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README.md
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---
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license: mit
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task_categories:
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- text-generation
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tags:
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- code
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pretty_name: pycoder-type
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---
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# PyCoder
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This repository contains the dataset for the paper [Syntax-Aware On-the-Fly Code Completion](https://arxiv.org/abs/2211.04673)
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The sample code to run the model can be found in directory: "`assets/notebooks/inference.ipynb`" in our GitHub: https://github.com/awsm-research/pycoder.
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PyCoder is an auto code completion model which leverages a Multi-Task Training technique (MTT) to cooperatively
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learn the code prediction task and the type prediction task. For the type prediction
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task, we propose to leverage the standard Python token
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type information (e.g., String, Number, Name, Keyword),
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which is readily available and lightweight, instead of using
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the AST information which requires source code to be parsable for an extraction, limiting its ability to perform on-the-fly code completion (see Section 2.3 in our paper).
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More information can be found in our paper.
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If you use our code or PyCoder, please cite our paper.
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<pre><code>@article{takerngsaksiri2022syntax,
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title={Syntax-Aware On-the-Fly Code Completion},
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author={Takerngsaksiri, Wannita and Tantithamthavorn, Chakkrit and Li, Yuan-Fang},
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journal={arXiv preprint arXiv:2211.04673},
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year={2022}
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}</code></pre>
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