load_script.py

# coding=utf-8                  
import json
import os
import datasets

_DESCRIPTION = """ Depression Severity Dataset. Unknown License.
"""
_CITATION = """ 
@inproceedings{naseem2022early,
  title={Early Identification of Depression Severity Levels on Reddit Using Ordinal Classification},
  author={Naseem, Usman and Dunn, Adam G and Kim, Jinman and Khushi, Matloob},
  booktitle={Proceedings of the ACM Web Conference 2022},
  pages={2563--2572},
  year={2022}
}
"""
_URLs = {
    "whole": "https://huggingface.co/datasets/siyangliu/Depression_Severity_Dataset/blob/main/Reddit_depression_dataset.json",
    "train": "https://huggingface.co/datasets/siyangliu/Depression_Severity_Dataset/blob/main/Reddit_depression_dataset_train.json",
    "val": "https://huggingface.co/datasets/siyangliu/Depression_Severity_Dataset/blob/main/Reddit_depression_dataset_val.json",
    "test": "https://huggingface.co/datasets/siyangliu/Depression_Severity_Dataset/blob/main/Reddit_depression_dataset_test.json",
}

class Reddit_depression(datasets.GeneratorBasedBuilder):
    """Reddit_depression dataset."""

    VERSION = datasets.Version("1.1.0")

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(
            name="withoutLabel",
            description="",
            version=VERSION,
        ),
        
        datasets.BuilderConfig(
            name="withLabel",
            description="",
            version=VERSION,
        )
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "text": datasets.Value("string"),
                    "label": datasets.Value("string")
                }
            ),
            supervised_keys=None,
            homepage="https://github.com/usmaann/Depression_Severity_Dataset",
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        data_dir = dl_manager.download_and_extract(_URLs)
            
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "filepath": data_dir["train"]
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    "filepath": data_dir["test"]
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION,
                gen_kwargs={
                    "filepath": data_dir["valid"]
                },
            )
        ]
           

    def _generate_examples(self, filepath):
        """Yields examples."""
        with open(filepath, encoding="utf-8") as input_file:
            dataset = json.load(input_file)
            idx = 0 
            for meta_data in dataset: 
                if self.config.name == "withoutLabel":              
                    yield idx, meta_data["text"]
                elif self.config.name == "withLabel": 
                    yield idx, meta_data["text"], meta_data["label"]
                else:
                    raise Exception("Not a Valid Config Name")    
                idx += 1