| """TODO(Indicxparaphrase): Add a description here.""" | |
| import json | |
| import pandas as pd | |
| import datasets | |
| _HOMEPAGE = "" | |
| _CITATION = """\ | |
| """ | |
| _DESCRIPTION = """\ | |
| """ | |
| _LANG = ["as", "bn", "gu", "hi", "kn", "ml", "mr", "or", "pa", "te"] | |
| _URL = "https://huggingface.co/datasets/ai4bharat/IndicXParaphrase/resolve/main/data/{language}.tsv" | |
| _VERSION = datasets.Version("1.0.0", "First version of Indicxparaphrase") | |
| class Indicxparaphrase(datasets.GeneratorBasedBuilder): | |
| """TODO(Indicxparaphrase): Short description of my dataset.""" | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig( | |
| name=f"{lang}", | |
| description=f"Cross-lingual paraphrase dataset for language {lang}", | |
| version=_VERSION, | |
| ) | |
| for lang in _LANG | |
| ] | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION + self.config.description, | |
| features=datasets.Features( | |
| { | |
| "english": datasets.Value("string"), | |
| "sentence1": datasets.Value("string"), | |
| "sentence2": datasets.Value("string"), | |
| "label": datasets.features.ClassLabel(names=["0", "1"]), | |
| } | |
| ), | |
| homepage=_HOMEPAGE, | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| """Returns SplitGenerators.""" | |
| language = self.config.name | |
| splits = {datasets.Split.TEST: "test"} | |
| data_urls = { | |
| split: _URL.format(language=language) for split in splits | |
| } | |
| dl_paths = dl_manager.download(data_urls) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=split, | |
| gen_kwargs={"filepath": dl_paths[split]}, | |
| ) | |
| for split in splits | |
| ] | |
| def _generate_examples(self, filepath): | |
| """Yields examples.""" | |
| df = pd.read_csv(filepath, sep="\t") | |
| for idx, row in df.iterrows(): | |
| yield idx, { | |
| "english": row['en'], | |
| "sentence1": row['sentence1'], | |
| "sentence2": row['sentence2'], | |
| "label": row['label'], | |
| } |