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