atlas-preprocessed-code.py

import json
import datasets
import traceback
import os

logger = datasets.logging.get_logger(__name__)

_DESCRIPTION = """\
RedPajama is a clean-room, fully open-source implementation of the LLaMa dataset.
"""

# Define a list of programming languages for the subsets
_LANGUAGE_SUBSETS = ["csharp", "cplusplus", "c", "go", "html", "haskell", 
                     "java", "javascript", "jupyter", "kotlin", "php", "perl",
                     "python", "ruby", "rust", "shell", "swift", "typescript", "v"]

# Generate URLs for the subsets
_URL_LISTS = {language: f"https://huggingface.co/datasets/AtlasUnified/atlas-preprocessed-code/blob/main/{language}.jsonl"
              for language in _LANGUAGE_SUBSETS}

_URL_BASE = 'https://data.together.xyz/redpajama-data-1T/v1.0.0'

_DATA_DIR = os.environ.get('RED_PAJAMA_DATA_DIR', None)

class RedPajama1TConfig(datasets.BuilderConfig):
    """BuilderConfig for RedPajama sample."""

    def __init__(self, *args, subsets, **kwargs):
        """BuilderConfig for RedPajama.
        Args:
          **kwargs: keyword arguments forwarded to super.
        """
        super(RedPajama1TConfig, self).__init__(**kwargs)
        self.subsets = subsets

class RedPajama1T(datasets.GeneratorBasedBuilder):
    """RedPajama: Reproducing the LLaMA training dataset of over 1.2 trillion tokens. Version 1.0.0."""

    # Generate builder configs for each language subset
    BUILDER_CONFIGS = [RedPajama1TConfig(name=language, 
                                         subsets=[language], 
                                         version=datasets.Version("1.0.0", ""), 
                                         description=f"RedPajama1T {language} subset") 
                       for language in _LANGUAGE_SUBSETS]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "text": datasets.Value("string"),
                    "meta": datasets.Value("string"),
                    "red_pajama_subset": datasets.Value("string"),
                }
            ),
            supervised_keys=None,
        )

    def _split_generators(self, dl_manager):
        url_lists = dl_manager.download_and_extract({
            subset: _URL_LISTS[subset] for subset in self.config.subsets
        })

        urls = {}

        for subset, url_list in url_lists.items():
            with open(url_list, encoding="utf-8") as f:
                urls[subset] = [line.strip() for line in f]

        if _DATA_DIR is not None:
            print(f'Reading data from {_DATA_DIR}')
            url_prefix_slashes = len(_URL_BASE.split('/'))
            downloaded_files = {
                subset: [
                    os.path.join(_DATA_DIR, *url.split('/')[url_prefix_slashes:])
                    for url in url_list
                ]
                for subset, url_list in urls.items()
            }
        else:
            downloaded_files = dl_manager.download(urls)

        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs = {
                    "files": {
                        subset: downloaded_files[subset]
                        for subset in self.config.subsets
                    }
                }
            )
        ]

    def _generate_examples(self, files):
        """This function returns the examples in the raw (text) form."""
        key = 0
        for subset in files:
            for path in files[subset]:
                with open(path, encoding="utf-8") as f:
                    for i, row in enumerate(f):
                        try:
                            data = json.loads(row)
                            if "meta" not in data:
                                text = data["text"]
                                del data["text"]
                                yield key, {
                                    "text": text,
                                    "meta": json.dumps(data),
                                    "red_pajama_subset": subset,
                                }
                            else:
                                yield key, {
                                    "text": data["text"],
                                    "meta": data["meta"],
                                    "red_pajama_subset": subset,
                                }
                            key += 1
                        except Exception as e:
                            print(f'Subset: {subset}')
                            print(f'Path: {path}')
                            print(f'Row: {row}')
                            traceback.print_exc()

                            raise e