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import json |
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import datasets |
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_DESCRIPTION = """The MBPP dataset in BabelCode format.""" |
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_URL = "https://raw.githubusercontent.com/google-research/babelcode/main/data/hf_datasets/mbpp.jsonl" |
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_LANGUAGES = { |
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"C++", |
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"CSharp", |
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"Dart", |
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"Go", |
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"Haskell", |
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"Java", |
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"Javascript", |
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"Julia", |
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"Kotlin", |
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"Lua", |
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"PHP", |
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"R", |
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"Rust", |
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"Scala", |
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"TypeScript", |
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} |
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_CITATION = """\ |
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@article{orlanski2023measuring, |
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title={Measuring The Impact Of Programming Language Distribution}, |
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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}, |
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journal={arXiv preprint arXiv:2302.01973}, |
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year={2023} |
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} |
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@article{Austin2021ProgramSW, |
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title={Program Synthesis with Large Language Models}, |
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author={Jacob Austin and Augustus Odena and Maxwell Nye and Maarten Bosma and Henryk Michalewski and David Dohan and Ellen Jiang and Carrie J. Cai and Michael Terry and Quoc V. Le and Charles Sutton}, |
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journal={ArXiv}, |
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year={2021}, |
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volume={abs/2108.07732} |
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}""" |
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_HOMEPAGE = "https://github.com/google-research/babelcode" |
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_LICENSE = "CC-BY-4.0" |
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_VERSION = "1.0.0" |
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class BCMBPP(datasets.GeneratorBasedBuilder): |
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"""BC-MBPP""" |
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VERSION = datasets.Version(_VERSION) |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig( |
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name="all", |
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version=datasets.Version(_VERSION), |
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description=_DESCRIPTION, |
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), |
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] + [ |
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datasets.BuilderConfig( |
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name=lang, |
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version=datasets.Version(_VERSION), |
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description=_DESCRIPTION + f" Examples are only in {lang}.", |
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) |
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for lang in _LANGUAGES |
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] |
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DEFAULT_CONFIG_NAME = "all" |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"qid": datasets.Value("string"), |
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"title": datasets.Value("string"), |
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"language": datasets.Value("string"), |
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"text":datasets.Value("string"), |
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"signature_with_docstring": datasets.Value("string"), |
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"signature": datasets.Value("string"), |
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"arguments": datasets.Sequence(datasets.Value("string")), |
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"entry_fn_name": datasets.Value("string"), |
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"entry_cls_name": datasets.Value("string"), |
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"test_code": datasets.Value("string"), |
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"solution":datasets.Value("string"), |
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"test_list": datasets.Value("string"), |
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"test_case_ids":datasets.Sequence(datasets.Value("string")) |
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} |
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) |
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description = _DESCRIPTION |
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if self.config.name != 'all': |
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description = _DESCRIPTION + f" Examples are only in {self.config.name}." |
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return datasets.DatasetInfo( |
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description=description, |
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features=features, |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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data_dir = dl_manager.download_and_extract(_URL) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={"filepath": data_dir, "split": "train"}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={"filepath": data_dir, "split": "test"}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={"filepath": data_dir, "split": "validation"}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split("prompt"), |
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gen_kwargs={"filepath": data_dir, "split": "prompt"}, |
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), |
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] |
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def _generate_examples(self, filepath, split): |
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""" Yields the examples from the dataset""" |
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with open(filepath, encoding='utf-8') as file: |
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id_ = 0 |
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idx_range = None |
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if split == 'test': |
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idx_range=(11,510) |
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elif split == "train": |
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idx_range=(601,974) |
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elif split == "validation": |
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idx_range=(511, 600) |
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else: |
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idx_range=(1,10) |
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for l in file: |
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if not l.strip(): |
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continue |
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d = json.loads(l) |
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if self.config.name != 'all' and d['language'] != self.config.name: |
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continue |
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idx = int(d['title'].split('/')[-1]) |
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if not (idx_range[0] <= idx <= idx_range[1]): |
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continue |
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d['test_list'] = json.dumps(d['test_list']) |
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d['solution'] = d.pop('solution_python') |
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yield id_, d |
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id_+=1 |
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