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"""The Multilingual Amazon Reviews Corpus""" |
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import json |
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import datasets |
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from datasets.exceptions import DefunctDatasetError |
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_DESCRIPTION = """\ |
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Please refer to https://huggingface.co/datasets/defunct-datasets/amazon_reviews_multi. |
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""" |
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_LANGUAGES = { |
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"de": "German", |
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"en": "English", |
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"es": "Spanish", |
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"fr": "French", |
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"ja": "Japanese", |
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"zh": "Chinese", |
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} |
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_ALL_LANGUAGES = "all_languages" |
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_VERSION = "1.0.0" |
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_HOMEPAGE_URL = "https://huggingface.co/datasets/defunct-datasets/amazon_reviews_multi" |
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_DOWNLOAD_URL = "https://huggingface.co/datasets/buruzaemon/amazon_reviews_multi/resolve/main/{lang}/{split}.jsonl.gz" |
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class AmazonReviewsMultiConfig(datasets.BuilderConfig): |
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"""BuilderConfig for AmazonReviewsMultiConfig.""" |
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def __init__(self, languages=None, **kwargs): |
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super(AmazonReviewsMultiConfig, self).__init__(version=datasets.Version(_VERSION, ""), **kwargs), |
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self.languages = languages |
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class AmazonReviewsMulti(datasets.GeneratorBasedBuilder): |
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"""The Multilingual Amazon Reviews Corpus""" |
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BUILDER_CONFIGS = [ |
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AmazonReviewsMultiConfig( |
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name=_ALL_LANGUAGES, |
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languages=_LANGUAGES, |
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description="A collection of Amazon reviews specifically designed to aid research in multilingual text classification.", |
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) |
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] + [ |
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AmazonReviewsMultiConfig( |
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name=lang, |
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languages=[lang], |
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description=f"{_LANGUAGES[lang]} examples from a collection of Amazon reviews specifically designed to aid research in multilingual text classification", |
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) |
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for lang in _LANGUAGES |
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] |
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BUILDER_CONFIG_CLASS = AmazonReviewsMultiConfig |
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DEFAULT_CONFIG_NAME = _ALL_LANGUAGES |
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def _info(self): |
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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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"review_id": datasets.Value("string"), |
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"product_id": datasets.Value("string"), |
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"reviewer_id": datasets.Value("string"), |
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"stars": datasets.Value("int32"), |
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"review_body": datasets.Value("string"), |
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"review_title": datasets.Value("string"), |
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"language": datasets.Value("string"), |
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"product_category": datasets.Value("string"), |
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} |
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), |
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supervised_keys=None, |
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license=None, |
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homepage=_HOMEPAGE_URL, |
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citation=None, |
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) |
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def _split_generators(self, dl_manager): |
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train_urls = [_DOWNLOAD_URL.format(split="train", lang=lang) for lang in self.config.languages] |
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dev_urls = [_DOWNLOAD_URL.format(split="validation", lang=lang) for lang in self.config.languages] |
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test_urls = [_DOWNLOAD_URL.format(split="test", lang=lang) for lang in self.config.languages] |
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train_paths = dl_manager.download_and_extract(train_urls) |
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dev_paths = dl_manager.download_and_extract(dev_urls) |
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test_paths = dl_manager.download_and_extract(test_urls) |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"file_paths": train_paths}), |
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datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"file_paths": dev_paths}), |
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"file_paths": test_paths}), |
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] |
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def _generate_examples(self, file_paths): |
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row_count = 0 |
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for file_path in file_paths: |
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with open(file_path, "r", encoding="utf-8") as f: |
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for line in f: |
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yield row_count, json.loads(line) |
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row_count += 1 |
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