Merge pull request #491 from microsoft/user/numform/set_model_names

Set Model Names in Samples for Telemetry

Author: nums11

Samples/WinMLSamplesGallery/WinMLSamplesGallery (Package)/WinMLSamplesGallery (Package).wapproj

@@ -132,7 +132,7 @@
   </ItemGroup>
   <Import Project="$(WapProjPath)\Microsoft.DesktopBridge.targets" />
   <ItemGroup>
-    <PackageReference Include="Microsoft.AI.MachineLearning" Version="1.9.1" />
+    <PackageReference Include="Microsoft.AI.MachineLearning" Version="1.11.0" />
     <PackageReference Include="Microsoft.WindowsAppSDK" Version="1.0.0-stable" />
   </ItemGroup>
 </Project>

Samples/WinMLSamplesGallery/WinMLSamplesGallery/Pages/SampleBasePage.xaml.cs

@@ -1,6 +1,8 @@
 using Microsoft.UI.Xaml;
 using Microsoft.UI.Xaml.Controls;
 using Microsoft.UI.Xaml.Navigation;
+using Microsoft.AI.MachineLearning;
+using Microsoft.AI.MachineLearning.Experimental;
 using System;
 
 namespace WinMLSamplesGallery
@@ -56,5 +58,12 @@ protected override async void OnNavigatingFrom(NavigatingCancelEventArgs e)
                 page.StopAllEvents();
             }
         }
+
+        public static void SetModelNameForTelemetry(String modelName, String sampleName, LearningModel model)
+        {
+            var telemetryModelName = modelName + "_" + sampleName;
+            var experimentalModel = new LearningModelExperimental(model);
+            experimentalModel.SetName(telemetryModelName);
+        }
     }
 }

Samples/WinMLSamplesGallery/WinMLSamplesGallery/Samples/AdapterSelection/AdapterSelection.xaml.cs

@@ -33,6 +33,9 @@ public AdapterSelection()
 
             adapter_options.AddRange(adapters);
             AdapterListView.ItemsSource = adapter_options;
+
+            // Run in background thread to avoid blocking UI on sample launch
+            Task.Run(() => SetModelNameForTelemetry(device));
         }
 
         private void ChangeAdapter(object sender, RoutedEventArgs e)
@@ -100,5 +103,16 @@ private List<string> RemoveMicrosoftBasicRenderDriver(string[] adapters_arr)
             }
             return adapters;
         }
+
+        // Session must be created for telemety to be sent
+        private void SetModelNameForTelemetry(LearningModelDevice device)
+        {
+            var modelName = "squeezenet1.1-7.onnx";
+            var modelPath = Path.Join(Windows.ApplicationModel.Package.Current.InstalledLocation.Path, "Models", modelName);
+            var model = LearningModel.LoadFromFilePath(modelPath);
+            var options = new LearningModelSessionOptions();
+            SampleBasePage.SetModelNameForTelemetry("SqueezeNet", "AdapterSelection", model);
+            new LearningModelSession(model, device, options);
+        }
     }
 }

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

@@ -44,6 +44,7 @@ public Batching()
             var modelName = "squeezenet1.1-7-batched.onnx";
             var modelPath = Path.Join(Windows.ApplicationModel.Package.Current.InstalledLocation.Path, "Models", modelName);
             _model = LearningModel.LoadFromFilePath(modelPath);
+            SampleBasePage.SetModelNameForTelemetry("SqueezeNet", "Batching", _model);
         }
 
         async private void StartInference(object sender, RoutedEventArgs e)

Samples/WinMLSamplesGallery/WinMLSamplesGallery/Samples/EncryptedModel/EncryptedModel.xaml.cs

@@ -54,6 +54,7 @@ private void DecryptAndEvauluate()
             // The encrypted model (encrypted.onnx) is embedded as a resource in
             // the native binary: WinMLSamplesGalleryNative.dll.
             var inferenceModel = WinMLSamplesGalleryNative.EncryptedModels.LoadEncryptedResource(DecryptionKey.Password);
+            SampleBasePage.SetModelNameForTelemetry("Encrypted", "EncryptedModel", inferenceModel);
             var postProcessingModel = TensorizationModels.SoftMaxThenTopK(10);
 
             // Update the status

Samples/WinMLSamplesGallery/WinMLSamplesGallery/Samples/ImageClassifier/ImageClassifier.xaml.cs

@@ -243,6 +243,8 @@ private void InitializeWindowsMachineLearning()
             {
                 var modelPath = _modelDictionary[model];
                 var inferenceModel = LearningModel.LoadFromFilePath(modelPath);
+                SetModelNameForTelemetry(inferenceModel);
+
                 _inferenceSession = CreateLearningModelSession(inferenceModel);
 
                 var preProcessor = _preProcessorDictionary[model];
@@ -444,5 +446,13 @@ private void DeviceComboBox_SelectionChanged(object sender, SelectionChangedEven
         {
             TryPerformInference();
         }
+
+        private void SetModelNameForTelemetry(LearningModel model)
+        {
+            var viewModel = (ClassifierViewModel)AllModelsGrid.SelectedItem;
+            var modelName = viewModel.Title;
+            var sampleName = "ImageClassifier";
+            SampleBasePage.SetModelNameForTelemetry(modelName, sampleName, model);
+        }
     }
 }

Samples/WinMLSamplesGallery/WinMLSamplesGallery/Samples/ImageEffects/ImageEffects.xaml.cs

@@ -364,6 +364,7 @@ private LearningModelSession CreateLearningModelSession(LearningModel model, boo
                 CloseModelOnSessionCreation = closeModel, // Close the model to prevent extra memory usage
                 BatchSizeOverride = 0
             };
+            SampleBasePage.SetModelNameForTelemetry("TensorizationModel", "ImageEffects", model);
             var session = new LearningModelSession(model, device, options);
             return session;
         }

Samples/WinMLSamplesGallery/WinMLSamplesGallery/Samples/ImageSharpInterop/ImageSharpInterop.xaml.cs

@@ -61,6 +61,7 @@ public ImageSharpInterop()
             var inferenceModelName = "squeezenet1.1-7.onnx";
             var inferenceModelPath = Path.Join(Windows.ApplicationModel.Package.Current.InstalledLocation.Path, "Models", inferenceModelName);
             var inferenceModel = LearningModel.LoadFromFilePath(inferenceModelPath);
+            SampleBasePage.SetModelNameForTelemetry("SqueezeNet", "ImageSharp", inferenceModel);
             _inferenceSession = CreateLearningModelSession(inferenceModel);
 
             var postProcessingModel = TensorizationModels.SoftMaxThenTopK(TopK);

Samples/WinMLSamplesGallery/WinMLSamplesGallery/WinMLSamplesGallery.csproj

@@ -78,7 +78,7 @@
   </ItemGroup>
 
   <ItemGroup>
-    <PackageReference Include="Microsoft.AI.MachineLearning" Version="1.9.1" />
+    <PackageReference Include="Microsoft.AI.MachineLearning" Version="1.11.0" />
     <PackageReference Include="Microsoft.Windows.CsWinRT" Version="1.3.5" />
     <PackageReference Include="Microsoft.WindowsAppSDK" Version="1.0.0-stable" />
     <PackageReference Include="SixLabors.ImageSharp" Version="1.0.4" />

Samples/WinMLSamplesGallery/WinMLSamplesGalleryNative.Interop/WinMLSamplesGalleryNative.Interop.csproj

@@ -9,7 +9,7 @@
   </PropertyGroup>
 
   <ItemGroup>
-    <PackageReference Include="Microsoft.AI.MachineLearning" Version="1.9.1" />
+    <PackageReference Include="Microsoft.AI.MachineLearning" Version="1.11.0" />
     <PackageReference Include="Microsoft.Windows.CsWinRT" Version="1.3.5" />
   </ItemGroup>
 
@@ -20,7 +20,7 @@
   <Target Name="GenerateProjection" BeforeTargets="DispatchToInnerBuilds;Build;CoreCompile">
     <ItemGroup>
       <WinMLSamplesGalleryNativeWinMDs Include="$(SolutionDir)WinMLSamplesGalleryNative\bin\neutral\WinMLSamplesGalleryNative.winmd" />
-      <WinMLSamplesGalleryNativeWinMDs Include="$(SolutionDir)packages\Microsoft.AI.MachineLearning.1.9.1\winmds\Microsoft.AI.MachineLearning.winmd" />
+      <WinMLSamplesGalleryNativeWinMDs Include="$(SolutionDir)packages\Microsoft.AI.MachineLearning.1.11.0\winmds\Microsoft.AI.MachineLearning.winmd" />
     </ItemGroup>
 
     <PropertyGroup>