mxeval.py

import json
import os
import requests
import datasets

import os
from collections import defaultdict

_CITATION = """\
@article{mbxp_athiwaratkun2022,
  title = {Multi-lingual Evaluation of Code Generation Models},
  author = {Athiwaratkun, Ben and
   Gouda, Sanjay Krishna and
   Wang, Zijian and
   Li, Xiaopeng and
   Tian, Yuchen and
   Tan, Ming
   and Ahmad, Wasi Uddin and
   Wang, Shiqi and
   Sun, Qing and
   Shang, Mingyue and
   Gonugondla, Sujan Kumar and
   Ding, Hantian and
   Kumar, Varun and
   Fulton, Nathan and
   Farahani, Arash and
   Jain, Siddhartha and
   Giaquinto, Robert and
   Qian, Haifeng and
   Ramanathan, Murali Krishna and
   Nallapati, Ramesh and
   Ray, Baishakhi and
   Bhatia, Parminder and
   Sengupta, Sudipta and
   Roth, Dan and
   Xiang, Bing},
  doi = {10.48550/ARXIV.2210.14868},
  url = {https://arxiv.org/abs/2210.14868},
  keywords = {Machine Learning (cs.LG), Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
  publisher = {arXiv},
  year = {2022},
  copyright = {Creative Commons Attribution 4.0 International}
}"""

VERSION=f"1.1.0"

_HOMEPAGE = "https://github.com/amazon-science/mxeval"

_LICENSE = "Apache License 2.0"

_DESCRIPTION = """\
A collection of execution-based multi-lingual benchmark for code generation.
"""

_LICENSES = defaultdict(lambda: _LICENSE)
_LICENSES["humaneval_python"] = "MIT License"
_LICENSES["mbxp_python"] = "CC-BY-4.0"

_CITATIONS = defaultdict(lambda: _CITATION)

_CITATIONS["multi-humaneval"] = """\
@article{mbxp_athiwaratkun2022,
  title = {Multi-lingual Evaluation of Code Generation Models},
  author = {Athiwaratkun, Ben and
   Gouda, Sanjay Krishna and
   Wang, Zijian and
   Li, Xiaopeng and
   Tian, Yuchen and
   Tan, Ming
   and Ahmad, Wasi Uddin and
   Wang, Shiqi and
   Sun, Qing and
   Shang, Mingyue and
   Gonugondla, Sujan Kumar and
   Ding, Hantian and
   Kumar, Varun and
   Fulton, Nathan and
   Farahani, Arash and
   Jain, Siddhartha and
   Giaquinto, Robert and
   Qian, Haifeng and
   Ramanathan, Murali Krishna and
   Nallapati, Ramesh and
   Ray, Baishakhi and
   Bhatia, Parminder and
   Sengupta, Sudipta and
   Roth, Dan and
   Xiang, Bing},
  doi = {10.48550/ARXIV.2210.14868},
  url = {https://arxiv.org/abs/2210.14868},
  keywords = {Machine Learning (cs.LG), Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
  publisher = {arXiv},
  year = {2022},
  copyright = {Creative Commons Attribution 4.0 International}
}
@misc{chen2021evaluating,
      title={Evaluating Large Language Models Trained on Code},
      author={Mark Chen and Jerry Tworek and Heewoo Jun and Qiming Yuan and Henrique Ponde de Oliveira Pinto and Jared Kaplan and Harri Edwards and Yuri Burda and Nicholas Joseph and Greg Brockman and Alex Ray and Raul Puri and Gretchen Krueger and Michael Petrov and Heidy Khlaaf and Girish Sastry and Pamela Mishkin and Brooke Chan and Scott Gray and Nick Ryder and Mikhail Pavlov and Alethea Power and Lukasz Kaiser and Mohammad Bavarian and Clemens Winter and Philippe Tillet and Felipe Petroski Such and Dave Cummings and Matthias Plappert and Fotios Chantzis and Elizabeth Barnes and Ariel Herbert-Voss and William Hebgen Guss and Alex Nichol and Alex Paino and Nikolas Tezak and Jie Tang and Igor Babuschkin and Suchir Balaji and Shantanu Jain and William Saunders and Christopher Hesse and Andrew N. Carr and Jan Leike and Josh Achiam and Vedant Misra and Evan Morikawa and Alec Radford and Matthew Knight and Miles Brundage and Mira Murati and Katie Mayer and Peter Welinder and Bob McGrew and Dario Amodei and Sam McCandlish and Ilya Sutskever and Wojciech Zaremba},
      year={2021},
      eprint={2107.03374},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}"""

_CITATIONS["mbxp"] = """\
@article{mbxp_athiwaratkun2022,
  title = {Multi-lingual Evaluation of Code Generation Models},
  author = {Athiwaratkun, Ben and
   Gouda, Sanjay Krishna and
   Wang, Zijian and
   Li, Xiaopeng and
   Tian, Yuchen and
   Tan, Ming
   and Ahmad, Wasi Uddin and
   Wang, Shiqi and
   Sun, Qing and
   Shang, Mingyue and
   Gonugondla, Sujan Kumar and
   Ding, Hantian and
   Kumar, Varun and
   Fulton, Nathan and
   Farahani, Arash and
   Jain, Siddhartha and
   Giaquinto, Robert and
   Qian, Haifeng and
   Ramanathan, Murali Krishna and
   Nallapati, Ramesh and
   Ray, Baishakhi and
   Bhatia, Parminder and
   Sengupta, Sudipta and
   Roth, Dan and
   Xiang, Bing},
  doi = {10.48550/ARXIV.2210.14868},
  url = {https://arxiv.org/abs/2210.14868},
  keywords = {Machine Learning (cs.LG), Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
  publisher = {arXiv},
  year = {2022},
  copyright = {Creative Commons Attribution 4.0 International}
}
@article{austin2021program,
  title={Program Synthesis with Large Language Models},
  author={Austin, Jacob and Odena, Augustus and Nye, Maxwell and Bosma, Maarten and Michalewski, Henryk and Dohan, David and Jiang, Ellen and Cai, Carrie and Terry, Michael and Le, Quoc and others},
  journal={arXiv preprint arXiv:2108.07732},
  year={2021}
}"""

_CITATIONS["mathqa-x"] = """\
@article{mbxp_athiwaratkun2022,
  title = {Multi-lingual Evaluation of Code Generation Models},
  author = {Athiwaratkun, Ben and
   Gouda, Sanjay Krishna and
   Wang, Zijian and
   Li, Xiaopeng and
   Tian, Yuchen and
   Tan, Ming
   and Ahmad, Wasi Uddin and
   Wang, Shiqi and
   Sun, Qing and
   Shang, Mingyue and
   Gonugondla, Sujan Kumar and
   Ding, Hantian and
   Kumar, Varun and
   Fulton, Nathan and
   Farahani, Arash and
   Jain, Siddhartha and
   Giaquinto, Robert and
   Qian, Haifeng and
   Ramanathan, Murali Krishna and
   Nallapati, Ramesh and
   Ray, Baishakhi and
   Bhatia, Parminder and
   Sengupta, Sudipta and
   Roth, Dan and
   Xiang, Bing},
  doi = {10.48550/ARXIV.2210.14868},
  url = {https://arxiv.org/abs/2210.14868},
  keywords = {Machine Learning (cs.LG), Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
  publisher = {arXiv},
  year = {2022},
  copyright = {Creative Commons Attribution 4.0 International}
}
@inproceedings{amini-etal-2019-mathqa,
    title={MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms},
    author={Amini, Aida  and
      Gabriel, Saadia  and
      Lin, Shanchuan  and
      Koncel-Kedziorski, Rik  and
      Choi, Yejin  and
      Hajishirzi, Hannaneh},
    booktitle={Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)},
    month={jun},
    year= {2019},
    address = {Minneapolis, Minnesota},
    publisher = {Association for Computational Linguistics},
    url={https://aclanthology.org/N19-1245}
    doi={10.18653/v1/N19-1245},
    pages={2357--2367},
}
"""

_DATASET_NAME_MAPPER = {
    "mbxp": "mbxp",
    "multi-humaneval": "multilingual_humaneval",
    "mathqa-x": "multilingual_mathqa"
}

_GITHUB_ROOT = "https://raw.githubusercontent.com/amazon-science/mxeval/main/data/"


def get_metadata_dict(dataset):
    metadata_dict_path = requests.get(os.path.join(_GITHUB_ROOT, dataset, "metadata.json"))
    metadata = json.loads(metadata_dict_path.text)
    return metadata


MBXP_LANGUAGES = get_metadata_dict("mbxp")

MATHQA_LANGUAGES = get_metadata_dict("multilingual_mathqa")

HUMANEVAL_LANGUAGES = get_metadata_dict("multilingual_humaneval")

_DATASET_LANGS = {
    "multi-humaneval": HUMANEVAL_LANGUAGES,
    "mathqa-x": MATHQA_LANGUAGES,
    "mbxp": MBXP_LANGUAGES
}

_INTERNAL_DATASET_NAMES = {
    "multi-humaneval": "multilingual_humaneval",
    "mathqa-x": "multilingual_mathqa",
    "mbxp": "mbxp"
}

_URL_DICT = {
    f"{dataset.lower()}_{language.lower()}": os.path.join(
        _GITHUB_ROOT,
        _INTERNAL_DATASET_NAMES[dataset],
        _DATASET_LANGS[dataset][language]
        )
    for dataset, languages in _DATASET_LANGS.items() for language in languages
}


class MxEvalConfig(datasets.BuilderConfig):
    """BuilderConfig for MxEval."""

    def __init__(
        self,
        dataset,
        citation,
        version,
        **kwargs,
    ):
        super(MxEvalConfig, self).__init__(version=datasets.Version(f"{version}", ""), **kwargs)
        self.dataset_name = dataset
        self.data_dir = os.path.join(_GITHUB_ROOT, dataset)
        self.citation = citation


class MxEval(datasets.GeneratorBasedBuilder):
    """MxEval: An execution-based multiLingual benchmark for code generation."""

    BUILDER_CONFIGS = [
        MxEvalConfig(
            name=f"{dataset}",
            version=VERSION,
            citation=_CITATIONS[f"{dataset}"],
            dataset=_DATASET_NAME_MAPPER[dataset],
            description=f"Benchmark for {dataset}",
        ) for dataset in _DATASET_LANGS
    ]

    def _info(self):
        self.build_name = self.name
        features = datasets.Features(
            {
                "task_id": datasets.Value("string"),
                "language": datasets.Value("string"),
                "prompt": datasets.Value("string"),
                "description": datasets.Value("string"),
                "test": datasets.Value("string"),
                "entry_point": datasets.Value("string"),
                "canonical_solution": datasets.Value("string"),
            }
        )

        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            supervised_keys=None,
            homepage=_HOMEPAGE,
            license=_LICENSES[self.config.name],
            citation=_CITATIONS[self.config.name],
        )


    def _split_generators(
            self, dl_manager
    ):
        """Returns SplitGenerators."""
        return [
            datasets.SplitGenerator(
                name=datasets.Split(lang),
                gen_kwargs={
                    "filepath": dl_manager.download_and_extract(
                        url_or_urls=_URL_DICT[f"{self.config.name}_{lang}"]
                    ),
                },
            ) for lang in _DATASET_LANGS[self.config.name]
        ]

    
    def _generate_examples(self, filepath):
        """Yields examples."""
        with open(filepath) as file:
            data = []
            for line in file:
                jd = json.loads(line)
                data.append(jd)
            id_ = 0
            for sample in data:
                yield id_, sample
                id_ += 1