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| | """The Open WebText Corpus""" |
| |
|
| |
|
| | import os |
| | import re |
| | from itertools import chain |
| | import tarfile |
| | import lzma |
| |
|
| | import datasets |
| |
|
| |
|
| | _CITATION = """\ |
| | @misc{Gokaslan2019OpenWeb, |
| | title={OpenWebText Corpus}, |
| | author={Aaron Gokaslan*, Vanya Cohen*, Ellie Pavlick, Stefanie Tellex}, |
| | howpublished{\\url{http://Skylion007.github.io/OpenWebTextCorpus}}, |
| | year={2019} |
| | } |
| | """ |
| |
|
| | _DESCRIPTION = """\ |
| | An open-source replication of the WebText dataset from OpenAI. |
| | """ |
| |
|
| | _URL = "https://zenodo.org/record/3834942/files/openwebtext.tar.xz" |
| |
|
| | def custom_iter_archive(path_or_buf, _filter=lambda x: True): |
| | decompressor = lzma.LZMADecompressor() |
| | def _iter_archive(f): |
| | stream = tarfile.open(fileobj=f, mode="r|*") |
| | for i, tarinfo in enumerate(stream): |
| | if not _filter(i): |
| | continue |
| | file_path = tarinfo.name |
| | if not tarinfo.isreg(): |
| | continue |
| | if file_path is None: |
| | continue |
| | if os.path.basename(file_path).startswith(".") or os.path.basename(file_path).startswith("__"): |
| | |
| | continue |
| | if not file_path.endswith('xz'): |
| | continue |
| | file_obj = stream.extractfile(tarinfo) |
| | decompressed = tarfile.open(fileobj=file_obj, mode='r|xz') |
| | for j, xzinfo in enumerate(decompressed): |
| | if not xzinfo.name.endswith('txt'): |
| | continue |
| | txt_file = decompressed.extractfile(xzinfo) |
| | yield txt_file |
| | stream.members = [] |
| | del stream |
| | if hasattr(path_or_buf, "read"): |
| | yield from _iter_archive(path_or_buf) |
| | else: |
| | with open(path_or_buf, "rb") as f: |
| | yield from _iter_archive(f) |
| |
|
| | class Openwebtext(datasets.GeneratorBasedBuilder): |
| | """The Open WebText 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({"text": datasets.Value("string")}), |
| | homepage="https://skylion007.github.io/OpenWebTextCorpus/", |
| | citation=_CITATION, |
| | ) |
| |
|
| | def _split_generators(self, dl_manager): |
| | archive = dl_manager.download(_URL) |
| | |
| | train_filter = lambda x : (x%10) < 8 |
| | val_filter = lambda x: (x%10) == 8 |
| | test_filter = lambda x: (x%10) == 9 |
| | return [ |
| | datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"files": custom_iter_archive(archive, train_filter)}), |
| | datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"files": custom_iter_archive(archive, val_filter)}), |
| | datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"files": custom_iter_archive(archive, test_filter)}), |
| | ] |
| |
|
| | def _generate_examples(self, files): |
| | """Yields examples.""" |
| | idx = 0 |
| | for f in files: |
| | lines = f.readlines() |
| | for line in lines: |
| | line_str = line.decode().strip() |
| | if line_str: |
| | idx+=1 |
| | yield idx, {"text": line_str} |
| |
|