Update doc for gpu version.

README.md

@@ -28,8 +28,14 @@ In comparison to other projects, like for instance TensorFlowSharp which only pr
 
 Install TF.NET and TensorFlow binary through NuGet.
 ```sh
+### install tensorflow C# binding
 PM> Install-Package TensorFlow.NET
+
+### Install tensorflow binary
+### For CPU version
 PM> Install-Package SciSharp.TensorFlow.Redist
+### For GPU version (CUDA and cuDNN are required)
+PM> Install-Package SciSharp.TensorFlow.Redist-Windows-GPU
 ```
 
 Import TF.NET.

tensorflowlib/README.md

@@ -16,6 +16,8 @@ Here are some pre-built TensorFlow binaries you can use for each platform:
   - CPU-only: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-windows-x86_64-1.14.0.zip
   - GPU-enabled: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-windows-x86_64-1.14.0.zip
 
+
+
 ### Run in Linux
 
 `Install-Package TensorFlow.NET`
@@ -31,10 +33,21 @@ sudo apt install libgdiplus
 
 More information about [System.Drawing on Linux](<https://www.hanselman.com/blog/HowDoYouUseSystemDrawingInNETCore.aspx>).
 
+
+
 ### Run in Mac OS
 
-### GPU Tensorflow for windows
-Before running verify you installed  CUDA and cuDNN
+
+
+### Tensorflow GPU for Windows
+
+Before running verify you installed  CUDA and cuDNN (TensorFlow v1.14 is compatible with CUDA v10.0 and cuDNN v7.4), and make sure the corresponding cuda version is compatible. 
+
+```powershell
+PM> Install-Package SciSharp.TensorFlow.Redist-Windows-GPU
+```
+
+
 
 ### Build from source for Windows
 

test/TensorFlowNET.Examples/ImageProcessing/DigitRecognitionCNN.cs

@@ -16,6 +16,7 @@
 
 using NumSharp;
 using System;
+using System.Diagnostics;
 using Tensorflow;
 using TensorFlowNET.Examples.Utility;
 using static Tensorflow.Python;
@@ -144,6 +145,8 @@ namespace TensorFlowNET.Examples.ImageProcess
             float loss_val = 100.0f;
             float accuracy_val = 0f;
 
+            var sw = new Stopwatch();
+            sw.Start();
             foreach (var epoch in range(epochs))
             {
                 print($"Training epoch: {epoch + 1}");
@@ -165,7 +168,8 @@ namespace TensorFlowNET.Examples.ImageProcess
                         var result = sess.run(new[] { loss, accuracy }, new FeedItem(x, x_batch), new FeedItem(y, y_batch));
                         loss_val = result[0];
                         accuracy_val = result[1];
-                        print($"iter {iteration.ToString("000")}: Loss={loss_val.ToString("0.0000")}, Training Accuracy={accuracy_val.ToString("P")}");
+                        print($"iter {iteration.ToString("000")}: Loss={loss_val.ToString("0.0000")}, Training Accuracy={accuracy_val.ToString("P")} {sw.ElapsedMilliseconds}ms");
+                        sw.Restart();
                     }
                 }