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Merge pull request #852 from dotnet/master
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‎csharp/events/Program.cs‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -96,7 +96,7 @@ public void Search(string directory, string searchPattern, bool searchSubDirs =
9696
{
9797
directoryChanged?.Invoke(this,
9898
new SearchDirectoryArgs(dir, totalDirs, completedDirs++));
99-
// Recursively search this child directory:
99+
// Search 'dir' and its subdirectories for files that match the search pattern:
100100
SearchDirectory(dir, searchPattern);
101101
}
102102
// Include the Current Directory:

‎machine-learning/tutorials/MovieRecommendation/MovieRecommendation.csproj‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -6,8 +6,8 @@
66
</PropertyGroup>
77

88
<ItemGroup>
9-
<PackageReference Include="Microsoft.ML" Version="0.11.0" />
10-
<PackageReference Include="Microsoft.ML.Recommender" Version="0.11.0" />
9+
<PackageReference Include="Microsoft.ML" Version="1.0.0-preview" />
10+
<PackageReference Include="Microsoft.ML.Recommender" Version="0.12.0-preview" />
1111
</ItemGroup>
1212

1313
<ItemGroup>

‎machine-learning/tutorials/MovieRecommendation/Program.cs‎

Lines changed: 6 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -3,8 +3,6 @@
33
using System.IO;
44
using Microsoft.ML;
55
using Microsoft.ML.Trainers;
6-
using Microsoft.ML.Data;
7-
using Microsoft.Data.DataView;
86
// </SnippetUsingStatements>
97

108
namespace MovieRecommendation
@@ -43,7 +41,7 @@ static void Main(string[] args)
4341

4442
// Save model
4543
// <SnippetSaveModelMain>
46-
SaveModel(mlContext, model);
44+
SaveModel(mlContext, trainingDataView.Schema, model);
4745
// </SnippetSaveModelMain>
4846
}
4947

@@ -103,11 +101,11 @@ public static void EvaluateModel(MLContext mlContext, IDataView testDataView, IT
103101
// </SnippetTransform>
104102

105103
// <SnippetEvaluate>
106-
var metrics = mlContext.Regression.Evaluate(prediction, label: DefaultColumnNames.Label, score: DefaultColumnNames.Score);
104+
var metrics = mlContext.Regression.Evaluate(prediction, labelColumnName: "Label", scoreColumnName: "Score");
107105
// </SnippetEvaluate>
108106

109107
// <SnippetPrintMetrics>
110-
Console.WriteLine("Rms: " + metrics.Rms.ToString());
108+
Console.WriteLine("Root Mean Squared Error : " + metrics.RootMeanSquaredError.ToString());
111109
Console.WriteLine("RSquared: " + metrics.RSquared.ToString());
112110
// </SnippetPrintMetrics>
113111
}
@@ -117,7 +115,7 @@ public static void UseModelForSinglePrediction(MLContext mlContext, ITransformer
117115
{
118116
// <SnippetPredictionEngine>
119117
Console.WriteLine("=============== Making a prediction ===============");
120-
var predictionEngine = model.CreatePredictionEngine<MovieRating, MovieRatingPrediction>(mlContext);
118+
var predictionEngine = mlContext.Model.CreatePredictionEngine<MovieRating, MovieRatingPrediction>(model);
121119
// </SnippetPredictionEngine>
122120

123121
// Create test input & make single prediction
@@ -140,15 +138,14 @@ public static void UseModelForSinglePrediction(MLContext mlContext, ITransformer
140138
}
141139

142140
//Save model
143-
public static void SaveModel(MLContext mlContext, ITransformer model)
141+
public static void SaveModel(MLContext mlContext, DataViewSchema trainingDataViewSchema, ITransformer model)
144142
{
145143
// Save the trained model to .zip file
146144
// <SnippetSaveModel>
147145
var modelPath = Path.Combine(Environment.CurrentDirectory, "Data", "MovieRecommenderModel.zip");
148146

149147
Console.WriteLine("=============== Saving the model to a file ===============");
150-
using (var fs = new FileStream(modelPath, FileMode.Create, FileAccess.Write, FileShare.Write))
151-
mlContext.Model.Save(model, fs);
148+
mlContext.Model.Save(model, trainingDataViewSchema, modelPath);
152149
// </SnippetSaveModel>
153150
}
154151

‎machine-learning/tutorials/TransferLearningTF/ImagePrediction.cs‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -3,7 +3,7 @@
33
namespace TransferLearningTF
44
{
55
// <SnippetDeclareTypes>
6-
public class ImagePrediction
6+
public class ImagePrediction : ImageData
77
{
88
public float[] Score;
99

‎machine-learning/tutorials/TransferLearningTF/Program.cs‎

Lines changed: 44 additions & 74 deletions
Original file line numberDiff line numberDiff line change
@@ -1,14 +1,13 @@
1-
// <SnippetAddUsings>
1+
// <SnippetAddUsings>
22
using System;
33
using System.Collections.Generic;
44
using System.IO;
55
using System.Linq;
6-
using Microsoft.Data.DataView;
76
using Microsoft.ML;
8-
using Microsoft.ML.Core.Data;
97
using Microsoft.ML.Data;
10-
using Microsoft.ML.ImageAnalytics;
8+
using Microsoft.ML.Data.IO;
119
using Microsoft.ML.Trainers;
10+
using Microsoft.ML.Transforms.Image;
1211
// </SnippetAddUsings>
1312

1413
namespace TransferLearningTF
@@ -26,27 +25,26 @@ class Program
2625
static readonly string _inputImageClassifierZip = Path.Combine(_assetsPath, "inputs-predict", "imageClassifier.zip");
2726
static readonly string _outputImageClassifierZip = Path.Combine(_assetsPath, "outputs", "imageClassifier.zip");
2827
private static string LabelTokey = nameof(LabelTokey);
29-
private static string ImageReal = nameof(ImageReal);
3028
private static string PredictedLabelValue = nameof(PredictedLabelValue);
3129
// </SnippetDeclareGlobalVariables>
3230

3331
static void Main(string[] args)
3432
{
3533
// Create MLContext to be shared across the model creation workflow objects
3634
// <SnippetCreateMLContext>
37-
MLContext mlContext = new MLContext(seed:1);
35+
MLContext mlContext = new MLContext(seed: 1);
3836
// </SnippetCreateMLContext>
3937

4038
// <SnippetCallReuseAndTuneInceptionModel>
41-
ReuseAndTuneInceptionModel(mlContext, _trainTagsTsv, _trainImagesFolder, _inceptionPb, _outputImageClassifierZip);
39+
var model = ReuseAndTuneInceptionModel(mlContext, _trainTagsTsv, _trainImagesFolder, _inceptionPb, _outputImageClassifierZip);
4240
// </SnippetCallReuseAndTuneInceptionModel>
4341

4442
// <SnippetCallClassifyImages>
45-
ClassifyImages(mlContext, _predictImageListTsv, _predictImagesFolder, _outputImageClassifierZip);
43+
ClassifyImages(mlContext, _predictImageListTsv, _predictImagesFolder, _outputImageClassifierZip, model);
4644
// </SnippetCallClassifyImages>
4745

4846
// <SnippetCallClassifySingleImage>
49-
ClassifySingleImage(mlContext, _predictSingleImage, _outputImageClassifierZip);
47+
ClassifySingleImage(mlContext, _predictSingleImage, _outputImageClassifierZip, model);
5048
// </SnippetCallClassifySingleImage>
5149
}
5250

@@ -62,32 +60,34 @@ private struct InceptionSettings
6260
// </SnippetInceptionSettings>
6361

6462
// Build and train model
65-
public static void ReuseAndTuneInceptionModel(MLContext mlContext, string dataLocation, string imagesFolder, string inputModelLocation, string outputModelLocation)
63+
public static ITransformer ReuseAndTuneInceptionModel(MLContext mlContext, string dataLocation, string imagesFolder, string inputModelLocation, string outputModelLocation)
6664
{
6765

6866
// <SnippetLoadData>
69-
var data = mlContext.Data.ReadFromTextFile<ImageData>(path: dataLocation, hasHeader: false);
67+
var data = mlContext.Data.LoadFromTextFile<ImageData>(path: dataLocation, hasHeader: false);
7068
// </SnippetLoadData>
7169

7270
// <SnippetMapValueToKey1>
73-
var estimator = mlContext.Transforms.Conversion.MapValueToKey(outputColumnName: LabelTokey, inputColumnName: DefaultColumnNames.Label)
71+
var estimator = mlContext.Transforms.Conversion.MapValueToKey(outputColumnName: LabelTokey, inputColumnName: "Label")
7472
// </SnippetMapValueToKey1>
7573
// The image transforms transform the images into the model's expected format.
7674
// <SnippetImageTransforms>
77-
.Append(mlContext.Transforms.LoadImages(_trainImagesFolder, (ImageReal, nameof(ImageData.ImagePath))))
78-
.Append(mlContext.Transforms.Resize(outputColumnName: ImageReal, imageWidth: InceptionSettings.ImageWidth, imageHeight: InceptionSettings.ImageHeight, inputColumnName: ImageReal))
79-
.Append(mlContext.Transforms.ExtractPixels(new ImagePixelExtractorTransformer.ColumnInfo(name: "input", inputColumnName: ImageReal, interleave: InceptionSettings.ChannelsLast, offset: InceptionSettings.Mean)))
75+
.Append(mlContext.Transforms.LoadImages(outputColumnName: "input", imageFolder: _trainImagesFolder, inputColumnName: nameof(ImageData.ImagePath)))
76+
.Append(mlContext.Transforms.ResizeImages(outputColumnName: "input", imageWidth: InceptionSettings.ImageWidth, imageHeight: InceptionSettings.ImageHeight, inputColumnName: "input"))
77+
.Append(mlContext.Transforms.ExtractPixels(outputColumnName: "input", interleavePixelColors: InceptionSettings.ChannelsLast, offsetImage: InceptionSettings.Mean))
8078
// </SnippetImageTransforms>
8179
// The ScoreTensorFlowModel transform scores the TensorFlow model and allows communication
8280
// <SnippetScoreTensorFlowModel>
83-
.Append(mlContext.Transforms.ScoreTensorFlowModel(modelLocation: inputModelLocation, outputColumnNames: new[] { "softmax2_pre_activation" }, inputColumnNames: new[] { "input" }))
81+
.Append(mlContext.Model.LoadTensorFlowModel(inputModelLocation).
82+
ScoreTensorFlowModel(outputColumnNames: new[] { "softmax2_pre_activation" }, inputColumnNames: new[] { "input" }, addBatchDimensionInput: true))
8483
// </SnippetScoreTensorFlowModel>
8584
// <SnippetAddTrainer>
86-
.Append(mlContext.MulticlassClassification.Trainers.LogisticRegression(labelColumn: LabelTokey, featureColumn: "softmax2_pre_activation"))
85+
.Append(mlContext.MulticlassClassification.Trainers.LbfgsMaximumEntropy(labelColumnName: LabelTokey, featureColumnName: "softmax2_pre_activation"))
8786
// </SnippetAddTrainer>
8887
// <SnippetMapValueToKey2>
89-
.Append(mlContext.Transforms.Conversion.MapKeyToValue((PredictedLabelValue, DefaultColumnNames.PredictedLabel)));
90-
// </SnippetMapValueToKey2>
88+
.Append(mlContext.Transforms.Conversion.MapKeyToValue(PredictedLabelValue, "PredictedLabel"))
89+
.AppendCacheCheckpoint(mlContext);
90+
// </SnippetMapValueToKey2>
9191

9292
// Train the model
9393
Console.WriteLine("=============== Training classification model ===============");
@@ -105,92 +105,67 @@ public static void ReuseAndTuneInceptionModel(MLContext mlContext, string dataLo
105105
// Create enumerables for both the ImageData and ImagePrediction DataViews
106106
// for displaying results
107107
// <SnippetEnumerateDataViews>
108-
var imageData = mlContext.CreateEnumerable<ImageData>(data, false, true);
109-
var imagePredictionData = mlContext.CreateEnumerable<ImagePrediction>(predictions, false, true);
108+
var imageData = mlContext.Data.CreateEnumerable<ImageData>(data, false, true);
109+
var imagePredictionData = mlContext.Data.CreateEnumerable<ImagePrediction>(predictions, false, true);
110110
// </SnippetEnumerateDataViews>
111111

112-
// Read the tags.tsv file and add the filepath to the image file name
113-
// before loading into ImageData
114-
// <SnippetCallPairAndDisplayResults1>
115-
PairAndDisplayResults(imageData, imagePredictionData);
116-
// </SnippetCallPairAndDisplayResults1>
112+
// <SnippetCallDisplayResults1>
113+
DisplayResults(imagePredictionData);
114+
// </SnippetCallDisplayResults1>
117115

118116
// Get some performance metrics on the model using training data
119117
Console.WriteLine("=============== Classification metrics ===============");
120118

121119
// <SnippetEvaluate>
122-
var regressionContext = new MulticlassClassificationCatalog(mlContext);
123-
var metrics = regressionContext.Evaluate(predictions, label: LabelTokey, predictedLabel: DefaultColumnNames.PredictedLabel);
120+
var multiclassContext = mlContext.MulticlassClassification;
121+
var metrics = multiclassContext.Evaluate(predictions, labelColumnName: LabelTokey, predictedLabelColumnName: "PredictedLabel");
124122
// </SnippetEvaluate>
125123

126124
//<SnippetDisplayMetrics>
127125
Console.WriteLine($"LogLoss is: {metrics.LogLoss}");
128126
Console.WriteLine($"PerClassLogLoss is: {String.Join(" , ", metrics.PerClassLogLoss.Select(c => c.ToString()))}");
129127
//</SnippetDisplayMetrics>
130128

131-
// Save the model to assets/outputs
132-
Console.WriteLine("=============== Save model to local file ===============");
133-
134-
// <SnippetSaveModel>
135-
using (var fileStream = new FileStream(outputModelLocation, FileMode.Create))
136-
mlContext.Model.Save(model, fileStream);
137-
// </SnippetSaveModel>
138-
139-
Console.WriteLine($"Model saved: {outputModelLocation}");
129+
// <SnippetReturnModel>
130+
return model;
131+
// </SnippetReturnModel>
140132
}
141133

142-
public static void ClassifyImages(MLContext mlContext, string dataLocation, string imagesFolder, string outputModelLocation)
134+
public static void ClassifyImages(MLContext mlContext, string dataLocation, string imagesFolder, string outputModelLocation, ITransformer model)
143135
{
144-
Console.WriteLine($"=============== Loading model ===============");
145-
Console.WriteLine($"Model loaded: {outputModelLocation}");
146-
// Load the model
147-
// <SnippetLoadModel>
148-
ITransformer loadedModel;
149-
using (var fileStream = new FileStream(outputModelLocation, FileMode.Open))
150-
loadedModel = mlContext.Model.Load(fileStream);
151-
// </SnippetLoadModel>
152136

153137
// Read the image_list.tsv file and add the filepath to the image file name
154138
// before loading into ImageData
155139
// <SnippetReadFromTSV>
156140
var imageData = ReadFromTsv(dataLocation, imagesFolder);
157-
var imageDataView = mlContext.Data.ReadFromEnumerable<ImageData>(imageData);
141+
var imageDataView = mlContext.Data.LoadFromEnumerable<ImageData>(imageData);
158142
// </SnippetReadFromTSV>
159-
143+
160144
// <SnippetPredict>
161-
var predictions = loadedModel.Transform(imageDataView);
162-
var imagePredictionData = mlContext.CreateEnumerable<ImagePrediction>(predictions, false,true);
145+
var predictions = model.Transform(imageDataView);
146+
var imagePredictionData = mlContext.Data.CreateEnumerable<ImagePrediction>(predictions, false, true);
163147
// </SnippetPredict>
164148

165149
Console.WriteLine("=============== Making classifications ===============");
166-
// <SnippetCallPairAndDisplayResults2>
167-
PairAndDisplayResults(imageData, imagePredictionData);
168-
// </SnippetCallPairAndDisplayResults2>
169150

151+
// <SnippetCallDisplayResults2>
152+
DisplayResults(imagePredictionData);
153+
// </SnippetCallDisplayResults2>
170154
}
171155

172-
public static void ClassifySingleImage(MLContext mlContext, string imagePath, string outputModelLocation)
156+
public static void ClassifySingleImage(MLContext mlContext, string imagePath, string outputModelLocation, ITransformer model)
173157
{
174-
Console.WriteLine($"=============== Loading model ===============");
175-
Console.WriteLine($"Model loaded: {outputModelLocation}");
176-
// Load the model
177-
// <SnippetLoadModel2>
178-
ITransformer loadedModel;
179-
using (var fileStream = new FileStream(outputModelLocation, FileMode.Open))
180-
loadedModel = mlContext.Model.Load(fileStream);
181-
// </SnippetLoadModel2>
182-
183158
// load the fully qualified image file name into ImageData
184159
// <SnippetLoadImageData>
185160
var imageData = new ImageData()
186161
{
187162
ImagePath = imagePath
188-
};
163+
};
189164
// </SnippetLoadImageData>
190165

191166
// <SnippetPredictSingle>
192-
// Make prediction function (input = ImageNetData, output = ImageNetPrediction)
193-
var predictor = loadedModel.CreatePredictionEngine<ImageData, ImagePrediction>(mlContext);
167+
// Make prediction function (input = ImageData, output = ImagePrediction)
168+
var predictor = mlContext.Model.CreatePredictionEngine<ImageData, ImagePrediction>(model);
194169
var prediction = predictor.Predict(imageData);
195170
// </SnippetPredictSingle>
196171

@@ -201,17 +176,12 @@ public static void ClassifySingleImage(MLContext mlContext, string imagePath, st
201176

202177
}
203178

204-
private static void PairAndDisplayResults(IEnumerable<ImageData> imageNetData, IEnumerable<ImagePrediction> imageNetPredictionData)
179+
private static void DisplayResults(IEnumerable<ImagePrediction> imagePredictionData)
205180
{
206-
// Builds pairs of (image, prediction) to sync up for display
207-
// <SnippetBuildImagePredictionPairs>
208-
IEnumerable<(ImageData image, ImagePrediction prediction)> imagesAndPredictions = imageNetData.Zip(imageNetPredictionData, (image, prediction) => (image, prediction));
209-
// </SnippetBuildImagePredictionPairs>
210-
211181
// <SnippetDisplayPredictions>
212-
foreach ((ImageData image, ImagePrediction prediction) item in imagesAndPredictions)
182+
foreach (ImagePrediction prediction in imagePredictionData)
213183
{
214-
Console.WriteLine($"Image: {Path.GetFileName(item.image.ImagePath)} predicted as: {item.prediction.PredictedLabelValue} with score: {item.prediction.Score.Max()} ");
184+
Console.WriteLine($"Image: {Path.GetFileName(prediction.ImagePath)} predicted as: {prediction.PredictedLabelValue} with score: {prediction.Score.Max()} ");
215185
}
216186
// </SnippetDisplayPredictions>
217187
}

‎machine-learning/tutorials/TransferLearningTF/TransferLearningTF.csproj‎

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
1-
<Project Sdk="Microsoft.NET.Sdk">
1+
<Project Sdk="Microsoft.NET.Sdk">
22

33
<PropertyGroup>
44
<OutputType>Exe</OutputType>
@@ -7,9 +7,9 @@
77
</PropertyGroup>
88

99
<ItemGroup>
10-
<PackageReference Include="Microsoft.ML" Version="0.10.0" />
11-
<PackageReference Include="Microsoft.ML.ImageAnalytics" Version="0.10.0" />
12-
<PackageReference Include="Microsoft.ML.TensorFlow" Version="0.10.0" />
10+
<PackageReference Include="Microsoft.ML" Version="1.0.0-preview" />
11+
<PackageReference Include="Microsoft.ML.ImageAnalytics" Version="1.0.0-preview" />
12+
<PackageReference Include="Microsoft.ML.TensorFlow" Version="0.12.0-preview" />
1313
</ItemGroup>
1414

1515
<ItemGroup>

‎snippets/csharp/VS_Snippets_Winforms/Classic CheckedListBox Example/CS/source.cs‎

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -17,17 +17,17 @@ public class Form1 : System.Windows.Forms.Form
1717
private System.Windows.Forms.Button button2;
1818
private System.Windows.Forms.ListBox listBox1;
1919
private System.Windows.Forms.Button button3;
20-
private System.ComponentModel.Container components;
20+
private System.ComponentModel.Container components;
2121

2222
public Form1()
2323
{
24-
InitializeComponent();
24+
InitializeComponent();
2525

2626
// Sets up the initial objects in the CheckedListBox.
27-
string[] myFruit = {"Apples", "Oranges","Tomato"};
27+
string[] myFruit = {"Apples", "Oranges","Tomato"};
2828
checkedListBox1.Items.AddRange(myFruit);
2929

30-
// Changes the selection mode from double-click to single click.
30+
// Changes the selection mode from double-click to single click.
3131
checkedListBox1.CheckOnClick = true;
3232
}
3333

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