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RETURNN development tree

RETURNN - RWTH extensible training framework for universal recurrent neural networks, is a Theano-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.

Features include:

  • Mini-batch training of feed-forward neural networks
  • Sequence-chunking based batch training for recurrent neural networks
  • Long short-term memory recurrent neural networks
  • Memory management for large data sets
  • Work distribution across multiple devices

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The RWTH extensible training framework for universal recurrent neural networks

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  • Python 93.7%
  • C++ 6.3%