"""German Social IQa (EllaMind) tasks.
https://huggingface.co/datasets/ellamind/siqa-multilingual
SIQA supplies separate easy and hard distractors.
"""
from typing import Any, Literal, final, override
from eval_framework.choices import ChoiceFields, ChoiceReader
from eval_framework.composed import ComposedBenchmark
from eval_framework.contract import Benchmark
from eval_framework.subjects import ListOfSubjects
from eval_framework.tasks.base import Language
from eval_framework.tasks.dataset_loading import DatasetPolicy
from eval_framework.tasks.dataset_revisions import pinned_by_framework
from eval_framework.tasks.task_style import BPBStyle, ClozeStyle, MCStyle, TaskStyler, shuffle_correct_with_distractors
[docs]
@final
class SiqaReader(ChoiceReader):
"""Reads a Social IQa item: the shown question is the context followed by the question, and the
easy/hard distractor list for the level is shuffled in with the correct answer."""
def __init__(self, distractor_level: Literal["easy", "hard"]) -> None:
self._distractor_level = distractor_level
[docs]
@override
def read(self, item: dict[str, Any]) -> ChoiceFields:
distractors = item["easy_distractors"] if self._distractor_level == "easy" else item["hard_distractors"]
choices, correct_index = shuffle_correct_with_distractors(
correct=item["correct_answer"],
distractors=distractors,
seed_text=item["question"] + item["correct_answer"],
)
return ChoiceFields(
raw_question=f"{item['context']} {item['question']}", choices=choices, correct_index=correct_index
)
def _siqa_ellamind_benchmark(
id: str, styler: TaskStyler, distractor_level: Literal["easy", "hard"], dataset: DatasetPolicy | None = None
) -> Benchmark:
dataset_policy = dataset if dataset is not None else pinned_by_framework("ellamind/siqa-multilingual")
return ComposedBenchmark.choice(
id=id,
reader=SiqaReader(distractor_level),
styler=styler,
sample_split="validation",
fewshot_split="validation",
subjects=ListOfSubjects(["deu"]),
dataset_policy=dataset_policy,
language=Language.DEU,
)
[docs]
def siqa_ellamind_mc_easy_de(dataset: DatasetPolicy | None = None) -> Benchmark:
return _siqa_ellamind_benchmark("SIQA_ELLAMIND_MC_EASY_DE", MCStyle.for_language(Language.DEU), "easy", dataset)
[docs]
def siqa_ellamind_mc_hard_de(dataset: DatasetPolicy | None = None) -> Benchmark:
return _siqa_ellamind_benchmark("SIQA_ELLAMIND_MC_HARD_DE", MCStyle.for_language(Language.DEU), "hard", dataset)
[docs]
def siqa_ellamind_cloze_easy_de(dataset: DatasetPolicy | None = None) -> Benchmark:
return _siqa_ellamind_benchmark(
"SIQA_ELLAMIND_CLOZE_EASY_DE", ClozeStyle.for_language(Language.DEU), "easy", dataset
)
[docs]
def siqa_ellamind_cloze_hard_de(dataset: DatasetPolicy | None = None) -> Benchmark:
return _siqa_ellamind_benchmark(
"SIQA_ELLAMIND_CLOZE_HARD_DE", ClozeStyle.for_language(Language.DEU), "hard", dataset
)
[docs]
def siqa_ellamind_bpb_de(dataset: DatasetPolicy | None = None) -> Benchmark:
return _siqa_ellamind_benchmark("SIQA_ELLAMIND_BPB_DE", BPBStyle.for_language(Language.DEU), "easy", dataset)
SIQA_ELLAMIND_BENCHMARKS: list[Benchmark] = [
siqa_ellamind_mc_easy_de(),
siqa_ellamind_mc_hard_de(),
siqa_ellamind_cloze_easy_de(),
siqa_ellamind_cloze_hard_de(),
siqa_ellamind_bpb_de(),
]