Add num_epoch and eval_metric training parameters to the CNNTrainer.ftl...

Add num_epoch and eval_metric training parameters to the CNNTrainer.ftl template and correct target code for corresponding test

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

@@ -16,6 +16,9 @@ if __name__ == "__main__":
 <#if (config.batchSize)??>
         batch_size = ${config.batchSize},
 </#if>
+<#if (config.numEpoch)??>
+        num_epoch = ${config.numEpoch},
+</#if>
 <#if (config.loadCheckpoint)??>
         load_checkpoint = ${config.loadCheckpoint?string("True","False")},
 </#if>
@@ -25,6 +28,9 @@ if __name__ == "__main__":
 <#if (config.normalize)??>
         normalize = ${config.normalize?string("True","False")},
 </#if>
+<#if (config.evalMetric)??>
+        eval_metric = ${config.evalMetric},
+</#if>
 <#if (config.configuration.optimizer)??>
         optimizer = '${config.optimizerName}',
         optimizer_params = {

src/test/resources/target_code/CNNTrainer_main.py

@@ -12,6 +12,7 @@ if __name__ == "__main__":
     main_net1 = CNNCreator_main_net1.CNNCreator_main_net1()
     main_net1.train(
         batch_size = 64,
+        num_epoch = 10,
         load_checkpoint = False,
         context = 'gpu',
         normalize = True,
@@ -25,6 +26,7 @@ if __name__ == "__main__":
     main_net2 = CNNCreator_main_net2.CNNCreator_main_net2()
     main_net2.train(
         batch_size = 32,
+        num_epoch = 10,
         load_checkpoint = False,
         context = 'gpu',
         normalize = True,