Uses old Rust 2015
|0.0.10||Sep 8, 2018|
|0.0.9||May 16, 2018|
|0.0.7||Jan 22, 2018|
|0.0.5||Sep 16, 2017|
|0.0.2||Aug 9, 2017|
#560 in Machine learning
22 downloads per month
TF deploy / Rust
A tiny TensorFlow inference-only executor.
TensorFlow is a big beast. It is designed for being as efficient as possible when training NN models on big platforms, with as much support for custom hardware as practical.
Performing inference, aka running trained models sometimes needs to happen on small-ish devices, like mobiles phones or single-board computers. Cross-compiling TensorFlow for these platforms can be a daunting task, and does produce a huge libraries.
TFDeploy is a tensorflow-compatible inference library. It loads a tensorflow
frozen model from the regular protobuf format, and runs data through it.
TFDeploy is very far from supporting any arbitrary model, it can run
Google Inception v3, or Snips hotword models, and missing operators are easy
One important guiding cross-concern: this library must cross-compile as easily as practical to small-ish devices (think 30$ boards).
- integrate other TF models to use as example, test and bench
- investigate alternative impls for Conv2D, and dilated convolutions
- consider having a separate set of non-TF mimicking operators
- optimise some ops combination (mul followed by add -> GEMM for instance)
- support kaldi
Note: files in the
protos/tensorflow directory are copied from the
TensorFlow project and are not
covered by the following licence statement.
All original work licensed under either of
- Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
- MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT) at your option.
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.