parquet-converter
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Update parquet files
Browse files- .gitattributes +0 -51
- AhmedSSoliman--DJANGO/csv-test.parquet +3 -0
- AhmedSSoliman--DJANGO/csv-train.parquet +3 -0
- AhmedSSoliman--DJANGO/csv-validation.parquet +3 -0
- README.md +0 -31
- test.csv +0 -0
- train.csv +0 -0
- validation.csv +0 -0
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AhmedSSoliman--DJANGO/csv-test.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:51b528bd7742d27167ac6bb765fb2fcaa586ac95275e6772789b131fb4e976f2
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size 127638
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AhmedSSoliman--DJANGO/csv-train.parquet
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AhmedSSoliman--DJANGO/csv-validation.parquet
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version https://git-lfs.github.com/spec/v1
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README.md
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Django Dataset for Code Translation Tasks
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=========================================
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*Django* dataset used in the paper
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[*"Learning to Generate Pseudo-Code from Source Code Using Statistical Machine Translation"*](http://ieeexplore.ieee.org/document/7372045/),
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Oda et al., ASE, 2015.
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The Django dataset is a dataset for code generation comprising of 16000 training, 1000 development and 1805 test annotations. Each data point consists of a line of Python code together with a manually created natural language description.
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```bibtex
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@inproceedings{oda2015ase:pseudogen1,
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author = {Oda, Yusuke and Fudaba, Hiroyuki and Neubig, Graham and Hata, Hideaki and Sakti, Sakriani and Toda, Tomoki and Nakamura, Satoshi},
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title = {Learning to Generate Pseudo-code from Source Code Using Statistical Machine Translation},
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booktitle = {Proceedings of the 2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)},
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series = {ASE '15},
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month = {November},
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year = {2015},
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isbn = {978-1-5090-0025-8},
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pages = {574--584},
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numpages = {11},
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url = {https://doi.org/10.1109/ASE.2015.36},
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doi = {10.1109/ASE.2015.36},
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acmid = {2916173},
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publisher = {IEEE Computer Society},
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address = {Lincoln, Nebraska, USA}
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}
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```
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test.csv
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train.csv
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validation.csv
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