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import csv |
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import json |
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import os |
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import datasets |
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from typing import List, Any |
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_CITATION = """\ |
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TBA |
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""" |
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_DESCRIPTION = """\ |
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This new dataset is designed to solve kp NLP task and is crafted with a lot of care. |
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""" |
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_HOMEPAGE = "" |
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_LICENSE = "" |
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_URLS = { |
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"test": "data/test.jsonl", |
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"train": "train.jsonl", |
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"valid": "data/valid.jsonl" |
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} |
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class LDKP3k(datasets.GeneratorBasedBuilder): |
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"""TODO: Short description of my dataset.""" |
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VERSION = datasets.Version("1.1.0") |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig(name="small", version=VERSION, description="This part of my dataset covers long document"), |
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datasets.BuilderConfig(name="medium", version=VERSION, description="This part of my dataset covers abstract only"), |
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datasets.BuilderConfig(name="large", version=VERSION, description="This part of my dataset covers abstract only") |
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] |
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DEFAULT_CONFIG_NAME = "small" |
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def _info(self): |
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_URLS['train']="data/"+str(self.config.name)+"/train.jsnol" |
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features = datasets.Features( |
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{ |
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"id": datasets.Value("string") |
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"sections": datasets.features.Sequence(datasets.Value("string")), |
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"sec_text": datasets.features.Sequence(datasets.features.Sequence(datasets.Value("string"))), |
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"extractive_keyphrases": datasets.features.Sequence(datasets.Value("string")), |
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"abstractive_keyphrases": datasets.features.Sequence(datasets.Value("string")), |
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"sec_bio_tags": datasets.features.Sequence(datasets.features.Sequence(datasets.Value("string"))) |
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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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data_dir = dl_manager.download_and_extract(_URLS) |
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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": data_dir['train'], |
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"split": "train", |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={ |
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"filepath": data_dir['test'], |
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"split": "test" |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={ |
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"filepath": data_dir['valid'], |
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"split": "valid", |
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}, |
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), |
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] |
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def _generate_examples(self, filepath, split): |
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with open(filepath, encoding="utf-8") as f: |
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for key, row in enumerate(f): |
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data = json.loads(row) |
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yield key, { |
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"id": data['paper_id'] |
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"document": data["document"], |
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"document_tags": data["document_tags"], |
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"extractive_keyphrases": data["extractive_keyphrases"], |
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"abstractive_keyphrases": data["abstractive_keyphrases"], |
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"other_metadata": data["other_metadata"] |
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} |
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