| import csv |
| import os |
|
|
| import datasets |
|
|
| logger = datasets.logging.get_logger(__name__) |
|
|
| _DESCRIPTION = """ |
| """ |
|
|
| _URLS = { |
| "clothing": "https://drive.google.com/u/0/uc?id=1HP3EPX9Q8JffUUZz2czXD7qudzvitscq&export=download", |
| "electronics": "https://drive.google.com/u/0/uc?id=1W50FNd0707qK1CCktEF30nlDqsImLg3X&export=download", |
| "office": "https://drive.google.com/u/0/uc?id=1lsttnBIjFD4nQw9idZYQNUWKSzj5VibD&export=download", |
| } |
|
|
| _FIELDS = ["date", "rating", "reviewText", "summary"] |
| _RATINGS = ["1", "2", "3", "4", "5"] |
|
|
|
|
| class AmazonConfig(datasets.BuilderConfig): |
| def __init__( |
| self, |
| training_files, |
| testing_files, |
| url, |
| label_classes=_RATINGS, |
| **kwargs, |
| ): |
| super().__init__(version=datasets.Version("1.0.0", ""), **kwargs) |
| self.label_classes = label_classes |
| self.training_files = training_files |
| self.testing_files = testing_files |
| self.url = url |
|
|
|
|
| class Amazon(datasets.GeneratorBasedBuilder): |
| BUILDER_CONFIGS = [ |
| AmazonConfig( |
| name="clothing_majorshift01", |
| description="", |
| url=_URLS["clothing"], |
| training_files=[ |
| "201011.csv", |
| "201012.csv", |
| "201101.csv", |
| "201102.csv", |
| "201103.csv", |
| "201104.csv", |
| "201105.csv", |
| "201106.csv", |
| "201107.csv", |
| "201108.csv", |
| "201109.csv", |
| "201110.csv", |
| "201111.csv", |
| "201112.csv", |
| "201201.csv", |
| "201202.csv", |
| "201203.csv", |
| "201204.csv", |
| "201205.csv", |
| "201206.csv", |
| "201207.csv", |
| "201208.csv", |
| "201209.csv", |
| "201210.csv", |
| ], |
| testing_files=[ |
| "201211.csv", |
| "201212.csv", |
| "201301.csv", |
| "201302.csv", |
| "201303.csv", |
| "201304.csv", |
| ], |
| ), |
| AmazonConfig( |
| name="clothing_majorshift02", |
| description="", |
| url=_URLS["clothing"], |
| training_files=[ |
| "200808.csv", |
| "200809.csv", |
| "200810.csv", |
| "200811.csv", |
| "200812.csv", |
| "200901.csv", |
| "200902.csv", |
| "200903.csv", |
| "200904.csv", |
| "200905.csv", |
| "200906.csv", |
| "200907.csv", |
| "200908.csv", |
| "200909.csv", |
| "200910.csv", |
| "200911.csv", |
| "200912.csv", |
| "201001.csv", |
| "201002.csv", |
| "201003.csv", |
| "201004.csv", |
| "201005.csv", |
| "201006.csv", |
| "201007.csv", |
| ], |
| testing_files=[ |
| "201008.csv", |
| "201009.csv", |
| "201010.csv", |
| "201011.csv", |
| "201012.csv", |
| "201101.csv", |
| ], |
| ), |
| AmazonConfig( |
| name="clothing_majorshift03", |
| description="", |
| url=_URLS["clothing"], |
| training_files=[ |
| "201602.csv", |
| "201603.csv", |
| "201604.csv", |
| "201605.csv", |
| "201606.csv", |
| "201607.csv", |
| "201608.csv", |
| "201609.csv", |
| "201610.csv", |
| "201611.csv", |
| "201612.csv", |
| "201701.csv", |
| "201702.csv", |
| "201703.csv", |
| "201704.csv", |
| "201705.csv", |
| "201706.csv", |
| "201707.csv", |
| "201708.csv", |
| "201709.csv", |
| "201710.csv", |
| "201711.csv", |
| "201712.csv", |
| "201801.csv", |
| ], |
| testing_files=[ |
| "201802.csv", |
| "201803.csv", |
| "201804.csv", |
| "201805.csv", |
| "201806.csv", |
| "201807.csv", |
| ], |
| ), |
| ] |
|
|
| 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): |
| dirname = dl_manager.download_and_extract(self.config.url) |
| logger.info(str(dirname)) |
| category = self.config.name.split("_")[ |
| 0 |
| ] |
| train_filepaths = tuple( |
| os.path.join(dirname, category, fname) |
| for fname in self.config.training_files |
| ) |
| test_filepaths = tuple( |
| os.path.join(dirname, category, fname) |
| for fname in self.config.testing_files |
| ) |
| return [ |
| datasets.SplitGenerator( |
| name=datasets.Split.TRAIN, |
| gen_kwargs={"filepaths": train_filepaths}, |
| ), |
| datasets.SplitGenerator( |
| name=datasets.Split.TEST, |
| gen_kwargs={"filepaths": test_filepaths}, |
| ), |
| ] |
|
|
| def _generate_examples(self, filepaths): |
| logger.info(f"generating examples from {len(filepaths)} files") |
| idx = 0 |
| for filepath in filepaths: |
| with open(filepath, encoding="utf-8") as f: |
| reader = csv.DictReader(f, fieldnames=_FIELDS) |
| for row in reader: |
| yield idx, { |
| "date": row["date"], |
| "id": idx, |
| "label": row["rating"], |
| "text": row["reviewText"], |
| } |
| idx += 1 |
|
|
