Commit
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6a2cae5
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Parent(s):
6fce381
Upload atlas-preprocessed-code.py
Browse files- atlas-preprocessed-code.py +91 -25
atlas-preprocessed-code.py
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"Kotlin", "PHP", "Perl", "Python", "Ruby", "Rust", "Shell", "Swift", "TypeScript", "V"]
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"""BuilderConfig for Repository."""
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def __init__(self, language, **kwargs):
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"""
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Args:
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language: the programming language of the repository
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**kwargs: keyword arguments forwarded to super.
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"""
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super().__init__(**kwargs)
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self.language = language
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BUILDER_CONFIGS = [
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version=Version("1.0.0"),
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language=lang,
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description=f"Repository of {lang} programs",
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)
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for lang in _LANGUAGES
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]
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import gzip
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import json
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import datasets
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logger = datasets.logging.get_logger(__name__)
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_HOMEPAGE = "https://github.com/atlasunified"
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_DESCRIPTION = "\
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Your description here.\
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"
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_LICENSE = "odc-by"
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_VARIANTS = {
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"C#": {
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"version": "1.0.0",
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"download_size": 12345678, # replace with actual size
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"dataset_size": 12345678, # replace with actual size
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"splits": {
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"train": {
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"num_bytes": 12345678, # replace with actual size
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"num_examples": 12345678, # replace with actual size
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"files": [
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"data/C#.jsonl",
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# continue with other file paths...
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],
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},
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},
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},
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"C++": {
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# similar structure as above, replace with actual data
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},
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# continue for other languages...
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}
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_FEATURES = datasets.Features(
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added=datasets.Value("string"),
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created=datasets.Value("string"),
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id=datasets.Value("string"),
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source=datasets.Value("string"),
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text=datasets.Value("string"),
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version=datasets.Value("string"),
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)
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_CITATION = """\
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Your citation here.
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"""
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class MyHFRepo(datasets.GeneratorBasedBuilder):
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"""Your dataset description here."""
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(name=name, version=config["version"])
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for name, config in _VARIANTS.items()
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]
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DEFAULT_CONFIG_NAME = "C#" # replace with the language you want as default
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def _info(self):
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"""Give information and typings for the dataset."""
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=_FEATURES,
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supervised_keys=None,
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homepage=_HOMEPAGE,
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license=_LICENSE,
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citation=_CITATION,
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dataset_size=_VARIANTS[self.config.name]["dataset_size"],
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download_size=_VARIANTS[self.config.name]["download_size"],
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)
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def _split_generators(self, dl_manager):
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train_downloaded_files = dl_manager.download(
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_VARIANTS[self.config.name]["splits"]["train"]["files"]
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)
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return [
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datasets.SplitGenerator(
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name=str(datasets.Split.TRAIN),
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gen_kwargs={"filepaths": train_downloaded_files},
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),
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]
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def _generate_examples(self, filepaths):
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"""This function returns the examples in the raw (text) form by
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iterating on all the files."""
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id_ = 0
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for filepath in filepaths:
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logger.info("generating examples from = %s", filepath)
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with gzip.open(open(filepath, "rb"), "rt", encoding="utf-8") as f:
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for line in f:
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if line:
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example = json.loads(line)
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yield id_, example
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id_ += 1
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