Abstract
Marian is a self-contained neural machine translation framework with integrated dynamic computation graphs for efficient training and translation.
AI-generated summary
We present Marian, an efficient and self-contained Neural Machine Translation framework with an integrated automatic differentiation engine based on dynamic computation graphs. Marian is written entirely in C++. We describe the design of the encoder-decoder framework and demonstrate that a research-friendly toolkit can achieve high training and translation speed.
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