Datasets:
Tasks:
Text Classification
Formats:
parquet
Sub-tasks:
semantic-similarity-classification
Languages:
code
Size:
1M - 10M
License:
File size: 2,353 Bytes
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from typing import List
import datasets
# Citation, taken from https://github.com/microsoft/CodeXGLUE
_DEFAULT_CITATION = """@article{CodeXGLUE,
title={CodeXGLUE: A Benchmark Dataset and Open Challenge for Code Intelligence},
year={2020},}"""
class Child:
_DESCRIPTION = None
_FEATURES = None
_CITATION = None
SPLITS = {"train": datasets.Split.TRAIN}
_SUPERVISED_KEYS = None
def __init__(self, info):
self.info = info
def homepage(self):
return self.info["project_url"]
def _info(self):
# This is the description that will appear on the datasets page.
return datasets.DatasetInfo(
description=self.info["description"] + "\n\n" + self._DESCRIPTION,
features=datasets.Features(self._FEATURES),
homepage=self.homepage(),
citation=self._CITATION or _DEFAULT_CITATION,
supervised_keys=self._SUPERVISED_KEYS,
)
def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
SPLITS = self.SPLITS
_URL = self.info["raw_url"]
urls_to_download = {}
for split in SPLITS:
if split not in urls_to_download:
urls_to_download[split] = {}
for key, url in self.generate_urls(split):
if not url.startswith("http"):
url = _URL + "/" + url
urls_to_download[split][key] = url
downloaded_files = {}
for k, v in urls_to_download.items():
downloaded_files[k] = dl_manager.download_and_extract(v)
return [
datasets.SplitGenerator(
name=SPLITS[k],
gen_kwargs={"split_name": k, "file_paths": downloaded_files[k]},
)
for k in SPLITS
]
def check_empty(self, entries):
all_empty = all([v == "" for v in entries.values()])
all_non_empty = all([v != "" for v in entries.values()])
if not all_non_empty and not all_empty:
raise RuntimeError("Parallel data files should have the same number of lines.")
return all_empty
class TrainValidTestChild(Child):
SPLITS = {
"train": datasets.Split.TRAIN,
"valid": datasets.Split.VALIDATION,
"test": datasets.Split.TEST,
}
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