diff --git a/src/Microsoft.ML.Vision/ImageClassificationTrainer.cs b/src/Microsoft.ML.Vision/ImageClassificationTrainer.cs
index 5958e9920d..0b862669b3 100644
--- a/src/Microsoft.ML.Vision/ImageClassificationTrainer.cs
+++ b/src/Microsoft.ML.Vision/ImageClassificationTrainer.cs
@@ -471,8 +471,11 @@ public sealed class Options : TrainerInputBaseWithLabel
         private readonly string _checkpointPath;
         private readonly string _bottleneckOperationName;
         private readonly bool _useLRScheduling;
+        private readonly bool _cleanupWorkspace;
         private int _classCount;
         private Graph Graph => _session.graph;
+        private static readonly string _resourcePath = Path.Combine(Path.GetTempPath(), "MLNET");
+        private readonly string _sizeFile;
 
         /// <summary>
         /// Initializes a new instance of <see cref="ImageClassificationTrainer"/>
@@ -518,6 +521,12 @@ internal ImageClassificationTrainer(IHostEnvironment env, Options options)
             if (string.IsNullOrEmpty(options.WorkspacePath))
             {
                 options.WorkspacePath = GetTemporaryDirectory();
+                _cleanupWorkspace = true;
+            }
+
+            if (!Directory.Exists(_resourcePath))
+            {
+                Directory.CreateDirectory(_resourcePath);
             }
 
             if (string.IsNullOrEmpty(options.TrainSetBottleneckCachedValuesFileName))
@@ -536,6 +545,7 @@ internal ImageClassificationTrainer(IHostEnvironment env, Options options)
             _useLRScheduling = _options.LearningRateScheduler != null;
             _checkpointPath = Path.Combine(_options.WorkspacePath, _options.FinalModelPrefix +
                     ModelFileName[_options.Arch]);
+            _sizeFile = Path.Combine(_options.WorkspacePath, "TrainingSetSize.txt");
 
             // Configure bottleneck tensor based on the model.
             var arch = _options.Arch;
@@ -546,8 +556,8 @@ internal ImageClassificationTrainer(IHostEnvironment env, Options options)
             }
             else if (arch == Architecture.InceptionV3)
             {
-                _bottleneckOperationName = "module_apply_default/hub_output/feature_vector/SpatialSqueeze";
-                _inputTensorName = "Placeholder";
+                _bottleneckOperationName = "InceptionV3/Logits/SpatialSqueeze";
+                _inputTensorName = "input";
             }
             else if (arch == Architecture.MobilenetV2)
             {
@@ -574,7 +584,7 @@ private void InitializeTrainingGraph(IDataView input)
 
             _classCount = labelCount == 1 ? 2 : (int)labelCount;
             var imageSize = ImagePreprocessingSize[_options.Arch];
-            _session = LoadTensorFlowSessionFromMetaGraph(Host, _options.Arch, _options.WorkspacePath).Session;
+            _session = LoadTensorFlowSessionFromMetaGraph(Host, _options.Arch).Session;
             (_jpegData, _resizedImage) = AddJpegDecoding(imageSize.Item1, imageSize.Item2, 3);
             _jpegDataTensorName = _jpegData.name;
             _resizedImageTensorName = _resizedImage.name;
@@ -631,7 +641,7 @@ private protected override ImageClassificationModelParameters TrainModelCore(Tra
                     ImageClassificationMetrics.Dataset.Train, _options.MetricsCallback);
 
                 // Write training set size to a file for use during training
-                File.WriteAllText("TrainingSetSize.txt", trainingsetSize.ToString());
+                File.WriteAllText(_sizeFile, trainingsetSize.ToString());
             }
 
             if (validationSet != null &&
@@ -899,7 +909,7 @@ private void TrainAndEvaluateClassificationLayer(string trainBottleneckFilePath,
             {
                 BatchSize = options.BatchSize,
                 BatchesPerEpoch =
-                (trainingsetSize < 0 ? GetNumSamples("TrainingSetSize.txt") : trainingsetSize) / options.BatchSize
+                (trainingsetSize < 0 ? GetNumSamples(_sizeFile) : trainingsetSize) / options.BatchSize
             };
 
             for (int epoch = 0; epoch < epochs; epoch += 1)
@@ -1123,11 +1133,27 @@ private void TrainAndEvaluateClassificationLayer(string trainBottleneckFilePath,
 
             trainSaver.save(_session, _checkpointPath);
             UpdateTransferLearningModelOnDisk(_classCount);
+            TryCleanupTemporaryWorkspace();
+        }
+
+        private void TryCleanupTemporaryWorkspace()
+        {
+            if (_cleanupWorkspace && Directory.Exists(_options.WorkspacePath))
+            {
+                try
+                {
+                    Directory.Delete(_options.WorkspacePath, true);
+                }
+                catch (Exception)
+                {
+                    //We do not want to stop pipeline due to failed cleanup.
+                }
+            }
         }
 
         private (Session, Tensor, Tensor, Tensor) BuildEvaluationSession(int classCount)
         {
-            var evalGraph = LoadMetaGraph(Path.Combine(_options.WorkspacePath, ModelFileName[_options.Arch]));
+            var evalGraph = LoadMetaGraph(Path.Combine(_resourcePath, ModelFileName[_options.Arch]));
             var evalSess = tf.Session(graph: evalGraph);
             Tensor evaluationStep = null;
             Tensor prediction = null;
@@ -1285,24 +1311,12 @@ private void AddTransferLearningLayer(string labelColumn,
 
         }
 
-        private static TensorFlowSessionWrapper LoadTensorFlowSessionFromMetaGraph(IHostEnvironment env, Architecture arch, string path)
+        private static TensorFlowSessionWrapper LoadTensorFlowSessionFromMetaGraph(IHostEnvironment env, Architecture arch)
         {
-            if (string.IsNullOrEmpty(path))
-            {
-                path = GetTemporaryDirectory();
-            }
-
             var modelFileName = ModelFileName[arch];
-            var modelFilePath = Path.Combine(path, modelFileName);
+            var modelFilePath = Path.Combine(_resourcePath, modelFileName);
             int timeout = 10 * 60 * 1000;
-            DownloadIfNeeded(env, modelFileName, path, modelFileName, timeout);
-            if (arch == Architecture.InceptionV3)
-            {
-                DownloadIfNeeded(env, @"tfhub_modules.zip", path, @"tfhub_modules.zip", timeout);
-                if (!Directory.Exists(@"tfhub_modules"))
-                    ZipFile.ExtractToDirectory(Path.Combine(path, @"tfhub_modules.zip"), @"tfhub_modules");
-            }
-
+            DownloadIfNeeded(env, modelFileName, _resourcePath, modelFileName, timeout);
             return new TensorFlowSessionWrapper(GetSession(env, modelFilePath, true), modelFilePath);
         }
 
diff --git a/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/TensorflowTests.cs b/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/TensorflowTests.cs
index 3c3b078130..7e626ed2d3 100644
--- a/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/TensorflowTests.cs
+++ b/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/TensorflowTests.cs
@@ -1289,6 +1289,7 @@ public void TensorFlowImageClassificationDefault()
         [InlineData(ImageClassificationTrainer.Architecture.ResnetV2101)]
         [InlineData(ImageClassificationTrainer.Architecture.MobilenetV2)]
         [InlineData(ImageClassificationTrainer.Architecture.ResnetV250)]
+        [InlineData(ImageClassificationTrainer.Architecture.InceptionV3)]
         public void TensorFlowImageClassification(ImageClassificationTrainer.Architecture arch)
         {
             string assetsRelativePath = @"assets";
@@ -1582,8 +1583,9 @@ internal void TensorFlowImageClassificationWithLRScheduling(LearningRateSchedule
 
             Assert.True(File.Exists(Path.Combine(options.WorkspacePath, options.TrainSetBottleneckCachedValuesFileName)));
             Assert.True(File.Exists(Path.Combine(options.WorkspacePath, options.ValidationSetBottleneckCachedValuesFileName)));
-            Assert.True(File.Exists(Path.Combine(options.WorkspacePath, ImageClassificationTrainer.ModelFileName[options.Arch])));
+            Assert.True(File.Exists(Path.Combine(options.WorkspacePath, "TrainingSetSize.txt")));
             Directory.Delete(options.WorkspacePath, true);
+            Assert.True(File.Exists(Path.Combine(Path.GetTempPath(), "MLNET", ImageClassificationTrainer.ModelFileName[options.Arch])));
         }
 
         [TensorFlowFact]