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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
@@ -45,11 +45,15 @@ and this to your crate root:
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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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@@ -101,16 +102,16 @@ use. See http://doc.crates.io/manifest.html#the-features-section.
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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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