mathqa-x.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/mbxp-exec-eval"

_LICENSE = "Apache License 2.0"

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

_LICENSES = defaultdict(lambda: _LICENSE)

_CITATIONS = defaultdict(lambda: _CITATION)
_CITATIONS["python"] = """\
@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},
}
@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}
}"""

_GITHUB_ROOT = "https://raw.githubusercontent.com/amazon-science/mbxp-exec-eval/main/data/multilingual_mathqa/"

metadata_dict_path = requests.get(os.path.join(_GITHUB_ROOT, "metadata.json"))
metadata = json.loads(metadata_dict_path.text)

class MathQAXConfig(datasets.BuilderConfig):
    """BuilderConfig for MathQA-X."""

    def __init__(
        self,
        language,
        data_url,
        citation,
        version,
        **kwargs,
    ):
        super(MathQAXConfig, self).__init__(version=datasets.Version(f"{version}", ""), **kwargs)
        self.name = language
        self.data_url = data_url
        self.citation = citation


class MathQAX(datasets.GeneratorBasedBuilder):
    """MathQA-X: An execution-based MathQA-X benchmark for code generation."""

    BUILDER_CONFIGS = [
        MathQAXConfig(
            name=f"{language}",
            language=f"{language}",
            version=VERSION,
            citation=_CITATIONS[f"{language}"],
            description=f"MathQA-X benchmark in {language}",
            data_url=os.path.join(_GITHUB_ROOT, language_path)
        ) for language, language_path in metadata.items()
    ]

    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."""
        data_file = dl_manager.download_and_extract(url_or_urls=self.config.data_url)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    "filepath": data_file,
                },
            )
        ]

    
    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