siyangliu/Depression_Severity_Dataset

1# coding=utf-8                  2import json3import os4import datasets5 6_DESCRIPTION = """ Depression Severity Dataset. Unknown License.7"""8_CITATION = """ 9@inproceedings{naseem2022early,10  title={Early Identification of Depression Severity Levels on Reddit Using Ordinal Classification},11  author={Naseem, Usman and Dunn, Adam G and Kim, Jinman and Khushi, Matloob},12  booktitle={Proceedings of the ACM Web Conference 2022},13  pages={2563--2572},14  year={2022}15}16"""17_URLs = {18    "whole": "https://huggingface.co/datasets/siyangliu/Depression_Severity_Dataset/blob/main/Reddit_depression_dataset.json",19    "train": "https://huggingface.co/datasets/siyangliu/Depression_Severity_Dataset/blob/main/Reddit_depression_dataset_train.json",20    "val": "https://huggingface.co/datasets/siyangliu/Depression_Severity_Dataset/blob/main/Reddit_depression_dataset_val.json",21    "test": "https://huggingface.co/datasets/siyangliu/Depression_Severity_Dataset/blob/main/Reddit_depression_dataset_test.json",22}23 24class Reddit_depression(datasets.GeneratorBasedBuilder):25    """Reddit_depression dataset."""26 27    VERSION = datasets.Version("1.1.0")28 29    BUILDER_CONFIGS = [30        datasets.BuilderConfig(31            name="withoutLabel",32            description="",33            version=VERSION,34        ),35        36        datasets.BuilderConfig(37            name="withLabel",38            description="",39            version=VERSION,40        )41    ]42 43    def _info(self):44        return datasets.DatasetInfo(45            description=_DESCRIPTION,46            features=datasets.Features(47                {48                    "text": datasets.Value("string"),49                    "label": datasets.Value("string")50                }51            ),52            supervised_keys=None,53            homepage="https://github.com/usmaann/Depression_Severity_Dataset",54            citation=_CITATION,55        )56 57    def _split_generators(self, dl_manager):58        """Returns SplitGenerators."""59        data_dir = dl_manager.download_and_extract(_URLs)60            61        return [62            datasets.SplitGenerator(63                name=datasets.Split.TRAIN,64                gen_kwargs={65                    "filepath": data_dir["train"]66                },67            ),68            datasets.SplitGenerator(69                name=datasets.Split.TEST,70                gen_kwargs={71                    "filepath": data_dir["test"]72                },73            ),74            datasets.SplitGenerator(75                name=datasets.Split.VALIDATION,76                gen_kwargs={77                    "filepath": data_dir["valid"]78                },79            )80        ]81           82 83    def _generate_examples(self, filepath):84        """Yields examples."""85        with open(filepath, encoding="utf-8") as input_file:86            dataset = json.load(input_file)87            idx = 0 88            for meta_data in dataset: 89                if self.config.name == "withoutLabel":              90                    yield idx, meta_data["text"]91                elif self.config.name == "withLabel": 92                    yield idx, meta_data["text"], meta_data["label"]93                else:94                    raise Exception("Not a Valid Config Name")    95                idx += 196