diff --git a/README.md b/README.md index 7f7d14a4..9cf23da2 100644 --- a/README.md +++ b/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. diff --git a/tensorflowlib/README.md b/tensorflowlib/README.md index 63cba815..318e5dc9 100644 --- a/tensorflowlib/README.md +++ b/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](). + + ### 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 diff --git a/test/TensorFlowNET.Examples/ImageProcessing/DigitRecognitionCNN.cs b/test/TensorFlowNET.Examples/ImageProcessing/DigitRecognitionCNN.cs index 2dc355c4..a5c757b9 100644 --- a/test/TensorFlowNET.Examples/ImageProcessing/DigitRecognitionCNN.cs +++ b/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(); } }