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README.md

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[![Status](https://travis-ci.org/tensorflow/rust.svg?branch=master)](https://travis-ci.org/tensorflow/rust)
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TensorFlow Rust provides idiomatic [Rust](https://www.rust-lang.org) language
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bindings for [TensorFlow](http://tensorflow.org).
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bindings for [TensorFlow](https://www.tensorflow.org).
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**Notice:** This project is still under active development and not guaranteed to have a
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stable API. This is especially true because the underlying TensorFlow C API has not yet
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been stabilized as well.
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* [Documentation](https://tensorflow.github.io/rust/tensorflow/)
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* [TensorFlow website](http://tensorflow.org)
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* [TensorFlow website](https://www.tensorflow.org)
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* [TensorFlow GitHub page](https://github.com/tensorflow/tensorflow)
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## Getting Started
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extern crate tensorflow;
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```
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Then run `cargo build -j 1`. Since TensorFlow is built during this process, and
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the TensorFlow build is very memory intensive, we recommend using the `-j 1`
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flag which tells cargo to use only one task, which in turn tells TensorFlow to
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build with only one task. Of course, if you have a lot of RAM, you can use a
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higher value.
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Then run `cargo build -j 1`. The tensorflow-sys crate's
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[`build.rs`](https://github.com/tensorflow/rust/blob/f204b39/tensorflow-sys/build.rs#L44-L52)
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now either downloads a pre-built, basic CPU only binary
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([the default](https://github.com/tensorflow/rust/pull/65))
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or compiles TensorFlow if forced to by an environment variable. If TensorFlow
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is compiled during this process, since the full compilation is very memory
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intensive, we recommend using the `-j 1` flag which tells cargo to use only one
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task, which in turn tells TensorFlow to build with only one task. Though, if
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you have a lot of RAM, you can obviously use a higher value.
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To include the especially unstable API (which is currently the `expr` module),
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use `--features tensorflow_unstable`.
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1. Install [SWIG](http://www.swig.org) and [NumPy](http://www.numpy.org). The
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version from your distro's package manager should be fine for these two.
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2. [Install Bazel](http://bazel.io/docs/install.html), which you may need to do
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2. [Install Bazel](https://bazel.io/docs/install.html), which you may need to do
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from source.
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3. `git clone https://github.com/tensorflow/tensorflow`
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4. `cd tensorflow`
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You may need to run `ldconfig` to reset `ld`'s cache after copying `libtensorflow.so`.
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**OSX Note**: If you are running on OSX, there is a
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[Homebrew PR](https://github.com/Homebrew/homebrew-core/pull/10273) in process which, once merged,
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will make it easy to install `libtensorflow` wihout hassle. In the meantime, you can take a look at
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[snipsco/tensorflow-build](https://github.com/snipsco/tensorflow-build) which provides a homebrew
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tap that does essentially the same.
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**macOS Note**: Via [Homebrew](https://brew.sh/), you can just run
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`brew install libtensorflow`.
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## FAQ's
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## Contributing
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Developers and users are welcome to join
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[#tensorflow-rust](http://chat.mibbit.com/?server=irc.mozilla.org&channel=%23tensorflow-rust)
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[#tensorflow-rust](https://chat.mibbit.com/?server=irc.mozilla.org&channel=%23tensorflow-rust)
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on irc.mozilla.org.
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See [CONTRIBUTING.md](CONTRIBUTING.md) for information on how to contribute code.
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Please read the [contribution guidelines](CONTRIBUTING.md) on how to contribute code.
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This is not an official Google product.
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RFCs are [issues tagged with RFC](https://github.com/tensorflow/rust/labels/rfc).
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Check them out and comment. Discussions are welcome. After all, thats what a Request For
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Comment is for!
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Check them out and comment. Discussions are welcomed. After all, that is the purpose of
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Request For Comment!
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## License
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This project is licensed under the terms of the [Apache 2.0 license](https://github.com/tensorflow/rust/blob/master/LICENSE).
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This project is licensed under the terms of the [Apache 2.0 license](LICENSE).

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