[update] test pass fix, CNNSupervisedTrainer.ftl

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

@@ -555,9 +555,12 @@ class ${tc.fileNameWithoutEnding}:
     def __init__(self, data_loader, net_constructor):
         self._data_loader = data_loader
         self._net_creator = net_constructor
+        <#if tc.containsAdaNet()>
         self._dataClass = net_constructor.dataClass
-        self._networks = {}
         self.AdaNet = ${tc.containsAdaNet()?string('True','False')}
+        </#if>
+        self._networks = {}
+
 
     def train(self, batch_size=64,
               num_epoch=10,
@@ -687,8 +690,9 @@ class ${tc.fileNameWithoutEnding}:
         else:
             logging.error("Invalid loss parameter.")
         loss_function.hybridize()
-<#list tc.architecture.networkInstructions as networkInstruction>
 <#if tc.containsAdaNet()>
+<#list tc.architecture.networkInstructions as networkInstruction>
+
         assert self._networks[${networkInstruction?index}].AdaNet, "passed model is not an AdaNet model"
         self._networks[${networkInstruction?index}] = fit(model= self._networks[${networkInstruction?index}],
                     loss=loss_function,
@@ -706,8 +710,8 @@ class ${tc.fileNameWithoutEnding}:
                 )
         logging.info(self._networks[0])
         #put here the AdaNet logic
-</#if>
 </#list>
+</#if>
 <#list tc.architecture.networkInstructions as networkInstruction>    
 <#if networkInstruction.body.episodicSubNetworks?has_content>
 <#assign episodicReplayVisited = true>