Source code for nemo_rl.data.eval_datasets.gpqa

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"""GPQA dataset and its variants."""

import random
from typing import Any, Literal, Optional

from datasets import load_dataset

from nemo_rl.data import processors
from nemo_rl.data.interfaces import TaskDataSpec




class GPQADataset:
    def __init__(
        self,
        variant: Literal["diamond", "main"] = "diamond",
        prompt_file: Optional[str] = None,
        system_prompt_file: Optional[str] = None,
    ):
        ds = load_dataset("Idavidrein/gpqa", f"gpqa_{variant}", split="train")
        self._rng = random.Random()
        self.rekeyed_ds = ds.map(self._rekey, remove_columns=ds.column_names)
        self.task_spec = TaskDataSpec(
            task_name=f"GPQA_{variant}",
            prompt_file=prompt_file,
            system_prompt_file=system_prompt_file,
        )
        self.processor = processors.multichoice_qa_processor



    def _rekey(self, data: dict[str, Any]):
        choices = [
            data["Correct Answer"],
            data["Incorrect Answer 1"],
            data["Incorrect Answer 2"],
            data["Incorrect Answer 3"],
        ]
        permutation = self._rng.sample(range(4), 4)
        choices = [choices[i] for i in permutation]
        correct_index = choices.index(data["Correct Answer"])
        correct_answer = "ABCD"[correct_index]
        return {
            "question": data["Question"],
            "options": dict(
                A=choices[0],
                B=choices[1],
                C=choices[2],
                D=choices[3],
            ),
            "answer": correct_answer,
        }