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import csv |
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from dataclasses import dataclass |
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from typing import Any, Dict, List, Tuple |
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import datasets |
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logger = datasets.logging.get_logger(__name__) |
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_DESCRIPTION = ( |
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"日本語の感情分析データセット WRIME を、ポジティブ/ネガティブの二値分類のタスクに加工したデータセットです。" |
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"GitHub リポジトリ ids-cv/wrime で公開されているデータセットを利用しています。" |
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) |
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_URL = "https://raw.githubusercontent.com/ids-cv/wrime/master/wrime-ver2.tsv" |
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@dataclass |
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class WrimeSentimentConfig(datasets.BuilderConfig): |
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remove_neutral: bool = True |
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class WrimeSentiment(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIG_CLASS = WrimeSentimentConfig |
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def _info(self) -> datasets.DatasetInfo: |
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labels = ["positive", "negative"] |
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if not self.config.remove_neutral: |
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labels += ["neutral"] |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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"sentence": datasets.Value("string"), |
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"label": datasets.ClassLabel( |
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num_classes=len(labels), names=labels |
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), |
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"user_id": datasets.Value("int64"), |
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"datetime": datasets.Value("string") |
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} |
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), |
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) |
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def _split_generators( |
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self, dl_manager: datasets.DownloadManager |
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) -> List[datasets.SplitGenerator]: |
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downloaded_file = dl_manager.download_and_extract(_URL) |
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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": downloaded_file, |
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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.VALIDATION, |
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gen_kwargs={ |
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"filepath": downloaded_file, |
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"split": "dev", |
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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": downloaded_file, |
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"split": "test", |
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}, |
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), |
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] |
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def _generate_examples( |
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self, filepath: str, split: str |
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) -> Tuple[str, Dict[str, Any]]: |
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logger.info(f"generating examples from {filepath}") |
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_key = 0 |
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with open(filepath, "r", encoding="utf-8") as f: |
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reader = csv.DictReader(f, delimiter="\t") |
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for data in reader: |
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if data["Train/Dev/Test"].lower() != split: |
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continue |
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sentiment_score = int(data["Avg. Readers_Sentiment"]) |
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if sentiment_score > 0: |
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label = "positive" |
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elif sentiment_score < 0: |
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label = "negative" |
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else: |
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label = "neutral" |
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if self.config.remove_neutral and label == "neutral": |
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continue |
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yield _key, { |
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"sentence": data["Sentence"], |
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"label": label, |
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"user_id": data["UserID"], |
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"datetime": data["Datetime"].strip(), |
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} |
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_key += 1 |
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