Datasets:
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#!/usr/bin/python3
# -*- coding: utf-8 -*-
from glob import glob
import os
from pathlib import Path
import datasets
import pandas as pd
import requests
_METADATA_URL = "metadata.csv"
_CITATION = """\
@dataset{h_novel,
author = {Xing Tian},
title = {h_novel},
month = aug,
year = 2023,
publisher = {Xing Tian},
version = {1.0},
}
"""
_DESCRIPTION = """\
This dataset contains some SQ novel.
It is supposed to be used for text generation tasks.
"""
class HNovel(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="ltxsba", version=VERSION, description="ltxsba"),
datasets.BuilderConfig(name="ltxsba_1gb", version=VERSION, description="ltxsba_1gb"),
datasets.BuilderConfig(name="ltxsba_5gb", version=VERSION, description="ltxsba_5gb"),
datasets.BuilderConfig(name="ltxsba_100m", version=VERSION, description="ltxsba_100m"),
datasets.BuilderConfig(name="ltxsba_500m", version=VERSION, description="ltxsba_500m"),
datasets.BuilderConfig(name="yazhou", version=VERSION, description="yazhou"),
datasets.BuilderConfig(name="yazhou_5m", version=VERSION, description="yazhou_5m"),
datasets.BuilderConfig(name="yazhou_10m", version=VERSION, description="yazhou_10m"),
datasets.BuilderConfig(name="yazhou_20m", version=VERSION, description="yazhou_20m"),
datasets.BuilderConfig(name="yazhou_50m", version=VERSION, description="yazhou_50m"),
datasets.BuilderConfig(name="yazhou_70m", version=VERSION, description="yazhou_70m"),
datasets.BuilderConfig(name="all", version=VERSION, description="all"),
]
def _info(self):
features = datasets.Features(
{
"source": datasets.Value("string"),
"idx": datasets.Value("string"),
"filename": datasets.Value("string"),
"novel_name": datasets.Value("string"),
"row_idx": datasets.Value("string"),
"text": datasets.Value("string"),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
supervised_keys=None,
homepage="",
license="",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
dl_path = dl_manager.download(_METADATA_URL)
archive_path = dl_path
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"archive_path": archive_path, "dl_manager": dl_manager},
),
]
def _generate_examples(self, archive_path, dl_manager):
"""Yields examples."""
sample_idx = 0
df = pd.read_csv(archive_path)
for i, row in df.iterrows():
source = row["source"]
filename = row["filename"]
if self.config.name != "all" and source != self.config.name:
continue
try:
filename = dl_manager.download(filename)
except Exception:
continue
filename = Path(filename)
name = filename.stem
splits = name.split("_")
idx = splits[-1]
novel_name = "_".join(splits[:-1])
row_idx = 1
with open(filename.as_posix(), "r", encoding="utf-8") as f:
for txt_row in f:
txt_row = str(txt_row).strip()
if len(txt_row) == 0:
continue
yield sample_idx, {
"source": source,
"idx": idx,
"filename": "/".join(filename.parts[-3:]),
"novel_name": novel_name,
"row_idx": row_idx,
"text": txt_row,
}
row_idx += 1
sample_idx += 1
if __name__ == '__main__':
pass
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