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import os |
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import datasets |
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import json |
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import pandas as pd |
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_CITATION = """\ |
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""" |
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_DESCRIPTION = """\ |
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CSAT-QA |
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""" |
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_HOMEPAGE = "https://huggingface.co/HAERAE-HUB" |
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_LICENSE = "Proprietary" |
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split_names = ["all","WR", "GR", "RCS", "RCSS", "RCH", "LI"] |
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class CSATQAConfig(datasets.BuilderConfig): |
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def __init__(self, **kwargs): |
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super().__init__(version=datasets.Version("1.0.0"), **kwargs) |
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class CSATQA(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIGS = [ |
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CSATQAConfig( |
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name=name, |
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) |
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for name in split_names |
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] |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"question": datasets.Value("string"), |
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"context" : datasets.Value("string"), |
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"option#1": datasets.Value("string"), |
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"option#2": datasets.Value("string"), |
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"option#3": datasets.Value("string"), |
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"option#4": datasets.Value("string"), |
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"option#5": datasets.Value("string"), |
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"gold": datasets.Value("int8"), |
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"category": datasets.Value("string"), |
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"human_peformance": datasets.Value("float16"), |
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} |
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) |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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train_path = dl_manager.download_and_extract("./data/csatqa_eval.json") |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"filepath": train_path, |
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}, |
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), |
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] |
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def _generate_examples(self, filepath): |
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with open(filepath, encoding="utf-8") as f: |
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buffer = [] |
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for key, row in enumerate(f): |
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data = json.loads(row) |
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buffer.append({ |
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"question": data["question"], |
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"context" : data["context"], |
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"option#1": data["option#1"], |
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"option#2": data["option#2"], |
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"option#3": data["option#3"], |
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"option#4": data["option#4"], |
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"option#5": data["option#5"], |
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"gold": data["gold"], |
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"category": data["Category"], |
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"human_peformance": data["Human_Peformance"]}) |
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for idx, dat in enumerate(buffer): |
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yield idx,dat |
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