ui fixes and code cleanup

Author: Sheil Kumar

Samples/WinMLSamplesGallery/.editorconfig

@@ -0,0 +1,4 @@
+[*.cs]
+
+# CA1416: Validate platform compatibility
+dotnet_diagnostic.CA1416.severity = silent

Samples/WinMLSamplesGallery/WinMLSamplesGallery.sln

@@ -1,7 +1,7 @@
 
 Microsoft Visual Studio Solution File, Format Version 12.00
-# Visual Studio Version 16
-VisualStudioVersion = 16.0.31112.23
+# Visual Studio Version 17
+VisualStudioVersion = 17.0.31919.166
 MinimumVisualStudioVersion = 10.0.40219.1
 Project("{C7167F0D-BC9F-4E6E-AFE1-012C56B48DB5}") = "WinMLSamplesGallery (Package)", "WinMLSamplesGallery (Package)\WinMLSamplesGallery (Package).wapproj", "{DEA7791F-55CF-4ED5-BC99-3870997B1242}"
 EndProject
@@ -11,6 +11,11 @@ Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "WinMLSamplesGalleryNative",
 EndProject
 Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "WinMLSamplesGalleryNative.Interop", "WinMLSamplesGalleryNative.Interop\WinMLSamplesGalleryNative.Interop.csproj", "{8E1F2E33-58A3-4454-926E-1C98B93A2A30}"
 EndProject
+Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "Solution Items", "Solution Items", "{7EDD189E-04E6-432A-80A6-7811E157E9F6}"
+	ProjectSection(SolutionItems) = preProject
+		.editorconfig = .editorconfig
+	EndProjectSection
+EndProject
 Global
 	GlobalSection(SolutionConfigurationPlatforms) = preSolution
 		Debug|arm64 = Debug|arm64

Samples/WinMLSamplesGallery/WinMLSamplesGallery/MainWindow.xaml

@@ -17,7 +17,9 @@
             AlwaysShowHeader="False"
             PaneTitle="Windows ML"
             FontFamily="Arial"
-            IsSettingsVisible="False">
+            IsSettingsVisible="False"
+            PaneClosing="nvSample_PaneClosing"
+            PaneOpening="nvSample_PaneOpening">
             <NavigationView.Resources>
                 <SolidColorBrush x:Key="NavigationViewExpandedPaneBackground" Color="#f5f5f5"/>
                 <SolidColorBrush x:Key="NavigationViewDefaultPaneBackground" Color="#f5f5f5" />
@@ -26,11 +28,13 @@
                 <NavigationViewItem Icon="Flag" Content="Home" Tag="home" />
                 <NavigationViewItem Icon="Library" Content="All samples" Tag="all_samples" />
                 <NavigationViewItemSeparator />
-                <TextBlock>
-                    <Hyperlink TextDecorations="None" NavigateUri="https://docs.microsoft.com/en-us/windows/ai/windows-ml/">
-                        Learn more about Windows ML
-                    </Hyperlink>
-                </TextBlock>
+                <Grid>
+                    <TextBlock x:Name="LearnMoreLink">
+                        <Hyperlink  TextDecorations="None" NavigateUri="https://docs.microsoft.com/en-us/windows/ai/windows-ml/">
+                            Learn more about Windows ML
+                        </Hyperlink>
+                    </TextBlock>
+                </Grid>
             </NavigationView.MenuItems>
             <Frame x:Name="contentFrame" Navigated="contentFrame_Navigated" BorderBrush="#dbdbdb" BorderThickness="1,1,0,0" Margin="0,40,0,0"
                    CornerRadius="5,0,0,0" Background="White" FontFamily="Arial"/>

Samples/WinMLSamplesGallery/WinMLSamplesGallery/MainWindow.xaml.cs

@@ -110,5 +110,15 @@ private void nvSample_Loaded(object sender, RoutedEventArgs e)
             // here to load the home page.
             NavView_Navigate("home", new Microsoft.UI.Xaml.Media.Animation.EntranceNavigationTransitionInfo());
         }
+
+        private void nvSample_PaneClosing(NavigationView sender, NavigationViewPaneClosingEventArgs args)
+        {
+            LearnMoreLink.Visibility = Visibility.Collapsed;
+        }
+
+        private void nvSample_PaneOpening(NavigationView sender, object args)
+        {
+            LearnMoreLink.Visibility = Visibility.Visible;
+        }
     }
 }

Samples/WinMLSamplesGallery/WinMLSamplesGallery/Samples/Batching/Batching.xaml.cs

@@ -3,6 +3,7 @@
 using Microsoft.UI.Xaml.Controls;
 using System;
 using System.Collections.Generic;
+using System.IO;
 using System.Threading.Tasks;
 using Windows.Graphics.Imaging;
 using Windows.Media;
@@ -19,14 +20,15 @@ public sealed class EvalResult
 
     public sealed partial class Batching : Page
     {
-        const int numInputImages = 50;
-        const int numEvalIterations = 100;
+        const int NumInputImages = 50;
+        const int NumEvalIterations = 100;
 
-        private LearningModelSession nonBatchingSession_;
-        private LearningModelSession batchingSession_;
-
-        float avgNonBatchedDuration_ = 0;
-        float avgBatchDuration_ = 0;
+        private LearningModel _model = null;
+        private LearningModelSession _nonBatchingSession = null;
+        private LearningModelSession _batchingSession = null;
+
+        float _avgNonBatchedDuration = 0;
+        float _avgBatchDuration = 0;
 
         // Marked volatile since it's updated across threads
         static volatile bool navigatingAwayFromPage = false;
@@ -36,28 +38,35 @@ public Batching()
         {
             this.InitializeComponent();
             // Ensure static variable is always false on page initialization
-            navigatingAwayFromPage = false;
+            navigatingAwayFromPage = false;
+
+            // Load the model
+            var modelName = "squeezenet1.1-7-batched.onnx";
+            var modelPath = Path.Join(Windows.ApplicationModel.Package.Current.InstalledLocation.Path, "Models", modelName);
+            _model = LearningModel.LoadFromFilePath(modelPath);
         }
 
         async private void StartInference(object sender, RoutedEventArgs e)
         {
-            ShowEvalUI();
-            ResetEvalMetrics();
+            ShowStatus();
+            ResetMetrics();
 
             var inputImages = await GetInputImages();
             int batchSize = GetBatchSizeFromBatchSizeSlider();
-            await CreateSessions(batchSize);
 
-            UpdateEvalText(false);
+            _nonBatchingSession = await CreateLearningModelSession(_model);
+            _batchingSession = await CreateLearningModelSession(_model, batchSize);
+
+            UpdateStatus(false);
             await Classify(inputImages);
 
-            UpdateEvalText(true);
+            UpdateStatus(true);
             await ClassifyBatched(inputImages, batchSize);
 
-            GenerateEvalResultAndUI();
+            ShowUI();
         }
 
-        private void ShowEvalUI()
+        private void ShowStatus()
         {
             StartInferenceBtn.IsEnabled = false;
             BatchSizeSlider.IsEnabled = false;
@@ -66,10 +75,10 @@ private void ShowEvalUI()
             LoadingContainer.Visibility = Visibility.Visible;
         }
 
-        private void ResetEvalMetrics()
+        private void ResetMetrics()
         {
-            avgNonBatchedDuration_ = 0;
-            avgBatchDuration_ = 0;
+            _avgNonBatchedDuration = 0;
+            _avgBatchDuration = 0;
         }
 
         // Test input consists of 50 images (25 bird and 25 cat)
@@ -80,7 +89,7 @@ private async Task<List<VideoFrame>> GetInputImages()
             var birdImage = await CreateSoftwareBitmapFromStorageFile(birdFile);
             var catImage = await CreateSoftwareBitmapFromStorageFile(catFile);
             var inputImages = new List<VideoFrame>();
-            for (int i = 0; i < numInputImages / 2; i++)
+            for (int i = 0; i < NumInputImages / 2; i++)
             {
                 inputImages.Add(VideoFrame.CreateWithSoftwareBitmap(birdImage));
                 inputImages.Add(VideoFrame.CreateWithSoftwareBitmap(catImage));
@@ -96,30 +105,23 @@ private async Task<SoftwareBitmap> CreateSoftwareBitmapFromStorageFile(StorageFi
             return bitmap;
         }
 
-        private void UpdateEvalText(bool isBatchingEval)
-        {
-            if (isBatchingEval)
-                EvalText.Text = "Inferencing Batched Inputs:";
-            else
-                EvalText.Text = "Inferencing Non-Batched Inputs:";
-        }
-
-        private async Task CreateSessions(int batchSizeOverride)
+        private void UpdateStatus(bool isBatchingEval)
         {
-            var modelPath = "ms-appx:///Models/squeezenet1.1-7-batched.onnx";
-            nonBatchingSession_ = await CreateLearningModelSession(modelPath);
-            batchingSession_ = await CreateLearningModelSession(modelPath, batchSizeOverride);
+            if (isBatchingEval)
+            {
+                EvalText.Text = "Inferencing Batched Inputs:";
+            }
+            else
+            {
+                EvalText.Text = "Inferencing Non-Batched Inputs:";
+            }
         }
 
-        private async Task<LearningModelSession> CreateLearningModelSession(string modelPath, int batchSizeOverride=-1)
+        private async Task<LearningModelSession> CreateLearningModelSession(LearningModel model, int batchSizeOverride=-1)
         {
-            var model = await CreateLearningModel(modelPath);
             var deviceKind = DeviceComboBox.GetDeviceKind();
             var device = new LearningModelDevice(deviceKind);
-            var options = new LearningModelSessionOptions()
-            {
-                CloseModelOnSessionCreation = true // Close the model to prevent extra memory usage
-            };
+            var options = new LearningModelSessionOptions();
             if (batchSizeOverride > 0)
             {
                 options.BatchSizeOverride = (uint)batchSizeOverride;
@@ -128,26 +130,21 @@ private async Task<LearningModelSession> CreateLearningModelSession(string model
             return session;
         }
 
-        private static async Task<LearningModel> CreateLearningModel(string modelPath)
-        {
-            var uri = new Uri(modelPath);
-            var file = await StorageFile.GetFileFromApplicationUriAsync(uri);
-            var model = await LearningModel.LoadFromStorageFileAsync(file);
-            return model;
-        }
-
         async private Task Classify(List<VideoFrame> inputImages)
         {
             float totalEvalDurations = 0;
-            for (int i = 0; i < numEvalIterations; i++)
+            for (int i = 0; i < NumEvalIterations; i++)
             {
-                if (navigatingAwayFromPage)
-                    break;
-                UpdateEvalProgressUI(i);
-                float evalDuration = await Task.Run(() => Evaluate(nonBatchingSession_, inputImages));
+                if (navigatingAwayFromPage)
+                {
+                    break;
+                }
+
+                UpdateProgress(i);
+                float evalDuration = await Task.Run(() => Evaluate(_nonBatchingSession, inputImages));
                 totalEvalDurations += evalDuration;
             }
-            avgNonBatchedDuration_ = totalEvalDurations / numEvalIterations;
+            _avgNonBatchedDuration = totalEvalDurations / NumEvalIterations;
         }
 
         private static float Evaluate(LearningModelSession session, List<VideoFrame> input)
@@ -157,8 +154,11 @@ private static float Evaluate(LearningModelSession session, List<VideoFrame> inp
             var binding = new LearningModelBinding(session);
             for (int j = 0; j < input.Count; j++)
             {
-                if (navigatingAwayFromPage)
-                    break;
+                if (navigatingAwayFromPage)
+                {
+                    break;
+                }
+
                 var start = HighResolutionClock.UtcNow();
                 binding.Bind(inputName, input[j]);
                 session.Evaluate(binding, "");
@@ -172,15 +172,15 @@ private static float Evaluate(LearningModelSession session, List<VideoFrame> inp
         async private Task ClassifyBatched(List<VideoFrame> inputImages, int batchSize)
         {
             float totalEvalDurations = 0;
-            for (int i = 0; i < numEvalIterations; i++)
+            for (int i = 0; i < NumEvalIterations; i++)
             {
                 if (navigatingAwayFromPage)
                     break;
-                UpdateEvalProgressUI(i);
-                float evalDuration = await Task.Run(() => EvaluateBatched(batchingSession_, inputImages, batchSize));
+                UpdateProgress(i);
+                float evalDuration = await Task.Run(() => EvaluateBatched(_batchingSession, inputImages, batchSize));
                 totalEvalDurations += evalDuration;
             }
-            avgBatchDuration_ = totalEvalDurations / numEvalIterations;
+            _avgBatchDuration = totalEvalDurations / NumEvalIterations;
         }
 
         private static float EvaluateBatched(LearningModelSession session, List<VideoFrame> input, int batchSize)
@@ -191,8 +191,11 @@ private static float EvaluateBatched(LearningModelSession session, List<VideoFra
             var binding = new LearningModelBinding(session);
             for (int i = 0; i < numBatches; i++)
             {
-                if (navigatingAwayFromPage)
-                    break;
+                if (navigatingAwayFromPage)
+                {
+                    break;
+                }
+
                 int rangeStart = batchSize * i;
                 List<VideoFrame> batch;
                 // Add padding to the last batch if necessary
@@ -222,19 +225,19 @@ private int GetBatchSizeFromBatchSizeSlider()
             return int.Parse(BatchSizeSlider.Value.ToString());
         }
 
-        private void UpdateEvalProgressUI(int attemptNumber)
+        private void UpdateProgress(int attemptNumber)
         {
-            EvalProgressText.Text = "Attempt " + attemptNumber.ToString() + "/" + numEvalIterations.ToString();
+            EvalProgressText.Text = "Attempt " + attemptNumber.ToString() + "/" + NumEvalIterations.ToString();
             EvalProgressBar.Value = attemptNumber + 1;
         }
 
-        private void GenerateEvalResultAndUI()
+        private void ShowUI()
         {
-            float ratio = (1 - (avgBatchDuration_ / avgNonBatchedDuration_)) * 100;
+            float ratio = (1 - (_avgBatchDuration / _avgNonBatchedDuration)) * 100;
             var evalResult = new EvalResult
             {
-                nonBatchedAvgTime = avgNonBatchedDuration_.ToString("0.00"),
-                batchedAvgTime = avgBatchDuration_.ToString("0.00"),
+                nonBatchedAvgTime = _avgNonBatchedDuration.ToString("0.00"),
+                batchedAvgTime = _avgBatchDuration.ToString("0.00"),
                 timeRatio = ratio.ToString("0.0")
             };
             List<EvalResult> results = new List<EvalResult>();