TensorFlow.NET pack all required libraries in architecture-specific assemblies folders per NuGet standard [Deprecated] .

We changed to use Microsoft.ML.TensorFlow.Redist to maintain the TensorFlow library.

Here are some pre-built TensorFlow binaries you can use for each platform:

• Linux
  • CPU-only: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-linux-x86_64-1.14.0.tar.gz
  • GPU-enabled: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-linux-x86_64-1.14.0.tar.gz
• Mac: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-darwin-x86_64-1.14.0.tar.gz
• Windows
  • 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

Install-Package TensorFlow.NET

Download Linux pre-built library and unzip libtensorflow.so and libtensorflow_framework.so into current running directory.

To run image recognition in Linux, please ensure some prerequisite libraries is install.

sudo apt install libc6-dev 
sudo apt install libgdiplus

More information about System.Drawing on Linux.

Before running verify you installed CUDA and cuDNN

https://www.tensorflow.org/install/source_windows

pacman -S git patch unzip

1. Build static library

bazel build --config=opt //tensorflow:libtensorflow.so

2. Build pip package

bazel build --config=opt //tensorflow/tools/pip_package:build_pip_package

3. Generate pip installation file

bazel-bin\tensorflow\tools\pip_package\build_pip_package C:/tmp/tensorflow_pkg

4. Install from local wheel file.

pip install C:/tmp/tensorflow_pkg/tensorflow-1.14.0-cp36-cp36m-win_amd64.whl

Add more api to c_api.h

TF_CAPI_EXPORT extern void AddControlInput(TF_Graph* graph, TF_Operation* op, TF_Operation* input);
TF_CAPI_EXPORT extern void UpdateEdge(TF_Graph* graph, TF_Output new_src, TF_Input dst, TF_Status* status);
TF_CAPI_EXPORT extern void RemoveAllControlInputs(TF_Graph* graph, TF_Operation* op);