FIX: validation step not performed if not user parameters are set

app/otbTensorflowModelTrain.cxx

@@ -468,32 +468,32 @@ public:
       AddProcess(m_TrainModelFilter, "Training epoch #" + std::to_string(epoch));
       m_TrainModelFilter->Update();
 
-      if (do_validation)
+      // Validate the model
+      if (epoch % GetParameterInt("validation.step") == 0)
       {
-        // Validate the model
-        if (epoch % GetParameterInt("validation.step") == 0)
-        {
-          // 1. Evaluate the metrics against the learning data
+        // 1. Evaluate the metrics against the learning data
 
-          for (unsigned int i = 0 ; i < m_InputSourcesForEvaluationAgainstLearningData.size() ; i++)
-          {
-            m_ValidateModelFilter->SetInput(i, m_InputSourcesForEvaluationAgainstLearningData[i]);
-          }
-          m_ValidateModelFilter->SetInputReferences(m_InputTargetsForEvaluationAgainstLearningData);
+        for (unsigned int i = 0 ; i < m_InputSourcesForEvaluationAgainstLearningData.size() ; i++)
+        {
+          m_ValidateModelFilter->SetInput(i, m_InputSourcesForEvaluationAgainstLearningData[i]);
+        }
+        m_ValidateModelFilter->SetInputReferences(m_InputTargetsForEvaluationAgainstLearningData);
 
-          // As we use the learning data here, it's rational to use the same option as streaming during training
-          m_ValidateModelFilter->SetUseStreaming(GetParameterInt("training.usestreaming"));
+        // As we use the learning data here, it's rational to use the same option as streaming during training
+        m_ValidateModelFilter->SetUseStreaming(GetParameterInt("training.usestreaming"));
 
-          // Update
-          AddProcess(m_ValidateModelFilter, "Evaluate model (Learning data)");
-          m_ValidateModelFilter->Update();
+        // Update
+        AddProcess(m_ValidateModelFilter, "Evaluate model (Learning data)");
+        m_ValidateModelFilter->Update();
 
-          for (unsigned int i = 0 ; i < m_TargetTensorsNames.size() ; i++)
-          {
-            otbAppLogINFO("Metrics for target \"" << m_TargetTensorsNames[i] << "\":");
-            PrintClassificationMetrics(m_ValidateModelFilter->GetConfusionMatrix(i), m_ValidateModelFilter->GetMapOfClasses(i));
-          }
+        for (unsigned int i = 0 ; i < m_TargetTensorsNames.size() ; i++)
+        {
+          otbAppLogINFO("Metrics for target \"" << m_TargetTensorsNames[i] << "\":");
+          PrintClassificationMetrics(m_ValidateModelFilter->GetConfusionMatrix(i), m_ValidateModelFilter->GetMapOfClasses(i));
+        }
 
+        if (do_validation)
+        {
           // 2. Evaluate the metrics against the validation data
 
           // Here we just change the input sources and references
@@ -514,7 +514,7 @@ public:
             PrintClassificationMetrics(m_ValidateModelFilter->GetConfusionMatrix(i), m_ValidateModelFilter->GetMapOfClasses(i));
           }
         } // Step is OK to perform validation
-      }
+      } // Do the validation against the validation data
 
       } // Next epoch