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arXiv · 2202.00367

Natural Language to Code Using Transformers

Uday Kusupati·Venkata Ravi Teja Ailavarapu
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Abstract

We tackle the problem of generating code snippets from natural language descriptions using the CoNaLa dataset. We use the self-attention based transformer architecture and show that it performs better than recurrent attention-based encoder decoder. Furthermore, we develop a modified form of back translation and use cycle consistent losses to train the model in an end-to-end fashion. We achieve a BLEU score of 16.99 beating the previously reported baseline of the CoNaLa challenge.

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Uday Kusupati, Venkata Ravi Teja Ailavarapu. 2022-02-01. Natural Language to Code Using Transformers. https://arxiv.org/abs/2202.00367

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