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"""The BookCorpus dataset based on Shawn Presser's work https://github.com/soskek/bookcorpus/issues/27 """ |
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from __future__ import absolute_import, division, print_function |
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import glob |
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import os |
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import pathlib |
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import datasets |
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_DESCRIPTION = """\ |
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Books are a rich source of both fine-grained information, how a character, \ |
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an object or a scene looks like, as well as high-level semantics, what \ |
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someone is thinking, feeling and how these states evolve through a story.\ |
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This version of bookcorpus has 17868 dataset items (books). Each item contains \ |
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two fields: title and text. The title is the name of the book (just the file name) \ |
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while text contains unprocessed book text. The bookcorpus has been prepared by \ |
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Shawn Presser and is generously hosted by The-Eye. The-Eye is a non-profit, community \ |
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driven platform dedicated to the archiving and long-term preservation of any and \ |
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all data including but by no means limited to... websites, books, games, software, \ |
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video, audio, other digital-obscura and ideas. |
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""" |
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_CITATION = """\ |
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@InProceedings{Zhu_2015_ICCV, |
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title = {Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books}, |
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author = {Zhu, Yukun and Kiros, Ryan and Zemel, Rich and Salakhutdinov, Ruslan and Urtasun, Raquel and Torralba, Antonio and Fidler, Sanja}, |
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booktitle = {The IEEE International Conference on Computer Vision (ICCV)}, |
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month = {December}, |
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year = {2015} |
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} |
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""" |
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_PROJECT_URL = "https://github.com/soskek/bookcorpus/issues/27" |
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_DOWNLOAD_URL = "https://the-eye.eu/public/AI/pile_preliminary_components/books1.tar.gz" |
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class BookCorpusOpenConfig(datasets.BuilderConfig): |
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"""BuilderConfig for BookCorpus.""" |
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def __init__(self, **kwargs): |
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"""BuilderConfig for BookCorpus. |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(BookCorpusOpenConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs) |
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class BookCorpusOpen(datasets.GeneratorBasedBuilder): |
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"""BookCorpus dataset.""" |
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BUILDER_CONFIGS = [ |
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BookCorpusOpenConfig( |
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name="plain_text", |
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description="Plain text", |
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) |
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] |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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"title": datasets.Value("string"), |
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"text": datasets.Value("string"), |
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} |
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), |
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supervised_keys=None, |
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homepage=_PROJECT_URL, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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arch_path = dl_manager.download_and_extract(_DOWNLOAD_URL) |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"directory": arch_path}), |
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] |
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def _generate_examples(self, directory): |
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glob_target = os.path.join(directory, "**/*.epub.txt") |
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book_files = glob.glob(glob_target, recursive=True) |
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book_files = sorted(book_files) |
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_id = 0 |
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for book_file_path in book_files: |
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path = pathlib.PurePath(book_file_path) |
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with open(book_file_path, mode="r", encoding="utf-8") as f: |
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yield _id, {"title": str(path.name), "text": f.read()}, |
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_id += 1 |
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