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#TensorFlow Rust

TensorFlow Rust provides Rust language bindings for TensorFlow.

This project is still under active development and not yet ready for widespread use.

Install TensorFlow from source. The Python/pip steps are not necesary, but building tensorflow:libtensorflow.so is.

In short:

1. Install Bazel
2. git clone --recurse-submodules https://github.com/tensorflow/tensorflow
3. cd tensorflow
4. ./configure
5. bazel build -c opt tensorflow:libtensorflow.so

Copy $TENSORFLOW_SRC/tensorflow/core/public/tensor_c_api.h to /usr/local/include, and copy $TENSORFLOW_SRC/bazel-bin/tensorflow/libtensorflow.so to /usr/local/lib. If this is not possible, add $TENSORFLOW_SRC/tensorflow/core/public to CPATH and $TENSORFLOW_SRC/bazel-bin/tensorflow to LD_LIBRARY_PATH.

You may need to run ldconfig to reset ld's cache after copying libtensorflow.so.

Now run cargo build as usual. To include the unstable API (which is currently the entire API), use --features tensorflow_unstable.

Run cargo doc --features tensorflow_unstable. See below.

Run cargo test --features tensorflow_unstable. See below.

The unstable parts of the API (which is currently the entire API) are feature-gated behind the feature tensorflow_unstable to prevent accidental use. See http://doc.crates.io/manifest.html#the-features-section. (We would prefer using an #[unstable] attribute, but that doesn't exist yet.)

This project is not directly affiliated with the TensorFlow project, although we do intend to communicate and cooperate with them.

See CONTRIBUTING.md for information on how to contribute code.

This is not an official Google product.

##For more information

• TensorFlow website
• TensorFlow GitHub page