fixed unit test, minor formatting

Author: ashbhandare

src/Microsoft.ML.Dnn/DnnUtils.cs

@@ -7,11 +7,9 @@
 using System.IO;
 using System.IO.Compression;
 using System.Linq;
-using System.Net;
 using System.Net.Http;
 using System.Security.AccessControl;
 using System.Security.Principal;
-using System.Threading.Tasks;
 using Microsoft.ML.Data;
 using Microsoft.ML.Runtime;
 using Tensorflow;
@@ -93,6 +91,7 @@ internal static Session LoadTFSession(IExceptionContext ectx, byte[] modelBytes,
             }
             return new Session(graph);
         }
+
         internal static void DownloadIfNeeded(Uri address, string fileName)
         {
             using HttpClient client = new HttpClient();
@@ -305,33 +304,30 @@ internal static DnnModel LoadDnnModel(IHostEnvironment env, string modelPath, bo
         internal static DnnModel LoadDnnModel(IHostEnvironment env, ImageClassificationEstimator.Architecture arch, bool metaGraph = false)
         {
             var modelPath = ImageClassificationEstimator.ModelLocation[arch];
-            if (!File.Exists(modelPath))
+            if (arch == ImageClassificationEstimator.Architecture.InceptionV3)
             {
-                if (arch == ImageClassificationEstimator.Architecture.InceptionV3)
-                {
-                    var baseGitPath = @"https://raw.githubusercontent.com/SciSharp/TensorFlow.NET/master/graph/InceptionV3.meta";
-                    DownloadIfNeeded(new Uri($"{baseGitPath}"), @"InceptionV3.meta");
+                var baseGitPath = @"https://raw.githubusercontent.com/SciSharp/TensorFlow.NET/master/graph/InceptionV3.meta";
+                DownloadIfNeeded(new Uri($"{baseGitPath}"), @"InceptionV3.meta");
 
-                    baseGitPath = @"https://github.com/SciSharp/TensorFlow.NET/raw/master/data/tfhub_modules.zip";
-                    DownloadIfNeeded(new Uri($"{baseGitPath}"), @"tfhub_modules.zip");
-                    if (!Directory.Exists(@"tfhub_modules"))
-                        ZipFile.ExtractToDirectory(Path.Combine(Directory.GetCurrentDirectory(), @"tfhub_modules.zip"), @"tfhub_modules");
-                }
-                else if (arch == ImageClassificationEstimator.Architecture.ResnetV2101)
-                {
-                    var baseGitPath = @"https://aka.ms/mlnet-resources/image/ResNet101Tensorflow/resnet_v2_101_299.meta";
-                    DownloadIfNeeded(new Uri($"{baseGitPath}"), @"resnet_v2_101_299.meta");
-                }
-                else if (arch == ImageClassificationEstimator.Architecture.MobilenetV2)
-                {
-                    var baseGitPath = @"https://tlcresources.blob.core.windows.net/image/MobileNetV2TensorFlow/mobilenet_v2.meta";
-                    DownloadIfNeeded(new Uri($"{baseGitPath}"), @"mobilenet_v2.meta");
-                }
-                else if (arch == ImageClassificationEstimator.Architecture.ResnetV250)
-                {
-                    var baseGitPath = @"https://tlcresources.blob.core.windows.net/image/ResNetV250TensorFlow/resnet_v2_50_299.meta";
-                    DownloadIfNeeded(new Uri($"{baseGitPath}"), @"resnet_v2_50_299.meta");
-                }
+                baseGitPath = @"https://github.com/SciSharp/TensorFlow.NET/raw/master/data/tfhub_modules.zip";
+                DownloadIfNeeded(new Uri($"{baseGitPath}"), @"tfhub_modules.zip");
+                if (!Directory.Exists(@"tfhub_modules"))
+                    ZipFile.ExtractToDirectory(Path.Combine(Directory.GetCurrentDirectory(), @"tfhub_modules.zip"), @"tfhub_modules");
+            }
+            else if (arch == ImageClassificationEstimator.Architecture.ResnetV2101)
+            {
+                var baseGitPath = @"https://aka.ms/mlnet-resources/image/ResNet101Tensorflow/resnet_v2_101_299.meta";
+                DownloadIfNeeded(new Uri($"{baseGitPath}"), @"resnet_v2_101_299.meta");
+            }
+            else if (arch == ImageClassificationEstimator.Architecture.MobilenetV2)
+            {
+                var baseGitPath = @"https://tlcresources.blob.core.windows.net/image/MobileNetV2TensorFlow/mobilenet_v2.meta";
+                DownloadIfNeeded(new Uri($"{baseGitPath}"), @"mobilenet_v2.meta");
+            }
+            else if (arch == ImageClassificationEstimator.Architecture.ResnetV250)
+            {
+                var baseGitPath = @"https://tlcresources.blob.core.windows.net/image/ResNetV250TensorFlow/resnet_v2_50_299.meta";
+                DownloadIfNeeded(new Uri($"{baseGitPath}"), @"resnet_v2_50_299.meta");
             }
 
             var session = GetSession(env, modelPath, metaGraph);

test/Microsoft.ML.TestFramework/Attributes/TensorflowTheoryAttribute.cs

@@ -20,4 +20,4 @@ protected override bool IsEnvironmentSupported()
             return Environment.Is64BitProcess;
         }
     }
-}
+}

test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/TensorflowTests.cs

@@ -1820,22 +1820,21 @@ public void TensorflowRedownloadModelFile(ImageClassificationEstimator.Architect
                 using (File.Create(@"InceptionV3.meta")) { }
             }
 
+            var options = new ImageClassificationEstimator.Options()
+            {
+                FeaturesColumnName = "Image",
+                LabelColumnName = "Label",
+                Arch = arch,
+                Epoch = 1,
+                BatchSize = 10,
+                MetricsCallback = (metrics) => Console.WriteLine(metrics),
+                TestOnTrainSet = false,
+                DisableEarlyStopping = true
+            };
+
             //Create pipeline and run
             var pipeline = mlContext.Transforms.LoadImages("Image", fullImagesetFolderPath, false, "ImagePath") // false indicates we want the image as a VBuffer<byte>
-                .Append(mlContext.Model.ImageClassification(
-                    "Image", "Label",
-                    // Just by changing/selecting InceptionV3 here instead of 
-                    // ResnetV2101 you can try a different architecture/pre-trained 
-                    // model. 
-                    arch: arch,
-                    epoch: 1,
-                    batchSize: 10,
-                    learningRate: 0.01f,
-                    metricsCallback: (metrics) => Console.WriteLine(metrics),
-                    testOnTrainSet: false,
-                    disableEarlyStopping: true,
-                    reuseTrainSetBottleneckCachedValues: true,
-                    reuseValidationSetBottleneckCachedValues: true)
+                .Append(mlContext.Model.ImageClassification(options)
                 .Append(mlContext.Transforms.Conversion.MapKeyToValue(outputColumnName: "PredictedLabel", inputColumnName: "PredictedLabel")));
 
             var trainedModel = pipeline.Fit(trainDataset);