5,5), channels=128) ->
-            Lrn(nsize=5, alpha=0.0001, beta=0.75) ->
-            Pooling(pool_type="max", kernel=(3,3), stride=(2,2), padding="no_loss") ->
-            Relu()
-        }
-        def split2(i){
-            [i] ->
-            Convolution(kernel=(3,3), channels=192) ->
-            Relu() ->
-            Convolution(kernel=(3,3), channels=128) ->
-            Pooling(pool_type="max", kernel=(3,3), stride=(2,2), padding="no_loss") ->
-            Relu()
-        }
-        def fc(){
-            FullyConnected(units=4096) ->
-            Relu() ->
-            Dropout()
-        }
-
-        image ->
-        Convolution(kernel=(11,11), channels=96, stride=(4,4), padding="no_loss") ->
-        Lrn(nsize=5, alpha=0.0001, beta=0.75) ->
-        Pooling(pool_type="max", kernel=(3,3), stride=(2,2), padding="no_loss") ->
-        Relu() ->
-        Split(n=2) ->
-        split1(i=[0|1]) ->
-        Concatenate() ->
-        Convolution(kernel=(3,3), channels=384) ->
-        Relu() ->
-        Split(n=2) ->
-        split2(i=[0|1]) ->
-        Concatenate() ->
-        fc(->=2) ->
-        FullyConnected(units=10) ->
-        Softmax() ->
-        predictions
-
-    }
-}
\ No newline at end of file

CNNModelTraining/src/main/models/AlexnetConfig.cnnt

-configuration AlexnetConfig{
-     num_epoch : 100
-     batch_size : 500
-     optimizer : adam{
-         learning_rate : 0.001
-     }
-}

CNNModelTraining/src/main/models/Dpnet.cnnt

+configuration Dpnet{
+     num_epoch : 100
+     batch_size : 64
+     optimizer : sgd{
+         learning_rate : 0.01
+     }
+}

CNNModelTraining/src/main/models/Dpnet.emadl

+component Dpnet{
+    ports in Z(0:255)^{3, 210, 280} image,
+         out Q(0:1)^{13,1,1} predictions;
+
+    implementation CNN {
+
+        def conv(kernel, channels, hasPool=true, convStride=(1,1)){
+            Convolution(kernel=kernel, channels=channels, stride=convStride) ->
+            Relu() ->
+            Pooling(pool_type="max", kernel=(3,3), stride=(2,2), ?=hasPool)
+        }
+        def fc(){
+            FullyConnected(units=4096) ->
+            Relu() ->
+            Dropout()
+        }
+
+        image ->
+        conv(kernel=(11,11), channels=96, convStride=(4,4)) ->
+        conv(kernel=(5,5), channels=256, convStride=(4,4)) ->
+        conv(kernel=(3,3), channels=384, hasPool=false) ->
+        conv(kernel=(3,3), channels=384, hasPool=false) ->
+        conv(kernel=(3,3), channels=256) ->
+        fc() ->
+        fc() ->
+        FullyConnected(units=13) ->
+        Sigmoid() ->
+        predictions
+
+    }
+}

CNNModelTraining/src/main/resources/de/monticore/lang/monticar/generator/middleware/IAdapterTemplate.ftl

-#pragma once
-#include "${compName}.h"
-
-class IAdapter_${compName}{
-	public:
-		virtual ~IAdapter_${compName}(){}
-		virtual void init(${compName}* comp) = 0;
-		virtual void tick() = 0;
-};

CNNModelTraining/src/main/resources/de/monticore/lang/monticar/generator/middleware/cmakeCppTemplate.ftl

-cmake_minimum_required(VERSION 3.5)
-project(${compName} LANGUAGES CXX)
-add_library(${compName} ${compName}.h)
-target_include_directories(${compName} PUBLIC ${CMAKE_CURRENT_SOURCE_DIR})
-set_target_properties(${compName} PROPERTIES LINKER_LANGUAGE CXX)
-export(TARGETS ${compName} FILE ${compName}.cmake)

CNNModelTraining/src/main/resources/de/monticore/lang/monticar/generator/middleware/coordinatorCmakeListsTemplate.ftl

-cmake_minimum_required(VERSION 3.5)
-project (Coordinator_${compName} CXX)
-
-set (CMAKE_CXX_STANDARD 11)
-set (THREADS_PREFER_PTHREAD_FLAG ON)
-find_package(Threads REQUIRED)
-
-add_executable(Coordinator_${compName} Coordinator_${compName}.cpp)
-set_target_properties(Coordinator_${compName} PROPERTIES LINKER_LANGUAGE CXX)
-target_link_libraries(Coordinator_${compName} ${targets} Threads::Threads)
-target_include_directories(Coordinator_${compName} PUBLIC ${CMAKE_CURRENT_SOURCE_DIR})
-
-export(TARGETS Coordinator_${compName} FILE Coordinator_${compName}.cmake)
\ No newline at end of file

CNNModelTraining/src/main/resources/de/monticore/lang/monticar/generator/middleware/coordinatorTemplate.ftl

-#include <iostream>
-#include <thread>
-#include <chrono>
-#include <atomic>
-#include <list>
-#include "IAdapter_${compName}.h"
-
-${includes}
-
-using namespace std;
-using namespace chrono;
-
-static int exeMs = 100;
-
-bool parseCommandLineParameters(int argc, char* argv[]){
-  if(argc == 1){
-    return true;
-  }
-  if(argc == 3 && string(argv[1]) == "-t"){
-    try{
-      int tmp = stoi(argv[2]);
-      if(tmp >= 0){
-        exeMs = tmp;
-        return true;
-      }
-    }catch(...){
-      //Ignore
-    }
-  }
-  cout << "Usage: " << argv[0] << " [-h | -t sleepTimeMs]\n";
-  return false;
-}
-
-void startMiddleware(IAdapter_${compName}& adapter,${compName}& comp,atomic<bool>& done){
-  adapter.init(&comp);
-  done = true;
-}
-
-int main(int argc, char* argv[])
-{
-  if(!parseCommandLineParameters(argc,argv)){
-    return 1;
-  }
-
-  atomic<bool> done(false);
-  ${compName} comp;
-  comp.init();
-
-  list<IAdapter_${compName}*> adapters;
-  ${addAdapters}
-
-  list<thread*> threads;
-  for(auto a : adapters){
-    threads.push_back(new thread(startMiddleware,ref(*a),ref(comp),ref(done)));
-  }
-
-  cout << "waiting for all middleware to start\n";
-  this_thread::sleep_for(seconds(3));
-  cout << "started! Executing every " << exeMs << "ms\n";
-
-  time_point<system_clock> start, end;
-  while(!done){
-    start = system_clock::now();
-
-    comp.execute();
-    for(auto a : adapters){
-       (*a).tick();
-    }
-
-    end = system_clock::now();
-    int elapsedMs = duration_cast<milliseconds>(end-start).count();
-    int newSleep = exeMs - elapsedMs;
-    if(newSleep <= 0){
-      cout << "Cant keep up! "<< (-newSleep) <<"ms late!\n";
-    }else{
-       this_thread::sleep_for(milliseconds(newSleep));
-    }
-  }
-
-  return 0;
-}
\ No newline at end of file

CNNModelTraining/src/main/resources/de/monticore/lang/monticar/generator/middleware/struct_msgsCmakeTemplate.ftl

-cmake_minimum_required(VERSION 3.5)
-project (struct_msgs)
-
-find_package(genmsg REQUIRED)
-
-FILE(GLOB MSG_FILES_RAW RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} ../*/roscpp/struct_msgs/*.msg)
-
-#generate struct_msgs iff .msg files where found
-if(MSG_FILES_RAW)
-#filter: add each struct msg only once (distinct by filename without path)
-foreach(CUR_MSG_FILE ${MSG_FILES_RAW})
-get_filename_component(TMP_MSG_NAME ${CUR_MSG_FILE} NAME)
-IF(NOT MSG_DEFINED_${TMP_MSG})
-LIST(APPEND MSG_FILES ${CUR_MSG_FILE})
-SET(MSG_DEFINED_${TMP_MSG} TRUE)
-ENDIF()
-endforeach(CUR_MSG_FILE)
-
-#generate messages
-add_message_files(DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR} FILES ${MSG_FILES})
-generate_messages()
-
-#export the include_dirs, so that other subprojects can use it
-set(struct_msgs_INCLUDE_DIRS ${struct_msgs_INCLUDE_DIRS} PARENT_SCOPE)
-endif()