| import csv |
| import os |
|
|
| import datasets |
|
|
| logger = datasets.logging.get_logger(__name__) |
|
|
| _DESCRIPTION = """ |
| """ |
|
|
| _URLS = { |
| "ccd": "https://drive.google.com/u/0/uc?id=13UYcJ6BcojsCKy-yc9qgHTyBMCCWB-w1&export=download", |
| "clothing": "https://drive.google.com/u/0/uc?id=1BwDS30xzFEDqP-z9adj4wVSlsSjOIGqc&export=download", |
| "clothing_binary": "https://drive.google.com/u/0/uc?id=1P5aPKD0wU1NWUlh2QiIYwSPN-S3wD3ua&export=download", |
| "electronics": "https://drive.google.com/u/0/uc?id=1ztIUsraLPJSKkkle_uTrd78hYsSKKmur&export=download", |
| "electronics_binary": "https://drive.google.com/u/0/uc?id=103kJN6snOc2sSMH9ojd_PNohVQ1g4XUJ&export=download", |
| "office": "https://drive.google.com/u/0/uc?id=1DbrvS02d75sXoxaaPh90bJdRvr15fUS5&export=download", |
| "office_binary": "https://drive.google.com/u/0/uc?id=1ED4JnoTFu_4H80jBUJlqRrEor-taZ2Qz&export=download", |
| "toxicity": "https://drive.google.com/u/0/uc?id=1iATGRaGuOqiUrj31jYjAzns8iS_BJh1h&export=download", |
| } |
|
|
| _FIELDS = { |
| "amazon": ["date", "rating", "reviewText", "summary"], |
| "ccd": ["date", "product", "subproduct", "issue", "subissue", "text"], |
| "toxicity": ["rev_id", "toxicity", "date", "comment", "sample"], |
| } |
|
|
| _LABELS = { |
| "amazon": ["1", "2", "3", "4", "5"], |
| "amazon_binary": ["0", "1"], |
| "ccd": [ |
| "Checking or savings account", |
| "Credit card or prepaid card", |
| "Credit reporting, credit repair services, or other personal consumer reports", |
| "Debt collection", |
| "Money transfer, virtual currency, or money service", |
| "Mortgage", |
| "Payday loan, title loan, or personal loan", |
| "Student loan", |
| "Vehicle loan or lease", |
| ], |
| "toxicity": [0, 1], |
| } |
|
|
|
|
| class QBConfig(datasets.BuilderConfig): |
| def __init__( |
| self, |
| csv_fields, |
| label_classes, |
| label_column, |
| text_column, |
| url, |
| **kwargs, |
| ): |
| super().__init__(version=datasets.Version("1.0.0", ""), **kwargs) |
| self.csv_fields = csv_fields |
| self.label_classes = label_classes |
| self.label_column = label_column |
| self.text_column = text_column |
| self.url = url |
|
|
|
|
| class QB(datasets.GeneratorBasedBuilder): |
| BUILDER_CONFIGS = [ |
| QBConfig( |
| name="ccd", |
| description="Consumer Complaints Database", |
| url=_URLS["ccd"], |
| csv_fields=_FIELDS["ccd"], |
| label_classes=_LABELS["ccd"], |
| label_column="product", |
| text_column="text", |
| ), |
| QBConfig( |
| name="clothing", |
| description="Amazon Reviews (Clothing)", |
| url=_URLS["clothing"], |
| csv_fields=_FIELDS["amazon"], |
| label_classes=_LABELS["amazon"], |
| label_column="rating", |
| text_column="reviewText", |
| ), |
| QBConfig( |
| name="clothing_binary", |
| description="Amazon Reviews (Clothing) with binary labels", |
| url=_URLS["clothing_binary"], |
| csv_fields=_FIELDS["amazon"], |
| label_classes=_LABELS["amazon_binary"], |
| label_column="rating", |
| text_column="reviewText", |
| ), |
| QBConfig( |
| name="electronics", |
| description="Amazon Reviews (Electronics)", |
| url=_URLS["electronics"], |
| csv_fields=_FIELDS["amazon"], |
| label_classes=_LABELS["amazon"], |
| label_column="rating", |
| text_column="reviewText", |
| ), |
| QBConfig( |
| name="electronics_binary", |
| description="Amazon Reviews (Electronics) with binary labels", |
| url=_URLS["electronics_binary"], |
| csv_fields=_FIELDS["amazon"], |
| label_classes=_LABELS["amazon_binary"], |
| label_column="rating", |
| text_column="reviewText", |
| ), |
| QBConfig( |
| name="office", |
| description="Amazon Reviews (Office)", |
| url=_URLS["office"], |
| csv_fields=_FIELDS["amazon"], |
| label_classes=_LABELS["amazon"], |
| label_column="rating", |
| text_column="reviewText", |
| ), |
| QBConfig( |
| name="office_binary", |
| description="Amazon Reviews (Office) with binary labels", |
| url=_URLS["office_binary"], |
| csv_fields=_FIELDS["amazon"], |
| label_classes=_LABELS["amazon_binary"], |
| label_column="rating", |
| text_column="reviewText", |
| ), |
| QBConfig( |
| name="toxicity", |
| description="Wikipedia toxicity data set", |
| url=_URLS["toxicity"], |
| csv_fields=_FIELDS["toxicity"], |
| label_classes=_LABELS["toxicity"], |
| label_column="toxicity", |
| text_column="comment", |
| ), |
| ] |
|
|
| def _info(self): |
| features = { |
| "date": datasets.Value("string"), |
| "id": datasets.Value("int32"), |
| "label": datasets.features.ClassLabel(names=self.config.label_classes), |
| "text": datasets.Value("string"), |
| } |
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=datasets.Features(features), |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| downloaded_files = dl_manager.download_and_extract(self.config.url) |
| logger.info(str(downloaded_files)) |
| train_filepath = os.path.join(downloaded_files, "train.csv") |
| test_filepath = os.path.join(downloaded_files, "test.csv") |
| return [ |
| datasets.SplitGenerator( |
| name=datasets.Split.TRAIN, |
| gen_kwargs={"filepath": train_filepath}, |
| ), |
| datasets.SplitGenerator( |
| name=datasets.Split.TEST, |
| gen_kwargs={"filepath": test_filepath}, |
| ), |
| ] |
|
|
| def _generate_examples(self, filepath): |
| logger.info(f"generating examples from {filepath}") |
| idx = 0 |
| with open(filepath, encoding="utf-8") as f: |
| reader = csv.DictReader(f, fieldnames=self.config.csv_fields) |
| for row in reader: |
| yield idx, { |
| "date": row["date"], |
| "id": idx, |
| "label": row[self.config.label_column], |
| "text": row[self.config.text_column], |
| } |
| idx += 1 |
|
|
