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