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"""TODO: Add a description here."""
import json
import datasets
# TODO: Add BibTeX citation
_CITATION = """\
"""
# TODO: Add description of the dataset here
_DESCRIPTION = """\
"""
# TODO: Add a link to an official homepage for the dataset here
_HOMEPAGE = ""
# TODO: Add the licence for the dataset here if you can find it
_LICENSE = ""
_URL = "https://huggingface.co/datasets/alexjercan/bugnet/resolve/main/"
def _mk_urls(language):
return {
"train": _URL + language + "_train.jsonl",
"validation": _URL + language + "_validation.jsonl",
"test": _URL + language + "_test.jsonl",
"descriptions": _URL + "problem_descriptions.json",
"tests": _URL + "problem_tests.json",
}
class Bugnet(datasets.GeneratorBasedBuilder):
"""TODO: Short description of my dataset."""
VERSION = datasets.Version("3.0.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="Python", version=VERSION, description="This part of bugnet contains Python bugs"),
datasets.BuilderConfig(name="C++", version=VERSION, description="This part of bugnet contains C++ bugs"),
]
DEFAULT_CONFIG_NAME = "Python"
def _info(self):
features = datasets.Features(
{
"problem_id": datasets.Value("string"),
"language": datasets.Value("string"),
"original_status": datasets.Value("string"),
"fail": datasets.Value("string"),
"pass": datasets.Value("string"),
"change": datasets.Value("string"),
"i1": datasets.Value("uint32"),
"i2": datasets.Value("uint32"),
"j1": datasets.Value("uint32"),
"j2": datasets.Value("uint32"),
"error": datasets.Value("string"),
"stderr": datasets.Value("string"),
"stdout": datasets.Value("string"),
"description": datasets.Value("string"),
"input": datasets.Value("string"),
"output": datasets.Value("string"),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
urls = _mk_urls(self.config.name)
data_dir = dl_manager.download_and_extract(urls)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepath": data_dir["train"],
"descriptions": data_dir["descriptions"],
"tests": data_dir["tests"],
},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"filepath": data_dir["validation"],
"descriptions": data_dir["descriptions"],
"tests": data_dir["tests"],
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"filepath": data_dir["test"],
"descriptions": data_dir["descriptions"],
"tests": data_dir["tests"],
},
),
]
def _generate_examples(self, filepath, descriptions, tests):
with open(descriptions, encoding="utf-8") as file:
description_data = json.load(file)
descriptions = {}
for item in description_data:
key = item["problem_id"]
value = item["description"]
descriptions[key] = value
with open(tests, encoding="utf-8") as file:
tests_data = json.load(file)
inputs = {}
outputs = {}
for item in tests_data:
key = item["problem_id"]
inputs[key] = item["input"]
outputs[key] = item["output"]
with open(filepath, encoding="utf-8") as file:
for key, row in enumerate(file):
data = json.loads(row)
yield key, {
"problem_id": data["problem_id"],
"language": data["language"],
"original_status": data["original_status"],
"fail": data["fail"],
"pass": data["pass"],
"change": data["change"],
"i1": data["i1"],
"i2": data["i2"],
"j1": data["j1"],
"j2": data["j2"],
"error": data["error"],
"stderr": data["stderr"],
"stdout": data["stdout"],
"description": descriptions[data["problem_id"]],
"input": inputs[data["problem_id"]],
"output": outputs[data["problem_id"]],
}
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