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

```powershell
PM> Install-Package TensorFlow.NET
PM> Install-Package SciSharp.TensorFlow.Redist
```

### Run in Linux

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.

```shell
sudo apt install libc6-dev 
sudo apt install libgdiplus
```

More information about [System.Drawing on Linux](<https://www.hanselman.com/blog/HowDoYouUseSystemDrawingInNETCore.aspx>).

### Run TensorFlow in GPU
Before running verify you installed  CUDA and cuDNN (TensorFlow v1.15 is compatible with CUDA v10.0 and cuDNN v7.4 , TensorFlow v2.x is compatible with CUDA v10.2 and cuDNN v7.65), and make sure the corresponding cuda version is compatible. 

#### Run in Mac OS
There is no GPU support for macOS.

#### Tensorflow GPU for Windows

```powershell
PM> Install-Package SciSharp.TensorFlow.Redist-Windows-GPU
```

#### Tensorflow GPU for Linux
```powershell
PM> Install-Package SciSharp.TensorFlow.Redist-Linux-GPU
```

### Download prebuild binary manually

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_64-1.15.0.tar.gz
  - GPU-enabled: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-linux-x86_64-1.15.0.tar.gz
- Mac: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-darwin-x86_64-1.15.0.tar.gz
- Windows
  - CPU-only: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-windows-x86_64-1.15.0.zip
  - GPU-enabled: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-windows-x86_64-1.15.0.zip


### Build from source for Windows

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-1.15.0-cp36-cp36m-win_amd64.whl`

### Export more APIs

Add more api to `c_api.h`

```c++
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);
```

For Linux version, these APIs symbols should also be put into `tensorflow/c/version_script.lds` to be exported. 
Please refer to commit `https://github.com/SciSharp/tensorflow/commit/58122da06be3e7707500ad889dfd5c760a3e0424`