Delete loading script

indicxnli.py

@@ -1,149 +0,0 @@
-# coding=utf-8
-
-
-# Lint as: python3
-"""IndicXNLI: The Cross-Lingual NLI Corpus for Indic Languages."""
-
-
-import os
-import json
-
-import datasets
-
-
-_CITATION = """\
-@misc{https://doi.org/10.48550/arxiv.2204.08776,
-  doi = {10.48550/ARXIV.2204.08776},
-  
-  url = {https://arxiv.org/abs/2204.08776},
-  
-  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
-  
-  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
-  
-  title = {IndicXNLI: Evaluating Multilingual Inference for Indian Languages}, 
-  
-  publisher = {arXiv},
-  
-  year = {2022},
-  
-  copyright = {Creative Commons Attribution 4.0 International}
-}
-}"""
-
-_DESCRIPTION = """\
-IndicXNLI is a translated version of XNLI to 11 Indic Languages. As with XNLI, the goal is
-to predict textual entailment (does sentence A imply/contradict/neither sentence
-B) and is a classification task (given two sentences, predict one of three
-labels).
-"""
-
-_LANGUAGES = (
-    'hi',
-    'bn',
-    'mr',
-    'as',
-    'ta',
-    'te',
-    'or',
-    'ml',
-    'pa',
-    'gu',
-    'kn'
-)
-
-
-_URL = "https://huggingface.co/datasets/Divyanshu/indicxnli/resolve/main/forward"
-
-class IndicxnliConfig(datasets.BuilderConfig):
-    """BuilderConfig for XNLI."""
-
-    def __init__(self, language: str, **kwargs):
-        """BuilderConfig for XNLI.
-
-        Args:
-        language: One of hi, bn, mr, as, ta, te, or, ml, pa, gu, kn
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(IndicxnliConfig, self).__init__(**kwargs)
-        
-        self.language = language
-        self.languages = _LANGUAGES
-        
-        self._URLS = {
-            "train": os.path.join(_URL, "train", f"xnli_{self.language}.json"),
-            "test": os.path.join(_URL, "test", f"xnli_{self.language}.json"),
-            "dev": os.path.join(_URL, "dev", f"xnli_{self.language}.json")
-        }
-
-
-class Indicxnli(datasets.GeneratorBasedBuilder):
-    """IndicXNLI: The Cross-Lingual NLI Corpus for Indic Languages. Version 1.0."""
-
-    VERSION = datasets.Version("1.0.0", "")
-    BUILDER_CONFIG_CLASS = IndicxnliConfig
-    BUILDER_CONFIGS = [
-        IndicxnliConfig(
-            name=lang,
-            language=lang,
-            version=datasets.Version("1.0.0", ""),
-            description=f"Plain text import of IndicXNLI for the {lang} language",
-        )
-        for lang in _LANGUAGES
-    ]
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "premise": datasets.Value("string"),
-                "hypothesis": datasets.Value("string"),
-                "label": datasets.ClassLabel(names=["entailment", "neutral", "contradiction"]),
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            # No default supervised_keys (as we have to pass both premise
-            # and hypothesis as input).
-            supervised_keys=None,
-            homepage="https://github.com/divyanshuaggarwal/IndicXNLI",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        urls_to_download = self.config._URLS
-        
-        
-        downloaded_files = dl_manager.download(urls_to_download)
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "filepath": downloaded_files["train"],
-                    "data_format": "IndicXNLI",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"filepath": downloaded_files["test"], "data_format": "IndicXNLI"},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={"filepath": downloaded_files["dev"], "data_format": "IndicXNLI"},
-            ),
-        ]
-
-    def _generate_examples(self, data_format, filepath):
-        """This function returns the examples in the raw (text) form."""
-
-        with open(filepath, "r") as f:
-            data = json.load(f)
-            data = data[list(data.keys())[0]]
-
-        for idx, row in enumerate(data):
-            yield idx, {
-                "premise": row["premise"],
-                "hypothesis": row["hypothesis"],
-                "label": row["label"],
-            }