Include some missed logging in the generated code. (dotnet#199)

* added logging messages for generated code

* added log messages

* deleted file

Author: srsaggam

src/mlnet.Test/ApprovalTests/ConsoleCodeGeneratorTests.GeneratedTrainCodeTest.approved.txt

@@ -64,6 +64,7 @@ namespace MyNamespace
             var trainingPipeline = dataProcessPipeline.Append(trainer);
 
             // Train the model fitting to the DataSet
+            Console.WriteLine("=============== Training the model ===============");
             var trainedModel = trainingPipeline.Fit(trainingDataView);
 
             // Evaluate the model and show accuracy stats
@@ -73,6 +74,7 @@ namespace MyNamespace
             ConsoleHelper.PrintBinaryClassificationMetrics(trainer.ToString(), metrics);
 
             // Save/persist the trained model to a .ZIP file
+            Console.WriteLine($"=============== Saving the model  ===============");
             using (var fs = new FileStream(ModelPath, FileMode.Create, FileAccess.Write, FileShare.Write))
                 mlContext.Model.Save(trainedModel, fs);
 

src/mlnet/Templates/Console/MLCodeGen.cs

@@ -150,8 +150,9 @@ private static ITransformer BuildTrainEvaluateAndSaveModel(MLContext mlContext)
                     "rics(trainer.ToString(), crossValidationResults);\r\n");
 }
 } 
-            this.Write("\r\n            // Train the model fitting to the DataSet\r\n            var trainedM" +
-                    "odel = trainingPipeline.Fit(trainingDataView);\r\n\r\n");
+            this.Write("\r\n            // Train the model fitting to the DataSet\r\n            Console.Writ" +
+                    "eLine(\"=============== Training the model ===============\");\r\n            var tr" +
+                    "ainedModel = trainingPipeline.Fit(trainingDataView);\r\n\r\n");
  if(!string.IsNullOrEmpty(TestPath)){ 
             this.Write("            // Evaluate the model and show accuracy stats\r\n            Console.Wr" +
                     "iteLine(\"===== Evaluating Model\'s accuracy with Test data =====\");\r\n            " +
@@ -171,6 +172,7 @@ private static ITransformer BuildTrainEvaluateAndSaveModel(MLContext mlContext)
  } 
             this.Write(@"
             // Save/persist the trained model to a .ZIP file
+            Console.WriteLine($""=============== Saving the model  ==============="");
             using (var fs = new FileStream(ModelPath, FileMode.Create, FileAccess.Write, FileShare.Write))
                 mlContext.Model.Save(trainedModel, fs);
 

src/mlnet/Templates/Console/MLCodeGen.tt

@@ -101,6 +101,7 @@ else{#>
 } #>
 
             // Train the model fitting to the DataSet
+            Console.WriteLine("=============== Training the model ===============");
             var trainedModel = trainingPipeline.Fit(trainingDataView);
 
 <# if(!string.IsNullOrEmpty(TestPath)){ #>
@@ -117,6 +118,7 @@ else{#>
 <# } #>
 
             // Save/persist the trained model to a .ZIP file
+            Console.WriteLine($"=============== Saving the model  ===============");
             using (var fs = new FileStream(ModelPath, FileMode.Create, FileAccess.Write, FileShare.Write))
                 mlContext.Model.Save(trainedModel, fs);