|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
import csv |
|
import json |
|
import os |
|
|
|
import datasets |
|
|
|
|
|
_DESCRIPTION = """\ |
|
This new dataset is designed to solve persian long summarization tasks. |
|
""" |
|
|
|
_URLS = { |
|
"train": "https://huggingface.co/datasets/zedfum/long-summarization-persian/blob/main/train.csv", |
|
"validation": "https://huggingface.co/datasets/zedfum/long-summarization-persian/blob/main/validation.csv", |
|
"test": "https://huggingface.co/datasets/zedfum/long-summarization-persian/blob/main/test.csv", |
|
} |
|
class long_summarization_persianConfig(datasets.BuilderConfig): |
|
|
|
def __init__(self, **kwargs): |
|
"""BuilderConfig for long_summarization_persian. |
|
Args: |
|
**kwargs: keyword arguments forwarded to super. |
|
""" |
|
super(long_summarization_persianConfig, self).__init__(**kwargs) |
|
|
|
class long_summarization_persian(datasets.GeneratorBasedBuilder): |
|
|
|
BUILDER_CONFIGS = [ |
|
long_summarization_persianConfig( |
|
name="long_summarization_persian", |
|
version=datasets.Version("1.0.0"), |
|
description="long_summarization_persian dataset", |
|
), |
|
] |
|
|
|
def _info(self): |
|
|
|
return datasets.DatasetInfo( |
|
description=_DESCRIPTION, |
|
features=datasets.Features( |
|
{ |
|
"id": datasets.Value("string"), |
|
"article": datasets.Value("string"), |
|
"summary": datasets.Value("string") |
|
} |
|
), |
|
) |
|
|
|
def _split_generators(self, dl_manager): |
|
urls_to_download = _URLS |
|
downloaded_files = dl_manager.download_and_extract(urls_to_download) |
|
|
|
return [ |
|
datasets.SplitGenerator( |
|
name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]} |
|
), |
|
datasets.SplitGenerator( |
|
name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]} |
|
), |
|
datasets.SplitGenerator( |
|
name=datasets.Split.VALIDATION, |
|
gen_kwargs={"filepath": downloaded_files["validation"]}, |
|
), |
|
] |
|
|
|
|
|
|
|
def _generate_examples(self, filepath): |
|
"""This function returns the examples in the raw (text) form.""" |
|
logger.info("generating examples from = %s", filepath) |
|
with open(filepath, encoding="utf-8") as f: |
|
data = json.load(f) |
|
for id_, article in enumerate(data): |
|
article = article["article"] |
|
summary = article["summary"] |
|
yield id_, { |
|
"article": article, |
|
"summary": summary, |
|
} |