mimir.py

from datasets import (
    GeneratorBasedBuilder,
    SplitGenerator,
    DownloadManager,
    BuilderConfig,
)
import json
import os

import datasets

from typing import List


_HOMEPAGE = "http://github.com/iamgroot42/mimir"

_DESCRIPTION = """\
Member and non-member splits for our MI experiments using MIMIR. Data is available for each source.
"""

_CITATION = """\
@article{duan2024membership,
      title={Do Membership Inference Attacks Work on Large Language Models?}, 
      author={Michael Duan and Anshuman Suri and Niloofar Mireshghallah and Sewon Min and Weijia Shi and Luke Zettlemoyer and Yulia Tsvetkov and Yejin Choi and David Evans and Hannaneh Hajishirzi},
      year={2024},
      journal={arXiv:2402.07841},
}
"""

_DOWNLOAD_URL = "https://huggingface.co/datasets/iamgroot42/mimir/resolve/main/"


class MimirConfig(BuilderConfig):
    """BuilderConfig for Mimir dataset."""

    def __init__(self, *args, subsets: List[str] = [], **kwargs):
        """Constructs a MimirConfig.

        Args:
            **kwargs: keyword arguments forwarded to super.
        """
        super(MimirConfig, self).__init__(**kwargs)
        self.subsets = subsets


class MimirDataset(GeneratorBasedBuilder):
    VERSION = datasets.Version("1.3.0")

    BUILDER_CONFIG_CLASS = MimirConfig
    BUILDER_CONFIGS = [
        MimirConfig(
            name="arxiv",
            subsets=["ngram_7_0.2", "ngram_13_0.2", "ngram_13_0.8"],
            description="This split contains data from the Pile's Arxiv subset at various n-gram overlap thresholds"
        ),
        MimirConfig(
            name="dm_mathematics",
            subsets=["ngram_7_0.2", "ngram_13_0.2", "ngram_13_0.8"],
            description="This split contains data from the Pile's DM Mathematics subset at various n-gram overlap thresholds"
        ),
        MimirConfig(
            name="github",
            subsets=["ngram_7_0.2", "ngram_13_0.2", "ngram_13_0.8"],
            description="This split contains data from the Pile's GitHub subset at various n-gram overlap thresholds"
        ),
        MimirConfig(
            name="hackernews", 
            subsets=["ngram_7_0.2", "ngram_13_0.2", "ngram_13_0.8"],
            description="This split contains data from the Pile's HackerNews subset at various n-gram overlap thresholds"
        ),
        MimirConfig(
            name="pile_cc", 
            subsets=["ngram_7_0.2", "ngram_13_0.2", "ngram_13_0.8"],
            description="This split contains data from the Pile's Pile CC subset at various n-gram overlap thresholds"
        ),
        MimirConfig(
            name="pubmed_central", 
            subsets=["ngram_7_0.2", "ngram_13_0.2", "ngram_13_0.8"],
            description="This split contains data from the Pile's PubMed Central subset at various n-gram overlap thresholds"
        ),
        MimirConfig(
            name="wikipedia_(en)",
            subsets=["ngram_7_0.2", "ngram_13_0.2", "ngram_13_0.8"],
            description="This split contains data from the Pile's Wikipedia subset at various n-gram overlap thresholds"
        ),
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features({
                "input": datasets.Value("string"),
                "label": datasets.Value("int32"),
            }),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager: DownloadManager):
        """Returns SplitGenerators."""
        parent_dir = "cache_100_200_1000_512"

        if len(self.config.subsets) > 0:
            suffixes = [f"{subset}" for subset in self.config.subsets]
        else:
            suffixes = ["none"]

        file_paths = {}
        for subset_split_suffix in suffixes:
            internal_fp = {}

            subset_split_suffix_use = f"_{subset_split_suffix}" if subset_split_suffix != "none" else ""

            internal_fp['member'] = os.path.join(parent_dir, "train", f"{self.config.name}{subset_split_suffix_use}.jsonl")
            internal_fp['nonmember'] = os.path.join(parent_dir, "test", f"{self.config.name}{subset_split_suffix_use}.jsonl")

            file_paths[subset_split_suffix] = internal_fp

        # Download data
        data_dir = {}
        for k, v_dict in file_paths.items():
            download_paths = [_DOWNLOAD_URL + v for v in v_dict.values()]
            paths = dl_manager.download_and_extract(download_paths)
            internal_dict = {k: v for k, v in zip(v_dict.keys(), paths)}
            data_dir[k] = internal_dict

        splits = [SplitGenerator(name=k, gen_kwargs={"file_path_dict": data_dir[k]}) for k in suffixes]
        return splits

    def _generate_examples(self, file_path_dict):
        """Yields individual examples for members and non-members."""
        with open(file_path_dict["member"], "r") as f_member, open(file_path_dict["nonmember"], "r") as f_nonmember:
            for id, (member, nonmember) in enumerate(zip(f_member, f_nonmember)):
                member_text = json.loads(member)
                nonmember_text = json.loads(nonmember)

                # Yield separate examples for members and non-members
                yield f"{id}_member", {
                    "input": member_text,
                    "label": 1,  # Member example
                }
                yield f"{id}_nonmember", {
                    "input": nonmember_text,
                    "label": 0,  # Non-member example
                }