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# -*- coding: utf-8 -*-
import os
import json
import datasets
import pandas as pd
_DESCRIPTION = """datasets-for-simcse"""
_CITATION = ''
GITHUB_HOME = ''
class DatasetsForSimCSEConfig(datasets.BuilderConfig):
def __init__(self, features, data_url, citation, url, label_classes=(0, 1), **kwargs):
super().__init__(version=datasets.Version("1.0.0"), **kwargs)
self.features = features
self.label_classes = label_classes
self.data_url = data_url
self.citation = citation
self.url = url
class DatasetsForSimCSE(datasets.GeneratorBasedBuilder):
"""The Natural Language Inference Chinese(NLI_zh) Corpus."""
BUILDER_CONFIGS = [
DatasetsForSimCSEConfig(
name="nli_for_simcse",
description=_DESCRIPTION,
features=datasets.Features({"sent0": datasets.Value("string"),
"sent1": datasets.Value("string"),
"hard_neg": datasets.Value("string")}),
data_url='https://huggingface.co/datasets/princeton-nlp/datasets-for-simcse/resolve/main/nli_for_simcse.csv',
citation=_CITATION,
url=GITHUB_HOME,
)
]
def _info(self):
return datasets.DatasetInfo(
description=self.config.description,
features=self.config.features,
homepage=self.config.url,
citation=self.config.citation,
)
def _split_generators(self, dl_manager):
filepath = dl_manager.download(self.config.data_url)
return [datasets.SplitGenerator(
name='train',
gen_kwargs={
"filepath": filepath,
})]
def _generate_examples(self, filepath):
"""This function returns the examples in the raw (text) form."""
df = pd.read_csv(filepath, sep=',')
for idx, row in df.iterrows():
context = {'sent0': row['sent0'], 'sent1': row['sent1'], 'hard_neg': row['hard_neg']}
yield idx, context |