|
|
import json |
|
|
import datasets |
|
|
|
|
|
logger = datasets.logging.get_logger(__name__) |
|
|
|
|
|
_CITATION = """\ |
|
|
@article{bavarian2022efficient, |
|
|
title={Efficient Training of Language Models to Fill in the Middle}, |
|
|
author={Bavarian, Mohammad and Jun, Heewoo and Tezak, Nikolas and Schulman, John and McLeavey, Christine and Tworek, Jerry and Chen, Mark}, |
|
|
journal={arXiv preprint arXiv:2207.14255}, |
|
|
year={2022} |
|
|
} |
|
|
""" |
|
|
|
|
|
_DESCRIPTION = """\ |
|
|
An evaluation benchamrk for infilling tasks on HumanEval dataset for code generation. |
|
|
""" |
|
|
|
|
|
_SUBSETS = [ "MultiLineInfilling", "SingleLineInfilling", "RandomSpanInfilling", "RandomSpanInfillingLight" ] |
|
|
|
|
|
|
|
|
class HumanevalConfig(datasets.BuilderConfig): |
|
|
"""BuilderConfig for HumanevalConfig.""" |
|
|
|
|
|
def __init__( |
|
|
self, |
|
|
subset, |
|
|
**kwargs, |
|
|
): |
|
|
self.subset = subset |
|
|
name = f"HumanEval-{subset}" |
|
|
kwargs["name"] = name |
|
|
super(HumanevalConfig, self).__init__(**kwargs) |
|
|
|
|
|
|
|
|
class MultiPLE(datasets.GeneratorBasedBuilder): |
|
|
BUILDER_CONFIG_CLASS = HumanevalConfig |
|
|
|
|
|
BUILDER_CONFIGS = [ |
|
|
HumanevalConfig( |
|
|
subset=subset, |
|
|
version=datasets.Version("1.0.0")) |
|
|
for subset in _SUBSETS |
|
|
] |
|
|
|
|
|
DEFAULT_CONFIG_NAME = "HumanEval-SingleLineInfilling" |
|
|
|
|
|
def _info(self): |
|
|
return datasets.DatasetInfo( |
|
|
description=_DESCRIPTION, |
|
|
license="MIT", |
|
|
features = datasets.Features({'task_id': datasets.Value(dtype='string'), |
|
|
'entry_point': datasets.Value(dtype='string'), |
|
|
'prompt': datasets.Value(dtype='string'), |
|
|
'suffix': datasets.Value(dtype='string'), |
|
|
'canonical_solution': datasets.Value(dtype='string'), |
|
|
'test': datasets.Value(dtype='string')}), |
|
|
supervised_keys=None, |
|
|
homepage="https://github.com/openai/human-eval-infilling", |
|
|
citation=_CITATION |
|
|
) |
|
|
|
|
|
def _split_generators(self, dl_manager: datasets.DownloadManager): |
|
|
files = dl_manager.download( |
|
|
f"data/{self.config.name}.jsonl" |
|
|
) |
|
|
return [ |
|
|
datasets.SplitGenerator( |
|
|
name=datasets.Split.TEST, |
|
|
gen_kwargs={ |
|
|
"filepath": files, |
|
|
} |
|
|
) |
|
|
] |
|
|
|
|
|
def _generate_examples(self, filepath): |
|
|
with open(filepath) as f: |
|
|
for id, line in enumerate(f): |
|
|
row = json.loads(line) |
|
|
yield id, row |
