|
|
|
|
|
from collections import defaultdict |
|
import json |
|
from pathlib import Path |
|
import random |
|
import re |
|
from typing import Any, Dict, List, Tuple |
|
|
|
import datasets |
|
|
|
|
|
_urls = { |
|
"enron_spam": "data/enron_spam.jsonl", |
|
"enron_spam_subset": "data/enron_spam_subset.jsonl", |
|
"ling_spam": "data/ling_spam.jsonl", |
|
"sms_spam": "data/sms_spam.jsonl", |
|
"spam_assassin": "data/spam_assassin.jsonl", |
|
"spam_detection": "data/spam_detection.jsonl", |
|
"spam_emails": "data/spam_emails.jsonl", |
|
"spam_message": "data/spam_message.jsonl", |
|
"spam_message_lr": "data/spam_message_lr.jsonl", |
|
"trec07p": "data/trec07p.jsonl", |
|
"youtube_spam_collection": "data/youtube_spam_collection.jsonl", |
|
|
|
} |
|
|
|
|
|
_CITATION = """\ |
|
@dataset{spam_detect, |
|
author = {Xing Tian}, |
|
title = {spam_detect}, |
|
month = sep, |
|
year = 2023, |
|
publisher = {Xing Tian}, |
|
version = {1.0}, |
|
} |
|
""" |
|
|
|
|
|
class SpamDetect(datasets.GeneratorBasedBuilder): |
|
VERSION = datasets.Version("1.0.0") |
|
|
|
intent_configs = list() |
|
for name in _urls.keys(): |
|
config = datasets.BuilderConfig(name=name, version=VERSION, description=name) |
|
intent_configs.append(config) |
|
|
|
BUILDER_CONFIGS = [ |
|
*intent_configs, |
|
] |
|
|
|
def _info(self): |
|
features = datasets.Features({ |
|
"text": datasets.Value("string"), |
|
"label": datasets.Value("string"), |
|
"category": datasets.Value("string"), |
|
"data_source": datasets.Value("string"), |
|
}) |
|
|
|
return datasets.DatasetInfo( |
|
features=features, |
|
supervised_keys=None, |
|
homepage="", |
|
license="", |
|
citation=_CITATION, |
|
) |
|
|
|
def _split_generators(self, dl_manager): |
|
"""Returns SplitGenerators.""" |
|
url = _urls[self.config.name] |
|
dl_path = dl_manager.download(url) |
|
archive_path = dl_path |
|
|
|
return [ |
|
datasets.SplitGenerator( |
|
name=datasets.Split.TRAIN, |
|
gen_kwargs={"archive_path": archive_path, "split": "train"}, |
|
), |
|
datasets.SplitGenerator( |
|
name=datasets.Split.VALIDATION, |
|
gen_kwargs={"archive_path": archive_path, "split": "validation"}, |
|
), |
|
datasets.SplitGenerator( |
|
name=datasets.Split.TEST, |
|
gen_kwargs={"archive_path": archive_path, "split": "test"}, |
|
), |
|
] |
|
|
|
def _generate_examples(self, archive_path, split): |
|
"""Yields examples.""" |
|
archive_path = Path(archive_path) |
|
|
|
idx = 0 |
|
|
|
with open(archive_path, "r", encoding="utf-8") as f: |
|
for row in f: |
|
sample = json.loads(row) |
|
|
|
if sample["split"] != split: |
|
continue |
|
|
|
yield idx, { |
|
"text": sample["text"], |
|
"label": sample["label"], |
|
"category": sample["category"], |
|
"data_source": sample["data_source"], |
|
} |
|
idx += 1 |
|
|
|
|
|
if __name__ == '__main__': |
|
pass |
|
|
