Datasets:
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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 |