UI missing features (dotnet#382)

srsaggam · Dmitry-A · commit 727f6c31fd05 · 2019-08-22T14:40:44.000-07:00
* added formatting changes

* added accuracy specifically
diff --git a/src/mlnet/CodeGenerator/CodeGenerationHelper.cs b/src/mlnet/CodeGenerator/CodeGenerationHelper.cs
@@ -39,6 +39,7 @@ public void GenerateCode()
         {
             Stopwatch watch = Stopwatch.StartNew();
             var context = new MLContext();
+            var verboseLevel = Utils.GetVerbosity(settings.Verbosity);
 
             // Infer columns
             ColumnInferenceResults columnInference = null;
@@ -56,7 +57,7 @@ public void GenerateCode()
             {
                 logger.Log(LogLevel.Error, $"{Strings.InferColumnError}");
                 logger.Log(LogLevel.Error, e.Message);
-                logger.Log(LogLevel.Debug, e.ToString());
+                logger.Log(LogLevel.Trace, e.ToString());
                 logger.Log(LogLevel.Error, Strings.Exiting);
                 return;
             }
@@ -79,9 +80,20 @@ public void GenerateCode()
             IEnumerable<RunDetail<BinaryClassificationMetrics>> binaryRunDetails = default;
             IEnumerable<RunDetail<MulticlassClassificationMetrics>> multiRunDetails = default;
             IEnumerable<RunDetail<RegressionMetrics>> regressionRunDetails = default;
+            if (verboseLevel > LogLevel.Trace)
+            {
+                Console.Write($"{Strings.ExplorePipeline}: ");
+                Console.ForegroundColor = ConsoleColor.Yellow;
+                Console.WriteLine($"{settings.MlTask}");
+                Console.ResetColor();
+                Console.Write($"{Strings.FurtherLearning}: ");
+                Console.ForegroundColor = ConsoleColor.Yellow;
+                Console.WriteLine($"{ Strings.LearningHttpLink}");
+                Console.ResetColor();
+            }
 
-            Console.WriteLine($"{Strings.ExplorePipeline}: {settings.MlTask}");
-            Console.WriteLine($"{Strings.FurtherLearning}: {Strings.LearningHttpLink}");
+            logger.Log(LogLevel.Trace, $"{Strings.ExplorePipeline}: {settings.MlTask}");
+            logger.Log(LogLevel.Trace, $"{Strings.FurtherLearning}: {Strings.LearningHttpLink}");
             try
             {
                 var options = new ProgressBarOptions
@@ -93,7 +105,6 @@ public void GenerateCode()
                     BackgroundCharacter = '─',
                 };
                 var wait = TimeSpan.FromSeconds(settings.MaxExplorationTime);
-                var verboseLevel = Utils.GetVerbosity(settings.Verbosity);
 
                 if (verboseLevel > LogLevel.Trace && !Console.IsOutputRedirected)
                 {
@@ -205,8 +216,8 @@ public void GenerateCode()
 
             // Generate the Project
             GenerateProject(columnInference, bestPipeline, columnInformation.LabelColumnName, modelPath);
-            logger.Log(LogLevel.Info, $"{Strings.GenerateModelConsumption} : { Path.Combine(settings.OutputPath.FullName, $"{settings.Name}.Predict")}");
-            logger.Log(LogLevel.Info, $"{Strings.GenerateModelTraining} : { Path.Combine(settings.OutputPath.FullName, $"{settings.Name}.Train")}");
+            logger.Log(LogLevel.Info, $"{Strings.GenerateModelConsumption}: { Path.Combine(settings.OutputPath.FullName, $"{settings.Name}.Predict")}");
+            logger.Log(LogLevel.Info, $"{Strings.GenerateModelTraining}: { Path.Combine(settings.OutputPath.FullName, $"{settings.Name}.Train")}");
             Console.ResetColor();
         }
 
diff --git a/src/mlnet/Utilities/ConsolePrinter.cs b/src/mlnet/Utilities/ConsolePrinter.cs
@@ -81,6 +81,14 @@ internal static void PrintIterationSummary(IEnumerable<RunDetail<BinaryClassific
             foreach (var pair in topNResults)
             {
                 var result = pair.Item1;
+                if (i == 0)
+                {
+                    // Print top iteration colored.
+                    Console.ForegroundColor = ConsoleColor.Yellow;
+                    PrintMetrics(++i, result?.TrainerName, result?.ValidationMetrics, metricsAgent.GetScore(result?.ValidationMetrics), result?.RuntimeInSeconds, LogLevel.Info, pair.Item2);
+                    Console.ResetColor();
+                    continue;
+                }
                 PrintMetrics(++i, result?.TrainerName, result?.ValidationMetrics, metricsAgent.GetScore(result?.ValidationMetrics), result?.RuntimeInSeconds, LogLevel.Info, pair.Item2);
             }
             logger.Log(LogLevel.Info, TABLESEPERATOR);
@@ -99,6 +107,14 @@ internal static void PrintIterationSummary(IEnumerable<RunDetail<RegressionMetri
             foreach (var pair in topNResults)
             {
                 var result = pair.Item1;
+                if (i == 0)
+                {
+                    // Print top iteration colored.
+                    Console.ForegroundColor = ConsoleColor.Yellow;
+                    PrintMetrics(++i, result?.TrainerName, result?.ValidationMetrics, metricsAgent.GetScore(result?.ValidationMetrics), result?.RuntimeInSeconds, LogLevel.Info, pair.Item2);
+                    Console.ResetColor();
+                    continue;
+                }
                 PrintMetrics(++i, result?.TrainerName, result?.ValidationMetrics, metricsAgent.GetScore(result?.ValidationMetrics), result?.RuntimeInSeconds, LogLevel.Info, pair.Item2);
             }
             logger.Log(LogLevel.Info, TABLESEPERATOR);
@@ -116,6 +132,14 @@ internal static void PrintIterationSummary(IEnumerable<RunDetail<MulticlassClass
             foreach (var pair in topNResults)
             {
                 var result = pair.Item1;
+                if (i == 0)
+                {
+                    // Print top iteration colored.
+                    Console.ForegroundColor = ConsoleColor.Yellow;
+                    PrintMetrics(++i, result?.TrainerName, result?.ValidationMetrics, metricsAgent.GetScore(result?.ValidationMetrics), result?.RuntimeInSeconds, LogLevel.Info, pair.Item2);
+                    Console.ResetColor();
+                    continue;
+                }
                 PrintMetrics(++i, result?.TrainerName, result?.ValidationMetrics, metricsAgent.GetScore(result?.ValidationMetrics), result?.RuntimeInSeconds, LogLevel.Info, pair.Item2);
             }
             logger.Log(LogLevel.Info, TABLESEPERATOR);
diff --git a/src/mlnet/Utilities/ProgressHandlers.cs b/src/mlnet/Utilities/ProgressHandlers.cs
@@ -64,12 +64,12 @@ internal class BinaryClassificationHandler : IProgress<RunDetail<BinaryClassific
             private RunDetail<BinaryClassificationMetrics> bestResult;
             private int iterationIndex;
             private ProgressBar progressBar;
-            private string optimizationMetric = string.Empty;
+            private BinaryClassificationMetric optimizationMetric;
 
             public BinaryClassificationHandler(BinaryClassificationMetric optimizationMetric, ProgressBar progressBar)
             {
                 this.isMaximizing = new OptimizingMetricInfo(optimizationMetric).IsMaximizing;
-                this.optimizationMetric = optimizationMetric.ToString();
+                this.optimizationMetric = optimizationMetric;
                 this.progressBar = progressBar;
                 GetScore = (RunDetail<BinaryClassificationMetrics> result) => new BinaryMetricsAgent(null, optimizationMetric).GetScore(result?.ValidationMetrics);
                 ConsolePrinter.PrintBinaryClassificationMetricsHeader(LogLevel.Trace);
@@ -80,14 +80,24 @@ public void Report(RunDetail<BinaryClassificationMetrics> iterationResult)
                 iterationIndex++;
                 UpdateBestResult(iterationResult);
                 if (progressBar != null)
-                    progressBar.Message = $"Best {this.optimizationMetric}: {GetScore(bestResult):F4}, Best Algorithm: {bestResult?.TrainerName}, Last Algorithm: {iterationResult?.TrainerName}";
+                    progressBar.Message = GetProgressBarMessage(iterationResult);
                 ConsolePrinter.PrintMetrics(iterationIndex, iterationResult?.TrainerName, iterationResult?.ValidationMetrics, GetScore(bestResult), iterationResult?.RuntimeInSeconds, LogLevel.Trace);
                 if (iterationResult.Exception != null)
                 {
                     ConsolePrinter.PrintException(iterationResult.Exception, LogLevel.Trace);
                 }
             }
 
+            private string GetProgressBarMessage(RunDetail<BinaryClassificationMetrics> iterationResult)
+            {
+                if (optimizationMetric == BinaryClassificationMetric.Accuracy)
+                {
+                    return $"Best Accuracy: {GetScore(bestResult) * 100:F2}%, Best Algorithm: {bestResult?.TrainerName}, Last Algorithm: {iterationResult?.TrainerName}";
+                }
+
+                return $"Best {this.optimizationMetric}: {GetScore(bestResult):F4}, Best Algorithm: {bestResult?.TrainerName}, Last Algorithm: {iterationResult?.TrainerName}";
+            }
+
             private void UpdateBestResult(RunDetail<BinaryClassificationMetrics> iterationResult)
             {
                 if (MetricComparator(GetScore(iterationResult), GetScore(bestResult), isMaximizing) > 0)
@@ -104,12 +114,12 @@ internal class MulticlassClassificationHandler : IProgress<RunDetail<MulticlassC
             private RunDetail<MulticlassClassificationMetrics> bestResult;
             private int iterationIndex;
             private ProgressBar progressBar;
-            private string optimizationMetric = string.Empty;
+            private MulticlassClassificationMetric optimizationMetric;
 
             public MulticlassClassificationHandler(MulticlassClassificationMetric optimizationMetric, ProgressBar progressBar)
             {
                 this.isMaximizing = new OptimizingMetricInfo(optimizationMetric).IsMaximizing;
-                this.optimizationMetric = optimizationMetric.ToString();
+                this.optimizationMetric = optimizationMetric;
                 this.progressBar = progressBar;
                 GetScore = (RunDetail<MulticlassClassificationMetrics> result) => new MultiMetricsAgent(null, optimizationMetric).GetScore(result?.ValidationMetrics);
                 ConsolePrinter.PrintMulticlassClassificationMetricsHeader(LogLevel.Trace);
@@ -120,7 +130,7 @@ public void Report(RunDetail<MulticlassClassificationMetrics> iterationResult)
                 iterationIndex++;
                 UpdateBestResult(iterationResult);
                 if (progressBar != null)
-                    progressBar.Message = $"Best {this.optimizationMetric}: {GetScore(bestResult):F4}, Best Algorithm: {bestResult?.TrainerName}, Last Algorithm: {iterationResult?.TrainerName}";
+                    progressBar.Message = GetProgressBarMessage(iterationResult);
                 ConsolePrinter.PrintMetrics(iterationIndex, iterationResult?.TrainerName, iterationResult?.ValidationMetrics, GetScore(bestResult), iterationResult?.RuntimeInSeconds, LogLevel.Trace);
                 if (iterationResult.Exception != null)
                 {
@@ -135,6 +145,16 @@ private void UpdateBestResult(RunDetail<MulticlassClassificationMetrics> iterati
                     bestResult = iterationResult;
                 }
             }
+
+            private string GetProgressBarMessage(RunDetail<MulticlassClassificationMetrics> iterationResult)
+            {
+                if (optimizationMetric == MulticlassClassificationMetric.MicroAccuracy)
+                {
+                    return $"Best Accuracy: {GetScore(bestResult) * 100:F2}%, Best Algorithm: {bestResult?.TrainerName}, Last Algorithm: {iterationResult?.TrainerName}";
+                }
+
+                return $"Best {this.optimizationMetric}: {GetScore(bestResult):F4}, Best Algorithm: {bestResult?.TrainerName}, Last Algorithm: {iterationResult?.TrainerName}";
+            }
         }
 
     }
