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 (TensorFlow v1.14 is compatible with CUDA v10.0 and cuDNN v7.4), and make sure the corresponding cuda version is compatible.

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

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);