import json import datasets _DESCRIPTION = """The Transcoder dataset in BabelCode format. Currently supports translation from C++ and Python.""" _URL = "https://raw.githubusercontent.com/google-research/babelcode/main/data/hf_datasets/transcoder.jsonl" _LANGUAGES = { "C++", "CSharp", "Dart", "Go", "Haskell", "Java", "Javascript", "Julia", "Kotlin", "Lua", "PHP", "Python", "R", "Rust", "Scala", "TypeScript", } _CITATION = """\ @article{orlanski2023measuring, title={Measuring The Impact Of Programming Language Distribution}, author={Orlanski, Gabriel and Xiao, Kefan and Garcia, Xavier and Hui, Jeffrey and Howland, Joshua and Malmaud, Jonathan and Austin, Jacob and Singh, Rishah and Catasta, Michele}, journal={arXiv preprint arXiv:2302.01973}, year={2023} } @article{roziere2020unsupervised, title={Unsupervised translation of programming languages}, author={Roziere, Baptiste and Lachaux, Marie-Anne and Chanussot, Lowik and Lample, Guillaume}, journal={Advances in Neural Information Processing Systems}, volume={33}, year={2020} }""" _HOMEPAGE = "https://github.com/google-research/babelcode" _LICENSE = "CC-BY-4.0" _VERSION = "1.0.0" _KEYS_REMOVE = {"text", "signature_with_docstring"} _QUESTION_INFO_KEYS = { "entry_fn_name", "entry_cls_name", "test_code", "test_list", "test_case_ids", "commands", "timeouts", "extension" } class BCTranscoder(datasets.GeneratorBasedBuilder): """BC-Transcoder""" VERSION = datasets.Version(_VERSION) BUILDER_CONFIGS = [ datasets.BuilderConfig( name="all", version=datasets.Version(_VERSION), description=_DESCRIPTION, ), ] + [ datasets.BuilderConfig( name=lang, version=datasets.Version(_VERSION), description=_DESCRIPTION + f" Examples are only in {lang}.", ) for lang in _LANGUAGES ] DEFAULT_CONFIG_NAME = "all" def _info(self): list_keys = ['timeouts', 'commands', 'test_case_ids'] question_info_type = { k:datasets.Value(dtype="string") for k in _QUESTION_INFO_KEYS if k not in list_keys } question_info_type['test_case_ids'] = datasets.Sequence(datasets.Value('string')) question_info_type['commands'] = datasets.Sequence(datasets.Sequence(datasets.Value('string'))) question_info_type['timeouts'] = datasets.Sequence(datasets.Value('int32')) features = datasets.Features({ "qid": datasets.Value("string"), "title": datasets.Value("string"), "language": datasets.Value("string"), "signature": datasets.Value("string"), "arguments": datasets.Sequence(datasets.Value("string")), "source_py": datasets.Value("string"), "source_cpp": datasets.Value("string"), "question_info": datasets.Features(question_info_type) }) description = _DESCRIPTION if self.config.name != 'all': description = _DESCRIPTION + f" Examples are only in {self.config.name}." return datasets.DatasetInfo( description=description, features=features, supervised_keys=None, homepage=_HOMEPAGE, license=_LICENSE, citation=_CITATION, ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" data_dir = dl_manager.download_and_extract(_URL) return [ datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={"filepath": data_dir}, ), ] def _generate_examples(self, filepath): """ Yields the examples from the dataset""" with open(filepath, encoding='utf-8') as file: id_ = 0 for l in file: if not l.strip(): continue d = json.loads(l) if self.config.name != 'all' and d['language'] != self.config.name: continue question_info = {} for k in _QUESTION_INFO_KEYS: question_info[k] = d.pop(k) question_info['test_list'] = json.dumps(question_info['test_list']) d['question_info'] = question_info d['source_py'] = d.pop('solution_python') d['source_cpp'] = d.pop('solution_cpp') for k in _KEYS_REMOVE: d.pop(k) yield id_, d id_ += 1