Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling

Kavli Affiliate: John Richardson

| First 5 Authors: Jonathan Shen, Patrick Nguyen, Yonghui Wu, Zhifeng Chen, Mia X. Chen

| Summary:

Lingvo is a Tensorflow framework offering a complete solution for
collaborative deep learning research, with a particular focus towards
sequence-to-sequence models. Lingvo models are composed of modular building
blocks that are flexible and easily extensible, and experiment configurations
are centralized and highly customizable. Distributed training and quantized
inference are supported directly within the framework, and it contains existing
implementations of a large number of utilities, helper functions, and the
newest research ideas. Lingvo has been used in collaboration by dozens of
researchers in more than 20 papers over the last two years. This document
outlines the underlying design of Lingvo and serves as an introduction to the
various pieces of the framework, while also offering examples of advanced
features that showcase the capabilities of the framework.

| Search Query: ArXiv Query: search_query=au:”John Richardson”&id_list=&start=0&max_results=10

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