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

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.

sudo apt install libc6-dev 
sudo apt install libgdiplus

More information about System.Drawing on Linux.

Run TensorFlow with 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.

Mac OS

There is no GPU support for macOS.

GPU for Windows

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

GPU for Linux

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

Download prebuild binary manually

Tensorflow packages are built nightly and uploaded to GCS for all supported platforms. They are uploaded to the libtensorflow-nightly GCS bucket and are indexed by operating system and date built.

Build from source for Windows

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

Download Bazel 2.0.0 to build tensorflow2.x. We build customized binary to export c_api from this fork.

Set ENV BAZEL_VC=C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC.

pacman -S git patch unzip

  1. Build static library

bazel build --config=opt //tensorflow:tensorflow

  1. Build pip package

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

  1. Generate pip installation file

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

  1. Install from local wheel file.

pip install C:/tmp/tensorflow_pkg/tensorflow-1.15.0-cp36-cp36m-win_amd64.whl

Build specific version for tf.net

https://github.com/SciSharp/tensorflow

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