fixed issues about displaying progress in console when download/unzip resources

src/TensorFlowHub/MnistModelLoader.cs

@@ -15,14 +15,15 @@ namespace Tensorflow.Hub
         private const string TEST_IMAGES = "t10k-images-idx3-ubyte.gz";
         private const string TEST_LABELS = "t10k-labels-idx1-ubyte.gz";
 
-        public static async Task<Datasets<MnistDataSet>> LoadAsync(string trainDir, bool oneHot = false, int? trainSize = null, int? validationSize = null, int? testSize = null)
+        public static async Task<Datasets<MnistDataSet>> LoadAsync(string trainDir, bool oneHot = false, int? trainSize = null, int? validationSize = null, int? testSize = null, bool showProgressInConsole = false)
         {
             var loader = new MnistModelLoader();
 
             var setting = new ModelLoadSetting
             {
                 TrainDir = trainDir,
-                OneHot = oneHot
+                OneHot = oneHot,
+                ShowProgressInConsole = showProgressInConsole
             };
 
             if (trainSize.HasValue)
@@ -48,37 +49,37 @@ namespace Tensorflow.Hub
                 sourceUrl = DEFAULT_SOURCE_URL;
 
             // load train images
-            await this.DownloadAsync(sourceUrl + TRAIN_IMAGES, setting.TrainDir, TRAIN_IMAGES)
+            await this.DownloadAsync(sourceUrl + TRAIN_IMAGES, setting.TrainDir, TRAIN_IMAGES, showProgressInConsole: setting.ShowProgressInConsole)
                 .ShowProgressInConsole(setting.ShowProgressInConsole);
 
-            await this.UnzipAsync(Path.Combine(setting.TrainDir, TRAIN_IMAGES), setting.TrainDir)
+            await this.UnzipAsync(Path.Combine(setting.TrainDir, TRAIN_IMAGES), setting.TrainDir, showProgressInConsole: setting.ShowProgressInConsole)
                 .ShowProgressInConsole(setting.ShowProgressInConsole);
 
             var trainImages = ExtractImages(Path.Combine(setting.TrainDir, Path.GetFileNameWithoutExtension(TRAIN_IMAGES)), limit: setting.TrainSize);
 
             // load train labels
-            await this.DownloadAsync(sourceUrl + TRAIN_LABELS, setting.TrainDir, TRAIN_LABELS)
+            await this.DownloadAsync(sourceUrl + TRAIN_LABELS, setting.TrainDir, TRAIN_LABELS, showProgressInConsole: setting.ShowProgressInConsole)
                 .ShowProgressInConsole(setting.ShowProgressInConsole);
 
-            await this.UnzipAsync(Path.Combine(setting.TrainDir, TRAIN_LABELS), setting.TrainDir)
+            await this.UnzipAsync(Path.Combine(setting.TrainDir, TRAIN_LABELS), setting.TrainDir, showProgressInConsole: setting.ShowProgressInConsole)
                 .ShowProgressInConsole(setting.ShowProgressInConsole);
 
             var trainLabels = ExtractLabels(Path.Combine(setting.TrainDir, Path.GetFileNameWithoutExtension(TRAIN_LABELS)), one_hot: setting.OneHot, limit: setting.TrainSize);
 
             // load test images
-            await this.DownloadAsync(sourceUrl + TEST_IMAGES, setting.TrainDir, TEST_IMAGES)
+            await this.DownloadAsync(sourceUrl + TEST_IMAGES, setting.TrainDir, TEST_IMAGES, showProgressInConsole: setting.ShowProgressInConsole)
                 .ShowProgressInConsole(setting.ShowProgressInConsole);
 
-            await this.UnzipAsync(Path.Combine(setting.TrainDir, TEST_IMAGES), setting.TrainDir)
+            await this.UnzipAsync(Path.Combine(setting.TrainDir, TEST_IMAGES), setting.TrainDir, showProgressInConsole: setting.ShowProgressInConsole)
                 .ShowProgressInConsole(setting.ShowProgressInConsole);
 
             var testImages = ExtractImages(Path.Combine(setting.TrainDir, Path.GetFileNameWithoutExtension(TEST_IMAGES)), limit: setting.TestSize);
 
             // load test labels
-            await this.DownloadAsync(sourceUrl + TEST_LABELS, setting.TrainDir, TEST_LABELS)
+            await this.DownloadAsync(sourceUrl + TEST_LABELS, setting.TrainDir, TEST_LABELS, showProgressInConsole: setting.ShowProgressInConsole)
                 .ShowProgressInConsole(setting.ShowProgressInConsole);
 
-            await this.UnzipAsync(Path.Combine(setting.TrainDir, TEST_LABELS), setting.TrainDir)
+            await this.UnzipAsync(Path.Combine(setting.TrainDir, TEST_LABELS), setting.TrainDir, showProgressInConsole: setting.ShowProgressInConsole)
                 .ShowProgressInConsole(setting.ShowProgressInConsole);
 
             var testLabels = ExtractLabels(Path.Combine(setting.TrainDir, Path.GetFileNameWithoutExtension(TEST_LABELS)), one_hot: setting.OneHot, limit: setting.TestSize);

src/TensorFlowHub/Utils.cs

@@ -19,7 +19,7 @@ namespace Tensorflow.Hub
             await modelLoader.DownloadAsync(url, dir, fileName);
         }
 
-        public static async Task DownloadAsync<TDataSet>(this IModelLoader<TDataSet> modelLoader, string url, string dirSaveTo, string fileName)
+        public static async Task DownloadAsync<TDataSet>(this IModelLoader<TDataSet> modelLoader, string url, string dirSaveTo, string fileName, bool showProgressInConsole = false)
             where TDataSet : IDataSet
         {
             if (!Path.IsPathRooted(dirSaveTo))
@@ -27,18 +27,30 @@ namespace Tensorflow.Hub
 
             var fileSaveTo = Path.Combine(dirSaveTo, fileName);
 
+            if (showProgressInConsole)
+            {
+                Console.WriteLine($"Downloading {fileName}");
+            }
+
             if (File.Exists(fileSaveTo))
+            {
+                if (showProgressInConsole)
+                {
+                    Console.WriteLine($"The file {fileName} already exists");
+                }
+
                 return;
+            }
             
             Directory.CreateDirectory(dirSaveTo);
                 
             using (var wc = new WebClient())
             {
-                await wc.DownloadFileTaskAsync(url, fileSaveTo);
+                await wc.DownloadFileTaskAsync(url, fileSaveTo).ConfigureAwait(false);
             }
         }
 
-        public static async Task UnzipAsync<TDataSet>(this IModelLoader<TDataSet> modelLoader, string zipFile, string saveTo)
+        public static async Task UnzipAsync<TDataSet>(this IModelLoader<TDataSet> modelLoader, string zipFile, string saveTo, bool showProgressInConsole = false)
             where TDataSet : IDataSet
         {
             if (!Path.IsPathRooted(saveTo))
@@ -49,67 +61,76 @@ namespace Tensorflow.Hub
             if (!Path.IsPathRooted(zipFile))
                 zipFile = Path.Combine(AppContext.BaseDirectory, zipFile);
 
-            var destFilePath = Path.Combine(saveTo, Path.GetFileNameWithoutExtension(zipFile));
+            var destFileName = Path.GetFileNameWithoutExtension(zipFile);
+            var destFilePath = Path.Combine(saveTo, destFileName);
+
+            if (showProgressInConsole)
+                Console.WriteLine($"Unzippinng {Path.GetFileName(zipFile)}");
 
             if (File.Exists(destFilePath))
-                File.Delete(destFilePath);
+            {
+                if (showProgressInConsole)
+                    Console.WriteLine($"The file {destFileName} already exists");
+            }            
 
             using (GZipStream unzipStream = new GZipStream(File.OpenRead(zipFile), CompressionMode.Decompress))
             {
                 using (var destStream = File.Create(destFilePath))
                 {
-                    await unzipStream.CopyToAsync(destStream);
-                    await destStream.FlushAsync();
+                    await unzipStream.CopyToAsync(destStream).ConfigureAwait(false);
+                    await destStream.FlushAsync().ConfigureAwait(false);
                     destStream.Close();
                 }
 
                 unzipStream.Close();
             }
-        }
-
-        public static async Task ShowProgressInConsole(this Task task)
-        {
-            await ShowProgressInConsole(task, true);
-        }
+        }        
 
         public static async Task ShowProgressInConsole(this Task task, bool enable)
         {
             if (!enable)
             {
                 await task;
+                return;
             }
 
             var cts = new CancellationTokenSource();
+
             var showProgressTask = ShowProgressInConsole(cts);
 
             try
-            {
+            {                
                 await task;
             }
             finally
             {
-                cts.Cancel();
+                cts.Cancel();                
             }
+
+            await showProgressTask;
+            Console.WriteLine("Done.");
         }
 
         private static async Task ShowProgressInConsole(CancellationTokenSource cts)
         {
             var cols = 0;
 
+            await Task.Delay(1000);
+
             while (!cts.IsCancellationRequested)
             {
                 await Task.Delay(1000);
                 Console.Write(".");
                 cols++;
 
-                if (cols >= 50)
+                if (cols % 50 == 0)
                 {
-                    cols = 0;
                     Console.WriteLine();
                 }
             }
 
-            Console.WriteLine();
+            if (cols > 0)
+                Console.WriteLine();
         }
     }
 }

test/TensorFlowNET.Examples/BasicModels/KMeansClustering.cs

@@ -70,7 +70,8 @@ namespace TensorFlowNET.Examples
                 OneHot = true,
                 TrainSize = train_size,
                 ValidationSize = validation_size,
-                TestSize = test_size
+                TestSize = test_size,
+                ShowProgressInConsole = true
             };
 
             mnist = loader.LoadAsync(setting).Result;

test/TensorFlowNET.Examples/BasicModels/LogisticRegression.cs

@@ -124,7 +124,7 @@ namespace TensorFlowNET.Examples
 
         public void PrepareData()
         {
-            mnist = MnistModelLoader.LoadAsync(".resources/mnist", oneHot: true, trainSize: train_size, validationSize: validation_size, testSize: test_size).Result;
+            mnist = MnistModelLoader.LoadAsync(".resources/mnist", oneHot: true, trainSize: train_size, validationSize: validation_size, testSize: test_size, showProgressInConsole: true).Result;
         }
 
         public void SaveModel(Session sess)

test/TensorFlowNET.Examples/BasicModels/NearestNeighbor.cs

@@ -84,7 +84,7 @@ namespace TensorFlowNET.Examples
 
         public void PrepareData()
         {
-            mnist = MnistModelLoader.LoadAsync(".resources/mnist", oneHot: true, trainSize: TrainSize, validationSize: ValidationSize, testSize: TestSize).Result;
+            mnist = MnistModelLoader.LoadAsync(".resources/mnist", oneHot: true, trainSize: TrainSize, validationSize: ValidationSize, testSize: TestSize, showProgressInConsole: true).Result;
             // In this example, we limit mnist data
             (Xtr, Ytr) = mnist.Train.GetNextBatch(TrainSize == null ? 5000 : TrainSize.Value / 100); // 5000 for training (nn candidates)
             (Xte, Yte) = mnist.Test.GetNextBatch(TestSize == null ? 200 : TestSize.Value / 100); // 200 for testing

test/TensorFlowNET.Examples/ImageProcessing/DigitRecognitionCNN.cs

@@ -310,7 +310,7 @@ namespace TensorFlowNET.Examples
             
         public void PrepareData()
         {
-            mnist = MnistModelLoader.LoadAsync(".resources/mnist", oneHot: true).Result;
+            mnist = MnistModelLoader.LoadAsync(".resources/mnist", oneHot: true, showProgressInConsole: true).Result;
             (x_train, y_train) = Reformat(mnist.Train.Data, mnist.Train.Labels);
             (x_valid, y_valid) = Reformat(mnist.Validation.Data, mnist.Validation.Labels);
             (x_test, y_test) = Reformat(mnist.Test.Data, mnist.Test.Labels);

test/TensorFlowNET.Examples/ImageProcessing/DigitRecognitionNN.cs

@@ -121,7 +121,7 @@ namespace TensorFlowNET.Examples
             
         public void PrepareData()
         {
-            mnist = MnistModelLoader.LoadAsync(".resources/mnist", oneHot: true).Result;
+            mnist = MnistModelLoader.LoadAsync(".resources/mnist", oneHot: true, showProgressInConsole: true).Result;
         }
 
         public void Train(Session sess)

test/TensorFlowNET.Examples/ImageProcessing/DigitRecognitionRNN.cs

@@ -143,7 +143,7 @@ namespace TensorFlowNET.Examples
 
         public void PrepareData()
         {
-            mnist = MnistModelLoader.LoadAsync(".resources/mnist", oneHot: true).Result;
+            mnist = MnistModelLoader.LoadAsync(".resources/mnist", oneHot: true, showProgressInConsole: true).Result;
             (x_train, y_train) = (mnist.Train.Data, mnist.Train.Labels);
             (x_valid, y_valid) = (mnist.Validation.Data, mnist.Validation.Labels);
             (x_test, y_test) = (mnist.Test.Data, mnist.Test.Labels);