Datasets:
Modalities:
Text
Size:
10K - 100K
File size: 2,916 Bytes
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import csv
import datasets
_CITATION = """\
@article{hendryckstest2021,
title={Measuring Massive Multitask Language Understanding},
author={Dan Hendrycks and Collin Burns and Steven Basart and Andy Zou and Mantas Mazeika and Dawn Song and Jacob Steinhardt},
journal={Proceedings of the International Conference on Learning Representations (ICLR)},
year={2021}
}
"""
_DESCRIPTION = """\
Psycholinguistics word datasets
"""
_HOMEPAGE = "To Add"
_URL = "data.tar"
_SUBJECTS = [
"SimCat-TASLP2018",
"SimLex999-COLI2015"
]
class MyDataset(datasets.GeneratorBasedBuilder):
"""Psycholinguistics word datasets"""
# # 从 YAML 文件加载配置
# with open("dataset_infos.yaml", "r") as f:
# configs = yaml.safe_load(f)["configs"]
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name=sub, version=datasets.Version("1.0.0"), description=f"Psycholinguistics Volcabulary Datasets {sub}"
)
for sub in _SUBJECTS
# MyDatasetConfig(
# name=config["name"],
# version=datasets.Version(config["version"]),
# description=config["description"],
# data_files=config["data_files"]
# )
# for config in configs
]
def _info(self):
features = datasets.Features(
{
"word": datasets.Value("string"),
"category": datasets.Value("string"),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
archive = dl_manager.download(_URL)
return [
datasets.SplitGenerator(
name=datasets.Split.TEST,
# 传递给 _generate_examples 方法的参数
gen_kwargs={"iter_archive": dl_manager.iter_archive(archive), "split": "test"},
),
]
def _generate_examples(self, iter_archive, split):
"""Yields examples as (key, example) tuples."""
n_yielded_files = 0
for id_file, (path, file) in enumerate(iter_archive):
# For example, we iterate through the data folder and find a file with the path "data/test"
if f"data/{split}/" in path:
# For example, SimCat-TASLP2018_test.csv
if f"{self.config.name}_{split}.csv" in path:
n_yielded_files += 1
lines = (line.decode("utf-8") for line in file)
reader = csv.reader(lines)
for id_line, data in enumerate(reader):
yield f"{id_file}_{id_line}", {"Word": data[0], "Category": data[1]}
if n_yielded_files == 8:
break |