multi-humaneval.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)
_LICENSES["python"] = "MIT License"

_CITATIONS = defaultdict(lambda: _CITATION)

_CITATIONS["python"] = """\
@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}
}"""

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

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

class MultiHumanEvalConfig(datasets.BuilderConfig):
    """BuilderConfig for MultiHumanEval."""

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


class MultiHumanEval(datasets.GeneratorBasedBuilder):
    """MultiHumanEval: An execution-based multi-lingual HumanEval benchmark for code generation."""

    BUILDER_CONFIGS = [
        MultiHumanEvalConfig(
            name=f"{language}",
            language=f"{language}",
            version=VERSION,
            citation=_CITATIONS[f"{language}"],
            description=f"HumanEval 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"),
                "test": datasets.Value("string"),
                "entry_point": datasets.Value("string"),
                "canonical_solution": datasets.Value("string"),
                "description": 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