Notice: This project is still under active development and not guaranteed to have a stable API. This is especially true because the underlying TensorFlow C API has not yet been stabilized as well.
Since this crate depends on the TensorFlow C API, it needs to be compiled first. This crate will automatically compile TensorFlow for you, but it is also possible to manually install TensorFlow and the crate will pick it up accordingly.
The following dependencies are needed to compile and build this crate (assuming TensorFlow itself should also be compiled transparently):
- Python Dependencies
- Optionally, CUDA packages to support GPU-based processing
The TensorFlow website provides detailed instructions on how to obtain and install said dependencies, so if you are unsure please check out the docs for further details.
Add this to your
[dependencies] tensorflow = "0.4.0"
and this to your crate root:
extern crate tensorflow;
cargo build -j 1. The tensorflow-sys crate's
now either downloads a pre-built, basic CPU only binary
or compiles TensorFlow if forced to by an environment variable. If TensorFlow
is compiled during this process, since the full compilation is very memory
intensive, we recommend using the
-j 1 flag which tells cargo to use only one
task, which in turn tells TensorFlow to build with only one task. Though, if
you have a lot of RAM, you can obviously use a higher value.
To include the especially unstable API (which is currently the
For now, please see the Examples for more details on how to use this binding.
Manual TensorFlow Compilation
If you don't want to build TensorFlow after every
cargo clean or you want to work against
unreleased/unsupported TensorFlow versions, manual compilation is the way to go.
See TensorFlow from source first.
The Python/pip steps are not necessary, but building
Install Bazel, which you may need to do from source.
git clone https://github.com/tensorflow/tensorflow
bazel build --compilation_mode=opt --copt=-march=native --jobs=1 tensorflow:libtensorflow.so
--jobs=1is recommended unless you have a lot of RAM, because TensorFlow's build is very memory intensive.
If this is not possible, add
You may need to run
ldconfig to reset
ld's cache after copying
macOS Note: Via Homebrew, you can just run
brew install libtensorflow.
Why does the compiler say that parts of the API don't exist?
The especially unstable parts of the API (which is currently the
expr modul) 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.)
Developers and users are welcome to join #tensorflow-rust on irc.mozilla.org.
Please read the contribution guidelines on how to contribute code.
This is not an official Google product.
RFCs are issues tagged with RFC. Check them out and comment. Discussions are welcomed. After all, that is the purpose of Request For Comment!
This project is licensed under the terms of the Apache 2.0 license.