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| | """E Corpus""" |
| |
|
| | import re |
| |
|
| | import datasets |
| |
|
| |
|
| | _CITATION = """\ |
| | @misc{E Dataset, |
| | title={E Dataset}, |
| | author={Jameson Quave}, |
| | howpublished{\\url{https://huggingface.co/jquave}}, |
| | year={2023} |
| | } |
| | """ |
| |
|
| | _DESCRIPTION = """\ |
| | An open-source replication of E |
| | """ |
| |
|
| | _N_DATA_FILES = 17 |
| | _N_DATA_FILES = 1 |
| | _DATA_FILES = ["ethereum_{:02d}.tar".format(i) for i in range(_N_DATA_FILES)] |
| | print(_DATA_FILES) |
| |
|
| |
|
| | class EDataset(datasets.GeneratorBasedBuilder): |
| | """The E dataset.""" |
| |
|
| | BUILDER_CONFIGS = [ |
| | datasets.BuilderConfig( |
| | name="plain_text", |
| | description="Plain text", |
| | version=datasets.Version("1.0.0"), |
| | ) |
| | ] |
| |
|
| | def _info(self): |
| | return datasets.DatasetInfo( |
| | description=_DESCRIPTION, |
| | features=datasets.Features({"train": datasets.Value("string")}), |
| | homepage="https://huggingface.co/jquave", |
| | citation=_CITATION, |
| | ) |
| |
|
| | def _split_generators(self, dl_manager): |
| | archives = dl_manager.download(_DATA_FILES) |
| | return [ |
| | datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={ |
| | "archive_iterators": [ |
| | dl_manager.iter_archive(archive) for archive in archives |
| | ], |
| | "iter_archive": dl_manager.iter_archive |
| | }), |
| | ] |
| |
|
| | def _generate_examples(self, archive_iterators, iter_archive): |
| | """Yields examples.""" |
| | for archive_iterator in archive_iterators: |
| | for code_path, code_f in archive_iterator: |
| | if code_path.endswith(".sol.txt") or code_path.endswith(".sol"): |
| | yield code_path, {"train": code_f.read().decode("utf-8").strip()} |