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Merge pull request #765 from dotnet/master
Update live with current master
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‎.github/CODEOWNERS‎

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@@ -27,3 +27,5 @@
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/snippets/csharp/** @BillWagner
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# Visual Basic snippets:
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/snippets/visualbasic/** @rpetrusha
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# F# Snippets:
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/snippets/fsharp/** @cartermp

‎machine-learning/tutorials/TransferLearningTF/Program.cs‎

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@@ -18,9 +18,10 @@ class Program
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// <SnippetDeclareGlobalVariables>
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static readonly string _assetsPath = Path.Combine(Environment.CurrentDirectory, "assets");
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static readonly string _trainTagsTsv = Path.Combine(_assetsPath, "inputs-train", "data", "tags.tsv");
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static readonly string _predictTagsTsv = Path.Combine(_assetsPath, "inputs-predict", "data", "tags.tsv");
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static readonly string _predictImageListTsv = Path.Combine(_assetsPath, "inputs-predict", "data", "image_list.tsv");
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static readonly string _trainImagesFolder = Path.Combine(_assetsPath, "inputs-train", "data");
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static readonly string _predictImagesFolder = Path.Combine(_assetsPath, "inputs-predict", "data");
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static readonly string _predictSingleImage = Path.Combine(_assetsPath, "inputs-predict-single", "data", "toaster3.jpg");
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static readonly string _inceptionPb = Path.Combine(_assetsPath, "inputs-train", "inception", "tensorflow_inception_graph.pb");
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static readonly string _inputImageClassifierZip = Path.Combine(_assetsPath, "inputs-predict", "imageClassifier.zip");
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static readonly string _outputImageClassifierZip = Path.Combine(_assetsPath, "outputs", "imageClassifier.zip");
@@ -41,8 +42,12 @@ static void Main(string[] args)
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// </CallSnippetReuseAndTuneInceptionModel>
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// <SnippetCallClassifyImages>
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ClassifyImages(mlContext, _predictTagsTsv, _predictImagesFolder, _outputImageClassifierZip);
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ClassifyImages(mlContext, _predictImageListTsv, _predictImagesFolder, _outputImageClassifierZip);
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// </SnippetCallClassifyImages>
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// <SnippetCallClassifySingleImage>
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ClassifySingleImage(mlContext, _predictSingleImage, _outputImageClassifierZip);
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// </SnippetCallClassifySingleImage>
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}
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// <SnippetInceptionSettings>
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public static void ReuseAndTuneInceptionModel(MLContext mlContext, string dataLocation, string imagesFolder, string inputModelLocation, string outputModelLocation)
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{
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Console.WriteLine("Read model");
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Console.WriteLine($"Model location: {inputModelLocation}");
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Console.WriteLine($"Images folder: {_trainImagesFolder}");
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Console.WriteLine($"Training file: {dataLocation}");
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Console.WriteLine($"Default parameters: image size=({InceptionSettings.ImageWidth},{InceptionSettings.ImageHeight}), image mean: {InceptionSettings.Mean}");
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// <SnippetLoadData>
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var data = mlContext.Data.ReadFromTextFile<ImageData>(path: dataLocation, hasHeader: true);
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var data = mlContext.Data.ReadFromTextFile<ImageData>(path: dataLocation, hasHeader: false);
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// </SnippetLoadData>
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// <SnippetMapValueToKey1>
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{
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Console.WriteLine($"=============== Loading model ===============");
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Console.WriteLine($"Model loaded: {outputModelLocation}");
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// Load the model
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// <SnippetLoadModel>
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ITransformer loadedModel;
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using (var fileStream = new FileStream(outputModelLocation, FileMode.Open))
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loadedModel = mlContext.Model.Load(fileStream);
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// </SnippetLoadModel>
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// Read the tags.tsv file and add the filepath to the image file name
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// Read the image_list.tsv file and add the filepath to the image file name
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// before loading into ImageData
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// <SnippetReadFromTSV>
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var imageData = ReadFromTsv(dataLocation, imagesFolder);
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}
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public static void ClassifySingleImage(MLContext mlContext, string imagePath, string outputModelLocation)
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{
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Console.WriteLine($"=============== Loading model ===============");
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Console.WriteLine($"Model loaded: {outputModelLocation}");
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// Load the model
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// <SnippetLoadModel2>
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ITransformer loadedModel;
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using (var fileStream = new FileStream(outputModelLocation, FileMode.Open))
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loadedModel = mlContext.Model.Load(fileStream);
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// </SnippetLoadModel2>
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// load the fully qualified image file name into ImageData
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// <SnippetLoadImageData>
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var imageData = new ImageData()
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{
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ImagePath = imagePath
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};
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// </SnippetReadFromTSV2>
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// <SnippetPredictSingle>
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// Make prediction function (input = ImageNetData, output = ImageNetPrediction)
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var predictor = loadedModel.CreatePredictionEngine<ImageData, ImagePrediction>(mlContext);
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var prediction = predictor.Predict(imageData);
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// </SnippetPredictSingle>
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Console.WriteLine("=============== Making single image classification ===============");
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// <SnippetDisplayPrediction>
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Console.WriteLine($"Image: {Path.GetFileName(imageData.ImagePath)} predicted as: {prediction.PredictedLabelValue} with score: {prediction.Score.Max()} ");
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// </SnippetDisplayPrediction>
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}
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private static void PairAndDisplayResults(IEnumerable<ImageData> imageNetData, IEnumerable<ImagePrediction> imageNetPredictionData)
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{
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// Builds pairs of (image, prediction) to sync up for display
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.Select(line => line.Split('\t'))
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.Select(line => new ImageData()
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{
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ImagePath = Path.Combine(folder, line[0]),
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Label = line[1],
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ImagePath = Path.Combine(folder, line[0])
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});
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// </SnippetReadFromTsv>
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}

‎machine-learning/tutorials/TransferLearningTF/TransferLearningTF.csproj‎

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<None Update="assets\inputs-predict\data\pizza3.jpg">
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<CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
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</None>
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<None Update="assets\inputs-predict\data\tags.tsv">
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<None Update="assets\inputs-predict\data\Rogalik.jpg">
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<CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
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</None>
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<None Update="assets\inputs-predict\data\image_list.tsv">
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<CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
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</None>
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<None Update="assets\inputs-predict\data\teddy6.jpg">
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<CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
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</None>
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<None Update="assets\inputs-predict\data\toaster3.jpg">
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<None Update="assets\inputs-predict-single\data\toaster3.jpg">
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<CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
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</None>
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<None Update="assets\inputs-predict\imageClassifier.zip">

‎machine-learning/tutorials/TransferLearningTF/assets/inputs-predict/data/toaster3.jpg‎ renamed to ‎machine-learning/tutorials/TransferLearningTF/assets/inputs-predict-single/data/toaster3.jpg‎

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‎machine-learning/tutorials/TransferLearningTF/assets/inputs-predict-single/data/wikimedia.md‎

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MichalPL, [Ok Toaster](https://commons.wikimedia.org/wiki/File:OK._Toaster.jpg) [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/deed.en)

‎machine-learning/tutorials/TransferLearningTF/assets/inputs-predict/data/image_list.tsv‎

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broccoli.png
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pizza3.jpg
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teddy6.jpg

‎machine-learning/tutorials/TransferLearningTF/assets/inputs-predict/data/tags.tsv‎

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‎machine-learning/tutorials/TransferLearningTF/assets/inputs-predict/data/wikimedia.md‎

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MichalPL, [Ok Toaster](https://commons.wikimedia.org/wiki/File:OK._Toaster.jpg) [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/deed.en)
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Agnieszka Kwiecień, [Spinach pizza](https://commons.wikimedia.org/wiki/File:Spinach_pizza.jpg), [GNU Free Documentation License v1.2 or later](https://en.wikipedia.org/wiki/en:GNU_Free_Documentation_License) and [CC BY-SA 3.0](https://creativecommons.org/licenses/by-sa/3.0/legalcode)
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David Monniaux, [Broccoli DSC00862](https://commons.wikimedia.org/wiki/File:Broccoli_DSC00862.png), [GNU Free Documentation License v1.2 or later](https://en.wikipedia.org/wiki/en:GNU_Free_Documentation_License) and [CC BY-SA 3.0](https://creativecommons.org/licenses/by-sa/3.0/legalcode)
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Earlgray.Ler2ra, [My teddy bear](https://commons.wikimedia.org/wiki/File:My_teddy_bear.jpg), [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/deed.en)
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Earlgray.Ler2ra, [My teddy bear](https://commons.wikimedia.org/wiki/File:My_teddy_bear.jpg), [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/deed.en)

‎machine-learning/tutorials/TransferLearningTF/assets/inputs-train/data/tags.tsv‎

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broccoli.jpg broccoli
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pizza.jpg pizza
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pizza2.jpg pizza
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teddy2.jpg teddy
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teddy3.jpg teddy
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teddy4.jpg teddy
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toaster.jpg toaster
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toaster2.png toaster
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broccoli.jpg food
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pizza.jpg food
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pizza2.jpg food
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teddy2.jpg toy
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teddy3.jpg toy
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teddy4.jpg toy
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toaster.jpg appliance
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toaster2.png appliance

‎snippets/cpp/VS_Snippets_Remoting/Classic SoapExtension.ChainStream Example/CPP/source.cpp‎

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return String::Format( "C:\\{0}.log", WebServiceType->FullName );
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}
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// Recieve the filename stored by GetInitializer and store it in a member variable
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// Receive the filename stored by GetInitializer and store it in a member variable
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// for this specific instance.
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virtual void Initialize( Object^ initializer ) override
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{

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