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Author
Contributors
Last Commit
Oct. 15, 2017
Created
Sep. 8, 2017

OpenSeq2Seq: multi-gpu sequence to sequence learning

This is a research project, not an official NVIDIA product.

Features

  1. Sequence to sequence learning
    1. Different cell types: LSTM, GRU, GLSTM, SLSTM
    2. Encoders: RNN-based, unidirectional, bi-directional, GNMT-like
    3. Attention mechanisms: Bahdanau, Luong, GNMT-like
    4. Beam search for inference
  2. Data parallel multi-gpu training
  3. LARS norm scaling algorithm

Getting started

Requirements

  • Python 3.6
  • Tensorflow r1.2 or r1.3 (with GPU support)
  • NLTK v3.2.3+

Unit tests

Checkout the code and make sure the following test pass: You should see OK after each test

./create_toy_data.sh
python -m unittest test/data_layer_tests.py
python -m unittest test/model_tests.py

Full documentation is available on the repository wiki.