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GNMT v2 for PyTorch
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NVIDIA Deep Learning Examples
NVIDIA Deep Learning Examples
GNMT v2 for PyTorch

The GNMT v2 model is an improved version of the first Google's Neural Machine Translation System with a modified attention mechanism.

Changelog

  • July 2020
    • Added support for NVIDIA DGX A100
    • Default container updated to NGC PyTorch 20.06-py3
  • June 2019
    • Default container updated to NGC PyTorch 19.05-py3
    • Mixed precision training implemented using APEX AMP
    • Added inference throughput and latency results on NVIDIA T4 and NVIDIA Tesla V100 16GB
    • Added option to run inference on user-provided raw input text from command line
  • February 2019
    • Different batching algorithm (bucketing with 5 equal-width buckets)
    • Additional dropouts before first LSTM layer in encoder and in decoder
    • Weight initialization changed to uniform (-0.1,0.1)
    • Switched order of dropout and concatenation with attention in decoder
    • Default container updated to NGC PyTorch 19.01-py3
  • December 2018
    • Added exponential warm-up and step learning rate decay
    • Multi-GPU (distributed) inference and validation
    • Default container updated to NGC PyTorch 18.11-py3
    • General performance improvements
  • August 2018
    • Initial release

Known issues

There are no known issues in this release.

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