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# coding=utf-8
# Lint as: python3
"""XWinograd"""
import json
import pandas as pd
import datasets
logger = datasets.logging.get_logger(__name__)
_CITATION = """\
@misc{tikhonov2021heads,
title={It's All in the Heads: Using Attention Heads as a Baseline for Cross-Lingual Transfer in Commonsense Reasoning},
author={Alexey Tikhonov and Max Ryabinin},
year={2021},
eprint={2106.12066},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
"""
_DESCRIPTION = """\
A multilingual collection of Winograd Schemas in six languages \
that can be used for evaluation of cross-lingual commonsense reasoning capabilities.
"""
_URL = "https://huggingface.co/datasets/Muennighoff/xwinograd/resolve/main/data/xwinograd.tsv"
import json
import random
def winogrande_format(row):
array = row["pronoun"]
position_idx = json.loads(array)[1][0]
# Turn unicode into proper chinese characters
sent = str(u"{}".format(row["sent"]))
start_idx = 0
for i, tok in enumerate(json.loads(row["toks"])):
tok = str(u"{}".format(tok))
cur_start_idx = sent.find(tok)
if i == position_idx:
break
sent = sent[cur_start_idx + len(tok):]
start_idx += cur_start_idx + len(tok)
# +1 to give room for an optional space
row["sentence"] = row["sent"][:start_idx] + row["sent"][start_idx:start_idx+len(tok)+1].replace(tok, "_") + row["sent"][start_idx+len(tok)+1:]
sol = json.loads(row["solution"])
cor_answer_idx = random.choice([1, 2])
incor_answer_idx = 2 if cor_answer_idx == 1 else 1
cor_answer = str(u"{}".format(sol[0][0])) if sol[0][-1] == True else str(u"{}".format(sol[1][0]))
incor_answer = str(u"{}".format(sol[0][0])) if sol[0][-1] == False else str(u"{}".format(sol[1][0]))
row[f"option{cor_answer_idx}"] = cor_answer
row[f"option{incor_answer_idx}"] = incor_answer
row["answer"] = cor_answer_idx
return row
class XWinograd(datasets.GeneratorBasedBuilder):
"""XWinograd"""
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name="en",
version=VERSION,
description="X",
),
datasets.BuilderConfig(
name="fr",
version=VERSION,
description="X",
),
datasets.BuilderConfig(
name="jp",
version=VERSION,
description="X",
),
datasets.BuilderConfig(
name="pt",
version=VERSION,
description="X",
),
datasets.BuilderConfig(
name="ru",
version=VERSION,
description="X",
),
datasets.BuilderConfig(
name="zh",
version=VERSION,
description="X",
),
]
DEFAULT_CONFIG_NAME = "en"
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"sentence": datasets.Value("string"),
"option1": datasets.Value("string"),
"option2": datasets.Value("string"),
"answer": datasets.Value("string")
}
),
supervised_keys=None,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
downloaded_files = dl_manager.download_and_extract(_URL)
return [
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={'filepath': downloaded_files}
)
]
def _generate_examples(self, filepath):
"""This function returns the examples in the raw (text) form."""
logger.info("generating examples from = %s", filepath)
ds = pd.read_csv(
filepath, sep='\t', header=None,
names=["lang", "type", "original", "sent", "toks", "pronoun", "solution"]
)
if self.config.name:
ds = ds[ds["lang"] == self.config.name]
ds = ds.apply(winogrande_format, axis=1)
for idx, row in ds.iterrows():
yield idx, {
"sentence": row["sentence"],
"option1": row["option1"],
"option2": row["option2"],
"answer": row["answer"],
}
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