atlas-preprocessed-code.py

import gzip
import json

import datasets

logger = datasets.logging.get_logger(__name__)


_HOMEPAGE = "https://github.com/atlasunified"


_DESCRIPTION = "\
Your description here.\
"

_LICENSE = "odc-by"

_VARIANTS = {
    "C#": {
        "version": "1.0.0",
        "download_size": 12345678,  # replace with actual size
        "dataset_size": 12345678,   # replace with actual size
        "splits": {
            "train": {
                "num_bytes": 12345678,  # replace with actual size
                "num_examples": 12345678,   # replace with actual size
                "files": [
                    "data/C#.jsonl",
                    # continue with other file paths...
                ],
            },
        },
    },
    "C++": {
        # similar structure as above, replace with actual data
    },
    # continue for other languages...
}

_FEATURES = datasets.Features(
    added=datasets.Value("string"),
    created=datasets.Value("string"),
    id=datasets.Value("string"),
    source=datasets.Value("string"),
    text=datasets.Value("string"),
    version=datasets.Value("string"),
)

_CITATION = """\
Your citation here.
"""


class MyHFRepo(datasets.GeneratorBasedBuilder):
    """Your dataset description here."""

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(name=name, version=config["version"])
        for name, config in _VARIANTS.items()
    ]

    DEFAULT_CONFIG_NAME = "C#"  # replace with the language you want as default

    def _info(self):
        """Give information and typings for the dataset."""
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=_FEATURES,
            supervised_keys=None,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
            dataset_size=_VARIANTS[self.config.name]["dataset_size"],
            download_size=_VARIANTS[self.config.name]["download_size"],
        )

    def _split_generators(self, dl_manager):
        train_downloaded_files = dl_manager.download(
            _VARIANTS[self.config.name]["splits"]["train"]["files"]
        )
        return [
            datasets.SplitGenerator(
                name=str(datasets.Split.TRAIN),
                gen_kwargs={"filepaths": train_downloaded_files},
            ),
        ]

    def _generate_examples(self, filepaths):
        """This function returns the examples in the raw (text) form by
        iterating on all the files."""
        id_ = 0
        for filepath in filepaths:
            logger.info("generating examples from = %s", filepath)
            with gzip.open(open(filepath, "rb"), "rt", encoding="utf-8") as f:
                for line in f:
                    if line:
                        example = json.loads(line)
                        yield id_, example
                        id_ += 1