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