GitHub repository <https://github.com/rwth-i6/returnn>_.
RETURNN paper 2016 <https://arxiv.org/abs/1608.00895>,
RETURNN paper 2018 <https://arxiv.org/abs/1805.05225>_.
RETURNN - RWTH extensible training framework for universal recurrent neural networks, is a Theano/TensorFlow-based implementation of modern recurrent neural network architectures. It is optimized for fast and reliable training of recurrent neural networks in a multi-GPU environment.
The high-level features and goals of RETURNN are:
All items are important for research, decoding speed is esp. important for production.
Interspeech 2020 tutorial "Efficient and Flexible Implementation of Machine Learning for ASR and MT" video <https://www.youtube.com/watch?v=wPKdYqSOlAY>
with an introduction of the core concepts.
More specific features include:
basic usage <https://returnn.readthedocs.io/en/latest/basic_usage.html>
technological overview <https://returnn.readthedocs.io/en/latest/tech_overview.html>__.
Here is the video recording of a RETURNN overview talk <https://www-i6.informatik.rwth-aachen.de/web/Software/returnn/downloads/workshop-2019-01-29/01.recording.cut.mp4>_
exercise sheet <https://www-i6.informatik.rwth-aachen.de/web/Software/returnn/downloads/workshop-2019-01-29/01.exercise_sheet.pdf>;
hosted by eBay).
many example demos <https://github.com/rwth-i6/returnn/blob/master/demos/>_
which work on artificially generated data,
i.e. they should work as-is.
some real-world examples <https://github.com/rwth-i6/returnn-experiments>_
such as setups for speech recognition on the Switchboard or LibriSpeech corpus.
Some benchmark setups against other frameworks
can be found
The results are in the
RETURNN paper 2016 <https://arxiv.org/abs/1608.00895>.
Performance benchmarks of our LSTM kernel vs CuDNN and other TensorFlow kernels
TensorFlow LSTM benchmark <https://returnn.readthedocs.io/en/latest/tf_lstm_benchmark.html>__.
There is also
a wiki <https://github.com/rwth-i6/returnn/wiki>.
Questions can also be asked on
StackOverflow using the RETURNN tag <https://stackoverflow.com/questions/tagged/returnn>.